Device and method for simulating dust migration rule in high-temperature and high-humidity environment

Abstract

The invention discloses a device and method for simulating a dust migration rule in a high-temperature and high-humidity environment, and the device comprises a tunnel simulation cabin, a temperature and humidity regulation and control module, a wind speed regulation and control module, a dust generation and collection module, and a tunnel dust concentration distribution processing module. The temperature and humidity regulation and control module comprises an electric heater, an air-cooled refrigerating unit, an ultrasonic humidifier, a rotary dehumidifier, a temperature sensor and a humidity sensor; the wind speed regulation and control module comprises a negative pressure fan and a wind speed sensor; the dust generation and collection module comprises an aerosol generator and a dust collection bin; and the roadway dust concentration distribution processing module comprises a wide-range dust concentration sensor, a data acquisition card and an industrial computer. A roadway three-dimensional space dust concentration monitoring network is constructed, high-density and synchronous monitoring of a roadway three-dimensional space dust concentration field is achieved, the problem of dust migration and distribution law research is solved, and accurate and reliable experimental data and an analysis method are provided for optimization design of a ventilation dust removal technology.

Description

Technical Field

[0001] This invention belongs to the field of mine ventilation and dust control technology, specifically involving a device and method for simulating dust transport patterns under high temperature and high humidity conditions. It is particularly suitable for studying the effects of different ventilation methods (including forced in, extracted, and a combination of forced in and extracted) on the diffusion, settling, and concentration distribution of dust in roadways under complex hot and humid conditions in deep mines, providing accurate experimental simulation and data analysis methods for optimizing mine ventilation and dust removal and controlling dust sources. Background Technology

[0002] As shallow mineral resources become increasingly depleted, mining continues to advance into deeper areas, with kilometer-deep shafts becoming the norm in the industry. Deep mines generally face extreme environments of high temperature (15℃~60℃) and high humidity (30%~95% RH), resulting in unprecedented complexity in the transport, diffusion, and settling of rock dust and coal dust within the tunnels under the influence of ventilation airflow. This complexity directly determines the design efficiency of underground dust removal systems, the optimization potential of ventilation schemes, and, more importantly, the occupational health and safety of frontline miners. Accurately understanding the dust transport patterns under high temperature and high humidity conditions is the core theoretical foundation for developing scientific and efficient dust control strategies. However, current technologies in this field have three major shortcomings:

[0003] First, the ability to reproduce the environment is insufficient: existing experimental devices are unable to accurately and stably simulate the coupled environment of "high temperature-high humidity-multiple ventilation modes" in deep mines. Most devices can only control temperature, humidity or ventilation mode individually, and cannot achieve parameter linkage, resulting in a serious disconnect between experimental conditions and real working conditions, and greatly reducing the engineering guidance value of experimental results.

[0004] Secondly, the monitoring accuracy and dimensionality are limited: traditional studies often rely on simplified numerical models or single-point concentration measurements, lacking full-scale, high-density monitoring of dust concentration fields in the three-dimensional space of the tunnel. This localized observation method cannot reveal the true distribution characteristics and dynamic evolution process of dust in high-temperature and high-humidity airflows, making it difficult to support the design of refined dust removal solutions.

[0005] Third, the system integration and automation level are low: the existing simulation system's temperature and humidity control, wind speed regulation, dust generation and collection modules are independent of each other, lacking a unified linkage control and data acquisition platform. The experimental process requires frequent manual intervention, which is not only inefficient but also prone to introducing human error, resulting in poor experimental repeatability and insufficient data reliability.

[0006] Chinese utility model patent CN223597148U discloses a multifunctional horizontal wind tunnel for simulating dust environments. The tunnel includes a frame, a high-speed wind measurement section, a flared mixing section, a first flow equalization section, and a second flow equalization section. The high-speed wind measurement section is connected to the small-diameter section of the flared mixing section. The high-speed wind measurement section is equipped with a window and a high-speed standard connection port. The large-diameter end of the flared mixing section is connected to the first flow equalization section. The first and second flow equalization sections have the same diameter and a circular cross-section. The top of the second flow equalization section is equipped with a low-speed standard connection port, and the bottom of the second flow equalization section is equipped with a first sampling tube installation port and a second sampling tube installation port. Temperature and humidity sensors are also installed on the sidewall of the second flow equalization section, as well as a side sampling calibration installation port. An operation window with an operation chamber door is also provided on the sidewall of the second flow equalization section. This horizontal wind tunnel can meet the calibration requirements for high and low wind speeds and dust concentrations, exhibiting strong adaptability. However, this technical solution still has four major limitations: First, the environmental simulation accuracy is insufficient, and it can only passively monitor temperature and humidity, unable to actively regulate the high temperature and high humidity coupled environment of deep mines (15℃~60℃, 30%~95%RH); second, the ventilation mode is singular, and no pressure-in / extraction / pressure-extraction mixed ventilation switching device is set up, making it impossible to reproduce the real ventilation conditions of the mine; third, the monitoring dimensions are limited, and it can only achieve single-point dust concentration measurement, lacking three-dimensional full-scale monitoring capabilities; fourth, the system integration is low, with each module operating independently, failing to achieve multi-parameter linkage control, resulting in poor experimental efficiency and repeatability.

[0007] Therefore, there is an urgent need for a dedicated experimental device and method that can highly reproduce the humid and hot environment of deep mines, integrate multiple ventilation modes for simulation, and have high-precision distributed dust concentration monitoring capabilities, in order to make up for the deficiencies in basic research on dust transport under high temperature and high humidity conditions. Summary of the Invention

[0008] The purpose of this invention is to address the technical challenges of existing technologies, such as the lack of full-scale, high-density monitoring of dust concentration fields (including different cross-sections and locations) in the three-dimensional space of roadways, the independent functional modules of the simulation system, poor experimental efficiency and repeatability, and the difficulty in accurately and stably reproducing the complex environment of high temperature, high humidity, and multiple ventilation modes coupled in deep mines. This invention provides a device for simulating dust transport patterns under high temperature and high humidity conditions, thereby solving the problem that existing technologies cannot study the influence of complex thermal and humid conditions and multiple ventilation modes on the three-dimensional spatial transport patterns of dust in a controllable and stable environment.

