Dangerous chemical substance dynamic risk assessment and disposal method and system
By performing grid-based modeling and risk density field calculation on hazardous chemical storage areas, the problems of lag and qualitative risk assessment in existing technologies have been solved, enabling real-time risk assessment and future trend simulation, and providing a scientific basis for emergency response.
Patent Information
- Application Number
- CN202610076777.9
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2026-01-21
- Publication Date
- 2026-04-24
AI Technical Summary
Existing risk assessment methods for hazardous chemical storage areas cannot achieve real-time dynamic perception, lack unified and objective quantitative indicators, cannot accurately locate risk accumulation points and diffusion paths, have weak predictive capabilities, and result in weak targeted emergency response.
By collecting raw data and dividing it into grids, a risk density assessment model is constructed, a risk discretization continuity equation is built, the risk flow rate is solved, a risk assessment report is generated, and the optimal disposal strategy is formulated.
It enables the visualization and quantitative dynamic perception of hazardous chemical risks, simulates future risk evolution trends, provides a scientific basis for emergency decision-making, and improves the pertinence of emergency response.
Smart Images
Figure CN121920835A_ABST
Abstract
Description
Technical Field
[0001] This invention belongs to the field of hazardous chemical risk assessment technology, specifically relating to a method and system for dynamic risk assessment and disposal of hazardous chemicals. Background Technology
[0002] Currently, risk assessment and management in hazardous chemical storage areas primarily rely on static, discrete, and experience-based traditional methods. These methods include regular manual inspections, inherent hazard classification based on Safety Data Sheets (MSDS), installation of independent gas leak or fire alarm sensors at critical points, and fixed-interval inspections and records based on regulations. The shortcomings of existing technologies are obvious: First, they cannot achieve real-time dynamic perception; risk assessment lags significantly behind actual changes and cannot capture the initial transients of processes such as leaks, volatilization, and the approach of incompatible substances. Second, assessment methods are mostly qualitative or semi-quantitative, relying on personnel's experience and judgment, lacking unified and objective quantitative indicators, making it difficult to accurately compare the contribution and evolution trends of different risk sources. Third, existing technologies lack refined spatial analysis, typically treating the entire warehouse or large area as a homogeneous whole, failing to pinpoint specific risk accumulation points, diffusion paths, and potential impact ranges, resulting in weak targeted emergency response. Finally, these technologies have weak predictive capabilities, primarily limited to alarms based on the current state, unable to simulate and warn of risk evolution in the short term based on physicochemical laws, leaving proactive prevention and optimization decisions without a basis. Summary of the Invention
[0003] To address the aforementioned problems in the existing technology, this invention provides a method and system for dynamic risk assessment and disposal of hazardous chemicals.
[0004] The objective of this invention can be achieved through the following technical solutions: A method for dynamic risk assessment and disposal of hazardous chemicals, the implementation of which includes the following steps: Step S1: Collect raw data and preprocess it, and at the same time divide the hazardous chemical storage area into grids to obtain structured data; Step S2: Based on the structured data, perform risk density assessment to obtain the risk density value for each grid. Step S3: Perform source and sink statistics based on the structured data to obtain the risk source items and risk sink items for each grid; Step S4: Construct and solve the risk discretization continuity equation based on the risk density value, the risk source term, and the risk sink term to obtain the updated risk density value; Step S5: Update the risk flow rate based on the risk density value to obtain the updated risk flow rate value; Step S6: Based on the updated risk density value and the updated risk velocity value, obtain key risk assessment indicators and output a risk assessment report. The key risk assessment indicators include total risk score, risk kinetic energy, eddy current, and Richardson number. Step S7: Generate the optimal handling strategy based on the risk assessment report.
[0005] Preferably, step S1 specifically includes: Collect the raw data, which includes reagent static data, reagent dynamic data, and environmental system data; The raw data is cleaned, and the hazardous chemical storage area is divided into a three-dimensional grid with grid numbers (i,j,k) and corresponding spatial locations (x,y,z). At the same time, the evaluation time step is set. The structured data of the three-dimensional mesh is obtained based on the original data.
