A multi-mode adaptive freeze-thaw system and method of use thereof

Abstract

The present application belongs to the technical field of geotechnical engineering and geological disaster simulation test, and particularly relates to a multi-mode self-adaptive freeze-thaw system and an application method thereof. The system comprises a central controller, a monitoring module, and at least three freeze-thaw mode execution modules connected with the central controller and capable of independent or collaborative work. Mode A performs controllable freeze-thaw on a physical model through surface heat conduction; mode B performs uniform or approximately uniform temperature cycling on the whole physical model by adjusting ambient air temperature; and mode C realizes rapid freeze-thaw by spraying phase-change working medium on the surface of the physical model. The central controller controls according to preset test target parameters, and dynamically adjusts the operating parameters of each freeze-thaw mode execution module according to real-time feedback data of the monitoring module. The method realizes precise and stable target field construction, automatically selects the optimal hardware mode based on parameters such as gradient, rate and uniformity, and improves the authenticity and accuracy of simulation.

Description

Technical Field

[0001] This invention belongs to the field of geotechnical engineering and geological disaster simulation test technology, specifically involving a multi-mode adaptive freeze-thaw system and its application method. Background Technology

[0002] Freeze-thaw cycles, as typical natural forces in cold regions and seasonally frozen soil areas, are key environmental drivers leading to the progressive deterioration and sudden instability of geotechnical engineering structures (such as slopes, roadbeds, and open-pit mine slopes). To reveal their mechanisms and assess the long-term stability of engineering projects, indoor scaled physical model tests have become an indispensable research method. However, existing freeze-thaw simulation technologies and testing devices still have significant limitations in terms of simulation fidelity, adaptability to operating conditions, and system intelligence, restricting the depth of research and the reliability of engineering applications.

[0003] Currently, the most widely used freeze-thaw simulation technology in laboratories is the surface contact simulation method. This method typically involves laying cooling coils or cold plates on the surface of the model, controlling the surface temperature through direct heat conduction, and thus inducing phase changes and temperature redistribution within the model. While this technology can achieve localized temperature control, it has significant shortcomings: First, the freezing and thawing rates are slow, making it difficult to simulate rapid temperature changes such as sudden drops in temperature. Second, the depth of temperature influence is limited, with a significant decrease in the simulation effect of freeze-thaw effects on deep soil or rock layers. Third, the hardware layout is rigid; once the coils or cold plates are fixed, it is difficult to flexibly adjust the spatial arrangement, failing to adapt to the differentiated simulation needs of different geometries or key research areas. More importantly, existing systems have limited control strategies, mostly only able to execute preset constant temperatures or simple periodic changes, lacking the ability to make intelligent decisions and dynamically optimize parameters based on complex experimental requirements such as "target freezing depth," "specific temperature gradient," and "non-uniform freeze-thaw fields."

[0004] While existing patented technologies attempt to improve the systematic nature of freeze-thaw tests, they have not fundamentally solved the aforementioned problems. For example, patent CN117969795A discloses an experimental system for an ice-rock debris slope model under freeze-thaw cycles. This system achieves coupled control of temperature and moisture conditions by introducing hot and cold air into the test chamber and combining this with water spraying to simulate rainfall. However, this system is essentially still a holistic environmental simulation method. Its temperature field relies on gas convection, making it difficult to actively and accurately construct a non-uniform spatial temperature distribution within the model that conforms to the actual field conditions, particularly in terms of precisely controlling the temperature gradient from the slope surface to deeper layers. Furthermore, the freeze-thaw action mode of this system is relatively fixed, making it impossible to flexibly adjust the simulation strategy for different failure modes such as "shallow spalling," "deep sliding," and "rapid freezing." Another patent, CN1190668868A, innovates at the analytical method level by establishing a porosity analysis model and a sliding force prediction model through experiments, thereby constructing a slope stability assessment system. Although this method emphasizes the correlation between the microstructure evolution and macroscopic stability of soil and rock under freeze-thaw conditions, its experimental basis still relies on traditional freeze-thaw simulation devices.