[0009] Another objective of this invention is to provide a method for simulating the transport patterns of dust under high temperature and high humidity conditions.

[0010] To achieve the above-mentioned objectives of this invention, the device for simulating dust transport patterns under high temperature and high humidity environments comprises a tunnel simulation chamber, a temperature and humidity control module, a wind speed control module, a dust generation and collection module, and a tunnel dust concentration distribution processing module.

[0011] The tunnel simulation chamber is a cuboid structure with overall dimensions not exceeding 20m × 4.5m × 3.5m. The exterior of the tunnel simulation chamber is equipped with a sealed door and a double-layered glass observation window, while the interior is equipped with a rock wool insulation layer. The overall air leakage rate is ≤1% / h. The tunnel simulation chamber is used to provide a space for simulation experiments.

[0012] The temperature and humidity control module includes an electric heater, an air-cooled refrigeration unit, an ultrasonic humidifier, a rotary dehumidifier, a temperature sensor, and a humidity sensor. The electric heater and the air-cooled refrigeration unit are connected in parallel and connected to the tunnel simulation chamber via an air duct. The ultrasonic humidifier and the rotary dehumidifier are connected in parallel and connected to the tunnel simulation chamber via another air duct. The electric heater, air-cooled refrigeration unit, ultrasonic humidifier, and rotary dehumidifier are all installed in the rear equipment area of ​​the tunnel simulation chamber. The temperature sensor and humidity sensor are respectively suspended at designated positions inside the tunnel simulation chamber. The temperature and humidity control module is used for precise temperature and humidity control. The temperature and humidity inside the tunnel simulation chamber are precisely controlled; the total power of the electric heater is no more than 32kW, and independent temperature control is adopted; the cooling capacity of the air-cooled refrigeration unit is no less than 18kW; the humidification capacity of the ultrasonic humidifier is no less than 15kg / h; the dehumidification capacity of the rotary dehumidifier is no less than 20kg / h; the temperature and humidity control module is used to precisely control the temperature and humidity inside the tunnel simulation chamber, and precisely control the environment inside the chamber within the range of temperature 15℃~60℃ (accuracy ±1℃) and humidity 30%~95%RH (accuracy ±5%RH).

[0013] The wind speed control module includes a negative pressure fan and a wind speed sensor. The negative pressure fan is installed in the rear equipment area of ​​the tunnel simulation chamber and is connected to the tunnel simulation chamber through a duct. The wind speed sensor is located inside the tunnel simulation chamber and is arranged at intervals along the length of the tunnel. The frequency control range of the inverter of the negative pressure fan is 5~50Hz. By adjusting the fan frequency, a tunnel wind speed of 0~1m / s (accuracy ±0.05m / s) can be simulated, and it can be flexibly configured as a forced-in, forced-out, or forced-extraction hybrid ventilation mode.

[0014] The dust generation and collection module includes an aerosol generator and a dust collection chamber. The aerosol generator is installed at the front of the tunnel simulation chamber, and the dust collection chamber is installed at the rear equipment area of ​​the tunnel simulation chamber. The dust collection chamber is connected to a negative pressure fan through a pipeline. The aerosol generator can generate dust environments with an adjustable concentration of 0 to 500 mg / m³, suitable for coal dust or rock dust with a particle size of 20 μm to 200 μm, with a concentration control accuracy of ±5%. The aerosol generator is used to generate experimental dust in the tunnel simulation chamber, and the dust collection chamber is used to collect the experimental dust overflowing from the negative pressure fan.

[0015] The aforementioned roadway dust concentration distribution processing module includes a large-range dust concentration sensor, a data acquisition card, and an industrial computer. The large-range dust concentration sensor is installed inside the roadway simulation chamber, and a monitoring section is set at regular intervals along the length of the roadway in the roadway simulation chamber, and is arranged in the height and width directions respectively, so as to achieve high-density and synchronous monitoring of the dust concentration field in the three-dimensional space of the roadway.

[0016] The signal cables of the large-range dust concentration sensor, temperature sensor, humidity sensor, and wind speed sensor are connected to the data acquisition card, and then connected to an industrial computer with data processing software installed via a control bus.

[0017] Preferably, the dust collection bin is equipped with a bag filter.

[0018] Preferably, the large-range dust concentration sensor is set with a monitoring section every 2 to 4 meters along the length of the tunnel simulation chamber, preferably 3 meters; on each monitoring section, measuring points are evenly arranged at intervals of 0.3 to 0.6 meters in the width and height directions of the tunnel, preferably 0.5 meters, to form a three-dimensional monitoring grid containing at least 20 measuring points.

[0019] Preferably, in the wind speed control module, wind speed sensors are arranged every 3 to 6 meters along the length of the tunnel simulation chamber, with 5 meters being preferable.

[0020] Preferably, the thickness of the rock wool insulation layer is not less than 50 mm.

[0021] The present invention discloses a method for simulating dust transport patterns under high temperature and high humidity conditions, which comprises the following steps:

[0022] S1. Set the target temperature, humidity, ventilation mode, and wind speed via an industrial computer;

[0023] S2. Start the temperature and humidity control module and the wind speed control module. After the environmental parameters inside the cabin stabilize, start the aerosol generator to generate dust in the tunnel of the tunnel simulation cabin.

[0024] S3. Through the tunnel dust concentration distribution processing module, real-time dust concentration data of no less than 100 measuring points in each section of the entire tunnel are collected synchronously at a sampling interval of ≤0.5 seconds / time.

[0025] S4. Use data processing software to process the collected three-dimensional concentration field data and draw dust concentration contour maps and spatiotemporal evolution curves at different times and cross sections.

[0026] S5. Based on three-dimensional dynamic data, analyze the diffusion rate, settling pattern and spatial distribution characteristics of dust under different temperature and humidity conditions and different ventilation modes, and summarize its transport pattern.

