Airflow-dust-behavior coupling exposure risk experiment system and method

Abstract

The invention relates to the technical field of individual exposure risk assessment, and particularly discloses an airflow-dust-behavior coupling exposure risk experiment system and method, and the system comprises a multi-agent behavior simulation and control module which comprises a motion control unit which is used for generating and sending a motion instruction to each manned mobile platform, and a breathing parameter control unit; the dynamic dust source generation and regulation and control module is used for generating a dust source of which the release position, strength and physical property parameters can be regulated and controlled in real time in the experiment module; the variable wind field generation and regulation module is used for generating a ventilation airflow field of which the wind speed and the wind direction can be dynamically adjusted in the experiment module; an empirical research platform capable of simulating and quantifying the dust inhalation risk is constructed by integrating a remote-control movable simulation human model, a programmable movable dust source, a dynamically adjustable wind field and high-temporal-spatial-resolution real-time monitoring in a unified experiment module.

Description

Technical Field

[0001] This invention relates to the field of individual exposure risk assessment technology, specifically an airflow-dust-behavior coupled exposure risk experimental system and method. Background Technology

[0002] Pneumoconiosis has become the most serious occupational disease in my country, characterized by four major features: large existing cases, rapid increase, incurability, and lifelong disability. Furthermore, pneumoconiosis exhibits a trend of "crossing industries, multiple occupations, and high concentration," becoming a major public health challenge faced by emerging fields such as coal mining, metal mining, building materials, metallurgy, machinery manufacturing, construction tunnels, and even gemstone photovoltaics. This invention, "An Integrated Platform for Simulation Experiment of Airflow-Dust-Behavior Coupling Exposure Risk Based on Multi-Agent Dynamic Interaction," urgently needs to provide repeatable and quantifiable dynamic dose assessment and protection verification methods for these multiple fields, thereby curbing the increase of pneumoconiosis at its source.

[0003] Currently, the assessment and research methods for workplace dust exposure risks are mainly divided into the following three categories, but they all have significant limitations when simulating real, dynamic, and complex industrial scenarios:

[0004] On-site measurement and individual sampling methods are currently the most direct and standard technical means in occupational health assessment. By deploying regional or individual samplers in real workplaces, they obtain legally valid time-weighted average exposure concentration data, which can most intuitively reflect the actual exposure status of workers.

[0005] The limitations of this method are significant: it is essentially a passive and delayed assessment approach, capable only of monitoring after exposure, and cannot be used for pre-exposure prediction or proactive optimization of protective measures; the assessment process is costly and time-consuming, making it difficult to support large-scale, multi-condition comparative studies; more importantly, its measurement results are only average concentrations over a period of time, completely failing to analyze the complex dynamic diffusion process of dust in transiently changing wind fields caused by human movement and changes in dust source location, and also failing to capture the instantaneous high-concentration impact on an individual's breathing zone. Furthermore, due to ethical and safety considerations, this method is completely unsuitable for human testing in extremely high-risk or unknown hazard scenarios.

[0006] The scaled-down or full-scale physical experiment method involves constructing a controllable scenario model in the laboratory and using tracer substances to study the distribution patterns of ventilation and dust. It has the advantages of being repeatable and highly controllable, and can partially reveal the basic characteristics of environmental flow fields and pollutant distribution.

[0007] This method suffers from fundamental flaws in its simulation of realism: Experiments typically use stationary dummies with fixed breathing patterns, which completely fail to simulate the autonomous movement, posture adjustments, and spatial interactions between multiple people in real-world operations. Human movement is precisely the core dynamic factor that disturbs local airflow and alters the exposure of the individual and those around them. Furthermore, the dust sources in the experiments are mostly fixed in location and constant in intensity, making it difficult to simulate the mobile or intermittent dust sources generated in actual production (such as material handling and mechanical cutting). In addition, limited by sensor density and sampling frequency, this method struggles to achieve accurate and continuous concentration monitoring with high spatiotemporal resolution for the rapidly changing microenvironment of the individual's breathing zone as the body moves.

[0008] Computational fluid dynamics (CFD) numerical simulation is a powerful tool for ventilation system design and research. It solves the equations of motion of fluids and particles by computer, and can simulate various ventilation and diffusion scenarios in a low cost and with flexibility.

[0009] The application of this method in dynamic exposure risk assessment faces severe challenges: the simulation of personnel behavior is highly abstract and simplified, and the calculations for simulating movement using techniques such as "dynamic mesh" are extremely complex, making it difficult to achieve realistic simulations of real-time, irregular interactions among multiple people and their bidirectional dynamic feedback with the flow field; the reliability of its model predictions heavily depends on boundary conditions, but the high-precision empirical data required for verification can only be obtained from the aforementioned static or simplified physical experiments, resulting in a lack of effective "gold standard" verification data for dynamic scenario simulations, forming a critical verification loop gap. Finally, CFD outputs a spatial concentration field, and individual dose assessment requires post-calculation by "substituting" pre-set, simplified personnel trajectories, which is an offline, uncoupled, indirect assessment that cannot reflect the real-time interaction between behavioral decisions and exposure risk. All of the above methods ignore the multi-field dynamic feedback of the human model's movement field, breathing field, dust field, and wind field, leading to high dose assessment errors. In addition, although some existing technologies have achieved dust generation, breathing simulation or wind speed control, they lack system integration for the spatial movement of dust sources, release timing waveforms, and dynamic coordinated control of wind speed and direction. Furthermore, they have not achieved exposure feedback simulation under multi-person collaborative operation, which makes it impossible to truly reflect the exposure mechanism of the dynamic coupling of "human-dust-wind" in industrial sites.

