A radioactive waste liquid treatment system

Abstract

The present application relates to the technical field of radioactive pollution treatment, and particularly relates to a radioactive waste liquid treatment system, which distributes waste liquid to several decay tanks according to nuclide types and half-life intervals through a pretreatment module; obtains the pH value, oxidation-reduction potential and fluorescence spectrum intensity of waste liquid in each decay tank through a complex characteristic acquisition module; determines the pollution complex index of complex formed by organic matter and radioactive nuclide in the current decay tank through a process construction module to construct a decision graph; analyzes the change result of the pollution complex index through a pollution analysis module; determines whether to change the purification mode through a pollution treatment module, and adjusts the drainage cycle of the liquid level controller according to the purification mode change effect. Furthermore, the purification mode and the drainage cycle are dynamically adjusted according to the organic matter concentration fluctuation in waste liquid and the nuclide decay characteristics, the problem of treatment failure caused by complex accumulation is avoided, and the efficiency of radioactive waste liquid treatment is improved.

Description

Technical Field

[0001] This invention relates to the field of radioactive pollution treatment technology, and in particular to a radioactive waste liquid treatment system. Background Technology

[0002] Radioactive waste treatment is a critical aspect of nuclear industry and nuclear medicine treatment. Existing treatment methods typically rely on natural decay or fixed-cycle physicochemical processes such as precipitation, ion exchange, and evaporation. However, actual waste often contains organic ligands such as EDTA, citric acid, and surfactants. These organic compounds readily form water-soluble, stable complexes with some radionuclides. These complexes are not only difficult to remove using traditional adsorption and precipitation processes, but they also persist in decay pools for extended periods, leading to abnormal radionuclide activity decay and an increased risk of exceeding emission limits. Existing systems lack online monitoring and risk prediction capabilities for the complex formation process, often resulting in forced treatment interruptions due to complex accumulation, prolonged decay cycles, or secondary pollution.

[0003] Existing radioactive waste treatment systems lack the ability to identify and predict the formation of stable complexes between organic matter and radionuclides in waste liquids online. They are unable to dynamically adjust the purification mode and discharge cycle based on fluctuations in the concentration of organic matter and the decay characteristics of radionuclides, leading to technical problems such as treatment failures caused by the accumulation of complexes. Summary of the Invention

[0004] To address this, the present invention provides a radioactive waste liquid treatment system to overcome the problem in the prior art that lacks the ability to identify and predict the formation of stable complexes between organic matter and radionuclides in waste liquid online, and cannot dynamically adjust the purification mode and discharge cycle according to the fluctuation of organic matter concentration and the decay characteristics of radionuclides, resulting in treatment failure due to the accumulation of complexes.

[0005] To achieve the above objectives, the present invention provides a radioactive waste liquid treatment system, comprising: The pretreatment module includes a radionuclide analyzer for detecting the types and activities of radionuclides in the waste liquid, a diversion valve group for distributing the waste liquid to several decay cells according to the types and half-life intervals of radionuclides, and a level controller installed in each decay cell for controlling the discharge of liquid. The complexation feature acquisition module is used to acquire the complexation feature parameters of the waste liquid in each decay tank. The complexation feature parameters include pH value, redox potential and fluorescence spectrum intensity. The process construction module, which is connected to the complexation feature acquisition module, is used to determine the pollution complexation index of the complex formed by organic matter and radionuclides in the current decay pool based on the complexation feature parameters, and to construct a decision map based on the pollution complexation index level nodes and the purification mode time consumption. The pollution analysis module, which is connected to the pretreatment module, is used to analyze and obtain the change results of the pollution complexation index based on the fluctuation of organic matter concentration and the degree of radionuclide decay in the waste liquid. The pollution treatment module is connected to the process construction module and the pollution analysis module respectively. It is used to determine whether to change the purification mode based on the change of the pollution complexation index, select the changed purification mode based on the decision map, and adjust the drainage cycle of the liquid level controller according to the effect of the purification mode change.

[0006] Furthermore, the diversion valve assembly is used to distribute the waste liquid to several decay cells according to the type of nuclide and its half-life range, wherein, The diversion valve group pre-divides the half-life into a first half-life interval, a second half-life interval, and a third half-life interval, and configures a corresponding dedicated decay pool for each half-life interval; The diversion valve assembly delivers the waste liquid to the corresponding decay cell based on the type of nuclide detected by the nuclide analyzer and its half-life range.