[0027] The calculation formula and method are as follows:

[0028] Using the α monitoring sections arranged along the length of the tunnel in the tunnel simulation chamber (13), the time for the dust cloud head to reach each section is accurately obtained; the formula for calculating the axial average diffusion velocity of the dust cloud is:

[0029]

[0030] Among them, V d Let t1 be the axial average diffusion velocity of the dust cloud over a length L (m / s), where L is the distance (m) from the first monitoring section to the nth (n≤α) monitoring section, and t1 and t2 are also given. n These represent the times (in seconds) when the dust concentration reaches the preset threshold at the first and nth monitoring sections, respectively; this model is used to quantify the combined impact of ventilation velocity, temperature, and humidity on dust diffusion velocity; the calculation formula is:

[0031]

[0032] Among them, V d denoted as axial diffusion velocity of dust cloud (m / s), V as ventilation velocity in tunnel (m / s), T as ambient temperature (°C), RH as relative humidity (%), T0 and RH0 as reference temperature and humidity, and a, b, c, d as model coefficients obtained by fitting experimental data from this device.

[0033] Let the number of layers in the monitoring section be β, and the number of columns be γ. Using δ = β × γ measuring points arranged on each monitoring section, and utilizing the synchronous concentration data of the measuring points, the dust mass percentage at different height layers is calculated. The calculation formula is:

[0034]

[0035] Among them, S i (t) represents the settlement intensity index of the i-th (i≤α) monitoring section at time t, C ijk (t) represents the dust concentration (mg / m³) at the i-th cross section, j-th layer, and k-th column measuring point at time t.3 ), h j Let H be the height (m) of the measuring point above the tunnel floor, and H be the tunnel height. Based on this, the spatiotemporal evolution model of the settlement index is derived as follows:

[0036]

[0037] Where S(x,t) is the settlement intensity index at location x and time t in the tunnel, which is a function F of ambient temperature T, relative humidity RH, ventilation speed V, ventilation mode, location x, and time t. This functional relationship is determined by two-dimensional interpolation or fitting methods based on the obtained experimental data. The settlement intensity index is obtained by analyzing S(x,t) at different times and cross-sections. i (t) is analyzed to establish a two-dimensional distribution model S(x,t) of the settlement index along the tunnel length (x) and time (t) in order to visualize and quantify the development of the settlement process in the entire tunnel;

[0038] Finally, the dust removal efficiency index of the ventilation mode is calculated, providing a quantitative indicator based on full-space data for evaluating the dust removal efficiency of different ventilation modes; the calculation formula is:

[0039]

[0040] Where η is the result of t e Dust emission efficiency (%) after time, M(t) p ) is the time when dust generation ends (t) p The peak total mass (mg) of dust in the roadway, M(t) e () represents the elapsed time t e The total mass of dust remaining in the tunnel after the ventilation mode (mg); this formula obtains a characteristic time constant characterizing the dust removal speed of the ventilation mode by fitting the dust decay curve. The calculation formula is as follows:

[0041]

[0042] Where M(t) is the total mass of dust in the roadway at time t (mg), M0 is the initial mass of the fitted material (mg), and τ is the cleaning time constant (s); the smaller the value of τ, the faster the dust is discharged under this ventilation mode.

[0043] Compared with the prior art, the device and method of the present invention for simulating the dust transport law under high temperature and high humidity environment, after adopting the above technical solution, has the following beneficial effects:

[0044] (1) The device designed to simulate the dust transport pattern under high temperature and high humidity conditions can highly restore the real working conditions, break through the environmental simulation limitations of existing devices, and accurately reproduce the extreme environment of deep mines with high temperature of 15℃~60℃ and high humidity of 30%~95%RH, with the error controlled within ±1℃ / ±5%RH; at the same time, it supports flexible switching and stable operation of three ventilation modes: forced in, extracted, and mixed forced extraction. The experimental conditions are highly matched with the real working conditions underground, which fundamentally solves the problem of disconnect between traditional simulation and the field, and the experimental reliability is strong.

[0045] (2) Data acquisition enables full-scale, high-density monitoring and precise capture of the three-dimensional concentration field. An innovative three-dimensional dust concentration monitoring network for the tunnel was constructed: a monitoring section was set up every 2-4 meters, and measuring points were evenly arranged at 0.3-0.6 meter intervals along both the width and height directions of each monitoring section, forming a three-dimensional monitoring grid containing at least 20 measuring points, achieving millimeter-level grid coverage of the tunnel section. Compared to traditional single-point / sparse-point measurements, this device can simultaneously acquire real-time concentration data from hundreds of measuring points throughout the entire tunnel, completely reconstructing the spatial distribution gradient and evolution process of dust, providing full-dimensional, high-density core data support for the study of its patterns.

[0046] (3) The constructed models and formulas can quantify and analyze transport characteristics, providing a scientific basis for prevention and control design. Based on full-scale monitoring data, the spatiotemporal evolution of the axial diffusion velocity of dust clouds, the proportion of dust mass at different heights, and the settling intensity index can be accurately quantified. At the same time, the dust removal efficiency index and cleaning time constant can be used to quantitatively compare the dust removal effects of different ventilation modes. These quantitative indicators can intuitively reveal the coupled effects of temperature, humidity, and ventilation parameters on dust diffusion, settling, and discharge, providing a direct scientific basis for the optimized design of ventilation and dust removal systems in deep mines and the formulation of dust source control solutions.

[0047] (4) The system deeply integrates functional modules such as temperature and humidity control, wind speed regulation, dust generation and collection, three-dimensional concentration monitoring, and intelligent data analysis to achieve multi-parameter linkage control and real-time data processing. The entire experimental process is automated, and the entire process of environmental parameter stabilization, dust generation, data collection and analysis can be completed without human intervention. This not only improves experimental efficiency by more than 30%, but also ensures the repeatability of experimental results through precise parameter control, providing a reliable guarantee for batch and comparative studies. Attached Figure Description

[0048] Figure 1 This is a three-dimensional view of a device for simulating dust transport patterns under high temperature and high humidity conditions, according to the present invention.

[0049] Figure 2 This is the front view of the present invention.

[0050] Figure 3 This is a side view of the present invention.

[0051] Figure 4 This is a top view of the present invention.

[0052] Figure 5 This is a three-dimensional perspective view of the present invention.

[0053] Figure 6 This is the perspective front view of the present invention.

[0054] Figure 7 This is a perspective top view of the present invention.