[0005] In summary, existing slope model freeze-thaw test systems and methods suffer from several shortcomings, including rigid models, poor adaptability to operating conditions, distorted temperature field simulation, lack of gradient control, low level of intelligent control, and insufficient system integration and coordination. Therefore, there is an urgent need to develop a novel freeze-thaw simulation system and technology. This system should overcome the limitations of existing single-mode approaches, integrate multiple freeze-thaw action methods (such as contact refrigeration, convection heat transfer, and radiation cooling), and possess the ability to intelligently select the optimal combination of action modes and parameter sequences based on preset test objectives (such as specific freezing front advance curves and spatial temperature distribution requirements). Simultaneously, the system needs to achieve efficient integration and collaborative control with other test modules at both the hardware and software levels. This would provide a more accurate, flexible, and intelligent physical simulation test platform for the study of freeze-thaw disaster mechanisms, stability assessment, and prevention technology development in cold-region geotechnical engineering structures. Summary of the Invention

[0006] The technical problem to be solved by the present invention is to provide a multi-mode adaptive freeze-thaw system and its application method. By transforming complex experimental requirements into quantitative parameters and automatically matching the best freeze-thaw mode and collaborative scheme by an intelligent system, the scientificity and efficiency of experimental design are greatly improved, and the drawbacks of the single mode of traditional methods are overcome.

[0007] The technical solution adopted is as follows: A multi-mode adaptive freeze-thaw system includes a central controller, a monitoring module, and at least three freeze-thaw mode execution modules connected to the central controller, which can work independently or collaboratively. Mode A: Surface heat-conducting coil freeze-thaw module, which includes a heat-conducting coil network flexibly laid according to the surface morphology of the slope model, a cold / heat integrated unit that pumps cold / heat working fluid to the coil network, and auxiliary structures for fixing the coils and reducing heat loss, so as to realize the controllable freeze-thaw of the surface and shallow layers of the slope model, that is, to controllable freeze-thaw of the physical model through surface heat conduction. Mode B: Environmental Chamber Overall Alternating Freeze-Thaw Module, which includes a sealed simulation chamber surrounding the entire slope model, and a temperature control system installed in the simulation chamber. The temperature control system includes a refrigeration subsystem, a heating subsystem, and a forced gas circulation system, which adjusts the ambient air temperature to perform uniform or near-uniform temperature circulation on the physical model as a whole. Mode C: Fluid jet rapid freeze-thaw module, which includes a rapid freezing component and a rapid thawing component. The rapid freezing component includes a liquid nitrogen storage tank and an array of atomizing nozzles connected thereto. The rapid thawing component includes a steam generator, which achieves rapid freeze-thaw by spraying a phase change working fluid onto the surface of the physical model. The monitoring module includes several temperature sensors, moisture sensors and / or deformation sensors arranged inside and on the surface of the physical model; The central controller automatically decides and controls at least one of the freeze-thaw mode execution modules to start, stop, or operate in combination based on preset test target parameters; the central controller dynamically adjusts the operating parameters of each freeze-thaw mode execution module based on real-time feedback data from the monitoring module.

[0008] Each freeze-thaw mode execution module is physically integrated on a unified test platform. The environmental chamber of mode B is designed with openable and closable doors or movable walls to enable or adjust the components of mode A and mode C without disassembling the physical model.

[0009] Preferably, in Mode A, the integrated cooling and heating unit is connected to a flexible heat-conducting coil network via external pipelines, which can provide a circulating working fluid with precise and controllable temperature; the temperature range of the circulating working fluid provided by the integrated cooling and heating unit is adjustable between -40℃ and +40℃. The insulation layer covers the outside of the flexible heat-conducting coil network.

[0010] Preferably, in Mode B, the simulated chamber further includes a humidifier and a dehumidifier for adjusting the humidity inside the chamber; the forced gas circulation system includes a fan and air ducts to ensure uniform temperature inside the chamber.

[0011] Preferably, in mode C, the atomizing nozzle array of the rapid freezing component is positioned above the model and its position and / or angle are adjustable; the system also includes a safety ventilation and exhaust device to prevent local enrichment of low-temperature nitrogen or high-temperature vapor.

[0012] Preferably, the central controller receives a test plan input by the user, which includes the target boundary type, temperature parameters, and spatial parameters, and has a built-in mode determination engine; it automatically recommends and executes the corresponding freeze-thaw mode or mode combination based on the test plan according to preset rules; and it performs closed-loop control on the freeze-thaw module during the execution process.