[0007] Furthermore, the process construction module is used to determine the pollution complexation index, wherein, The process construction module compares the collected pH value, redox potential and fluorescence spectrum intensity with the corresponding threshold range in the preset complexation feature judgment rule library to obtain the complexation contribution score corresponding to each parameter, and then normalizes the weighted sum of each complexation contribution score to obtain the pollution complexation index between 0 and 1. The complexation feature determination rule base includes the complexation constants and corresponding feature parameter ranges between different nuclides and typical organic compounds.

[0008] Furthermore, the process construction module is used to construct a decision graph, wherein, The decision graph uses several level intervals divided by the pollution complexation index as nodes, and determines the edge weights by the average time taken for the pollution complexation index corresponding to different purification modes to drop below a preset safety threshold. The edge weights are negatively correlated with the average time taken.

[0009] Furthermore, the pollution analysis module is used to analyze the changes in the pollution complexation index, wherein, The pollution analysis module calculates the weighted sum of the rate of change of organic matter concentration and the decay rate of radionuclide activity over several consecutive collection cycles to obtain the index fluctuation prediction value. The index fluctuation prediction value is then compared with a preset characteristic threshold to determine the upward or downward trend of the pollution complexation index in subsequent collection cycles.

[0010] Furthermore, the pollution analysis module is used to compare the predicted index fluctuation value with preset rising and falling characteristic thresholds to determine the rising or falling trend of the pollution complexation index in subsequent collection periods. If the predicted value of the index fluctuation is greater than the rising characteristic threshold, the pollution analysis module determines that the pollution complexation index will show an upward trend in the subsequent collection period. If the predicted value of the index fluctuation is less than the decreasing characteristic threshold, the pollution analysis module determines that the pollution complexation index shows a decreasing trend in the subsequent collection period.

[0011] Furthermore, the pollution treatment module is used to determine whether to change the purification mode based on the change in the pollution complexation index, wherein, If it is determined that the pollution complexation index shows an upward trend in the subsequent collection period, the pollution treatment module will use the pollution complexation index as an input node to query the decision graph and select the purification mode with the largest edge weight to change the purification mode. If the pollution complexation index is determined to show a decreasing trend in subsequent collection cycles, the pollution treatment module will maintain the current purification mode.

[0012] Furthermore, the pollution treatment module selects one of the following purification modes: oxidative degradation, ultrasonic-assisted dissociation, and nano-adsorption.

[0013] Furthermore, the contamination treatment module is used to determine whether the drainage cycle of the liquid level controller needs to be adjusted, wherein, The pollution treatment module calculates the efficiency difference between the actual purification efficiency of the modified purification mode and the target purification efficiency in the decision graph. If the efficiency difference is greater than the preset efficiency deviation threshold, the pollution treatment module determines that the drainage cycle of the liquid level controller needs to be adjusted. The target purification efficiency is the average time taken for the pollution complexation index to decrease to a preset safety threshold in the corresponding purification mode in the decision graph, and the actual purification efficiency is the actual time taken for the pollution complexation index to decrease to the preset safety threshold in real time in the current purification mode.

[0014] Furthermore, the contamination treatment module is used to determine the adjusted drainage cycle, wherein, The pollution treatment module determines the ratio of the actual time consumed to the average time consumed as the cycle adjustment coefficient, and determines the adjusted drainage cycle based on the calculation result of the cycle adjustment coefficient and the initial drainage cycle.

[0015] The beneficial effects of the technical solution presented in this application include: a pretreatment module distributes waste liquid to several decay pools based on the type of nuclide and its half-life range; a complexation feature acquisition module acquires the pH value, redox potential, and fluorescence intensity of the waste liquid in each decay pool; a process construction module determines the pollution complexation index of the complexes formed between organic matter and radionuclides in the current decay pool, thereby constructing a decision map; a pollution analysis module analyzes the changes in the pollution complexation index based on fluctuations in the concentration of organic matter in the waste liquid and the degree of nuclide decay; and a pollution treatment module determines whether to change the purification mode and adjusts the drainage cycle of the level controller based on the effect of the purification mode change. Furthermore, this achieves dynamic adjustment of the purification mode and drainage cycle based on fluctuations in the concentration of organic matter in the waste liquid and the characteristics of nuclide decay, avoiding treatment failures caused by complex accumulation and improving the efficiency of radioactive waste liquid treatment.

[0016] Furthermore, this invention constructs a decision graph using pollution complexation index level ranges as nodes and the average time taken to reduce the index to a safe threshold under different purification modes as edge weights. This enables the system to automatically learn the optimal purification path from historical operations. The decision graph constructed by this invention supports dynamic updates, realizes the adaptive evolution of processing strategies, and improves the accuracy and timeliness of purification mode selection under complex working conditions.