[0055] Figure 8 This is a perspective side view of the present invention.

[0056] Figure 9 This is a schematic diagram of the insulation layer arrangement of the present invention.

[0057] Figure 10 This is a schematic diagram of the dust concentration monitoring section measurement point layout according to the present invention.

[0058] Figure 11 This is a schematic diagram of the internal layout of the dust collection bin of the present invention.

[0059] Figure 12 This is a flowchart illustrating the control process of a device for simulating dust transport patterns under high temperature and high humidity conditions during practical application.

[0060] The attached diagram is labeled as follows: 1-Electric heater; 2-Air-cooled refrigeration unit; 3-Ultrasonic humidifier; 4-Rotary dehumidifier; 5-Temperature sensor; 6-Humidity sensor; 7-Negative pressure fan; 8-Wind speed sensor; 9-Aerosol generator; 10-Dust collection bin; 11-Bag filter; 12-Large range dust concentration sensor; 13-Tunnel simulation chamber; 14-Sealed door; 15-Double-layer glass observation window; 16-Rock wool insulation layer. Detailed Implementation

[0061] The following will describe in more detail, with reference to the accompanying drawings of the embodiments of the present invention, an apparatus and method for simulating dust transport patterns under high temperature and high humidity environments. Obviously, the described embodiments are only a part of the embodiments of the present invention, and not all of them. All other embodiments obtained by those skilled in the art based on the embodiments of the present invention without creative effort are within the scope of protection of the present invention.

[0062] Depend on Figure 1 The image shown is a three-dimensional view of a device for simulating dust transport patterns under high temperature and high humidity conditions, as described in this invention, and is combined with... Figures 2-11As can be seen, the device for simulating dust transport patterns under high temperature and high humidity conditions according to the present invention is composed of a tunnel simulation chamber 13, a temperature and humidity control module, a wind speed control module, a dust generation and collection module, and a tunnel dust concentration distribution processing module.

[0063] The tunnel simulation chamber 13 has a rectangular structure. The exterior of the chamber is equipped with a sealed door 14 and double-layered glass observation windows 15, while the interior is insulated with rock wool insulation 16. The tunnel simulation chamber 13 provides a space for simulated experiments. In this embodiment, the tunnel simulation chamber 13 serves as the core experimental carrier, with overall dimensions of 20m × 4.5m × 3.5m (length × width × height). The internal tunnel body measures 15m × 3m × 2.5m (length × width × height) and has a rectangular cross-section, divided into the tunnel body, a front-end equipment area, and a rear-end equipment area. The chamber frame is made of Q235 galvanized steel plate, and the left and right sides of the wall panels feature double-layered tempered glass observation windows 15 for easy experimental observation. The exterior of the chamber is equipped with a sealed door 14, and an inspection door is installed every 5 meters along the length of the chamber. To ensure environmental stability, a rock wool insulation layer 16 with a thickness of not less than 50mm is adhered to the inner side of the chamber wall panels. Testing shows that the overall air leakage rate is no greater than 1% / h. During installation, ensure that the flatness deviation of the ground is ≤3mm / m and the load-bearing capacity is ≥10kN / m².

[0064] The temperature and humidity control module includes an electric heater 1, an air-cooled refrigeration unit 2, an ultrasonic humidifier 3, a rotary dehumidifier 4, a temperature sensor 5, and a humidity sensor 6. The electric heater 1 and the air-cooled refrigeration unit 2 are connected in parallel and connected to the tunnel simulation chamber 13 through an air duct. The ultrasonic humidifier 3 and the rotary dehumidifier 4 are connected in parallel and connected to the tunnel simulation chamber 13 through another air duct. The electric heater 1, the air-cooled refrigeration unit 2, the ultrasonic humidifier 3, and the rotary dehumidifier 4 are all installed in the rear equipment area of ​​the tunnel simulation chamber 13. The temperature sensor 5 and the humidity sensor 6 are respectively suspended and installed at set positions inside the tunnel simulation chamber 13. The temperature and humidity control module is used to precisely control the temperature and humidity inside the tunnel simulation chamber 13.

[0065] The wind speed control module includes a negative pressure fan 7 and a wind speed sensor 8. The negative pressure fan 7 is installed in the rear equipment area of ​​the tunnel simulation chamber 13. The air inlet of the negative pressure fan 7 is connected to the air duct of the tunnel simulation chamber 13 through a flexible short pipe. The wind speed sensor 8 is located inside the tunnel simulation chamber 13 and is arranged every 5 meters along the length of the tunnel. The negative pressure fan 7 can be flexibly configured into a forced-in, forced-out, or mixed forced-out ventilation mode.

[0066] The dust generation and collection module includes an aerosol generator 9 and a dust collection chamber 10. The aerosol generator 9 is installed at the front of the tunnel simulation chamber 13, and the dust collection chamber 10 is installed in the rear equipment area of ​​the tunnel simulation chamber 13. The dust collection chamber 10 is connected to the negative pressure fan 7 through a pipeline, and a bag filter 11 is installed inside the dust collection chamber 10. The aerosol generator 9 is used to generate experimental dust in the tunnel simulation chamber 13, and the dust collection chamber 10 is used to collect the experimental dust overflowing from the negative pressure fan 7.

[0067] The aforementioned roadway dust concentration distribution processing module includes a large-range dust concentration sensor 12, a data acquisition card, and an industrial computer. The large-range dust concentration sensor 12 has a monitoring section set every 3 meters along the length of the roadway in the roadway simulation chamber 13. On each monitoring section, measuring points are evenly arranged at 0.5-meter intervals in the width and height directions of the roadway to form a three-dimensional monitoring grid containing at least 20 measuring points. The sampling interval of the data acquisition card is no greater than 0.5 seconds / time, and the storage capacity of the industrial computer is no less than 1TB.

[0068] The signal cables of the large-range dust concentration sensor 12, temperature sensor 5, humidity sensor 6, and wind speed sensor 8 are connected to the data acquisition card, and then connected to an industrial computer with data processing software installed via a control bus. The data processing software has the functions of displaying the three-dimensional dust concentration field in real time, drawing the spatiotemporal evolution curve of dust concentration, and analyzing the dust diffusion rate and settling law. The data processing software reconstructs the dust concentration distribution cloud map in the three-dimensional space of the roadway at different times through interpolation calculation, and forms an animation through continuous time frame images to visualize the movement trajectory and concentration gradient evolution process of the dust cloud.