[0010] In summary, current methods, whether based on field measurements, physical experiments, or numerical simulations, all share a common core deficiency: the difficulty in achieving the synchronization, interaction, and coupling of the three key real-world elements—"dynamic personnel behavior," "dynamic dust release," and "dynamic ventilation adjustment"—within a controllable and repeatable experimental system. Furthermore, it is challenging to directly, accurately, and in real-time measure the changing inhaled dose for each individual. This deficiency results in a lack of effective quantitative research tools and validation platforms for assessing occupational health risks in complex dynamic work environments and optimizing personalized intelligent ventilation protection strategies. Summary of the Invention

[0011] The purpose of this invention is to provide an airflow-dust-behavior coupled exposure risk experimental system and method to solve the problems mentioned in the background art.

[0012] To achieve the above objectives, the present invention provides the following technical solution:

[0013] An airflow-dust-behavior coupled exposure risk experimental system, characterized in that the system comprises:

[0014] A physical experiment platform, comprising an experiment chamber and multiple manned mobile platforms disposed within the experiment chamber, wherein simulated individuals are arranged on the manned mobile platforms;

[0015] The multi-agent behavior simulation and control module includes a motion control unit for generating and sending motion commands to each manned mobile platform, and a respiratory parameter control unit for setting a differentiated respiratory model for each simulated individual;

[0016] The dynamic dust source generation and control module is used to generate dust sources in the experimental chamber whose release location, intensity, and physical property parameters can be controlled in real time.

[0017] The variable wind field generation and control module is used to generate a ventilation airflow field with dynamically adjustable wind speed and direction within the experimental chamber.

[0018] The monitoring and risk quantification module is signal-connected to the multi-agent behavior simulation and control module, the dynamic dust source generation and regulation module, and the variable wind field generation and regulation module. It performs the following actions: real-time acquisition of the actual pose, dust source release status, and wind field status data of each manned mobile platform; analysis of the turbulence induced by personnel movement based on the pose data, coupled with the variable wind field to construct a dynamic airflow field within the experimental chamber; simulation of dust diffusion and transport within the dynamic airflow field to form a dynamic dust concentration field; mapping exposure concentration from the breathing zone based on the real-time position of each manned mobile platform and its associated individualized breathing parameters to calculate the real-time cumulative inhalation dose; and outputting the dynamic exposure risk assessment result for each simulated individual based on the inhalation dose.

[0019] As a further embodiment of the present invention, the dynamic dust source generation and control module is a matrix dust nozzle array, including multiple independently controlled aerosol nozzles arranged in a row and column matrix on one side of the inner wall of the experimental chamber. Each nozzle is connected to an external gas and dust control system through an independent pipeline.

[0020] As a further embodiment of the present invention, the variable wind field generation and control module includes multiple independently controlled air supply units, and the air supply parameters of the air supply units are adjusted based on the dynamic exposure risk calculated by the monitoring and risk quantification module.

[0021] This invention also provides a method for testing the coupled exposure risk of airflow-dust-behavior, comprising the following steps:

[0022] Behavioral trajectories were planned for multiple simulated individuals, and individualized respiratory parameters related to behavioral intensity were set; at the same time, the spatiotemporal program of dust release and initial wind field parameters were set.

[0023] Drive each simulated individual to move along the planned trajectory inside the experimental chamber; simultaneously initiate the dust release procedure and wind field control;

[0024] Real-time coupled calculation and risk assessment based on monitoring and risk quantification modules specifically include:

[0025] The system simultaneously collects the real-time position and attitude of each simulated individual, real-time release source information of the dust field, and real-time status of the airflow field.

[0026] Based on the movement state of the simulated individual, its disturbance to the local airflow is analyzed, and the disturbance field is vector-superimposed with the current airflow field to update the comprehensive dynamic airflow field;

[0027] Based on the real-time release source information of the integrated dynamic airflow field and dust field, a dynamic dust concentration field is obtained;

[0028] For each simulated individual, the breathing zone is determined based on its real-time location, and the instantaneous dust concentration value of the breathing zone is mapped from the dynamic dust concentration field. The cumulative inhaled dust dose is calculated based on the instantaneous dust concentration value of the breathing zone and individualized breathing parameters.

[0029] Based on the cumulative inhaled dust dose, assess the real-time exposure risk level of the simulated individual;

[0030] Based on the assessed real-time exposure risk level, the parameters for the next monitoring cycle are dynamically adjusted to determine whether the experimental termination conditions are met. If not, the next cycle of calculation and assessment is performed.

[0031] As a further aspect of the present invention, if the real-time exposure risk level of a simulated individual exceeds a preset threshold, the wind field parameters are adjusted to enhance the ventilation intensity of the area where the individual is located or to change the air supply direction.

[0032] As a further aspect of the present invention, the spatiotemporal program of dust release is defined by a spatiotemporal control matrix, which specifies the opening and closing state, release intensity and duration of release points located at different spatial locations at specific times during the experiment.