[0006] Preferably, the risk density assessment in step S2 specifically includes: For each reagent a in the grid (i,j,k), the environmental factor is calculated based on the structured data, mathematically described as follows: ,in, For the environmental factors of reagent a, Let (i,j,k) be the current average temperature. The optimal storage temperature for reagent a is... The scale is affected by temperature. Let be the current average humidity of grid (i,j,k). The optimal storage humidity for reagent a is... The scale is affected by humidity; Based on the structured data and the environmental factors, the risk contribution density of reagent a in the current grid is obtained, mathematically described as follows: ,in, Risk contribution density for reagent a Let a be the inherent risk coefficient of reagent a. The mass of reagent a in the current grid. For the mesh volume, For container integrity factor; The risk density value of the entire grid is obtained based on the risk contribution density of all reagents within the grid.
[0007] Preferably, the source-sink statistics in step S3 specifically include: Based on the structured data, the risk source terms for reagent a are obtained, which are the weighted sum of leakage and volatilization source terms, chemical reaction source terms, and incompatible substance reaction source terms; based on the risk source terms of all reagents within the grid, the risk source terms for the entire grid are obtained; The risk pool for the current grid is obtained based on the structured data. The risk pool is a weighted sum of the ventilation elimination pool, the adsorbent elimination pool, and the natural decay pool.
[0008] Preferably, the construction of the risk continuity equation in step S4 specifically involves: Obtain the set wind speed for each vent and calculate the ventilation velocity for each grid; obtain the diffusion velocity based on the risk density value; estimate the initial risk velocity based on the ventilation velocity and the diffusion velocity and construct the initial risk velocity field; For each grid, define the grid face number and calculate the flux of each of the six faces, mathematically described as follows: ,in, For the flux of a single surface, For the risk density value of a single surface, Let n be the initial risk velocity for a single face, and n be the unit normal vector. The area of a single face; calculate the total net flux outflow for each grid based on the flux of a single face; The risk discretization continuity equation is constructed based on the risk density value, the risk source term, the risk sink term, and the total net flux outflow. Mathematically, it is described as follows: ,in, Update the risk density value for the current grid. Based on the previous risk density value, To predict the time step, For risk source items, For risk remittance, For the mesh volume, This represents the current net outflow of total flux in the grid.
[0009] Preferably, the update of the risk flow rate in step S5 specifically involves: Based on the risk density value, the pressure gradient term is obtained, mathematically described as follows: ,in, For the pressure gradient term, Let the risk propagation speed constant be... The pressure gradient is used; based on the risk velocity, the convection term is obtained, which is the sum of the partial derivatives of the risk velocity components in the three directions, multiplied by the risk velocity itself; based on the risk velocity, the viscosity term is obtained, mathematically described as follows: ,in, It is a viscous term. Kinematic viscosity, The Laplace of the risk flow velocity; based on the risk density value, the external force term is obtained, mathematically described as follows: ,in, For external force, The external force consists of gravity and ventilation force. The risk velocity update value is obtained based on the pressure gradient term, the convection term, the viscosity term, and the external force term. The data is described as follows: ,in, Update the risk flow rate value for the current grid. For the previous risk flow rate, This is a convection term.
[0010] Preferably, step S6 specifically includes: The total risk score is the sum of the risks of all grids within the hazardous chemical storage area. Areas with total risk scores exceeding a preset threshold are marked as high-risk areas. The mathematical description of the risk flow energy is... The vorticity is the sum of the partial derivatives of the components of the risk velocity in three directions; the Richardson number is mathematically described as follows: ,in, Here, g is the Richardson number, and g is the acceleration due to gravity. This represents the gradient of the risk density value in the vertical direction. Let be the gradient of the horizontal component of the risk flow velocity in the vertical direction. This represents the gradient of the vertical component of the risk flow velocity in the vertical direction. The risk assessment report is generated based on the aforementioned key risk assessment indicators.
[0011] A dynamic risk assessment and disposal system for hazardous chemicals, used to execute the dynamic risk assessment and disposal method for hazardous chemicals described above, includes a data processing module, a risk density assessment module, a source-sink statistics module, a risk update module, and a risk assessment and disposal module; The data processing module is used to collect and preprocess raw data, and at the same time, to divide the hazardous chemical storage area into grids to obtain structured data. The risk density assessment module is used to assess risk density based on the structured data to obtain the risk density value for each grid. The source-sink statistics module is used to perform source-sink statistics based on the structured data to obtain the risk source items and risk sink items for each grid. The risk update module is used to construct and solve a risk discretization continuity equation based on the risk density value, the risk source term, and the risk sink term to obtain a risk density update value; and to update the risk flow velocity based on the risk density value to obtain a risk flow velocity update value. The risk assessment and treatment module is used to obtain key risk assessment indicators and output a risk assessment report based on the risk density update value and the risk flow velocity update value. The key risk assessment indicators include total risk integral, risk flow energy, eddy current and Richardson number; and to generate the optimal treatment strategy based on the risk assessment report.