[0069] Depend on Figure 12 The diagram shown is a control flow chart of the device for simulating dust transport patterns under high temperature and high humidity conditions in practical application, and is also referenced. Figures 1-11 As can be seen, the method of the present invention for simulating the dust transport law under high temperature and high humidity environment is operated by the following steps:

[0070] S1: Experimental parameter setting and system startup

[0071] The experimental plan was set up using a human-machine interface (equipped with a 15-inch touchscreen) on an industrial computer. First, the target environmental parameters were set: the target temperature (range 15℃~60℃) and target humidity (range 30%~95%RH) within the tunnel were set via the software interface. Next, the ventilation mode and air velocity were set: the ventilation mode was selected as "forced in," "exhaust," or "combined force and exhaust," and the target air velocity was set (range 0~1m / s). All parameter settings supported precise step adjustment (temperature 0.1℃, humidity 1%RH, air velocity 0.01m / s).

[0072] S2: High Temperature and High Humidity Environment Creation and Stabilization

[0073] After confirming the parameters, the temperature and humidity control module is activated. The system automatically adjusts based on real-time feedback from temperature sensor 5 and humidity sensor 6.

[0074] If the temperature is lower than the set value, the electric heater will start in stages (total power ≤ 32kW, with 3 independent temperature control circuits) to heat the water.

[0075] If the temperature is higher than the set value, the air-cooled refrigeration unit 2 (cooling capacity ≥18kW) will start to cool down;

[0076] If the humidity is lower than the set value, the ultrasonic humidifier 3 (humidification capacity ≥15kg / h) will start humidifying;

[0077] If the humidity is higher than the set value, the rotary dehumidifier 4 (dehumidification capacity ≥ 20 kg / h) will start dehumidification.

[0078] The control system employs a PID algorithm to automatically compensate for deviations until the cabin temperature fluctuation is ≤±5℃ / h and the humidity fluctuation is ≤±5%RH / h, reaching the set steady state. This process typically takes 30-60 minutes to complete.

[0079] S3: Ventilation flow field establishment and dust injection

[0080] Once the temperature and humidity have stabilized, the fan speed control module is activated. Based on the ventilation mode selected in S1, the control system automatically configures the operating logic of the negative pressure fan 7:

[0081] Forced ventilation: The negative pressure fan 7 works as an intake fan, drawing in air from outside the cabin and sending it into the tunnel after being guided;

[0082] Exhaust ventilation: The negative pressure fan 7 works as an exhaust fan to draw air from the tunnel;

[0083] Hybrid pressure-extraction: By configuring additional air valves (not shown in the figure, but supported by the actual system) and linking them with fans, a complex hybrid ventilation network is simulated.

[0084] By adjusting the frequency of the inverter of the negative pressure fan 7 (5~50Hz), the average cross-sectional wind speed monitored by the wind speed sensor 8 is precisely controlled within the set value with an accuracy of ±0.05m / s, ensuring that the cross-sectional wind speed uniformity deviation is ≤0.2m / s. After the flow field stabilizes, the aerosol generator 9 of the dust generation and collection module is started. This generator can produce coal dust or rock dust with an adjustable concentration range of 0~500mg / m³, suitable for particle sizes of 20μm~200μm, with a concentration control accuracy of ±5%. The dust enters the roadway simulation chamber 13 under the airflow.

[0085] S4: Synchronous Monitoring and Data Acquisition of Three-Dimensional Dust Concentration Field

[0086] Simultaneously with dust injection, the roadway dust concentration distribution processing module is activated. The core of this module is a high-density network of large-range dust concentration sensors (12). Specifically, a monitoring section is set up every 3 meters along the roadway length. On each section (3m wide × 2.5m high), 5 measuring points are placed at 0.5m intervals in the width direction and 4 measuring points at 0.5m intervals in the height direction, forming a monitoring grid of 20 measuring points. Therefore, in the entire 15m long core section of the roadway, a total of 5 sections are set up, totaling 100 real-time dust concentration monitoring points.

[0087] The data acquisition card synchronously collects data from 100 dust concentration measurement points, as well as data from temperature, humidity, and wind speed sensors at each cross-section, at sampling intervals of no more than 0.5 seconds. All data is transmitted to an industrial computer in real time, where data processing software receives, timestamps, and stores the data. The system has a storage capacity of no less than 1TB, supporting long-term continuous experiments.

[0088] S5: Dust Transport Pattern Analysis and Visualization

[0089] After the experiment, the massive amount of spatiotemporal data was processed and analyzed using data processing software:

[0090] Spatiotemporal evolution curve plotting: The software can plot the curve of the average dust concentration changing over time at any specified measuring point or cross section, intuitively showing the diffusion and settling process of dust with ventilation airflow;

[0091] 3D Concentration Field Reconstruction: Using synchronous data from 100 measuring points, the software can interpolate and reconstruct the dust concentration distribution cloud map in the 3D space of the tunnel at different times. Through images of continuous time frames, the migration trajectory of the dust cloud in the tunnel, the advancing speed of the diffusion front, and the evolution of the concentration gradient can be displayed in animation.

[0092] Quantitative analysis of patterns:

[0093] Diffusion law: By analyzing the time difference of the concentration reaching the peak at different cross sections and locations, the axial diffusion velocity of dust under specific ventilation modes and wind speeds is calculated;

[0094] Distribution patterns: By comparing concentration data at different heights and widths of the same cross section, the settling and suspension distribution characteristics of dust on the roadway cross section are analyzed, and the interaction between gravity settling and turbulent diffusion is studied.

[0095] Impact of ventilation mode:

[0096] By calling up experimental data under different ventilation modes (injection, extraction, and mixing), the differences in dust concentration field structure, residence time, and discharge efficiency are directly compared, providing a quantitative basis for the design of underground ventilation and dust removal.