[0033] As a further aspect of the present invention, the individualized respiratory parameters include respiratory rate and tidal volume, and the respiratory rate is dynamically adjusted according to the real-time movement speed of the simulated individual.

[0034] As a further aspect of the present invention, the actual motion trajectory and speed of the manned mobile platform are continuously monitored and fed back to the multi-agent behavior simulation and control module for online correction of the behavior model.

[0035] Compared with the prior art, the beneficial effects of the present invention are as follows: The present invention integrates a remotely controllable mobile simulated human model, a programmable mobile dust source, a dynamically adjustable wind field, and real-time monitoring with high spatiotemporal resolution in a unified experimental chamber, thereby constructing an empirical research platform that can simulate and quantify the entire chain of "work behavior changes the airflow of the microenvironment, the airflow affects the dust diffusion path, and ultimately determines the exposure dose of the individual's breathing zone".

[0036] This invention uses a "control matrix" to programmatically control the spatiotemporal release mode of the dust source in the nozzle array, controls the collaborative / interactive behavior of multiple agents through program control, and dynamically adjusts the array-type air supply unit through instructions to accurately reproduce or design various complex dynamic operation scenarios (such as multi-person cross-operation, dust generation from mobile equipment, intermittent dust release, ventilation strategy switching, etc.). Attached Figure Description

[0037] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention.

[0038] Figure 1 This is a schematic diagram of an airflow-dust-behavior coupled exposure risk experimental system provided in an embodiment of the present invention.

[0039] Figure 2 This is a schematic diagram of a simulated individual provided in an embodiment of the present invention.

[0040] Figure 3 The present invention provides dynamic breathing functions of different amplitudes for embodiments of the invention.

[0041] Figure 4 The present invention provides dynamic breathing functions of different frequencies for embodiments of the invention.

[0042] Figure 5 This is a diagram showing the internal equipment layout of the transparent experimental chamber provided in an embodiment of the present invention.

[0043] Figure 6 The trajectory design diagram of the intelligent agent provided in the embodiment of the present invention.

[0044] Figure 7 The diagram shows the relative positions of agents A and B as provided in an embodiment of the present invention.

[0045] Figure 8 This is a schematic diagram of the synchronous monitoring and data acquisition process provided in an embodiment of the present invention.

[0046] Figure 9 A flowchart illustrating the principle of multi-field cooperative control provided in an embodiment of the present invention.

[0047] The components include: 1. Wind speed sensor; 2. Dust measuring instrument; 3. Dust nozzle; 4. Mobile manned platform; 5. High-speed camera; 6. Computer; 7. Mannequin; 8. Respirator integrated mask; and 9. Air supply unit. Detailed Implementation

[0048] To make the technical problems, solutions, and beneficial effects of this invention clearer, the invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the invention.

[0049] In this embodiment of the invention, an airflow-dust-behavior coupled exposure risk experimental system is provided, the system comprising:

[0050] A physical experiment platform, comprising an experiment chamber and multiple manned mobile platforms disposed within the experiment chamber, wherein simulated individuals are arranged on the manned mobile platforms;

[0051] The multi-agent behavior simulation and control module includes a motion control unit for generating and sending motion commands to each manned mobile platform, and a respiratory parameter control unit for setting a differentiated respiratory model for each simulated individual;

[0052] The dynamic dust source generation and control module is used to generate dust sources in the experimental chamber whose release location, intensity, and physical property parameters can be controlled in real time.

[0053] The variable wind field generation and control module is used to generate a ventilation airflow field with dynamically adjustable wind speed and direction within the experimental chamber.

[0054] The monitoring and risk quantification module is signal-connected to the multi-agent behavior simulation and control module, the dynamic dust source generation and regulation module, and the variable wind field generation and regulation module. It performs the following actions: real-time acquisition of the actual pose, dust source release status, and wind field status data of each manned mobile platform; analysis of the turbulence induced by personnel movement based on the pose data, coupled with the variable wind field to construct a dynamic airflow field within the experimental chamber; simulation of dust diffusion and transport within the dynamic airflow field to form a dynamic dust concentration field; mapping exposure concentration from the breathing zone based on the real-time position of each manned mobile platform and its associated individualized breathing parameters to calculate the real-time cumulative inhalation dose; and outputting the dynamic exposure risk assessment result for each simulated individual based on the inhalation dose.

[0055] like Figure 1 , Figure 2 and Figure 5 As shown, in this embodiment, the experimental chamber is a transparent chamber visible from all four sides, providing a controllable and standardized physical experimental environment for the system. The chamber is constructed of high-strength transparent materials (such as polycarbonate or tempered glass) to ensure full visibility of the internal processes. Standardized interfaces and rails are pre-installed inside the chamber for installing and positioning other subsystem components. The experimental chamber possesses basic stability capabilities for environmental parameters (such as temperature and humidity) and is strictly sealed to prevent contaminant leakage, ensuring experimental safety and repeatability.