[0012] The beneficial effects of this invention are as follows: (1) By using grid modeling and risk density field calculation, the originally abstract risk is transformed into a field variable with clear spatial distribution and measurable values, making the safety status clear at a glance and enabling real-time tracking of its changes, thus realizing the visualization and quantitative dynamic perception of risk.
[0013] (2) By constructing and solving the risk continuity equation, we can simulate the future evolution trend of risk under multiple effects such as ventilation, diffusion, generation and elimination, realize early warning, and win valuable time for intervention decision-making.
[0014] (3) It provides multi-dimensional in-depth risk assessment indicators, including not only the total global risk, but also derivative indicators such as risk flow energy, eddy current, and Richardson number. It conducts a comprehensive diagnosis from multiple perspectives such as total risk, transport intensity, local clustering and environmental stability, and the assessment conclusions are more scientific and in-depth. Attached Figure Description
[0015] To facilitate understanding by those skilled in the art, the present invention will be further described below with reference to the accompanying drawings.
[0016] Figure 1 This is a flowchart of the steps of a method for dynamic risk assessment and disposal of hazardous chemicals according to the present invention. Detailed Implementation
[0017] To better understand the invention, various aspects of the invention will be described in more detail with reference to the accompanying drawings. It should be understood that these detailed descriptions are merely illustrative of exemplary embodiments of the invention and are not intended to limit the scope of the invention in any way. Throughout the specification, the expression "and / or" includes any and all combinations of one or more of the associated listed items. As used herein, the terms "approximately," "about," and similar terms are used as expressions of approximation, not as expressions of degree, and are intended to describe inherent deviations in measured or calculated values that will be recognized by those skilled in the art. Furthermore, the order in which the steps are described in this invention does not necessarily indicate the order in which these steps occur in actual operation, unless otherwise expressly defined or deduced from the context.
[0018] It should also be understood that expressions such as "comprising," "including," "having," "containing," and / or "comprising" are open-ended rather than closed-ended expressions in this specification, indicating the presence of the stated features, elements, and / or components, but not excluding the presence of one or more other features, elements, components, and / or combinations thereof. Furthermore, when expressions such as "at least one of..." appear after a list of listed features, they modify the entire list of features, not just individual elements in the list. Additionally, when describing embodiments of the invention, the word "may" is used to mean "one or more embodiments of the invention." And the term "exemplary" is intended to refer to examples or illustrations.
[0019] Unless otherwise specified, all terms used herein (including engineering and technical terms) shall have the same meaning as commonly understood by one of ordinary skill in the art to which this invention pertains. It should also be understood that, unless expressly stated herein, terms defined in common dictionaries shall be interpreted as having the meaning consistent with their meaning in the context of the relevant art, and not in an idealized or overly formalized sense.
[0020] It should be noted that, unless otherwise specified, the embodiments and features described in this invention can be combined with each other. The invention will now be described in detail with reference to the accompanying drawings and embodiments.
[0021] Example 1: Please see Figure 1 A method for dynamic risk assessment and disposal of hazardous chemicals, comprising: Step S1: Collect raw data and preprocess it, and at the same time divide the hazardous chemical storage area into grids to obtain structured data; Step S2: Based on the structured data, perform risk density assessment to obtain the risk density value for each grid. Step S3: Perform source and sink statistics based on the structured data to obtain the risk source items and risk sink items for each grid; Step S4: Construct and solve the risk discretization continuity equation based on the risk density value, the risk source term, and the risk sink term to obtain the updated risk density value; Step S5: Update the risk flow rate based on the risk density value to obtain the updated risk flow rate value; Step S6: Based on the updated risk density value and the updated risk velocity value, obtain key risk assessment indicators and output a risk assessment report. The key risk assessment indicators include total risk score, risk kinetic energy, eddy current, and Richardson number. Step S7: Generate the optimal disposal strategy based on the risk assessment report. The disposal goal is to reduce the total risk score, eliminate high-risk areas, reduce risk kinetic energy and eddy current, while keeping the Richardson number stable and greater than 0.25.