[0013] Preferably, the closed-loop control is a three-layer closed-loop control strategy, including: Inner loop: With the key point temperature as the direct target, the cooling power, heating power or valve opening is adjusted in real time; Central Ring: Monitors the temperature at multiple measuring points, calculates uniformity error, and adjusts the airflow circulation intensity or differentiates the chemical temperature for different zones; Outer ring: Real-time monitoring of over-temperature, pressure, and overload protection sensors, which execute protective operations when triggered.

[0014] Preferably, when a target temperature gradient or target freezing depth is set in the test plan, the central controller is configured to enable an active gradient temperature field construction strategy, which includes: firstly, starting mode B to stabilize the temperature of the environmental chamber near the deep target temperature to establish a background field; then starting mode A to apply stronger cooling or heating power to the coils in the slope surface area to make the surface temperature reach the set value; and dynamically fine-tuning the background temperature and surface power to stabilize the measured gradient within the target gradient range.

[0015] This invention provides an application method for a multi-mode adaptive freeze-thaw system, which includes the following steps: S1: Receive the input test plan, which includes at least the target boundary type, temperature parameters, and spatial parameters; S2: Based on preset rules and input criteria, automatically recommend and finally confirm the freeze-thaw mode or mode combination to be executed; S3: Perform interlock self-test on the hardware system corresponding to the selected freeze-thaw mode; S4: Generates detailed temperature-time control curves based on input parameters; S5: Initialize the sensor network preset inside and on the surface of the slope model; S6: During the freezing phase, the corresponding actuator is driven according to the selected mode and control curve, and the target temperature is achieved by adopting a closed-loop control strategy. S7: During the melting stage, switch to the melting curve, drive the corresponding actuator to heat, and adopt a closed-loop control strategy; S8: If a target temperature gradient is set, then actively construct the gradient temperature field. S9: Manage freeze-thaw cycles and record data and handle faults throughout the process.

[0016] Preferably, in step S2, the preset rules include: Rule 1: If the target is a uniform temperature change or a stable background temperature field is required, and the absolute value of the target temperature gradient is small, then mode B is recommended. Rule 2: If the objective is to enhance localized freeze-thaw cycles on slopes, control temperature in zones, or maintain a large temperature gradient, then mode A is recommended. Rule 3: If it is required to reach an extremely low surface temperature in a very short time to simulate a cold wave, then it is recommended to enable mode C; Rule 4: If it is necessary to simulate complex working conditions, the combined mode is recommended.

[0017] Preferably, in step S8, the active construction of the gradient temperature field specifically includes: first, activating mode B to stabilize the temperature of the environmental chamber near the deep target temperature; then activating mode A to enhance temperature control of the slope surface area; and finally, by comparing the data from the surface and deep sensors in real time, dynamically fine-tuning the background temperature of mode B and the surface power of mode A to make the measured gradient approach and stabilize within the target gradient range.

[0018] Compared with the prior art, the beneficial effects of the present invention are as follows: (1) This invention significantly expands the experimental capabilities and accuracy by moving from "single simulation" to multi-mode collaborative precision customization. Through three modes or combinations of modes (such as C→A, C→B), complex experimental requirements are transformed into quantitative parameters, and the intelligent system automatically matches the best freeze-thaw mode and collaborative scheme, which greatly improves the scientific nature and efficiency of experimental design and overcomes the drawbacks of the single mode of traditional methods. This is something that existing single technical means cannot achieve.

[0019] (2) The simulation of temperature field has been significantly improved. The "gradient field active construction" function and the "composite mode" timing control make it possible to reproduce the complex non-uniform freeze-thaw temperature field in the laboratory with high fidelity, and the engineering reference value of the test results is higher.

[0020] (3) This invention achieves accurate and stable target field construction by moving from "open-loop preset" to "intelligent adaptive closed-loop". It automatically selects the optimal hardware mode based on physical targets (gradient, rate, uniformity), reducing the operation threshold and avoiding human error in mode selection. The three-layer closed-loop control ensures that the temperature of key points accurately tracks the preset curve, the middle loop (uniformity control) actively adjusts the airflow or zone power, overcomes the technical problem of uneven temperature distribution in large slope models, ensures the consistency of experimental conditions, and the outer loop (protective loop) ensures the long-term stable and safe operation of the system. The active gradient construction is a creative progress. The system of this invention can actively construct and maintain a specified temperature gradient or reach the target freezing depth, rather than passively observing. This enables researchers to accurately study the water migration law and frost heave development process under a specific temperature gradient, and elevates the experiment from "phenomenon observation" to "mechanism controllable verification".

