Biological activated carbon in-situ adsorption capacity evaluation and failure prediction method based on adsorption-regeneration coupling kinetic model

Abstract

The invention relates to the technical field of water treatment and purification engineering, in particular to a biological activated carbon in-situ adsorption capacity evaluation and failure prediction method based on an adsorption-regeneration coupling kinetic model, which comprises the following steps: collecting monitoring data in the operation process of target biological activated carbon in real time; the monitoring data are input into a pre-constructed dynamic coupling kinetic model, the instantaneous adsorption capacity of the target biological activated carbon is calculated, the adsorption site availability rate change trend and the adsorption capacity change curve are obtained, the failure critical value is calculated, and the dynamic coupling kinetic model is used for determining the adsorption capacity of the target biological activated carbon through coupling water phase-adsorption phase-biological phase material balance. And the whole process of mass transfer migration, adsorption-desorption, microbial degradation and adsorption site regeneration of the biodegradable organic carbon and the non-biodegradable organic carbon in the biological activated carbon filter is quantitatively described. The in-situ adsorption capacity of the biological activated carbon is dynamically evaluated in real time based on a microorganism regeneration mechanism, and high-precision prediction of activated carbon failure is achieved.

Description

Technical Field

[0001] This invention relates to the field of water treatment and purification engineering technology, and in particular to a method for evaluating the in-situ adsorption capacity and predicting the failure of biological activated carbon based on an adsorption-regeneration coupled kinetic model. Background Technology

[0002] Biological activated carbon (BAC) technology is a crucial component in the field of advanced drinking water purification. Leveraging the adsorption capacity of activated carbon for soluble organic matter and the metabolic degradation capacity of attached microorganisms for some degradable organic matter, it plays a key role in ensuring water quality safety and improving water quality stability. Traditionally, it was believed that after long-term operation, the organic matter removal capacity of BAC primarily relied on the metabolism of microorganisms on the activated carbon surface, while the adsorption capacity of the activated carbon itself gradually decreased or even disappeared. However, recent studies have found that the adsorption effect of activated carbon persists throughout the entire BAC operating cycle, and the efficiency and stability of microbial metabolism are highly dependent on the substrate provided by the activated carbon adsorption, such as biodegradable organic carbon (BDOC). With prolonged operation, the BDOC adsorbed by the activated carbon is gradually replaced by non-biodegradable organic carbon (NBDOC), leading to irreversible loss of adsorption sites and resulting in activated carbon "failure." Currently, BAC failure assessment mainly relies on static single-index tests (such as iodine value and methylene blue value), which cannot truly reflect the in-situ state of the activated carbon in the BAC system, nor accurately describe the dynamic changes between adsorption and microbial regeneration. Furthermore, existing methods lack dynamic evaluation models that calibrate parameters based on actual field data, resulting in insufficient accuracy of evaluation results and a lack of scientific basis for carbon replacement decisions.

[0003] Therefore, in order to overcome the problem that traditional evaluation methods cannot truly reflect the in-situ adsorption state and failure trend of BAC, a method for evaluating the in-situ adsorption capacity and predicting the failure of bio-activated carbon based on an adsorption-regeneration coupled kinetic model is proposed. This method can accurately describe the dynamic coupling relationship between adsorption and microbial regeneration and achieve on-site parameter calibration, thereby accurately predicting the in-situ adsorption capacity and failure trend of activated carbon. Summary of the Invention

[0004] The purpose of this invention is to provide a method for evaluating the in-situ adsorption capacity and predicting the failure of bio-activated carbon based on an adsorption-regeneration coupled kinetic model. This method dynamically evaluates the in-situ adsorption capacity of bio-activated carbon in real time based on the microbial regeneration mechanism, achieving high-precision prediction of activated carbon failure and providing important decision support and scientific basis for activated carbon replacement strategies.