[0056] Mobile Manned Platform 4: Multiple independent, high-precision remotely controlled mobile platforms (such as manned balance vehicles) are deployed within the experimental cabin. Each platform carries a 1:1 simulated human model 7 equipped with a bionic respirator. The simulated human model 7 is made of rigid materials and designed and manufactured according to the P50 percentile of the Chinese adult anthropometric standard. Specific dimensions are: shoulder height 145 cm, mouth and nose height 165 cm, ensuring its standing posture conforms to typical industrial work scenarios. The skeleton is hollow internally for wiring, and the exterior is covered with common cotton or synthetic fiber work clothes to simulate the potential airflow interference from real clothing. The motion curve (stroke-time relationship) of the bionic respirator can be programmed and set via host computer software to accurately reproduce the human respiratory waveform (including tidal volume, respiratory rate, and inspiratory-expiratory ratio) under different intensities from resting state to heavy labor. See [link to documentation]. Figure 3 and Figure 4 , Figure 3 The three lines represent respiratory curves with a fixed frequency of 12 breaths per minute and amplitudes of 3 m / s, 1.9625 m / s, and 3.94 m / s, respectively. Figure 4 The three lines represent respiratory curves with a fixed amplitude of 3 m / s and respiratory rates of 20, 15, and 12 breaths / min, respectively. The inlet and outlet channels for the respiratory airflow extend to the mouth and nose of the head model. The bionic respirator can simulate the respiratory cycle and tidal volume of a real human body and can dynamically adjust respiratory parameters according to the platform's movement (such as increasing the respiratory rate during movement). The platform integrates a high-precision positioning module, which can provide real-time feedback of its precise three-dimensional coordinates, orientation, and velocity to the host computer.

[0057] A specially designed half-face respirator model, namely the respirator integrated mask 8, is worn on the head and face of the simulated human model 7. Internally, a miniature thin-film sampling pump is integrated, with a constant sampling flow rate of 2.0 liters / minute (±5%). An aerodynamic cutting head for inhalable dust (PM10) conforming to ISO 7708 standards is installed at the front end of the sampling inlet. The sampling pipeline is directly connected to external monitoring instruments, thereby achieving in-situ, real-time acquisition of dust mass concentration in the "breathing zone," directly reflecting the theoretical inhalation dose.

[0058] The mobile manned platform 4 uses a commercially available two-wheeled self-balancing vehicle chassis as its base, with two lockable omnidirectional driven wheels added to the rear to form a stable four-point support structure. The original vehicle control system is modified to receive commands from a wireless remote control (e.g., 2.4GHz) or via an IoT module (e.g., 4G / Wi-Fi). The movement speed is infinitely adjustable within the range of 0-1.5 m / s, and it can perform forward, backward, and stationary rotation (with adjustable turning radius). Equipped with a high-capacity lithium battery pack, it ensures continuous operation for at least 4 hours under typical experimental conditions.

[0059] In the multi-agent behavior simulation and control module, the motion control unit allows users to pre-program or drive the motion trajectories (straight lines, curves, and stationary positions), speeds, and interactive actions (such as merging, following, and collaborating) of multiple manned platforms in real-time, simulating the walking, turning, and other behaviors of workers in real-world operations.

[0060] It also includes a multi-parameter real-time monitoring and data acquisition module, used for synchronous and high-speed acquisition of key physical quantities.

[0061] Flow field measurement: An array of miniature wind speed sensors 1 is used to perform non-contact, full-field measurement of the overall or local airflow velocity field in the experimental chamber, accurately capturing the dynamic turbulent flow field induced by personnel movement and variable air supply.

[0062] Dust field measurement: Spatial concentration field measurement: Using laser sheet illumination combined with high-speed camera 5 and planar laser-induced fluorescence or scattering technology, the dust concentration field on a specific two-dimensional cross-section can be visualized and quantitatively measured.

[0063] Individual respiratory zone dose measurement: A miniature, high-response dust concentration sensor (such as a light-scattering type) is installed in the nasal respiratory hemisphere of each mannequin 7 to directly and continuously monitor the instantaneous concentration in the respiratory zone as the body moves. This concentration-time series is the direct input for calculating the individual inhaled dose.

[0064] A dust measuring instrument 2 is also installed on one side of the dust nozzle 3. All sensor data are synchronized through a high-speed data acquisition system with unified timestamps, providing a solid foundation for subsequent coupled analysis.

[0065] The monitoring and risk quantification module is responsible for integrating data and instructions from all subsystems to achieve dynamic coupling and risk calculation.

[0066] Real-time data fusion and driving: Receives real-time data streams from behavior control, dust sources, wind fields, and all monitoring sensors.

[0067] Multiphysics Dynamic Coupling Engine: Based on real-time platform position, velocity and wind field data, it analyzes local airflow disturbances induced by personnel movement and superimposes them with the background flow field generated by the variable wind field subsystem to update the dynamic airflow field of the entire cabin in real time.

[0068] Real-time calculation of individual exposure dose: In the updated dynamic airflow field, combined with the release information of dynamic dust sources and the dose measurement of individual breathing zones, the exposure concentration of the breathing zone is mapped from the predicted concentration field based on the real-time accurate position and breathing parameters of each simulated human model 7, and the concentration is integrated over time to calculate the cumulative inhaled dust dose of each "smart agent" in real time.