[0021] (4) The present invention features automated, intelligent, and integrated design. From parameter input, mode recommendation, interlocking checks to multi-layer closed-loop control, it achieves a high degree of automation throughout the entire process, reducing reliance on operator experience and enabling rapid and seamless switching between different complex working conditions. This ensures the repeatability and data consistency of the test process and saves a significant amount of preparation time. The hardware interlocking self-check and three-layer (control, uniform, protection) closed-loop control mechanism ensure the safety and stability of the system under complex multi-mode operation. Intelligent fault diagnosis and safety protection, interlocking logic, and fault code recording can prevent misoperation and provide clear diagnosis when problems occur, improving the safety and maintainability of the equipment and the test.

[0022] (5) This invention provides a refined research direction for the study of freeze-thaw landslide mechanisms, enabling the separation and study of the influence of single or composite variables such as "temperature gradient" and "freeze-thaw cycle form" on slope stability. The generated high-precision, multi-condition test data is a valuable resource for verifying and calibrating unsaturated soil water-thermal-mechanical coupled numerical models. It can more realistically simulate the freeze-thaw conditions in specific regions (such as cold regions with rapid freezing and slow thawing, and high-altitude regions with large diurnal temperature differences), providing direct experimental basis and optimization schemes for the protection design of slopes in freeze-thaw areas (such as insulation layer laying schemes and drainage system design), and realizing the optimal allocation of resources.

[0023] The core value of this invention lies in the deep integration of diversified hardware modules with intelligent control strategies. It not only solves the pain points of existing technologies such as limited simulation capabilities and crude control, but also creates a new paradigm for actively constructing complex temperature fields for mechanism research. It is a powerful tool innovation in the field of slope engineering freeze-thaw disaster research. Attached Figure Description

[0024] Figure 1 This is a schematic diagram of the structure of module A of the present invention.

[0025] Figure 2 This is a schematic diagram of the structure of module B of the present invention.

[0026] Figure 3 This is a schematic diagram of the structure of module C in this invention.

[0027] Figure 4 This is a side view schematic diagram of the integrated structure of a multi-mode adaptive freeze-thaw system.

[0028] Figure 5 This is a flowchart of the application method of the present invention.

[0029] In the figure, 1-coil, 2-external frame of slope model, 3-environmental chamber, 4-transfer frame, 5-guide rail, 6-liquid nitrogen storage tank, 7-pressure reducing valve, 8-solenoid valve, 9-atomizing nozzle array, 10-steam generator, 11-steam pipeline, 12-ventilation and exhaust device, 13-slope similar physical model. Detailed Implementation

[0030] The accompanying drawings are for illustrative purposes only; to enable those skilled in the art to better understand the technical solutions of the present invention, the preferred embodiments of the present invention are described below in conjunction with specific examples, but should not be construed as limiting the present patent.

[0031] Unless otherwise specified, the test methods or experimental methods described in the following examples are conventional methods or obtained from conventional commercial sources.

[0032] Example 1 A multi-mode adaptive freeze-thaw system (see) Figure 4 It includes a central controller, a monitoring module, and three freeze-thaw mode execution modules, each connected to the central controller and capable of working independently or collaboratively: Mode A: Surface heat-conducting coil freeze-thaw module.

[0033] like Figure 1 As shown, it is used to achieve controlled freeze-thaw cycles in the surface and shallow layers of the slope model.

[0034] Core component: A network of heat-conducting coils is flexibly laid according to the surface morphology of the slope model. The coils are made of high and low temperature resistant metal pipes and are connected to external pipelines through quick connectors.

[0035] Heat source: Integrated heat and cold unit, which can provide a circulating working fluid with a temperature range of -40℃ to +40℃.

[0036] Auxiliary components: snap-fit ​​mesh for securing the coil, and rubber and plastic insulation board covering the outside of the coil (to reduce ambient heat loss).

[0037] Working principle: By pumping low-temperature or high-temperature working fluid through the coil, heat exchange occurs with the surface of the slope model, achieving thermal heating or cooling of the model surface.

[0038] Mode B: Overall alternating freeze-thaw module for the environmental chamber. like Figure 2 As shown, this is used to ensure that the entire slope model (from the surface to the deep layer) undergoes uniform or nearly uniform temperature cycling.

[0039] Core component: A sealed experimental simulation chamber that surrounds the entire slope model and has excellent thermal insulation and sealing performance.