[0097] The calculation formula and method are as follows:

[0098] Using α monitoring sections arranged along the length of tunnel 13 in the tunnel simulation chamber, the time it takes for the dust cloud head to reach each section is accurately obtained; the formula for calculating the average axial diffusion velocity of the dust cloud is:

[0099]

[0100] Among them, V d Let t1 be the axial average diffusion velocity of the dust cloud over a length L (m / s), where L is the distance (m) from the first monitoring section to the nth (n≤α) monitoring section, and t1 and t2 are also given. n These represent the times (in seconds) when the dust concentration reaches a preset threshold (e.g., 10% of the peak concentration) at the first and nth monitoring sections, respectively. This model can be used to quantify the combined effects of ventilation velocity, temperature, and humidity on dust diffusion velocity. The calculation formula is:

[0101]

[0102] Among them, V d denoted as axial diffusion velocity of dust cloud (m / s), V as ventilation velocity in tunnel (m / s), T as ambient temperature (°C), RH as relative humidity (%), T0 and RH0 as reference temperature and humidity, and a, b, c, d as model coefficients obtained by fitting experimental data from this device.

[0103] In addition, using β layers × γ columns of measuring points arranged on each monitoring section, a total of δ measuring points (δ = β × γ) are used. In this example, each monitoring section has 20 measuring points (4 layers × 5 columns). Using the synchronous concentration data of the measuring points, the dust mass ratio of different height layers can be calculated. The calculation formula is:

[0104]

[0105] Among them, S i (t) represents the settlement intensity index (dimensionless) of the i-th (i≤α) monitoring section at time t, C ijk (t) represents the dust concentration (mg / m³) at the i-th cross section, j-th (j≤β) layer (height direction), and k-th (k≤γ) column (width direction) at time t. 3 ), h j Let H be the height (m) of the measuring point above the tunnel floor, and H be the tunnel height. Based on this, the spatiotemporal evolution model of the settlement index can be derived as follows:

[0106]

[0107] Where S(x,t) is the settlement intensity index at location x and time t in the tunnel, which is a function F of ambient temperature T, relative humidity RH, ventilation velocity V, ventilation mode, location x, and time t. This functional relationship can be determined by two-dimensional interpolation or fitting methods using experimental data obtained from the device of this invention. This model is used to describe the continuous change of the settlement intensity index in the entire tunnel's spatial and temporal dimensions, and is an extension of the aforementioned discrete calculation. By analyzing S(x,t) at different times and different cross-sections... i By analyzing (t), a two-dimensional distribution model S(x,t) of the settlement index along the tunnel length (x) and time (t) can be established to visualize and quantify the development of the settlement process throughout the tunnel.

[0108] Finally, this device can be used to calculate the dust removal efficiency index of ventilation modes, providing a quantitative indicator based on full-space data for evaluating the dust removal efficiency of different ventilation modes. The calculation formula is:

[0109]

[0110] Where η is the result of t e Dust emission efficiency (%) after time, M(t) p ) is the time when dust generation ends (t) p The peak total mass (mg) of dust in the roadway, M(t) e () represents the elapsed time t e The total mass (mg) of residual dust in the tunnel after ventilation. This formula, by fitting the dust decay curve, obtains a characteristic time constant characterizing the dust removal speed of the ventilation mode. The calculation formula is as follows:

[0111]

[0112] Where M(t) is the total mass of dust in the roadway at time t (mg), M0 is the initial mass of the fitted material (mg), and τ is the cleaning time constant (s). The smaller the value of τ, the faster the dust is discharged under this ventilation mode.

[0113] Typical application examples

[0114] Taking the study of "coal dust transport patterns under forced ventilation, wind speed of 0.8 m / s, temperature of 40℃, and humidity of 85%RH" as an example:

[0115] Set the above parameters on the industrial computer and start the system. After about 45 minutes, the environment inside the chamber stabilized at a temperature of (40±1)℃, humidity of (85±5)%RH, and wind speed of (0.8±0.05)m / s.

[0116] Start aerosol generator 9 to rapidly increase and stabilize the dust concentration at 300 mg / m³.

[0117] The system automatically began high-speed data acquisition. The experiment lasted 60 minutes.

[0118] Data processing software analysis revealed that under these conditions, the dust cloud head reached the end of the tunnel (15m) approximately 100 seconds after startup, with an axial diffusion velocity of about 0.15m / s. The cross-sectional concentration distribution showed that the concentration was higher in the area below 1.0m from the floor, exhibiting a clear settling trend. Comparison data with exhaust ventilation indicated that the dust concentration decreased faster in the later section of the tunnel under forced ventilation.

[0119] During the experiment, the escaped dust was collected by the end dust collection bin 10 and filtered by the bag filter 11, with a dust collection efficiency of ≥95%, ensuring a clean experimental environment.

[0120] It should be noted that the terms "upper," "lower," "left," "right," "inner," "outer," "front," "rear," and "top / bottom" used in this invention indicate the orientation or positional relationship based on the orientation or positional relationship shown in the accompanying drawings. They are only for the convenience of describing this invention and simplifying the description, and do not indicate or imply that the parts or elements referred to must have a specific orientation, or be constructed and operated in a specific orientation. The terms "first" and "second" are also only for the convenience of description and distinction, and therefore should not be construed as limitations on this invention.

[0121] The above description is only a preferred embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any equivalent substitutions or modifications made by those skilled in the art within the scope of the technology disclosed in the present invention, based on the technical solution and inventive concept of the present invention, should be covered within the scope of protection of the present invention.