[0069] Risk assessment and visualization output: The calculated real-time individual dose is compared with the preset risk threshold to output a dynamic risk level. All process data (behavioral trajectory, flow field, concentration field, and individual dose curve) are rendered and displayed in real time using 3D visualization software to form a visualized analysis report linking the four elements of "behavioral airflow dust dose".

[0070] Each module is connected to the central processing unit via a data bus. The central processing unit is integrated on computer 6, forming a closed-loop experimental platform that integrates hardware and software.

[0071] As a preferred embodiment of the present invention, the dynamic dust source generation and control module is a matrix dust nozzle array 3, including multiple independently controlled aerosol nozzles arranged in a row and column matrix on one side of the inner wall of the experimental chamber. Each nozzle is connected to an external gas and dust control system through an independent pipeline.

[0072] In this embodiment, the dynamic dust source generation and control module is used to generate highly controllable and dynamically changing dust exposure sources to simulate the spatiotemporal non-uniform characteristics of real industrial dust sources. The system precisely programs and controls the dust source through a "spatiotemporal control matrix." Sixteen independent aerosol nozzles are installed in a 4×4 matrix layout on one inner wall of the experimental chamber (defined as the "dust source wall"). Each nozzle extends out of the chamber wall through an independent polyurethane hose and connects to a centrally located air and dust path control system outside the chamber. The control cabinet integrates independent solenoid valves, mass flow controllers, and dust feeders to execute the commands of the "spatiotemporal control matrix," achieving independent and precise control over the opening and closing, duration, and release concentration of each nozzle.

[0073] The "spatiotemporal control matrix" is the core control logic of the subsystem. It is a pre-programmed or real-time generated data table that clearly defines the opening / closing state of each independent nozzle at each specific time point after the start of the experiment; the duration of each open nozzle; and the rotational speed of the feeder corresponding to each open nozzle (which directly determines the dust release concentration).

[0074] By executing this matrix command, the system can drive designated nozzles to open at preset times and specific spatial coordinates (i.e., the matrix positions on the "dust source wall"), releasing dust according to a set concentration (corresponding to the feeder rotation speed) and duration. This design transforms the dust source from a single, fixed point source into a spatially discrete, temporally triggered, array-type moving dust source system. The dust's physical properties (type, particle size distribution) and the spatiotemporal release program are all uniformly allocated and controlled by the central processing unit based on this "spatiotemporal control matrix."

[0075] In a preferred embodiment of the present invention, the variable wind field generation and control module includes multiple independently controlled air supply units 9, and the air supply parameters of the air supply units 9 are adjusted based on the dynamic exposure risk calculated by the monitoring and risk quantification module.

[0076] In this embodiment, the variable wind field generation and control module is used to construct a dynamic airflow environment simulating natural or mechanical ventilation within the experimental chamber. The module consists of an array of intelligent air supply units 9, an exhaust fan, and airflow guiding components. The air supply units 9 are arranged along one or more sides of the experimental chamber, and each unit can independently control its outlet air velocity and angle. By coordinating and controlling each air supply unit 9, various background wind fields, ranging from uniform flow to complex shear flow, can be generated within the experimental chamber, and smooth or rapid switching of wind direction can be achieved.

[0077] The control commands for the variable wind field generation and control module can come from a preset program or receive real-time commands from the central processing unit, enabling dynamic responsive adjustments of the wind field to specific high-risk areas or individuals, such as enhancing local ventilation to dilute dust.

[0078] This invention also includes a method for conducting airflow-dust-behavior coupled exposure risk experiments, comprising the following steps:

[0079] Behavioral trajectories were planned for multiple simulated individuals, and individualized respiratory parameters related to behavioral intensity were set; at the same time, the spatiotemporal program of dust release and initial wind field parameters were set.

[0080] Drive each simulated individual to move along the planned trajectory inside the experimental chamber; simultaneously initiate the dust release procedure and wind field control;

[0081] Real-time coupled calculation and risk assessment based on monitoring and risk quantification modules specifically include:

[0082] The system simultaneously collects the real-time position and attitude of each simulated individual, real-time release source information of the dust field, and real-time status of the airflow field.

[0083] Based on the movement state of the simulated individual, its disturbance to the local airflow is analyzed, and the disturbance field is vector-superimposed with the current airflow field to update the comprehensive dynamic airflow field;

[0084] Based on the real-time release source information of the integrated dynamic airflow field and dust field, a dynamic dust concentration field is obtained;

[0085] For each simulated individual, the breathing zone is determined based on its real-time location, and the instantaneous dust concentration value of the breathing zone is mapped from the dynamic dust concentration field. The cumulative inhaled dust dose is calculated based on the instantaneous dust concentration value of the breathing zone and individualized breathing parameters.

[0086] Based on the cumulative inhaled dust dose, assess the real-time exposure risk level of the simulated individual;

[0087] Based on the assessed real-time exposure risk level, the parameters for the next monitoring cycle are dynamically adjusted to determine whether the experimental termination conditions are met. If not, the next cycle of calculation and assessment is performed.

[0088] In this embodiment, the experimental scenario is set up in the control software, including defining the behavior sequence and interaction rules of multiple manned platforms, setting the movement path and release procedure of dynamic dust sources, and planning the control mode of variable wind fields.

[0089] Simultaneously start behavioral simulation, dust generation, wind field control, and all monitoring equipment to begin high-speed, synchronous data acquisition.