[0005] To achieve the above objectives, the present invention provides the following solution:

[0006] A method for in-situ adsorption capacity assessment and failure prediction of bio-activated carbon based on an adsorption-regeneration coupled kinetic model includes:

[0007] Real-time acquisition of monitoring data during the operation of the target bio-activated carbon;

[0008] The monitoring data is input into a pre-constructed adsorption-regeneration coupled kinetic model to calculate the instantaneous adsorption capacity of the target bio-activated carbon, obtain the trend of adsorption site availability and the adsorption capacity change curve, and calculate the failure threshold. The adsorption-regeneration coupled kinetic model is constructed by coupling the material balance of the aqueous phase, adsorption phase and biological phase, and quantitatively describing the entire process of mass transfer, adsorption-desorption, microbial degradation and adsorption site regeneration of biodegradable organic carbon and non-biodegradable organic carbon in the bio-activated carbon filter.

[0009] Optionally, the monitoring data includes: influent and effluent organic carbon concentration, microbial quantity, microbial degradation rate, organic carbon concentration adsorbed in activated carbon, adsorption capacity, availability of adsorption sites, adsorption rate constant, re-release rate, maximum specific growth rate of microorganisms, and regeneration efficiency.

[0010] Optionally, the adsorption-regeneration coupled kinetic model includes: a dynamic model of organic carbon concentration in influent and effluent, a dynamic model of organic carbon concentration in the activated carbon adsorption phase, a model of microbial regeneration and degradation rate, a dynamic model of microbial biomass, and a dynamic model of activated carbon adsorption site availability.

[0011] Optionally, the dynamic model of organic carbon concentration in the influent and effluent includes:

[0012] Relationship between influent and effluent concentrations of biodegradable organic carbon in aqueous phase:

[0013]

[0014] Relationship between influent and effluent concentrations of non-biodegradable organic carbon in the aqueous phase:

[0015]

[0016] Among them, C B,out (t) represents the concentration of biodegradable organic carbon in the effluent, t is time, Q is the influent flow rate, V is the volume of the carbon tank, and C is the concentration of biodegradable organic carbon in the effluent. B,in (t) represents the concentration of biodegradable organic carbon in the influent, k a,B S(t) represents the adsorption rate constant of biodegradable organic carbon, S(t) represents the availability of activated carbon adsorption sites, θ represents the contribution coefficient of microorganisms to the degradation of aqueous substrates, and μ represents the adsorption rate constant of biodegradable organic carbon. max K represents the maximum specific growth rate of microorganisms. sc λ is the Monod half-saturation constant of biodegradable organic carbon in the aqueous phase, X(t) is the amount of microorganisms attached to a unit mass of activated carbon, and λ is the total amount of microorganisms attached to the activated carbon. B q is the rate coefficient for the re-release of biodegradable organic carbon. B(t) represents the biodegradable organic carbon adsorbed on a unit mass of activated carbon, C N,out (t) represents the concentration of non-biodegradable organic carbon in the effluent, C N,in (t) represents the concentration of non-biodegradable organic carbon in the influent, k a,N λ is the adsorption rate constant of non-biodegradable organic carbon. N q is the rate coefficient for the re-release of non-biodegradable organic carbon. N (t) represents the amount of non-biodegradable organic carbon adsorbed on a unit mass of activated carbon.

[0017] Optionally, the dynamic change model of organic carbon concentration in the activated carbon adsorption phase includes:

[0018] The relationship between the mass change of biodegradable organic carbon in the adsorbed phase:

[0019]

[0020] Relationship between the mass change of non-biodegradable organic carbon in the adsorbed phase:

[0021]

[0022] Where, q B (t) represents the biodegradable organic carbon adsorbed on a unit mass of activated carbon, t represents time, and k represents the time. a,B C is the adsorption rate constant of biodegradable organic carbon. B,in (t) represents the concentration of biodegradable organic carbon in the influent, C B,out S(t) represents the concentration of biodegradable organic carbon in the effluent, S(t) represents the availability of activated carbon adsorption sites, R(t) represents the degradation rate of biodegradable organic carbon in the adsorbate phase by microorganisms, and λ B q is the rate coefficient for the re-release of biodegradable organic carbon. N (t) represents the non-biodegradable organic carbon adsorbed on a unit mass of activated carbon, k a,N C is the adsorption rate constant of non-biodegradable organic carbon. N,in (t) represents the concentration of non-biodegradable organic carbon in the influent, C N,out (t) represents the concentration of non-biodegradable organic carbon in the effluent, λ N The coefficient representing the rate of re-release of non-biodegradable organic carbon.