[0017] Furthermore, this invention continuously monitors the rate of change in organic matter concentration and the rate of decay of radionuclide activity, and obtains a predicted value for index fluctuation by weighted summation. This enables the early determination of the changing trend of the pollution complexation index in future collection cycles. By utilizing the correlation between increased organic matter concentration promoting complexation reactions and rapid radionuclide decay reducing complexation risk, sufficient response time is reserved for pollution treatment, effectively improving the treatment efficiency of radioactive pollutants.

[0018] Furthermore, this invention automatically queries the decision graph and selects the purification mode with the highest edge weight to perform the change; when the index shows a downward trend, the current mode is maintained to save processing resources. This trend-based change strategy avoids blindly and frequently switching purification modes, and at the same time, it uses historical efficiency data stored in the graph to select the optimal method, improving the success rate of complex destruction or nuclide separation. Attached Figure Description

[0019] Figure 1 This is a system block diagram of the radioactive waste liquid treatment system according to an embodiment of the present invention; Figure 2 This is a flowchart illustrating the logic of the pollution analysis module in this embodiment of the invention for determining the upward or downward trend of the pollution complexation index. Figure 3 This is a flowchart illustrating the logic of the pollution treatment module in an embodiment of the present invention for determining whether to change the purification mode. Figure 4 This is a flowchart illustrating the logic of the pollution treatment module in this embodiment of the invention for determining whether the drainage cycle needs to be adjusted. Detailed Implementation

[0020] To make the objectives and advantages of the present invention clearer, the present invention will be further described below with reference to embodiments; it should be understood that the specific embodiments described herein are merely for explaining the present invention and are not intended to limit the present invention.

[0021] Preferred embodiments of the present invention will now be described with reference to the accompanying drawings. Those skilled in the art should understand that these embodiments are merely illustrative of the technical principles of the present invention and are not intended to limit the scope of protection of the present invention.

[0022] It should be noted that in the description of this invention, the terms "upper," "lower," "inner," "outer," etc., which indicate the direction or positional relationship, are based on the direction or positional relationship shown in the drawings. This is only for the convenience of description and is not intended to indicate or imply that the device or element must have a specific orientation, or be constructed and operated in a specific orientation. Therefore, it should not be construed as a limitation of this invention.

[0023] It should be understood that although the terms "first," "second," etc., may be used in this invention to describe various types of information, these information should not be limited to these terms. These terms are only used to distinguish information of the same type from one another. For example, without departing from the scope of this invention, first information may also be referred to as second information, and similarly, second information may also be referred to as first information.

[0024] Furthermore, it should be noted that, in the description of this invention, unless otherwise explicitly specified and limited, the terms "installation" and "connection" should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integral connection; they can refer to a mechanical connection or an electrical connection; they can refer to a direct connection or an indirect connection through an intermediate medium; and they can refer to the internal connection of two components. Those skilled in the art can understand the specific meaning of the above terms in this invention according to the specific circumstances.

[0025] Please see Figure 1 The diagram shown is a system block diagram of a radioactive waste liquid treatment system according to an embodiment of the present invention. The radioactive waste liquid treatment system of the present invention includes: The pretreatment module includes a radionuclide analyzer for detecting the types and activities of radionuclides in the waste liquid, a diversion valve group for distributing the waste liquid to several decay cells according to the types and half-life intervals of radionuclides, and a level controller installed in each decay cell for controlling the discharge of liquid. During implementation, the nuclide analyzer uses a high-purity germanium gamma spectrometer to identify the types of major nuclides such as Cs-137, Sr-90, and Co-60 in the waste liquid through energy spectrum analysis. The activity of each nuclide is calculated by combining the detector efficiency curve. The activity unit is Bq / L. The nuclide analyzer is installed at the outlet of the inlet pipe of the decay cell.

[0026] In practice, the diversion valve group consists of an electric three-way ball valve, and the half-life intervals are pre-divided as follows: the first half-life interval T1 < 1 day, the second half-life interval 1 day ≤ T2 ≤ 7 days, and the third half-life interval T3 > 7 days.

[0027] In this invention, the liquid level controller is an electric regulating valve, which will not be described in detail here.

[0028] The complexation feature acquisition module is used to acquire the complexation feature parameters of the waste liquid in each decay tank. The complexation feature parameters include pH value, redox potential and fluorescence spectrum intensity. In this invention, a radiation-resistant pH electrode, an ORP composite electrode, and a fiber optic transmission fluorescence spectrometer are used, and each sensor sends real-time data to the process construction module.