[0022] In this embodiment, step S1 can be implemented through the following steps: S101: The raw data is collected through the central control panel, sensors, and cameras. The raw data includes reagent static data, reagent dynamic data, and environmental system data. The reagent static data includes, but is not limited to, reagent name, CAS number, MSDS information, inherent risk factor (based on GHS classification, such as flammability category, toxicity category, etc.), physicochemical properties (molecular weight, boiling point, flash point, explosion limits, volatility, etc.), and storage requirements (optimal temperature, humidity, list of incompatible substances, etc.). The reagent dynamic data includes, but is not limited to, storage location information (read via RFID / QR code to determine which compartment of which smart cabinet it is in), current weight, storage environment temperature, storage environment humidity, and volatile organic compound concentration. The environmental system data includes, but is not limited to, smoke sensor status, ventilation system status, air conditioning system status, and camera images. S102: Perform data cleaning on the raw data (remove outliers and fill in missing values), and divide the hazardous chemical storage area (such as each smart cabinet or warehouse) into a three-dimensional grid with grid number (i,j,k) and corresponding spatial location (x,y,z), and set the evaluation time step at the same time. S103: Based on the original data, obtain the structured data of the three-dimensional mesh (the reagent list and corresponding original data stored in each mesh cell).
[0023] In this embodiment, the risk density assessment specifically includes: S201: For each reagent a in the grid (i,j,k), calculate the environmental factor based on the structured data, mathematically described as follows: ,in, For the environmental factors of reagent a, Let (i,j,k) be the current average temperature. The optimal storage temperature for reagent a is... To account for the temperature effect, 10K is typically used. The current average humidity for grid (i,j,k) The optimal storage humidity for reagent a is... To account for the influence of humidity, a value of 50% is typically used. S202: Based on the structured data and the environmental factors, obtain the risk contribution density of reagent a in the current grid, mathematically described as follows: ,in, Risk contribution density for reagent a (reagent a is per m) 3 Risk of mesh contribution to volume, Risk / m 3 ), The inherent risk factor of reagent a (the risk units contained in each kg of reagent). The mass of reagent a in the current grid. For the mesh volume, The container integrity factor (obtained through AI visual recognition and weighing change analysis); S203: Obtain the risk density value (weighted sum) for the entire grid based on the risk contribution density of all reagents within the grid.
[0024] In this embodiment, the source-sink statistics specifically refer to: S301: Based on the structured data, obtain the risk source terms for reagent a. These risk source terms are a weighted sum of leakage and volatilization source terms, chemical reaction source terms (obtained only when an abnormal temperature rise is detected), and incompatible substance reaction source terms (obtained only when an incompatible substance pair exists within the grid). The mathematical description of the leakage and volatilization source terms is... ,in, For the leakage and evaporation source term of reagent a (Risk / m) 3 s (s, the same below) The mass change rate of reagent a (i.e., the rate of evaporation or leakage). Let be the evaporation rate coefficient of reagent a; the mathematical description of the chemical reaction source term is... , For reagent a, the chemical reaction source term, The thermal risk conversion coefficient of reagent a (i.e., the risk generated by the release of reagent a per unit of energy). Let a be the rate of temperature change of reagent a. The specific heat capacity of reagent a; the mathematical description of the incompatible reactant term is... ,in, Let n be the incompatible reactant term for reagent a, and n be the number of reagents in the grid that will chemically react with reagent a. denoted as the reaction rate constant between the two reagents (only reagents that react chemically with a are counted). Risk contribution density for reagent b The activation energy of the reaction. The ideal gas constant is used; the risk source terms for the entire grid are obtained based on the risk source terms for all reagents within the grid. S302: Based on the structured data, obtain the risk sink for the current grid. The risk sink is a weighted sum of the ventilation elimination sink, the adsorbent elimination sink (if the grid contains adsorbents such as activated carbon), and the natural decay sink. The mathematical description of the ventilation elimination sink is... ,in, To eliminate the risk of ventilation (Risk / m) 3 s (s, the same below) The current risk density value of the grid. The volumetric flow rate through the current grid (derived from ventilation system monitoring data, cubic meters per second); the mathematical description of the adsorbent elimination sink term is... ,in, Eliminating sinks for adsorbents is the adsorption rate constant (the proportion of risk adsorbed per unit time, 1 / second). The concentration of the adsorbent is expressed in kilograms per cubic meter. For reference adsorbent concentration; the mathematical description of the natural decay sink term is... ,in, For naturally decaying sink terms, The decay constant is the risk ratio of natural decay per unit time, 1 / second, derived from material stability data.