[0023] Optionally, the microbial regeneration and degradation rate model is as follows:

[0024]

[0025] Where R(t) is the degradation rate of biodegradable organic carbon in the adsorbed phase by microorganisms, Y is the bioyield coefficient, and μ max q represents the maximum specific growth rate of microorganisms.B (t) represents the biodegradable organic carbon adsorbed on a unit mass of activated carbon, K sq denoted as Monod half-saturation constant for biodegradable organic carbon in the adsorbed phase, and X(t) is the amount of microorganisms attached to a unit mass of activated carbon.

[0026] Optionally, the dynamic change model of microbial biomass is as follows:

[0027]

[0028] Where X(t) is the amount of microorganisms attached to a unit mass of activated carbon, t is time, Y is the biomass yield coefficient, and μ max η is the maximum specific growth rate of microorganisms, η is the dependence coefficient of microorganisms on biodegradable organic carbon in the adsorbed phase as substrate, and q is the maximum specific growth rate of microorganisms. B (t) represents the biodegradable organic carbon adsorbed on a unit mass of activated carbon, K sq C is the Monod half-saturation constant of the biodegradable organic carbon in the adsorbed phase. B,out (t) represents the concentration of biodegradable organic carbon in the effluent, K sc k is the Monod half-saturation constant for biodegradable organic carbon in the aqueous phase. decay This represents the natural mortality coefficient of microorganisms.

[0029] Optionally, the dynamic change model for the availability of activated carbon adsorption sites is as follows:

[0030]

[0031] Where S(t) is the availability of activated carbon adsorption sites, t is time, and k is the number of adsorption sites. d,B C is the loss coefficient of biodegradable organic carbon adsorption sites. B,in (t) represents the concentration of biodegradable organic carbon in the influent, C B,out S(t) represents the concentration of biodegradable organic carbon in the effluent, S(t) represents the availability of activated carbon adsorption sites, and k d,N C is the loss coefficient of non-biodegradable organic carbon adsorption sites. N,in (t) represents the concentration of non-biodegradable organic carbon in the influent, C N,out R(t) represents the concentration of non-biodegradable organic carbon in the effluent, α represents the regeneration and activation efficiency of the adsorption sites, and R(t) represents the degradation rate of biodegradable organic carbon in the adsorbed phase by microorganisms.

[0032] Optionally, the instantaneous adsorption capacity of the target bio-activated carbon is calculated, the trend of adsorption site availability and the adsorption capacity change curve are obtained, and the failure threshold is calculated, including:

[0033] Based on the adsorption-regeneration coupled kinetic model, the instantaneous adsorption flux of the target bio-activated carbon, the proportion of biodegradable and non-biodegradable organic carbon adsorbed on the target bio-activated carbon per unit mass, and the organic matter removal rate are continuously calculated.

[0034] The adsorption capacity of the target bio-activated carbon is dynamically evaluated based on continuous calculation results, and the failure status and failure time are determined based on a preset threshold.

[0035] The beneficial effects of this invention are as follows:

[0036] The coupled kinetic model established in this invention comprehensively considers the dynamic equilibrium of organic matter in the aqueous and adsorbed phases, clarifies the main degradation effect of microorganisms on adsorbed organic matter, and is dynamically corrected and verified with field data. This invention can evaluate the actual adsorption capacity of biological activated carbon filters in real time and accurately predict the failure trend and optimal replacement time of activated carbon, significantly improve the operation and management efficiency of BAC systems, reduce operating costs, and enhance the stability of system operation. Attached Figure Description

[0037] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0038] Figure 1 This is a flowchart of a method for evaluating the in-situ adsorption capacity and predicting the failure of bio-activated carbon based on an adsorption-regeneration coupled kinetic model, according to an embodiment of the present invention. Detailed Implementation

[0039] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0040] To make the above-mentioned objects, features and advantages of the present invention more apparent and understandable, the present invention will be further described in detail below with reference to the accompanying drawings and specific embodiments.