[0029] As is well known to those skilled in the art, the complexes formed by organic matter and nuclides in radioactive waste liquid are the main cause of the failure of conventional treatment processes. The formation and stability of complexes are affected by pH value and redox potential, and the intensity of fluorescence spectrum can reflect the concentration of organic complexes.

[0030] The process construction module, which is connected to the complexation feature acquisition module, is used to determine the pollution complexation index of the complex formed by organic matter and radionuclides in the current decay pool based on the complexation feature parameters, and to construct a decision map based on the pollution complexation index level nodes and the purification mode time consumption. The present invention does not limit the specific structure of the process construction module. The computing unit therein can be implemented using an industrial control computer, an embedded microprocessor, or a programmable logic controller. The calculation of the pollution complexation index and the construction and updating of the decision map are completed by a software program running on the above-mentioned hardware, which will not be described in detail here.

[0031] The pollution analysis module, which is connected to the pretreatment module, is used to analyze and obtain the change results of the pollution complexation index based on the fluctuation of organic matter concentration and the degree of radionuclide decay in the waste liquid. This invention does not limit the specific structure of the pollution analysis module, which can be an industrial control computer or a PLC. The weighted summation of the organic matter concentration change rate and the radionuclide activity decay rate, as well as the trend determination, are implemented through conventional numerical calculation logic.

[0032] The pollution treatment module is connected to the process construction module and the pollution analysis module respectively. It is used to determine whether to change the purification mode based on the change of the pollution complexation index, select the changed purification mode based on the decision map, and adjust the drainage cycle of the liquid level controller according to the effect of the purification mode change.

[0033] The present invention does not limit the specific structure of the pollution treatment module. The switching of its purification mode can be achieved by controlling the start and stop of external actuators, such as ozone generator, ultrasonic vibrating plate, nano-adsorbent dosing device and magnetic separation unit. The adjustment of the drainage cycle can be accomplished by modifying the timing parameters of the liquid level controller, which will not be elaborated here.

[0034] Specifically, the diversion valve assembly is used to distribute the waste liquid to several decay cells according to the type of nuclide and its half-life range, wherein, The diversion valve group pre-divides the half-life into a first half-life interval, a second half-life interval, and a third half-life interval, and configures a corresponding dedicated decay pool for each half-life interval; The diversion valve assembly delivers the waste liquid to the corresponding decay cell based on the type of nuclide detected by the nuclide analyzer and its half-life range.

[0035] Radioactive waste often contains multiple nuclides, such as Cs-137, Sr-90, and Co-60. These nuclides have vastly different half-lives. If long-lived and short-lived nuclides are mixed in the same decay pool, the long-lived nuclides will persist for a long time after the short-lived nuclides have decayed, making it impossible to empty the decay pool in a timely manner and consuming significant processing resources. Furthermore, different nuclides exhibit significantly different complexation tendencies with organic matter, and mixed disposal exacerbates the complexity of complexation risk identification.

[0036] Specifically, the process construction module is used to determine the pollution complexation index, wherein, The process construction module compares the collected pH value, redox potential and fluorescence spectrum intensity with the corresponding threshold range in the preset complexation feature judgment rule library to obtain the complexation contribution score corresponding to each parameter, and then normalizes the weighted sum of each complexation contribution score to obtain the pollution complexation index between 0 and 1. The complexation feature determination rule base includes the complexation constants and corresponding feature parameter ranges between different nuclides and typical organic compounds.

[0037] The pollution complexation index quantifies the risk and severity of the formation of complexes between radionuclides and organic matter in wastewater.

[0038] In this invention, a pre-established rule library for determining complexation characteristics is used to obtain typical distribution ranges of each parameter under different complexation degrees through static laboratory experiments for combinations of common nuclides and organic matter. During actual operation, the process construction module calculates the ratios of the real-time collected pH value, redox potential, and fluorescence spectral intensity to the corresponding preset reference values ​​in the rule library for determining complexation characteristics, thereby obtaining the complexation contribution ratio of each parameter. Then, the complexation contribution ratios are weighted, summed, and normalized to obtain a pollution complexation index between 0 and 1. Optionally, the weight of pH value is set to 0.4, the weight of redox potential is set to 0.3, and the weight of fluorescence spectral intensity is set to 0.3.