[0040] Temperature control system: includes refrigeration subsystem (fully enclosed compressor, air-cooled condenser, finned evaporator, etc.), heating subsystem (nickel-chromium alloy electric heater), and forced gas circulation system (fan and air duct) to ensure uniform temperature inside the chamber.

[0041] Auxiliary components: Humidifiers and dehumidifiers are used to simulate humidity-related boundary conditions such as frost formation and snow melting.

[0042] Working principle: The air temperature inside the chamber is regulated by the refrigeration and heating system, and combined with forced convection, the model is kept in a set temperature environment.

[0043] Mode C: Fluid jet rapid freeze-thaw module (enhanced module). like Figure 3 As shown, it is used to achieve rapid freezing or rapid thawing of the slope model surface to simulate extreme climate conditions.

[0044] Rapid freezing components: liquid nitrogen tank, pressure reducing valve, solenoid valve, and atomizing nozzle array. The nozzles are movable and positioned above the model.

[0045] Rapid melting component: electrically heated steam generator.

[0046] Safety components: ventilation and exhaust systems to prevent localized accumulation of low-temperature nitrogen or high-temperature vapor.

[0047] Working principle: Rapid freezing within minutes is achieved by spraying cryogenic liquid nitrogen mist onto the model surface; rapid melting is achieved by spraying steam.

[0048] The monitoring module includes several temperature sensors, moisture sensors, and / or deformation sensors arranged inside and on the surface of the physical model, which can be configured as needed.

[0049] The core of this invention lies in a complete intelligent control method, the process of which is as follows: Figure 5 As shown, the specific steps are as follows: S1: Input of test objectives and operating condition criteria The operator inputs or imports the test plan through the human-machine interface. The parameters must include at least: Target boundary type: surface freeze-thaw, overall freeze-thaw, or combined freeze-thaw.

[0050] Temperature parameters: target temperature upper and lower limits (e.g., -40℃ and +40℃), holding time, heating / cooling rate (0~40℃ / h), number of cycles.

[0051] Spatial parameters: target freezing depth Hf, target temperature gradient G: which is defined as the difference between the surface target temperature Ts and the deep target temperature Td divided by the corresponding depth difference.

[0052] Environmental parameters: Whether to enable humidity control to simulate frosting or condensation boundaries.

[0053] Model parameters: model size and estimated heat capacity.

[0054] S2: Automatic Mode Recommendation and Confirmation The central controller has a built-in "pattern determination engine" that automatically makes recommendations based on the criteria input from S1 and preset rules: Rule 1: If the goal is a uniform temperature change or a stable background temperature field is required, and |G| is small, then mode B (environmental chamber) is recommended.

[0055] Rule 2: If the goal is to enhance localized freeze-thaw cycles on slopes, control temperature in zones, or maintain a large temperature gradient (larger G), then mode A (surface coil) is recommended.

[0056] Rule 3: If it is required to reach an extremely low surface temperature in a very short time to simulate a cold wave, it is recommended to use Mode C (liquid nitrogen enhancement) as the start-up phase.

[0057] Rule 4: If it is necessary to simulate a complex working condition such as "rapid freezing and capping of the surface, slow freezing inside" or "rapid melting of the surface, slow heating inside", then a combination mode is recommended, such as "C→A" (first rapid freezing with liquid nitrogen, then maintaining the gradient with coils) or "B→A" (first overall cooling to create a background, then strengthening the surface with coils).

[0058] The recommended results are presented to the operator for final confirmation or modification.

[0059] S3: Mode Interlock Self-Test Based on the selected mode, the controller automatically checks the readiness and security of the corresponding hardware system, forming an interlock: Mode A Interlock: Check if the quick-connect coil is connected in place, the status of the manifold valves, and the status of the integrated cooling and heating unit (pressure, liquid level).

[0060] Mode B Interlock: Check the sealing status of the environmental chamber door, the status of the forced circulation fan, the status of the humidification and water supply system (if enabled), and the protection sensor signals for over-temperature, water shortage, and compressor overload.

[0061] Mode C Interlock: Check the liquid nitrogen storage tank pressure and level, the status of the spray device solenoid valve, the status of the steam / hot water supply system, and pre-start the safety ventilation device.