Claims

1. A device for simulating dust transport patterns under high temperature and high humidity conditions, characterized in that... It consists of a tunnel simulation chamber (13), a temperature and humidity control module, a wind speed control module, a dust generation and collection module, and a tunnel dust concentration distribution processing module. The tunnel simulation chamber (13) is a cuboid structure with an overall external size of no more than 20m×4.5m×3.5m. The tunnel simulation chamber (13) is equipped with a sealed door (14) and a double-layered glass observation window (15) on the outside, and a rock wool insulation layer (16) on the inside. The tunnel simulation chamber (13) is used to provide a simulation experimental space. The temperature and humidity control module includes an electric heater (1), an air-cooled refrigeration unit (2), an ultrasonic humidifier (3), a rotary dehumidifier (4), a temperature sensor (5), and a humidity sensor (6). The electric heater (1) and the air-cooled refrigeration unit (2) are connected in parallel and connected to the tunnel simulation chamber (13) through a duct. The ultrasonic humidifier (3) and the rotary dehumidifier (4) are connected in parallel and connected to the tunnel simulation chamber (13) through another duct. The electric heater (1), the air-cooled refrigeration unit (2), the ultrasonic humidifier (3), and the rotary dehumidifier (4) are all installed in the tunnel. The rear equipment area of ​​the tunnel simulation cabin (13); temperature sensor (5) and humidity sensor (6) are respectively suspended and installed in the set positions inside the tunnel simulation cabin (13); temperature and humidity control module is used to accurately control the temperature and humidity inside the tunnel simulation cabin (13); the total power of the electric heater (1) is not greater than 32kW, and independent temperature control is adopted; the cooling capacity of the air-cooled refrigeration unit (2) is not less than 18kW; the humidification capacity of the ultrasonic humidifier (3) is not less than 15kg / h; the dehumidification capacity of the rotary dehumidifier (4) is not less than 20kg / h; The wind speed control module includes a negative pressure fan (7) and a wind speed sensor (8). The negative pressure fan (7) is installed in the rear equipment area of ​​the tunnel simulation chamber (13). The negative pressure fan (7) is connected to the tunnel simulation chamber (13) through a duct. The wind speed sensor (8) is located inside the tunnel simulation chamber (13) and is arranged at intervals along the length of the tunnel. The frequency control range of the inverter of the negative pressure fan (7) is 5~50Hz. The dust generation and collection module includes an aerosol generator (9) and a dust collection chamber (10). The aerosol generator (9) is installed at the front of the tunnel simulation chamber (13), and the dust collection chamber (10) is installed at the rear equipment area of ​​the tunnel simulation chamber (13). The dust collection chamber (10) is connected to the negative pressure fan (7) through a pipeline. The aerosol generator (9) can generate dust environments with a concentration adjustable from 0 to 500 mg / m³, suitable for coal dust or rock dust with a particle size of 20 μm to 200 μm, and the concentration control accuracy is ±5%. The aerosol generator (9) is used to generate experimental dust in the tunnel simulation chamber (13), and the dust collection chamber (10) is used to collect the experimental dust overflowing from the negative pressure fan (7). The roadway dust concentration distribution processing module includes a large-range dust concentration sensor (12), a data acquisition card, and an industrial computer. The large-range dust concentration sensor (12) is installed in the roadway simulation chamber (13), and a monitoring section is set at regular intervals along the roadway length direction of the roadway simulation chamber (13), and is arranged in the height direction and width direction respectively, so as to realize high-density and synchronous monitoring of the dust concentration field in the three-dimensional space of the roadway. The signal cables of the large-range dust concentration sensor (12), temperature sensor (5), humidity sensor (6) and wind speed sensor (8) are connected to the data acquisition card and then connected to an industrial computer with data processing software installed via the control bus.

2. The device for simulating dust transport patterns under high temperature and high humidity environments as described in claim 1, characterized in that: The dust collection bin (10) is equipped with a bag filter (11).

3. The device for simulating dust transport patterns under high temperature and high humidity environments as described in claim 1, characterized in that: The large-range dust concentration sensor (12) is set with a monitoring section every 2 to 4 meters along the length of the roadway simulation chamber (13); on each monitoring section, measuring points are evenly arranged at intervals of 0.3 to 0.6 meters in the width and height directions of the roadway to form a three-dimensional monitoring grid containing at least 20 measuring points.

4. The device for simulating dust transport patterns under high temperature and high humidity environments as described in claim 1, characterized in that: In the wind speed control module, wind speed sensors (8) are arranged every 3 to 6 meters along the length of the tunnel in the tunnel simulation cabin (13).

5. The device for simulating dust transport patterns under high temperature and high humidity environments as described in claim 1, characterized in that: The thickness of the rock wool insulation layer (16) is not less than 50 mm.

6. The device for simulating dust transport patterns under high temperature and high humidity environments as described in claim 1, characterized in that: The negative pressure fan (7) can be flexibly configured as a forced-in, forced-out, or forced-extraction mixed ventilation mode.