[0039] For example, taking radioactive waste containing Co60 as an example, the waste liquid contains EDTA-like organic matter, and the two readily form stable complexes. Reference values ​​in the complexation characteristic determination rule library for the Co60 and EDTA combination were pre-defined through static laboratory experiments: pH. ref =6.5, ORP ref =220mV, Fluorescence spectral intensity reference value FL ref =85%, FL ref The relative values ​​are determined with the fluorescence intensity in pure water as 100%. The weighting coefficients are set as follows: pH weight w1 = 0.4, ORP weight w2 = 0.3, and fluorescence spectral intensity weight w3 = 0.3.

[0040] One instance of real-time data collection was: pH real =6.2, ORP real =210mV, FL real =90%. The process construction module calculates the contamination complexation index according to the following steps: R pH =6.2 / 6.5≈0.9538, R ORP =210 / 220≈0.9545, R FL =90% / 85%≈1.0588; The weighted summation yields a pollution complexation index S = 0.9855. If the weighted summation result is greater than 1, then the pollution complexation index is set to 1.

[0041] As is well known to those skilled in the art, changes in pH value can affect the existing form of nuclide ions and the degree of dissociation of functional groups of organic matter, thereby changing the equilibrium constant of complexation reactions; redox potential determines the valence state of nuclides, and there are significant differences in the complexation ability of nuclides with organic matter in different valence states; organic complexes will produce characteristic fluorescence under specific wavelength excitation, and the intensity of the fluorescence is positively correlated with the concentration of the complex.

[0042] Specifically, the process construction module is used to construct a decision graph, wherein, The decision graph uses several level intervals divided by the pollution complexation index as nodes, and determines the edge weights by the average time taken for the pollution complexation index corresponding to different purification modes to drop below a preset safety threshold. The edge weights are negatively correlated with the average time taken.

[0043] The core objective of radioactive waste treatment is to reduce pollution to a safe level in the shortest possible time. Treatment time is the most direct indicator for evaluating the quality of a purification mode. Using time as a weight ensures that the system prioritizes the purification mode with the highest treatment efficiency.

[0044] In this invention, the pollution complexation index is divided into several levels from 0 to 1. For example, the pollution complexation index is divided into five different level intervals: [0, 0.2), [0.2, 0.4), [0.4, 0.6), [0.6, 0.8), and [0.8, 1]. Each level interval corresponds to a node in the graph. For nodes i to j, where node j corresponds to a lower index level interval, if a purification mode exists that can reduce the index from level i to level j, a directed edge is used to connect them, and the average time taken to use this mode multiple times in history is recorded. The edge weight is defined as the reciprocal of the average time taken. During system operation, starting from the current node, all paths that can reach nodes below the safety threshold are searched, and the purification mode corresponding to the path with the largest sum of edge weights is selected as the optimal purification mode. After each execution, the actual time taken is fed back and the graph edge weights are updated, achieving self-learning.

[0045] This invention constructs a decision graph using pollution complexation index level ranges as nodes and the average time taken to reduce the index to a safe threshold under different purification modes as edge weights. This enables the system to automatically learn the optimal purification path from historical operations. The decision graph constructed by this invention supports dynamic updates, realizes the adaptive evolution of processing strategies, and improves the accuracy and timeliness of purification mode selection under complex working conditions.

[0046] Specifically, the pollution analysis module is used to analyze the changes in the pollution complexation index, wherein... The pollution analysis module calculates the weighted sum of the rate of change of organic matter concentration and the decay rate of radionuclide activity over several consecutive collection cycles to obtain the index fluctuation prediction value. The index fluctuation prediction value is then compared with a preset characteristic threshold to determine the upward or downward trend of the pollution complexation index in subsequent collection cycles.

[0047] In this invention, the concentration of organic matter is measured using an online total organic carbon analyzer, with units of mg / L; the activity of radionuclides is measured using a radionuclide analyzer, with units of Bq / L.

[0048] Understandably, changes in the concentration of organic matter and the activity of radionuclides in wastewater are two major factors driving the evolution of complexation risk. Increased organic matter concentration raises the probability of complexation reactions; similarly, radionuclide activity naturally decreases due to decay, and decay products may possess different complexation properties. If the direction of change in the pollution complexation index can be predicted in advance, proactive intervention can be taken before the risk escalates, avoiding treatment delays caused by passive adjustments.