[0025] In this embodiment, the construction of the risk continuity equation is specifically as follows: S401: Obtain the set wind speed for each vent from the ventilation system, and calculate the ventilation velocity for each grid using a simplified fluid dynamics method; based on the risk density value, obtain the diffusion velocity, mathematically described as... ,in, D is the diffusion velocity (m / s), and D is the diffusion coefficient (m). 2 / s), The current risk density value of the grid. The risk density gradient of the current grid. For small positive constants; based on the ventilation velocity and the diffusion velocity, the initial risk velocity is estimated and an initial risk velocity field is constructed, mathematically described as follows: ,in, The initial risk velocity (m / s) for the current grid. Ventilation speed; S402: For each grid, define the grid face number and calculate the flux of each of the 6 faces, mathematically described as follows: ,in, Flux of a single surface (the amount of risk flowing through that surface per unit time). The risk density value for a single face (using linear interpolation, taking the average of the risk density values of two adjacent grids; if the grid is on the boundary, take the boundary value). The initial risk velocity for a single face (the average velocity of adjacent grids) is given by n, where n is the unit normal vector (n=(1,0,0) for the east face, (-1,0,0) for the west face, (0,1,0) for the north face, and so on). The area of a single face; calculate the total net flux outflow for each grid based on the flux of a single face (i.e., the sum of the fluxes of all faces); S403: Construct the risk discretization continuity equation based on the risk density value, the risk source term, the risk sink term, and the total net flux outflow, mathematically described as follows: ,in, Update the risk density value for the current grid. Based on the previous risk density value, To predict the time step, For risk source items, For risk remittance, For the mesh volume, This represents the current net outflow of total flux in the grid.
[0026] In this embodiment, the update of the risk flow rate specifically involves: S501: Based on the risk density value, the pressure gradient term is obtained, mathematically described as follows: ,in, Pressure gradient term (m / s) 2 ), The risk propagation velocity constant (m / s, determined based on the volatility of the substance; if there are multiple reagents in the grid, it is a mass-weighted average; if there are no reagents, it is a minimum value). Pressure gradient (Risk / m) 2 s 2 Based on the risk velocity (the initial state is the initial risk velocity, and subsequent values are taken from the previous iteration), a convection term is obtained to describe the inertial effect of the velocity itself, which is the sum of the partial derivatives of the risk velocity components in the three directions (x, y, z), multiplied by the risk velocity itself; based on the risk velocity, a viscosity term is obtained, mathematically described as... ,in, Viscosity term (m / s) 2 ), kinematic viscosity (m) 2 / s), The Laplace (1 / sm) of the risk flow velocity; based on the risk density value, the external force term is obtained, mathematically described as follows: ,in, External force term (m / s) 2 ), As an external force, caused by gravity ( g is the acceleration due to gravity. air density, (direction vector) and ventilation force ( ), For ventilation speed, It consists of relaxation time; S502: The risk velocity update value is obtained based on the pressure gradient term, the convection term, the viscosity term, and the external force term. The data description is as follows: ,in, Update the risk flow rate value for the current grid. For the previous risk flow rate, This is a convection term.
[0027] In this embodiment, step S6 can be implemented through the following steps: The total risk score is the sum of the risks of all grids within the hazardous materials storage area. The region where the total risk score exceeds a preset threshold is marked as a high-risk region; the mathematical description of the risk flow energy is... The vorticity represents the intensity of the risk flow; the vorticity is the sum of the partial derivatives of the risk flow velocity components in three directions; where the vorticity is large, risk tends to accumulate; the Richardson number is mathematically described as... ,in, Here, g is the Richardson number, and g is the acceleration due to gravity. This represents the gradient of the risk density value in the vertical direction. Let be the gradient of the horizontal component of the risk flow velocity in the vertical direction. Let be the gradient of the vertical component of the risk flow velocity in the vertical direction. Generally, when the Richardson number is greater than 0.25, the system is stable; when it is between 0 and 0.25, the system may be unstable; when it is less than 0, the system is unstable. The risk assessment report is generated based on the aforementioned key risk assessment indicators.