[0062] S4: Generation of freeze-thaw program curve The controller integrates the input parameters from S1 to generate detailed temperature-time control curves, clearly defining the cooling curve and plateau period during the freezing phase, the heating curve and plateau period during the thawing phase, and the loop logic. The system temperature control accuracy (±0.1~±0.5℃) and uniformity requirement (±1℃) serve as constraints for curve generation.

[0063] S5: Sensor Network Initialization The controller reads data from a pre-installed array of temperature sensors at different depths and on the surface of the slope model, performs baseline calibration and consistency checks, eliminates abnormal sensor signals, and provides reliable feedback for closed-loop control.

[0064] S6: Freeze Phase Execution and Closed-Loop Control Based on the selected mode and the curve generated by S4, the controller outputs commands to drive the corresponding actuators: Execution Mode A: Controls the integrated heating and cooling unit to output a low-temperature working fluid, which flows through the surface coil to conduct heat and cool the model.

[0065] Execution Mode B: The control environment chamber's cooling system is activated, combined with forced airflow circulation, to reduce the overall temperature inside the chamber.

[0066] Execution Mode C: Controls the activation of the liquid nitrogen spray system to rapidly spray and cool the model surface.

[0067] The control system adopts a three-layer closed-loop control strategy: Inner loop (execution control): Taking the temperature of key points on the slope as the direct target, the cooling power, heating power, valve opening, fan speed, etc. are adjusted in real time through algorithms such as PID.

[0068] Central Ring (Uniformity Control): Monitors the temperature at multiple points on the slope and inside the cabin, and calculates the uniformity error. If the error exceeds the limit, it adjusts the airflow circulation intensity or performs differentiated propellant temperature adjustments for different coil zones in Mode A.

[0069] Outer loop (protection loop): Real-time monitoring of all protection sensors (over-temperature, water shortage, pressure, overload, etc.). Once triggered, it immediately performs derating operation, sequential shutdown, or emergency shutdown, and issues an alarm.

[0070] S7: Melting Phase Execution and Closed-Loop Control After the freezing plateau period ends, the controller switches to the melting phase curve and drives the corresponding actuators to perform heating: Execution Mode A: Controls the integrated cooling and heating unit to output high-temperature working fluid, which flows through the coil for heat conduction and heating.

[0071] Execution Mode B: Start the environmental chamber heating system to raise the temperature inside the chamber.

[0072] Execution Mode C: Controls the start of the steam or warm water injection system to rapidly convectively heat the frozen surface.

[0073] The melting stage also employs the same three-layer closed-loop control strategy.

[0074] S8: Active Construction of Gradient Temperature Field The controller enables this function when a specific target temperature gradient G or freezing depth Hf is set in S1. A typical strategy is "background field + surface strengthening": First, activate mode B to stabilize the temperature of the environmental chamber near the deep target temperature Td, establishing an overall low-temperature background.

[0075] Then, mode A is activated, which applies stronger cooling (or heating) power to the coils in the slope surface area, causing the surface temperature to change towards Ts.

[0076] By comparing feedback data from surface and deep sensors in real time, the background temperature of mode B and the surface power of mode A are dynamically fine-tuned to make the measured gradient Gactual approach and stabilize within the allowable error range of the target gradient G.

[0077] S9: Loop Management, Data Logging, and Fault Handling The controller manages the number of freeze-thaw cycles. After a cycle is completed, it can automatically start the next cycle or wait for instructions.

[0078] It records all sensor data, control commands, and alarm events throughout the entire process and supports data export.

[0079] When any interlock alarm or protective shutdown occurs, the controller records the fault code and displays diagnostic information and maintenance suggestions on the human-machine interface.

[0080] Application Example 1 Using this invention, combined with the freeze-thaw conditions of an open-pit coal mine slope, the freeze-thaw process of the slope is simulated through the independent and coordinated operation of three freeze-thaw modules.

[0081] The first step is to create a physical model of the slope. Based on the geological data of a slope in an open-pit coal mine, a scaled-down model can be made according to a fixed similarity ratio. The model uses a mixture of silty clay, weathered rock, and crushed stone, with controlled moisture content and density. After being laid in layers, the model is left to stand for 72 hours before use.

[0082] The second step is to deploy the system modules. This involves deploying the various modules of the system to ensure the normal operation of the three freeze-thaw modes, as detailed below: (1) Mode A (Surface heat conduction coil freeze-thaw module): Stainless steel heat conduction coils are flexibly laid along the slope of the slope model and connected to the integrated heating and cooling unit. The outer side of the coil is covered with an insulation layer to achieve controllable freeze-thaw of the surface and shallow layers.