[0090] During system operation, the core processing unit performs a real-time coupled calculation cycle of "behavior, airflow, dust, and dosage," dynamically displaying and recording the exposure risk of each individual.

[0091] After the experiment, the system automatically processes the data and generates a comprehensive assessment report containing information such as individual inhalation dose, peak exposure concentration, and risk spatiotemporal distribution map, providing quantitative basis for risk assessment and protection optimization.

[0092] As a preferred embodiment of the present invention, if the real-time exposure risk level of a simulated individual exceeds a preset threshold, the wind field parameters are adjusted to enhance the ventilation intensity of the area where the individual is located or to change the air supply direction.

[0093] In a preferred embodiment of the present invention, the spatiotemporal procedure for dust release is defined by a spatiotemporal control matrix, which specifies the opening and closing state, release intensity and duration of release points located at different spatial locations at specific times during the experiment.

[0094] In a preferred embodiment of the present invention, the individualized respiratory parameters include respiratory rate and tidal volume, and the respiratory rate is dynamically adjusted according to the real-time movement speed of the simulated individual.

[0095] In a preferred embodiment of the present invention, the actual motion trajectory and speed of the manned mobile platform are continuously monitored and fed back to the multi-agent behavior simulation and control module for online correction of the behavior model.

[0096] Example of a specific experimental method: In the control software, the right side of the experimental chamber is set as the air supply side, generating a uniform background wind field with a wind speed of 0.5 m / s. A single nozzle located in the matrix coordinates of the dynamic dust source subsystem is activated and set to release PM10 standard test dust at a constant concentration from the start of the experiment (t=0s), simulating the continuous dust generation of a stationary device.

[0097] Behavioral programming: Programming two mobile manned platforms 4 (agents A and B). Agent A is programmed to perform figure-eight cyclical movement near the dust source, simulating an equipment operator's inspection work. Agent B is programmed to walk in a straight line from the south side of the cabin to the north side; its path will intersect with Agent A's path at a certain moment, see... Figure 6 The relative positions of agents A and B are variable, see Figure 7 .

[0098] Monitoring Configuration: Activate the multi-parameter monitoring module. Install miniature light-scattering dust sensors in the nasal breathing hemispheres of both simulated humanoid models 7 to collect real-time concentration data in the breathing zone. Activate the Particle Image Velocimetry (PIV) system, with its sheet light source plane configured to cover the intersection area of ​​the agent's path, to capture the dynamic flow field. (See [link to relevant documentation]). Figure 8 .

[0099] Experimental execution and data coupling: All subsystems are started synchronously. The central processing unit begins receiving and time-synchronizing all data streams, including real-time trajectory data of agents A and B, respiratory zone concentration data, instantaneous flow field image sequences acquired by PIV, and dust source status data. (See multi-field coordination...) Figure 9 .

[0100] The coupling engine within the monitoring and risk quantification module operates. It first estimates the human-induced turbulence field based on the agent's real-time position and velocity using monitored wind speed information. Then, it vector-superimposes this disturbance field with the background wind field provided by the variable wind field generation and control module to calculate the current comprehensive dynamic airflow field.

[0101] Subsequently, within this dynamic airflow field, dust transport and spatial concentration distribution are analyzed by combining information on dust release from fixed dust sources and dust monitoring data.

[0102] Finally, the location of each agent's breathing zone (a spatial point that changes dynamically with movement) is mapped to the concentration field calculated in real time, the instantaneous exposure concentration of its breathing zone is interpolated, and this concentration-time series is integrated to update and display the cumulative inhaled dose curve of each agent in real time.

[0103] Process Observation: During the experiment, the operator can observe through a visual interface how the wake vortex generated by agent A's movement is captured and visualized by the PIV system; whether pulse-like peaks appear in the respiratory zone sensor readings when agent B enters A's wake region; and how the central processing unit dynamically updates the slope difference between the two dose curves. All raw data and processing results are stored synchronously for subsequent in-depth causal analysis.

[0104] Testing a dynamic response ventilation strategy for mobile dust sources:

[0105] Strategy and Scenario Setting: A "dust source tracking localized air supply" strategy will be tested. A nozzle from the dynamic dust source generation and control module will be mounted on a small cart that can move along a ground guide rail to simulate a cutting dust source moving linearly at a speed of 0.2 m / s. A dynamic response algorithm will be written into the control program of the variable wind field subsystem: it will read the position coordinates of the moving dust source in real time and control the two nearest array air supply units 9 in front of the dust source to align their air outlet angle with the dust source, increasing the wind speed to 2.0 m / s, attempting to construct a barrier air curtain.

[0106] Experimental setup: Two experimental groups were defined. Control group: The dynamic response algorithm was turned off, and the entire wind field maintained a uniform low-speed airflow of 0.3 m / s. Experimental group: The dynamic response algorithm was enabled.

[0107] Execution and Comparison: Under identical dust source movement procedures and background conditions, the control group and experimental group were run sequentially. A static simulated human model 7 and its breathing zone sensor were deployed at a fixed point (simulating a fixed workstation) downwind of the dust source.

[0108] Key points of data collection and analysis: The experiment focuses on collecting and comparing the concentration-time curves of the fixed-station breathing zone in the two groups of experiments.