[0028] Example 2: A dynamic risk assessment and disposal system for hazardous chemicals includes a data processing module, a risk density assessment module, a source-sink statistics module, a risk update module, and a risk assessment and disposal module. The data processing module is used to collect and preprocess raw data, and at the same time, to divide the hazardous chemical storage area into grids to obtain structured data. The risk density assessment module is used to assess risk density based on the structured data to obtain the risk density value for each grid. The source-sink statistics module is used to perform source-sink statistics based on the structured data to obtain the risk source items and risk sink items for each grid. The risk update module is used to construct and solve a risk discretization continuity equation based on the risk density value, the risk source term, and the risk sink term to obtain a risk density update value; and to update the risk flow velocity based on the risk density value to obtain a risk flow velocity update value. The risk assessment and mitigation module is used to obtain key risk assessment indicators and output a risk assessment report based on the updated risk density and the updated risk velocity. The key risk assessment indicators include total risk score, risk flow energy, eddy current, and Richardson number. Based on the risk assessment report, an optimal mitigation strategy is generated, with the mitigation objectives being to reduce the total risk score, eliminate high-risk areas, reduce risk flow energy and eddy current, while keeping the Richardson number stable and greater than 0.25.
[0029] The above description is merely a preferred embodiment of the present invention and is not intended to limit the present invention in any way. Although the present invention has been disclosed above with reference to preferred embodiments, it is not intended to limit the present invention. Any person skilled in the art can make some modifications or alterations to the above-disclosed technical content to create equivalent embodiments without departing from the scope of the present invention. Any simple modifications, equivalent changes and alterations made to the above embodiments based on the technical essence of the present invention without departing from the scope of the present invention shall still fall within the scope of the present invention.
Claims
1. A method for dynamic risk assessment and disposal of hazardous chemicals, characterized in that, Includes the following steps: Step S1: Collect raw data and preprocess it, and at the same time divide the hazardous chemical storage area into grids to obtain structured data; Step S2: Based on the structured data, perform risk density assessment to obtain the risk density value for each grid. Step S3: Perform source and sink statistics based on the structured data to obtain the risk source items and risk sink items for each grid; Step S4: Construct and solve the risk discretization continuity equation based on the risk density value, the risk source term, and the risk sink term to obtain the updated risk density value; Step S5: Update the risk flow rate based on the risk density value to obtain the updated risk flow rate value; Step S6: Based on the updated risk density value and the updated risk velocity value, obtain key risk assessment indicators and output a risk assessment report. The key risk assessment indicators include total risk integral, risk kinetic energy, eddy current, and Richardson number. Step S7: Generate the optimal handling strategy based on the risk assessment report.
2. The method for dynamic risk assessment and disposal of hazardous chemicals according to claim 1, characterized in that, Step S1 specifically includes: Collect the raw data, which includes reagent static data, reagent dynamic data, and environmental system data; The raw data is cleaned, and the hazardous chemical storage area is divided into a three-dimensional grid with grid numbers (i,j,k) and corresponding spatial locations (x,y,z). At the same time, the evaluation time step is set. The structured data of the three-dimensional mesh is obtained based on the original data.
3. The method for dynamic risk assessment and disposal of hazardous chemicals according to claim 1, characterized in that, The risk density assessment in step S2 specifically involves: For each reagent a in the grid (i,j,k), the environmental factor is calculated based on the structured data, mathematically described as follows: ,in, For the environmental factors of reagent a, Let (i,j,k) be the current average temperature. The optimal storage temperature for reagent a is... The scale is affected by temperature. Let be the current average humidity of grid (i,j,k). The optimal storage humidity for reagent a is... The scale is affected by humidity; Based on the structured data and the environmental factors, the risk contribution density of reagent a in the current grid is obtained, mathematically described as follows: ,in, Risk contribution density for reagent a Let a be the inherent risk coefficient of reagent a. The mass of reagent a in the current grid. For the mesh volume, For container integrity factor; The risk density value of the entire grid is obtained based on the risk contribution density of all reagents within the grid.