7. A method for simulating dust transport patterns under high temperature and high humidity conditions, characterized in that... The simulation device used consists of a tunnel simulation chamber (13), a temperature and humidity control module, a wind speed control module, a dust generation and collection module, and a tunnel dust concentration distribution processing module. The tunnel simulation chamber (13) is a cuboid structure with an overall external size of no more than 20m×4.5m×3.5m. The tunnel simulation chamber (13) is equipped with a sealed door (14) and a double-layered glass observation window (15) on the outside, and a rock wool insulation layer (16) on the inside. The tunnel simulation chamber (13) is used to provide a simulation experimental space. The temperature and humidity control module includes an electric heater (1), an air-cooled refrigeration unit (2), an ultrasonic humidifier (3), a rotary dehumidifier (4), a temperature sensor (5), and a humidity sensor (6). The electric heater (1) and the air-cooled refrigeration unit (2) are connected in parallel and connected to the tunnel simulation chamber (13) through a duct. The ultrasonic humidifier (3) and the rotary dehumidifier (4) are connected in parallel and connected to the tunnel simulation chamber (13) through another duct. The electric heater (1), the air-cooled refrigeration unit (2), the ultrasonic humidifier (3), and the rotary dehumidifier (4) are all installed in the tunnel. The rear equipment area of ​​the tunnel simulation cabin (13); temperature sensor (5) and humidity sensor (6) are respectively suspended and installed in the set positions inside the tunnel simulation cabin (13); temperature and humidity control module is used to accurately control the temperature and humidity inside the tunnel simulation cabin (13); the total power of the electric heater (1) is not greater than 32kW, and independent temperature control is adopted; the cooling capacity of the air-cooled refrigeration unit (2) is not less than 18kW; the humidification capacity of the ultrasonic humidifier (3) is not less than 15kg / h; the dehumidification capacity of the rotary dehumidifier (4) is not less than 20kg / h; The wind speed control module includes a negative pressure fan (7) and a wind speed sensor (8). The negative pressure fan (7) is installed in the rear equipment area of ​​the tunnel simulation chamber (13). The negative pressure fan (7) is connected to the tunnel simulation chamber (13) through a duct. The wind speed sensor (8) is located inside the tunnel simulation chamber (13) and is arranged every 3 to 6 meters along the length of the tunnel. The frequency control range of the inverter of the negative pressure fan (7) is 5 to 50 Hz. The negative pressure fan (7) can be flexibly configured as a forced-in, forced-out, or a mixed forced-out ventilation mode. The dust generation and collection module includes an aerosol generator (9) and a dust collection chamber (10). The aerosol generator (9) is installed at the front of the tunnel simulation chamber (13), and the dust collection chamber (10) is installed at the rear equipment area of ​​the tunnel simulation chamber (13). The dust collection chamber (10) is connected to the negative pressure fan (7) through a pipeline. The aerosol generator (9) can generate dust environments with a concentration adjustable from 0 to 500 mg / m³, suitable for coal dust or rock dust with a particle size of 20 μm to 200 μm, and the concentration control accuracy is ±5%. The aerosol generator (9) is used to generate experimental dust in the tunnel simulation chamber (13), and the dust collection chamber (10) is used to collect the experimental dust overflowing from the negative pressure fan (7). The roadway dust concentration distribution processing module includes a large-range dust concentration sensor (12), a data acquisition card, and an industrial computer; the large-range dust concentration sensor (12) is set with a monitoring section every 2 to 4 meters along the roadway length direction of the roadway simulation chamber (13); on each monitoring section, measuring points are evenly arranged at intervals of 0.3 to 0.6 meters in the roadway width and height directions to form a three-dimensional monitoring grid containing at least 20 measuring points; The signal cables of the large-range dust concentration sensor (12), temperature sensor (5), humidity sensor (6) and wind speed sensor (8) are connected to the data acquisition card and then connected to an industrial computer with data processing software installed via the control bus. The following steps should be followed when using it: S1. Set the target temperature, humidity, ventilation mode, and wind speed via an industrial computer; S2. Start the temperature and humidity control module and the wind speed control module. After the environmental parameters inside the cabin stabilize, start the aerosol generator (9) to generate dust in the tunnel of the tunnel simulation cabin (13). S3. Through the tunnel dust concentration distribution processing module, real-time dust concentration data of no less than 100 measuring points in each section of the entire tunnel are collected synchronously at a sampling interval of ≤0.5 seconds / time. S4. Use data processing software to process the collected three-dimensional concentration field data and draw dust concentration contour maps and spatiotemporal evolution curves at different times and cross sections. S5. Based on three-dimensional dynamic data, analyze the diffusion rate, settling pattern and spatial distribution characteristics of dust under different temperature and humidity conditions and different ventilation modes, and summarize its transport pattern. The calculation formula and method are as follows: Using the α monitoring sections arranged along the length of the tunnel in the tunnel simulation chamber (13), the time for the dust cloud head to reach each section is accurately obtained; the formula for calculating the axial average diffusion velocity of the dust cloud is: Among them, V d Let t1 be the axial average diffusion velocity of the dust cloud over a length L (m / s), where L is the distance (m) from the first monitoring section to the nth (n≤α) monitoring section, and t1 and t2 are also given. n These represent the times (in seconds) when the dust concentration reaches the preset threshold at the first and nth monitoring sections, respectively; this model is used to quantify the combined impact of ventilation velocity, temperature, and humidity on dust diffusion velocity; the calculation formula is: Among them, V d denoted as axial diffusion velocity of dust cloud (m / s), V as ventilation velocity in tunnel (m / s), T as ambient temperature (°C), RH as relative humidity (%), T0 and RH0 as reference temperature and humidity, and a, b, c, d as model coefficients obtained by fitting experimental data from this device. Let the number of layers in the monitoring section be β, and the number of columns be γ. Using δ = β × γ measuring points arranged on each monitoring section, and utilizing the synchronous concentration data of the measuring points, the dust mass percentage at different height layers is calculated. The calculation formula is: Among them, S i (t) represents the settlement intensity index of the i-th (i≤α) monitoring section at time t, C ijk (t) represents the dust concentration (mg / m³) at the i-th cross section, j-th layer, and k-th column measuring point at time t. 3 ), h j Let H be the height (m) of the measuring point above the tunnel floor, and H be the tunnel height. Based on this, the spatiotemporal evolution model of the settlement index is derived as follows: Where S(x,t) is the settlement intensity index at location x and time t in the tunnel, which is a function F of ambient temperature T, relative humidity RH, ventilation speed V, ventilation mode, location x, and time t. This functional relationship is determined by two-dimensional interpolation or fitting methods based on the obtained experimental data. The settlement intensity index is obtained by analyzing S(x,t) at different times and cross-sections. i (t) is analyzed to establish a two-dimensional distribution model S(x,t) of the settlement index along the tunnel length (x) and time (t) in order to visualize and quantify the development of the settlement process in the entire tunnel; Finally, the dust removal efficiency index of the ventilation mode is calculated, providing a quantitative indicator based on full-space data for evaluating the dust removal efficiency of different ventilation modes; the calculation formula is: Where η is the result of t e Dust emission efficiency (%) after time, M(t) p ) is the time when dust generation ends (t) p The peak total mass (mg) of dust in the roadway, M(t) e () represents the elapsed time t e The total mass of dust remaining in the tunnel after the ventilation mode (mg); this formula obtains a characteristic time constant characterizing the dust removal speed of the ventilation mode by fitting the dust decay curve. The calculation formula is as follows: Where M(t) is the total mass of dust in the roadway at time t (mg), M0 is the initial mass of the fitted material (mg), and τ is the cleaning time constant (s); the smaller the value of τ, the faster the dust is discharged under this ventilation mode.

8. The method for simulating dust transport patterns under high temperature and high humidity environments as described in claim 1, characterized in that: The dust collection bin (10) is equipped with a bag filter (11).

9. The method for simulating dust transport patterns under high temperature and high humidity environments as described in claim 1, characterized in that: The thickness of the rock wool insulation layer (16) is not less than 50 mm.

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