[0041] This embodiment provides a method for evaluating the in-situ adsorption capacity and predicting the failure of bio-activated carbon based on an adsorption-regeneration coupled kinetic model, such as... Figure 1 As shown, it includes:

[0042] Real-time acquisition of monitoring data during the operation of the target bio-activated carbon;

[0043] The monitoring data is input into a pre-constructed adsorption-regeneration coupled kinetic model to calculate the instantaneous adsorption capacity of the target bio-activated carbon, obtain the trend of adsorption site availability and the adsorption capacity change curve, and calculate the failure threshold. The adsorption-regeneration coupled kinetic model is constructed by coupling the material balance of the aqueous phase, adsorption phase and biological phase, and quantitatively describing the entire process of mass transfer, adsorption-desorption, microbial degradation and adsorption site regeneration of biodegradable organic carbon and non-biodegradable organic carbon in the bio-activated carbon filter.

[0044] Specifically, the adsorption-regeneration coupled kinetic model established in this embodiment comprehensively considers the dynamic equilibrium of organic matter in the aqueous phase and the adsorption phase, clarifies the main degradation effect of microorganisms on adsorbed organic matter, and uses field data for dynamic correction and verification. This embodiment can evaluate the actual adsorption capacity of the biological activated carbon filter in real time and accurately predict the failure trend and optimal replacement time of activated carbon, significantly improve the operation and management efficiency of the BAC system, reduce operating costs, and enhance the stability of system operation.

[0045] Furthermore, the monitoring data includes: influent and effluent organic carbon concentration, microbial quantity, microbial degradation rate, organic carbon concentration adsorbed in activated carbon, adsorption capacity, availability of adsorption sites, adsorption rate constant, re-release rate, maximum specific growth rate of microorganisms, and regeneration efficiency.

[0046] Furthermore, the adsorption-regeneration coupled kinetic model includes: a dynamic model of organic carbon concentration in influent and effluent, a dynamic model of organic carbon concentration in the activated carbon adsorption phase, a model of microbial regeneration and degradation rate, a dynamic model of microbial biomass, and a dynamic model of activated carbon adsorption site availability.

[0047] Specifically, the construction and application of the adsorption-regeneration coupled kinetic model in this embodiment includes the following: comprehensively considering the migration process, adsorption process, and microbial regeneration process of organic matter between the aqueous and adsorbed phases; comprehensively considering the dynamic equilibrium and coupling relationship between biodegradable organic carbon (BDOC) and non-biodegradable organic carbon (NBDOC) in the aqueous and adsorbed phases; clarifying the degradation effect of microorganisms on adsorbed organic matter and their regeneration effect on adsorption sites; establishing a real-time calibration mechanism for model parameters based on field monitoring data, dynamically optimizing model parameters, and ensuring the accuracy of the evaluation results. A detailed introduction follows:

[0048] Step 1: Model Building;

[0049] The adsorption-regeneration coupled kinetic model is based on the principle of mass conservation, adsorption kinetics theory, and Monod growth kinetics. Through a coupled aqueous-adsorbed-biological phase mass balance model, the model quantitatively describes the entire process of mass transfer, adsorption-desorption, microbial degradation, and adsorption site regeneration of biodegradable organic carbon (BDOC) and non-biodegradable organic carbon (NBDOC) in a biological activated carbon (BAC) filter.

[0050] For ease of understanding, the BAC system can be modeled as a continuously operating reactor unit with influent and effluent flow. At the influent end, BDOC and NBDOC are introduced; dissolved organic matter in the aqueous phase comes into direct contact with microorganisms and can be partially degraded or adsorbed onto the activated carbon surface; organic matter enriched on the micropores and surface sites of the activated carbon in the adsorbed phase can undergo desorption or be degraded by attached microorganisms; the microbial community attached to the activated carbon utilizes the adsorbed substrate and organic matter in the water for growth and metabolism; residual organic matter is discharged at the effluent end. The material changes of the entire system satisfy the basic mass balance equation: Influent organic matter - Effluent organic matter = Accumulated organic matter adsorbed by activated carbon + Accumulated organic matter from biodegradation.