[0049] For example, if the concentration of organic matter in the i-th collection cycle is C i The activity of the nuclide is A i ; Calculate the rate of change: ΔC i =(C i -C i-1 ) / △t, △Ai=(A i -A i-1 The mean value of the organic matter change rate R is taken as the average value of n consecutive periods. C and the mean decay rate R of nuclides A The predicted index fluctuation value is P = α·R. C +β·(R A ), α = 0.6, β = 0.4, where the natural decay rate of nuclide activity is negative, and taking the negative sign results in a positive contribution because rapid decay reduces the risk of complexation. α and β are empirical weighting coefficients. Preset rising characteristic threshold T1 and falling characteristic threshold T2, T2 < 0 < T1. If P > T1, the pollution complexation index is determined to show an upward trend in the future; if P < T2, the pollution complexation index will show a downward trend in the future; optionally, n = 3 in this invention.

[0050] Specifically, please refer to Figure 2 The diagram shows a flowchart illustrating the logic of determining the upward or downward trend of the pollution complexation index according to an embodiment of the present invention. The pollution analysis module compares the predicted index fluctuation value with preset upward and downward threshold values ​​to determine the upward or downward trend of the pollution complexation index in subsequent collection periods. If the predicted value of the index fluctuation is greater than the rising characteristic threshold, the pollution analysis module determines that the pollution complexation index will show an upward trend in the subsequent collection period. If the predicted value of the index fluctuation is less than the decreasing characteristic threshold, the pollution analysis module determines that the pollution complexation index shows a decreasing trend in the subsequent collection period.

[0051] Based on multiple laboratory simulation experiments and field data statistics, the fluctuation range of the predicted index fluctuation value under normal and stable operating conditions is approximately between -0.05 and +0.05. Optionally, in the implementation of this invention, the rising characteristic threshold T1 = +0.05 and the falling characteristic threshold T2 = -0.05.

[0052] This invention continuously monitors the rate of change in organic matter concentration and the rate of decay of radionuclide activity, and obtains a predicted value for index fluctuation by weighted summation. This allows for the early determination of the trend of pollution complexation index changes in future collection periods. By utilizing the correlation between increased organic matter concentration promoting complexation reactions and rapid radionuclide decay reducing complexation risk, sufficient response time is reserved for pollution treatment, effectively improving the treatment efficiency of radioactive pollutants.

[0053] Specifically, please refer to Figure 3 The diagram shown is a flowchart illustrating the logic of the pollution treatment module in an embodiment of the present invention for determining whether to change the purification mode. The pollution treatment module determines whether to change the purification mode based on changes in the pollution complexation index. If it is determined that the pollution complexation index shows an upward trend in the subsequent collection period, the pollution treatment module will use the pollution complexation index as an input node to query the decision graph and select the purification mode with the largest edge weight to change the purification mode. If the pollution complexation index is determined to show a decreasing trend in subsequent collection cycles, the pollution treatment module will maintain the current purification mode.

[0054] This invention automatically queries the decision graph and selects the purification mode with the highest edge weight to implement the change; when the index shows a downward trend, the current mode is maintained to save processing resources. This trend-based change strategy avoids blindly and frequently switching purification modes, and at the same time, it uses historical efficiency data stored in the graph to select the optimal method, improving the success rate of complex destruction or nuclide separation.

[0055] Specifically, the pollution treatment module selects one of the following purification modes: oxidative degradation, ultrasonic-assisted dissociation, and nano-adsorption.

[0056] As is well known to those skilled in the art, when the risk of complexation increases, it is necessary to actively disrupt the complex structure or separate the nuclide. Different purification modes have significantly different effects on complexes between different nuclides and organic matter; oxidation can decompose organic ligands; ultrasonic-assisted dissociation breaks coordination bonds through cavitation; and nano-adsorption can selectively capture free nuclides. Blindly switching modes may result in ineffective treatment or increase secondary waste. Utilizing historical efficiency data stored in the decision graph to select the optimal mode is key to achieving intelligent treatment.

[0057] In this invention, oxidative degradation can be performed using an ultraviolet / hydrogen peroxide system. Optionally, the ultraviolet lamp power is 50W, the wavelength is 254nm, and the hydrogen peroxide concentration is 100mg / L. Ultrasonic-assisted dissociation uses an immersion ultrasonic transducer with a frequency of 40kHz and a power density of 0.5W / mL. Nano-adsorption can be performed using a magnetic nano-adsorbent with carboxyl groups modified on its surface, with an addition amount of 2g / L.