[0109] Record the differences in flow field structure near the dust source (the experimental group should be able to observe a clear interaction between the barrier air curtain and the dust cloud).

[0110] The cumulative inhalation dose of the fixed-station intelligent agent is calculated by the central processing unit.

[0111] By comparing the differences between the two sets of data, the protective effectiveness of the dynamic ventilation strategy can be quantitatively evaluated (such as the percentage reduction in peak concentration and the percentage reduction in total dose).

[0112] Simulating complex non-point source pollution events using a spatiotemporal control matrix:

[0113] Matrix programming: Simulate multi-point, multi-mode dust generation in a material handling workshop. Program a "spatiotemporal control matrix" in the central processing unit, for example:

[0114] t=0-10s: Open the nozzle at coordinate (R1, C2) and release it continuously at a low speed to simulate dust in the material pile.

[0115] t=15s: Simultaneously and instantaneously open the nozzles at coordinates (R3, C1) and (R3, C4) (pulse width 100ms) to simulate the simultaneous rupture of two packaging bags.

[0116] t=30-60s: Scan and open all 4 nozzles in row R2 sequentially from left to right, each opening for 5 seconds, to simulate the continuous material feeding process on the conveyor belt.

[0117] Synchronized Behavior and Monitoring: Simultaneously, two mobile intelligent agents are controlled to move erratically within the cabin. A planar laser scattering measurement system is activated, with its sheet light source plane vertically positioned in front of the "dust source wall" to visualize and quantitatively record the entire process of dust cloud generation, diffusion, and fusion, which is complexly distributed in both space and time and is scheduled by a matrix program.

[0118] Exposure source tracing analysis: After the experiment, the system can replay the entire process data. The operator can select any agent to view its complete movement trajectory and dose accumulation curve, and use the system's "exposure event tracing" function to analyze which (or which few) dust source nozzles were activated at a specific time and space to contribute to the rapid rise in dose. This achieves precise spatiotemporal tracing of the individual's exposure source.

[0119] This invention achieves a closed-loop, dynamically coupled experimental capability encompassing the entire process of "behavior-airflow-dust-dose": traditional methods (physical experiments or numerical simulations), due to technological fragmentation, cannot synchronously and interactively study the causal relationship between researchers' dynamic behavior, environmental airflow disturbances, dynamic dust diffusion, and individual real-time inhalation dose on a single controllable platform. This invention integrates a remotely controlled, mobile simulated human model 7, a programmable mobile dust source, a dynamically adjustable wind field, and high spatiotemporal resolution real-time monitoring within a unified experimental chamber. For the first time, it constructs an empirical research platform capable of simulating and quantifying the complete chain of "work behavior altering microenvironmental airflow, airflow influencing dust diffusion paths, and ultimately determining individual respiratory zone exposure dose." This provides an unprecedented "decoupling" and "source tracing" analysis tool for revealing the formation mechanism of exposure risk in complex dynamic scenarios.

[0120] This invention solves the problem of direct, real-time measurement of individual exposure doses: existing individual sampling methods are lagging and cannot reflect instantaneous fluctuations, while CFD simulations are indirect, post-hoc estimates. This invention achieves direct, continuous, and in-situ measurement of the concentration in the respiratory microenvironment, which changes rapidly with human movement, by directly deploying miniature, high-response sensors in the respiratory hemisphere of a moving simulated human model 7. Combined with precise behavioral trajectory timestamps, the system can directly integrate and calculate the cumulative inhaled dust dose during dynamic activities. The measurement results provide a high-fidelity approximation of the true exposure dose, offering the most direct and reliable quantitative data foundation for individual risk assessment.

[0121] This invention provides a highly controllable, repeatable, and scalable means of reproducing complex dynamic scenarios in the laboratory: field measurements are uncontrollable and difficult to repeat, while traditional physics experiments are statically simplified. This invention uses a "control matrix" to programmatically control the spatiotemporal release mode of the dust source in the nozzle array, controls the collaborative / interactive behavior of multiple agents through programming, and dynamically adjusts the array-type air supply unit 9 through commands. This allows researchers to precisely reproduce or design various complex dynamic work scenarios (such as multi-person cross-operation, dust generation from mobile equipment, intermittent dust release, and ventilation strategy switching) as if writing a script. All experimental conditions and processes can be accurately recorded and completely repeated, providing a standardized experimental benchmark for comparative studies of different protection strategies, verification of occupational exposure limits, and validation of numerical models.

[0122] This invention provides an empirical database for validating and calibrating numerical models such as CFD: current CFD models lack effective validation of their predictive accuracy in dynamic scenarios. This system can simultaneously output high-precision spatiotemporally matched data pairs, including: precise personnel movement trajectories, actual dynamic flow fields measured by PIV and other methods, dust diffusion processes measured by area array dust source release and planar laser technology, and finally, individual doses measured by breathing zone sensors. This complete set of synchronously measured multiphysics data with clear causal relationships provides a crucial and currently scarce database for developing and calibrating predictive models such as CFD and artificial intelligence used for dynamic exposure risk assessment.