[0051] Specifically, it includes the following core models:

[0052] 1.1 Dynamic model of organic carbon concentration in influent and effluent:

[0053] For aqueous BDOC, its concentration variation should simultaneously consider the hydraulic exchange between influent and effluent, adsorption on the activated carbon surface, direct biochemical degradation in the aqueous phase, and desorption and reflux of the adsorbed phase. The relationship can be expressed as follows:

[0054]

[0055] In the formula, C B,in (t) represents the BDOC concentration in the influent, mg / L; C B,out (t) represents the BDOC concentration in the effluent, mg / L; Q represents the influent flow rate, m³ / L. 3 / d; V is the volume of the carbon pool, m 3 ;k a,B θ is the BDOC adsorption rate constant, L / (mg·d); S(t) is the availability of activated carbon adsorption sites (0–1), dimensionless; θ is the contribution coefficient of microorganisms to the degradation of aqueous substrates (0–1), dimensionless; μ max The maximum specific growth rate of microorganisms, 1 / d; K sc λ is the Monod half-saturation constant of BDOC in the aqueous phase, mg / L; X(t) is the amount of microorganisms attached to a unit mass of activated carbon, μg / g; B q is the BDOC re-release rate coefficient, 1 / d; B(t) represents the amount of BDOC adsorbed on a unit mass of activated carbon, in mg / g.

[0056] For aqueous NBDOC, its concentration variation is mainly affected by hydraulic exchange, adsorption, and desorption processes, and biochemical degradation is generally not considered. The relationship can be expressed as follows:

[0057]

[0058] In the formula, C N,in (t) represents the NBDOC concentration in the influent, mg / L; C N,out (t) represents the NBDOC concentration in the effluent, mg / L; Q represents the influent flow rate, m³ / L. 3 / d; V is the volume of the carbon pool, m 3 ;k a,N λ is the adsorption rate constant of NBDOC, in L / (mg·d); N q is the NBDOC re-release rate coefficient, 1 / d; N (t) represents the amount of NBDOC adsorbed on a unit mass of activated carbon, in mg / g.

[0059] 1.2 Dynamic variation model of organic carbon concentration in the activated carbon adsorption phase:

[0060] For the adsorbed phase BDOC, its mass change consists of three parts: adsorption from the aqueous phase to the adsorbed phase, desorption back to the aqueous phase, and degradation by attached microorganisms. For the adsorbed phase NBDOC, its mass change is mainly determined by adsorption and desorption processes, without considering biochemical degradation. The relationship can be expressed as follows:

[0061]

[0062] In the formula, R(t) is the degradation rate of BDOC by microorganisms, mg / (g·d).

[0063] 1.3 Microbial regeneration and degradation rate model:

[0064] The degradation rate of BDOC adsorbed by activated carbon reflects the utilization of adsorbed BDOC by attached microorganisms, and can be expressed by the Monod kinetic expression, as follows:

[0065]

[0066] In the formula, Y is the biomass yield coefficient, mg biomass / mg BDOC; K sq denoted as Monod half-saturation constant of the adsorbed phase BDOC, in mg / L.

[0067] 1.4 Microbial biomass dynamic change model:

[0068] The change in the biomass of attached microorganisms over time is determined by both growth and death. The organic matter utilized by the growth is mainly adsorbed by activated carbon and dissolved BDOC in water. The relationship between their changes can be expressed by the following formula:

[0069]

[0070] In the formula, η is the dependence coefficient of microorganisms on the adsorbed phase BDOC as substrate (0.7~1); k decay 1 / d is the natural mortality coefficient of microorganisms.

[0071] 1.5 Dynamic variation model of activated carbon adsorption site availability:

[0072] The availability of adsorption sites over time is mainly affected by the loss caused by BDOC and NBDOC occupancy and the regeneration brought about by microbial degradation. The relationship between these factors can be expressed by the following formula:

[0073]

[0074] In the formula, k d,B k is the BDOC adsorption site loss coefficient. d,N α is the loss coefficient of NBDOC adsorption sites; α is the regeneration and activation efficiency of adsorption sites (0-1), dimensionless.