4. The method for dynamic risk assessment and disposal of hazardous chemicals according to claim 3, characterized in that, The source-sink statistics in step S3 specifically refer to: Based on the structured data, the risk source terms for reagent a are obtained, which are the weighted sum of leakage and volatilization source terms, chemical reaction source terms, and incompatible substance reaction source terms; based on the risk source terms of all reagents within the grid, the risk source terms for the entire grid are obtained; The risk pool for the current grid is obtained based on the structured data. The risk pool is a weighted sum of the ventilation elimination pool, the adsorbent elimination pool, and the natural decay pool.
5. The method for dynamic risk assessment and disposal of hazardous chemicals according to claim 4, characterized in that, The construction of the risk continuity equation in step S4 is specifically as follows: Obtain the set wind speed for each vent and calculate the ventilation velocity for each grid; obtain the diffusion velocity based on the risk density value; estimate the initial risk velocity based on the ventilation velocity and the diffusion velocity and construct the initial risk velocity field; For each grid, define the grid face number and calculate the flux of each of the six faces, mathematically described as follows: ,in, For the flux of a single surface, For the risk density value of a single surface, Let n be the initial risk velocity for a single face, and n be the unit normal vector. The area of a single face; calculate the total net flux outflow for each grid based on the flux of a single face; The risk discretization continuity equation is constructed based on the risk density value, the risk source term, the risk sink term, and the total net flux outflow. Mathematically, it is described as follows: ,in, Update the risk density value for the current grid. Based on the previous risk density value, To predict the time step, For risk source items, For risk remittance, For the mesh volume, This represents the total net outflow of the current grid.
6. The method for dynamic risk assessment and disposal of hazardous chemicals according to claim 5, characterized in that, The update of the risk flow rate in step S5 specifically refers to: Based on the risk density value, the pressure gradient term is obtained, mathematically described as follows: ,in, For the pressure gradient term, Let the risk propagation speed constant be... The pressure gradient is used; based on the risk velocity, the convection term is obtained, which is the sum of the partial derivatives of the risk velocity components in the three directions, multiplied by the risk velocity itself; based on the risk velocity, the viscosity term is obtained, mathematically described as follows: ,in, It is a viscous term. Kinematic viscosity, The Laplace of the risk flow velocity; based on the risk density value, the external force term is obtained, mathematically described as follows: ,in, For external force, The external force consists of gravity and ventilation force. The risk velocity update value is obtained based on the pressure gradient term, the convection term, the viscosity term, and the external force term. The data is described as follows: ,in, Update the current grid's risk flow rate value. For the previous risk flow rate, This is a convection term.
7. The method for dynamic risk assessment and disposal of hazardous chemicals according to claim 6, characterized in that, Step S6 specifically includes: The total risk score is the sum of the risks of all grids within the hazardous chemical storage area. Areas with total risk scores exceeding a preset threshold are marked as high-risk areas. The mathematical description of the risk flow energy is... The vorticity is the sum of the partial derivatives of the components of the risk velocity in three directions; the Richardson number is mathematically described as follows: ,in, Here, denoted by Richardson's number, and g is the acceleration due to gravity. This represents the gradient of the risk density value in the vertical direction. Let be the gradient of the horizontal component of the risk flow velocity in the vertical direction. This represents the gradient of the vertical component of the risk flow velocity in the vertical direction. The risk assessment report is generated based on the aforementioned key risk assessment indicators.
8. A dynamic risk assessment and disposal system for hazardous chemicals, characterized in that, The system is applied to the dynamic risk assessment and disposal method for hazardous chemicals as described in any one of claims 1-7, and includes a data processing module, a risk density assessment module, a source-sink statistics module, a risk update module, and a risk assessment and disposal module. The data processing module is used to collect and preprocess raw data, and at the same time, to divide the hazardous chemical storage area into grids to obtain structured data. The risk density assessment module is used to assess risk density based on the structured data to obtain the risk density value for each grid. The source-sink statistics module is used to perform source-sink statistics based on the structured data to obtain the risk source items and risk sink items for each grid. The risk update module is used to construct and solve a risk discretization continuity equation based on the risk density value, the risk source term, and the risk sink term to obtain the risk density update value. The risk flow velocity is updated based on the risk density value to obtain the updated risk flow velocity value. The risk assessment and handling module is used to obtain key risk assessment indicators and output a risk assessment report based on the risk density update value and the risk flow velocity update value. The key risk assessment indicators include total risk integral, risk kinetic energy, eddy current and Richardson number. The optimal response strategy is generated based on the risk assessment report.