[0123] This invention enhances the foresight and scientific rigor of occupational health risk assessment and protection strategy optimization: The system allows for pre-implementation simulation and quantitative evaluation of high-risk or unimplemented work processes and ventilation schemes in a safe and controlled laboratory environment. Engineers can pre-test the actual protective effects of different ventilation modes (such as localized air supply and global displacement) in dynamic scenarios, or assess the impact of different worker behavior patterns (such as walking routes and work rhythms) on their own and others' exposure risks. This enables a paradigm shift from "post-event monitoring" to "pre-event prediction and proactive optimization," providing a powerful decision support tool for developing more scientific and personalized engineering protection measures and occupational health standards.

[0124] The above description is merely a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A coupled airflow-dust-behavior exposure risk experimental system, characterized in that, The system includes: A physical experiment platform, comprising an experimental cabin and multiple manned mobile platforms disposed within the experimental cabin, wherein simulated individuals are arranged on the manned mobile platforms; The multi-agent behavior simulation and control module includes a motion control unit for generating and sending motion commands to each manned mobile platform, and a respiratory parameter control unit for setting a differentiated respiratory model for each simulated individual; The dynamic dust source generation and control module is used to generate dust sources in the experimental chamber whose release location, intensity, and physical property parameters can be controlled in real time. The variable wind field generation and control module is used to generate a ventilation airflow field with dynamically adjustable wind speed and direction within the experimental chamber. The monitoring and risk quantification module is signal-connected to the multi-agent behavior simulation and control module, the dynamic dust source generation and regulation module, and the variable wind field generation and regulation module. It performs the following actions: real-time acquisition of the actual pose, dust source release status, and wind field status data of each manned mobile platform; analysis of the turbulence induced by personnel movement based on the pose data, coupled with the variable wind field to construct a dynamic airflow field within the experimental chamber; simulation of dust diffusion and transport within the dynamic airflow field to form a dynamic dust concentration field; mapping exposure concentration from the breathing zone based on the real-time position of each manned mobile platform and its associated individualized breathing parameters to calculate the real-time cumulative inhalation dose; and outputting the dynamic exposure risk assessment result for each simulated individual based on the inhalation dose.

2. The airflow-dust-behavior coupled exposure risk experimental system according to claim 1, characterized in that, The dynamic dust source generation and control module is a matrix dust nozzle array, including multiple independently controlled aerosol nozzles arranged in a row and column matrix on the inner wall of one side of the experimental chamber. Each nozzle is connected to an external gas and dust control system through an independent pipeline.

3. The airflow-dust-behavior coupled exposure risk experimental system according to claim 1, characterized in that, The variable wind field generation and control module includes multiple independently controlled air supply units. The air supply parameters of the air supply units are adjusted based on the dynamic exposure risk calculated by the monitoring and risk quantification module.

4. A method for experimental testing of airflow-dust-behavior coupled exposure risk, the method being implemented based on an airflow-dust-behavior coupled exposure risk experimental system, characterized in that... Includes the following steps: Behavioral trajectories were planned for multiple simulated individuals, and individualized respiratory parameters related to behavioral intensity were set; at the same time, the spatiotemporal program of dust release and initial wind field parameters were set. Drive each simulated individual to move along a planned trajectory within the experimental chamber; Simultaneously initiate dust release procedures and wind field control; Real-time coupled calculation and risk assessment based on monitoring and risk quantification modules specifically include: The system simultaneously collects the real-time position and attitude of each simulated individual, real-time release source information of the dust field, and real-time status of the airflow field. Based on the movement state of the simulated individual, its disturbance to the local airflow is analyzed, and the disturbance field is vector-superimposed with the current airflow field to update the comprehensive dynamic airflow field; Based on the real-time release source information of the integrated dynamic airflow field and dust field, a dynamic dust concentration field is obtained; For each simulated individual, the breathing zone is determined based on its real-time location, and the instantaneous dust concentration value of the breathing zone is mapped from the dynamic dust concentration field. The cumulative inhaled dust dose is calculated based on the instantaneous dust concentration value of the breathing zone and individualized breathing parameters. Based on the cumulative inhaled dust dose, assess the real-time exposure risk level of the simulated individual; Based on the assessed real-time exposure risk level, the parameters for the next monitoring cycle are dynamically adjusted to determine whether the experimental termination conditions are met. If not, the next cycle of calculation and assessment is performed.

5. The airflow-dust-behavior coupled exposure risk experimental method according to claim 4, characterized in that, If the real-time exposure risk level of a simulated individual exceeds a preset threshold, the wind field parameters are adjusted to enhance the ventilation intensity of the area where the individual is located or to change the air supply direction.

6. The airflow-dust-behavior coupled exposure risk experimental method according to claim 4, characterized in that, The spatiotemporal procedure for dust release is defined by a spatiotemporal control matrix, which specifies the opening and closing state, release intensity, and duration of release points located at different spatial locations at specific times during the experiment.

7. The airflow-dust-behavior coupled exposure risk experimental method according to claim 4, characterized in that, Individualized respiratory parameters include respiratory rate and tidal volume, with the respiratory rate dynamically adjusted based on the simulated individual's real-time movement speed.

8. The airflow-dust-behavior coupled exposure risk experimental method according to claim 4, characterized in that, The actual motion trajectory and speed of the manned mobile platform are continuously monitored and fed back to the multi-agent behavior simulation and control module for online correction of the behavior model.

Images