[0075] Step 2: Model optimization;

[0076] During BAC operation, key indicators are continuously monitored on-site, including influent and effluent organic matter concentrations, microbial counts, and adsorption site availability. This monitoring data is input into a pre-established dynamic coupling kinetic model at set time steps. A recursive least squares online optimization algorithm is used to correct core parameters such as adsorption rate constant, re-release rate, maximum specific growth rate of microorganisms, adsorption site loss coefficient, and regeneration efficiency in real time. The deviation between predicted and measured values ​​is calculated to verify and optimize the parameter update effect, ensuring a high degree of consistency between the model calculation results and the on-site operating conditions, thereby guaranteeing the accuracy of adsorption capacity assessment and failure prediction.

[0077] Step 3: Model Application;

[0078] The corrected model is used for real-time analysis and calculation to dynamically assess the changing trend of the adsorption capacity of bio-activated carbon and accurately predict the failure state of activated carbon and the timing of carbon replacement.

[0079] Based on the corrected adsorption-regeneration coupled kinetic model, the instantaneous adsorption flux of bio-activated carbon, the proportion of biodegradable and non-biodegradable organic carbon adsorbed on the target bio-activated carbon per unit mass, and the organic matter removal rate are continuously calculated. The trend of adsorption capacity change of bio-activated carbon is dynamically evaluated based on the continuous calculation results, and the failure state and failure time are determined according to the preset threshold.

[0080] In this embodiment, to facilitate a more intuitive characterization of the adsorption intensity of biological activated carbon, the instantaneous adsorption flux J is defined based on the dynamic model of organic carbon concentration in the influent and effluent and the dynamic change model of organic carbon concentration in the activated carbon adsorption phase. ads (t), the proportion of BDOC and NBDOC adsorbed on unit mass activated carbon (P) N (t) and organic matter removal rate η(t).

[0081] J ads (t) reflects the net adsorption contribution of activated carbon to biodegradable organic carbon (BDOC) and non-biodegradable organic carbon (NBDOC) per unit time, and its expression is:

[0082] J ads (t)=k a,B ·[C B,in (t)-C B,out (t)]·S(t)+k a,N ·[C N,in (t)-C N,out [(t)]·S(t);

[0083] In the formula, k a,B k a,N The adsorption rate constants of BDOC and NBDOC are respectively; C B,in (t), C B,out (t) represents the BDOC concentration in the influent and effluent, respectively, and C. N,in (t), C N,out S(t) represents the NBDOC concentration in the influent and effluent, respectively; S(t) represents the availability of activated carbon adsorption sites, which is dimensionless.

[0084] P N (t) reflects the proportion of NBDOC adsorbed on a unit mass of activated carbon, and its expression is:

[0085]

[0086] In the formula, q N (t), q B (t) represents the amount of NBDOC and BDOC adsorbed on a unit mass of activated carbon, respectively.

[0087] η(t) reflects the organic matter removal rate, and its expression is:

[0088]

[0089] In the formula, C B,in (t), C B,out (t) represents the BDOC concentration in the influent and effluent, respectively, and C. N,in (t), C N,out (t) represents the NBDOC concentration in the influent and effluent, respectively.

[0090] By analyzing J ads The continuous calculation and plotting of (t) curves can reflect the changing trend of adsorption intensity in real time, and can be combined with other output quantities (such as S(t), P) N (t), η(t), etc., provide intuitive basis for dynamic evaluation of activated carbon operating status and failure prediction.

[0091] Based on the above output, the trend of changes in the adsorption capacity of biological activated carbon can be dynamically evaluated, and the failure state can be determined by combining the following criteria:

[0092] (1) Site method: When the availability of adsorption sites S(t) is lower than a set threshold S crit It is determined to be invalid after a certain period of time;

[0093] (2) Performance method: When the removal rate η(t) is lower than the design value or the limit of the effluent index, it is judged as failure;

[0094] (3) Occupation method: When the proportion of non-biodegradable organic carbon occupancy reaches the threshold P crit At that time, it is determined that the activated carbon has entered a failure trend.