[0058] Specifically, please refer to Figure 4 The diagram shown is a logic flowchart of the pollution treatment module in an embodiment of the present invention determining whether the drainage cycle needs to be adjusted. The pollution treatment module is used to determine whether the drainage cycle of the level controller needs to be adjusted. The pollution treatment module calculates the efficiency difference between the actual purification efficiency of the modified purification mode and the target purification efficiency in the decision graph. If the efficiency difference is less than or equal to the preset efficiency deviation threshold, the pollution treatment module determines that it is not necessary to adjust the drainage cycle of the liquid level controller. If the efficiency difference is greater than the preset efficiency deviation threshold, the pollution treatment module determines that the drainage cycle of the liquid level controller needs to be adjusted. The target purification efficiency is the average time taken for the pollution complexation index to decrease to a preset safety threshold in the corresponding purification mode in the decision graph, and the actual purification efficiency is the actual time taken for the pollution complexation index to decrease to the preset safety threshold in real time in the current purification mode.

[0059] In this invention, EDTA-Co-60-containing wastewater is treated by oxidation degradation, ultrasonic-assisted dissociation, and nano-adsorption. When the pollution complexation index drops below 0.2, the Co-60 activity in the effluent after passing through the ion exchange column is below 5 Bq / L, meeting the emission standards. Therefore, the preset safety threshold for the pollution complexation index can be 0.2.

[0060] In this invention, the discharge cycle of the decay tank determines the residence time of the waste liquid in the tank. Too short a residence time may lead to incomplete purification and excessive nuclide activity; too long a residence time will reduce the treatment throughput. By comparing the actual purification time with the historical average time, the discharge cycle can be quantitatively adjusted to achieve dynamic matching.

[0061] Specifically, the pollution treatment module is used to determine the adjusted drainage cycle, wherein, The pollution treatment module determines the ratio of the actual time consumed to the average time consumed as the cycle adjustment coefficient, and determines the adjusted drainage cycle based on the calculation result of the cycle adjustment coefficient and the initial drainage cycle.

[0062] In this invention, when the actual purification time is too long, the drainage cycle is automatically extended to ensure that the waste liquid has sufficient residence time in the pool to completely remove complex nuclides; when the actual purification time is too short, the drainage cycle is appropriately shortened to increase the system's processing throughput and maximize the processing efficiency.

[0063] For example, if the decision graph records that the average time it takes for the currently selected purification mode to reduce the pollution complexation index from its initial value to a preset safety threshold is T... avg The actual execution time after implementing this mode was measured to be T.act Calculate the efficiency difference ΔE = |T act -T avg | / T avg ×100%. The preset efficiency deviation threshold is 10%. If ΔE > 10%, it is determined that the drainage cycle needs to be adjusted.

[0064] Periodic adjustment coefficient k = T act / T avg Let the current drainage cycle be P. c The adjusted drainage cycle P new =P c ×k. When k>1, the drainage cycle is extended; when k<1, the drainage cycle is shortened. The adjusted new cycle is executed by the level controller, and the average time T of the corresponding edge in the decision graph is updated synchronously. avg =(T avg ×N+T act ) / (N+1), where N is the number of historical records, and T avg ´ represents the average time taken in history to reduce the contamination complexation index from the current level range to below the preset safety threshold before this operation.

[0065] The technical solution of the present invention has been described above with reference to the preferred embodiments shown in the accompanying drawings. However, it will be readily understood by those skilled in the art that the scope of protection of the present invention is obviously not limited to these specific embodiments. Without departing from the principles of the present invention, those skilled in the art can make equivalent changes or substitutions to the relevant technical features, and the technical solutions after these changes or substitutions will all fall within the scope of protection of the present invention.

[0066] The above description is merely a preferred embodiment of the present invention and is not intended to limit the invention. Various modifications and variations can be made to the present invention by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

Claims

1. A radioactive waste liquid treatment system, characterized in that, include: The pretreatment module includes a radionuclide analyzer for detecting the types and activities of radionuclides in the waste liquid, a diversion valve group for distributing the waste liquid to several decay cells according to the types and half-life intervals of radionuclides, and a level controller installed in each decay cell for controlling the discharge of liquid. The complexation feature acquisition module is used to acquire the complexation feature parameters of the waste liquid in each decay tank. The complexation feature parameters include pH value, redox potential and fluorescence spectrum intensity. The process construction module, which is connected to the complexation feature acquisition module, is used to determine the pollution complexation index of the complex formed by organic matter and radionuclides in the current decay pool based on the complexation feature parameters, and to construct a decision map based on the pollution complexation index level nodes and the purification mode time consumption. The pollution analysis module, which is connected to the pretreatment module, is used to analyze and obtain the change results of the pollution complexation index based on the fluctuation of organic matter concentration and the degree of radionuclide decay in the waste liquid. The pollution treatment module is connected to the process construction module and the pollution analysis module respectively. It is used to determine whether to change the purification mode based on the change of the pollution complexation index, select the changed purification mode based on the decision map, and adjust the drainage cycle of the liquid level controller according to the effect of the purification mode change.