[0083] (2) Mode B (Environmental Chamber Overall Alternating Freeze-Thaw Module): The model is placed in a sealed simulation chamber, and a temperature control system is installed inside the chamber.

[0084] (3) Mode C (fluid jet rapid freeze-thaw module): An adjustable atomizing nozzle array is arranged on the top of the model, connected to a liquid nitrogen storage tank and a steam generator, and equipped with a safety ventilation device to achieve rapid freeze-thaw of the surface.

[0085] (4) Monitoring module: Temperature, moisture and deformation sensors are arranged inside and on the surface of the model and connected to the central controller.

[0086] The third step is to develop the experimental protocol. Three groups of comparative experiments are set up, each with five freeze-thaw cycles, each cycle lasting 24 hours, with freezing and thawing each lasting 12 hours. Specific parameters are shown in the table below: Table 1 Experimental Setup Table The fourth step is to execute the experimental plan. This is done according to steps S1-S9 of the application method of this invention, with the core process as follows: (1) S1-S2: Input the test parameters. The central controller will automatically recommend the freeze-thaw mode. After confirmation, start the test.

[0087] (2) S3: The system completes the interlock self-test of each module to ensure that modes A, B, C and monitoring modules are normal.

[0088] (3) S4-S5: Generate freeze-thaw control curves, initialize sensor network, and eliminate abnormal signals.

[0089] (4) S6-S7: During the freezing stage, the corresponding modules are started according to the mode combination and three-layer closed-loop control is adopted; during the melting stage, the module heating state is switched to maintain parameter stability.

[0090] (5) S8: Enable active construction of gradient temperature field, establish background temperature through mode B, fine-tune surface temperature through mode A, and maintain target gradient.

[0091] (6) S9: Complete 5 freeze-thaw cycles, record the test data throughout the process, and ensure that the data is traceable.

[0092] Of course, the above description is not intended to limit the present invention, and the present invention is not limited to the examples given above. Any changes, modifications, additions or substitutions made by those skilled in the art within the scope of the present invention should also fall within the protection scope of the present invention.

Claims

1. A multi-mode adaptive freeze-thaw system, characterized in that, It includes a central controller, a monitoring module, and at least three freeze-thaw mode execution modules connected to the central controller, which can work independently or collaboratively: Mode A: Surface heat-conducting coil freeze-thaw module, which includes a heat-conducting coil network flexibly laid according to the surface morphology of the slope model, a cold / heat integrated unit that pumps cold / heat working fluid to the coil network, and auxiliary structures for fixing the coils and reducing heat loss, so as to realize the controllable freeze-thaw of the surface and shallow layers of the slope model, that is, to controllable freeze-thaw of the physical model through surface heat conduction. Mode B: Environmental Chamber Overall Alternating Freeze-Thaw Module, which includes a sealed simulation chamber surrounding the entire slope model, and a temperature control system installed in the simulation chamber. The temperature control system includes a refrigeration subsystem, a heating subsystem, and a forced gas circulation system, which adjusts the ambient air temperature to perform uniform or near-uniform temperature circulation on the physical model as a whole. Mode C: Fluid jet rapid freeze-thaw module, which includes a rapid freezing component and a rapid thawing component. The rapid freezing component includes a liquid nitrogen storage tank and an array of atomizing nozzles connected thereto. The rapid thawing component includes a steam generator, which achieves rapid freeze-thaw by spraying a phase change working fluid onto the surface of the physical model. The monitoring module includes several temperature sensors, moisture sensors and / or deformation sensors arranged inside and on the surface of the physical model; The central controller automatically decides and controls at least one of the freeze-thaw mode execution modules to start, stop, or operate in combination based on preset test target parameters; the central controller dynamically adjusts the operating parameters of each freeze-thaw mode execution module based on real-time feedback data from the monitoring module.

2. The multi-mode adaptive freeze-thaw system according to claim 1, characterized in that, In Mode A, the integrated cooling and heating unit is connected to a flexible heat-conducting coil network via external pipelines, enabling it to provide a circulating working fluid with precisely controllable temperature; the temperature range of the circulating working fluid provided by the integrated cooling and heating unit is adjustable between -40℃ and +40℃. The insulation layer covers the outside of the flexible heat-conducting coil network.