2. The radioactive waste liquid treatment system according to claim 1, characterized in that, The diversion valve assembly is used to distribute the waste liquid to several decay cells according to the type of nuclide and its half-life range. The diversion valve group pre-divides the half-life into a first half-life interval, a second half-life interval, and a third half-life interval, and configures a corresponding dedicated decay pool for each half-life interval; The diversion valve assembly delivers the waste liquid to the corresponding decay cell based on the type of nuclide detected by the nuclide analyzer and its half-life range.

3. The radioactive waste liquid treatment system according to claim 1, characterized in that, The process construction module is used to determine the pollution complexation index, wherein... The process construction module compares the collected pH value, redox potential and fluorescence spectrum intensity with the corresponding threshold range in the preset complexation feature judgment rule library to obtain the complexation contribution score corresponding to each parameter, and then normalizes the weighted sum of each complexation contribution score to obtain the pollution complexation index between 0 and 1. The complexation feature determination rule base includes the complexation constants and corresponding feature parameter ranges between different nuclides and typical organic compounds.

4. The radioactive waste liquid treatment system according to claim 3, characterized in that, The process construction module is used to construct a decision graph, wherein... The decision graph uses several level intervals divided by the pollution complexation index as nodes, and determines the edge weights by the average time taken for the pollution complexation index corresponding to different purification modes to drop below a preset safety threshold. The edge weights are negatively correlated with the average time taken.

5. The radioactive waste liquid treatment system according to claim 4, characterized in that, The pollution analysis module is used to analyze the changes in the pollution complexation index, wherein... The pollution analysis module calculates the weighted sum of the rate of change of organic matter concentration and the decay rate of radionuclide activity over several consecutive collection cycles to obtain the index fluctuation prediction value. The index fluctuation prediction value is then compared with a preset characteristic threshold to determine the upward or downward trend of the pollution complexation index in subsequent collection cycles.

6. The radioactive waste liquid treatment system according to claim 5, characterized in that, The pollution analysis module is used to compare the predicted index fluctuation value with preset rising and falling characteristic thresholds to determine the rising or falling trend of the pollution complexation index in subsequent collection periods. If the predicted value of the index fluctuation is greater than the rising characteristic threshold, the pollution analysis module determines that the pollution complexation index will show an upward trend in the subsequent collection period. If the predicted value of the index fluctuation is less than the decreasing characteristic threshold, the pollution analysis module determines that the pollution complexation index shows a decreasing trend in the subsequent collection period.

7. The radioactive waste liquid treatment system according to claim 6, characterized in that, The pollution treatment module is used to determine whether to change the purification mode based on the change in the pollution complexation index. If it is determined that the pollution complexation index shows an upward trend in the subsequent collection period, the pollution treatment module will use the current pollution complexation index as an input node to query the decision graph and select the purification mode with the largest edge weight to change the purification mode. If the pollution complexation index is determined to show a decreasing trend in subsequent collection cycles, the pollution treatment module will maintain the current purification mode.

8. The radioactive waste liquid treatment system according to claim 7, characterized in that, The pollution treatment module can select one of the following purification modes: oxidative degradation, ultrasonic-assisted dissociation, and nano-adsorption.

9. The radioactive waste liquid treatment system according to claim 7, characterized in that, The pollution treatment module is used to determine whether the drainage cycle of the liquid level controller needs to be adjusted. The pollution treatment module calculates the efficiency difference between the actual purification efficiency of the modified purification mode and the target purification efficiency in the decision graph. If the efficiency difference is greater than the preset efficiency deviation threshold, the pollution treatment module determines that the drainage cycle of the liquid level controller needs to be adjusted. The target purification efficiency is the average time taken for the pollution complexation index to decrease to a preset safety threshold in the corresponding purification mode in the decision graph, and the actual purification efficiency is the actual time taken for the pollution complexation index to decrease to the preset safety threshold in real time in the current purification mode.

10. The radioactive waste liquid treatment system according to claim 9, characterized in that, The pollution treatment module is used to determine the adjusted drainage cycle, wherein... The pollution treatment module determines the ratio of the actual time consumed to the average time consumed as the cycle adjustment coefficient, and determines the adjusted drainage cycle based on the calculation result of the cycle adjustment coefficient and the initial drainage cycle.

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