3. The multi-mode adaptive freeze-thaw system according to claim 1, characterized in that, In Mode B, the simulated chamber also includes a humidifier and a dehumidifier for regulating the humidity inside the chamber; the forced gas circulation system includes a fan and air ducts to ensure uniform temperature inside the chamber.

4. The multi-mode adaptive freeze-thaw system according to claim 1, characterized in that, In Mode C, the atomizing nozzle array of the rapid freezing component is positioned above the model and its position and / or angle are adjustable; the system also includes a safety ventilation and exhaust device to prevent local enrichment of low-temperature nitrogen or high-temperature vapor.

5. A multi-mode adaptive freeze-thaw system according to claim 1, characterized in that, The central controller receives test plans input by the user, including target boundary type, temperature parameters, and spatial parameters, and has a built-in mode determination engine. Based on preset rules and the test plan, the system automatically recommends and executes the corresponding freeze-thaw mode or mode combination; and performs closed-loop control of the freeze-thaw module during the execution process.

6. A multi-mode adaptive freeze-thaw system according to claim 5, characterized in that, The closed-loop control is a three-layer closed-loop control strategy, including: Inner loop: With the key point temperature as the direct target, the cooling power, heating power or valve opening is adjusted in real time; Central Ring: Monitors the temperature at multiple measuring points, calculates uniformity error, and adjusts the airflow circulation intensity or differentiates the chemical temperature for different zones; Outer ring: Real-time monitoring of over-temperature, pressure, and overload protection sensors, which execute protective operations when triggered.

7. The multi-mode adaptive freeze-thaw system according to claim 1, characterized in that, When a target temperature gradient or target freezing depth is set in the test plan, the central controller is configured to enable an active gradient temperature field construction strategy, which includes: firstly, starting mode B to stabilize the temperature of the environmental chamber near the deep target temperature to establish a background field; then starting mode A to apply stronger cooling or heating power to the coils in the slope surface area to make the surface temperature reach the set value; and dynamically fine-tuning the background temperature and surface power to stabilize the measured gradient within the target gradient range.

8. A method for applying a multi-mode adaptive freeze-thaw system, using the system described in any one of claims 1-7, characterized in that, Includes the following steps: S1: Receive the input test plan, which includes at least the target boundary type, temperature parameters, and spatial parameters; S2: Based on preset rules and input criteria, automatically recommend and finally confirm the freeze-thaw mode or mode combination to be executed; S3: Perform interlock self-test on the hardware system corresponding to the selected freeze-thaw mode; S4: Generates detailed temperature-time control curves based on input parameters; S5: Initialize the sensor network preset inside and on the surface of the slope model; S6: During the freezing phase, the corresponding actuator is driven according to the selected mode and control curve, and the target temperature is achieved by adopting a closed-loop control strategy. S7: During the melting stage, switch to the melting curve, drive the corresponding actuator to heat, and adopt a closed-loop control strategy; S8: If a target temperature gradient is set, then actively construct the gradient temperature field. S9: Manage freeze-thaw cycles and record data and handle faults throughout the process.

9. The application method of a multi-mode adaptive freeze-thaw system according to claim 8, characterized in that, In step S2, the preset rules include: Rule 1: If the target is a uniform temperature change or a stable background temperature field is required, and the absolute value of the target temperature gradient is small, then mode B is recommended. Rule 2: If the objective is to enhance localized freeze-thaw cycles on slopes, control temperature in zones, or maintain a large temperature gradient, then mode A is recommended. Rule 3: If it is required to reach an extremely low surface temperature in a very short time to simulate a cold wave, then it is recommended to enable mode C; Rule 4: If it is necessary to simulate complex working conditions, the combined mode is recommended; Each freeze-thaw mode execution module is physically integrated on a unified test platform. The environmental chamber of mode B is designed with openable and closable doors or movable walls to enable or adjust the components of mode A and mode C without disassembling the physical model.

10. The application method of a multi-mode adaptive freeze-thaw system according to claim 8, characterized in that, In step S8, the active construction of the gradient temperature field specifically includes: first, starting mode B to stabilize the temperature of the environmental chamber near the deep target temperature; then starting mode A to enhance temperature control of the slope surface area; and finally, by comparing the data from the surface and deep sensors in real time, dynamically fine-tuning the background temperature of mode B and the surface power of mode A, so that the measured gradient approaches and stabilizes within the target gradient range.

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