[0095] Based on this, the model predicts the operating status of the future window period [t0, t0+H] in a rolling manner, and determines the time point at which the failure criterion is first met as the predicted time to failure (TTF). Here, the window period H represents the time range for forward prediction, which is generally determined based on the typical operating cycle of the carbon pool, the accuracy of the model calculation, and the reliability of the monitoring data. It is usually taken as several months to one year to ensure that the prediction results are both forward-looking and operable.

[0096] To avoid replacing activated carbon only at its failure point, a preset lead time L is introduced. The lead time L reflects the safety margin in operation and management, and its value can be set based on actual water quality safety requirements, economic costs, and historical operating experience: A larger value for L is used when water quality requirements are high to ensure replacement before the activated carbon completely fails; if replacement costs are high, L can be appropriately reduced to extend its service life. Therefore, the recommended carbon replacement time is defined as: t * =TTF-L.

[0097] In practical applications, it is necessary to satisfy L < H to ensure that the lead time is within the prediction window, thus guaranteeing the connection between prediction and actual operation. By reasonably selecting H and L, it is possible to optimize the activated carbon replacement strategy while ensuring the safety of the effluent quality, achieving a balance between operating costs and risk control.

[0098] After the activated carbon is replaced, the above key indicators are re-detected, and continuous monitoring data at the initial stage of the new carbon operation are collected to obtain information such as the initial adsorption capacity, available site rate, and microbial attachment amount, and the initial conditions and parameter empirical values of the model are reset. Subsequently, the parameters are rapidly optimized in the high-frequency monitoring mode, enabling the model to converge to a state that reflects the true operating conditions of the new carbon in the short term. Through this process of parameter reset and rapid calibration after carbon replacement, it can be ensured that the model continues to provide accurate adsorption capacity evaluation and failure prediction results in the new operation cycle.

[0099] The above steps two and three are continuously and cyclically executed throughout the entire operation cycle of the BAC filter to ensure that the model parameters are always consistent with the actual operating state and to provide stable and accurate adsorption capacity evaluation and failure prediction results in each operation cycle. In the specific implementation process, key parameters such as the adsorption rate constant, microbial growth rate, adsorption site loss coefficient, and regeneration efficiency are dynamically adjusted by the actual on-site operation data to ensure that the model has high accuracy and practicality.

[0100] The embodiments described above are only descriptions of the preferred embodiments of the present invention and do not limit the scope of the present invention. Without departing from the design spirit of the present invention, various deformations and improvements made by those of ordinary skill in the art to the technical solutions of the present invention shall fall within the protection scope determined by the claims of the present invention.

Claims

1. A method for in-situ adsorption capacity evaluation and failure prediction of biological activated carbon based on adsorption-regeneration coupled kinetic model, characterized in that, The application relates to a method for monitoring the running state of target biological activated carbon. The method comprises the following steps: collecting monitoring data of the target biological activated carbon in real time; inputting the monitoring data into a pre-constructed adsorption-regeneration coupling kinetics model, calculating the instantaneous adsorption capacity of the target biological activated carbon, obtaining the variation trend of the adsorption site availability and the adsorption capacity variation curve, and calculating the failure critical value, wherein the adsorption-regeneration coupling kinetics model is constructed by coupling the material balance of the water phase-adsorption phase-biological phase, and quantitatively describing the whole process of the mass transfer migration of biodegradable organic carbon and non-biodegradable organic carbon in the biological activated carbon filter, adsorption-desorption, microbial degradation and adsorption site regeneration. The monitoring data comprises the influent and effluent organic carbon concentration, the microbial quantity, the microbial degradation rate, the adsorbed organic carbon concentration in the activated carbon, the adsorption capacity, the adsorption site availability, the adsorption rate constant, the re-release rate, the maximum specific growth rate of the microorganism and the regeneration efficiency.

2. The method for in-situ adsorption capacity evaluation and failure prediction of biological activated carbon based on adsorption-regeneration coupled kinetic model according to claim 1, characterized in that, The adsorption-regeneration coupling kinetics model comprises an influent and effluent organic carbon concentration dynamic model, an activated carbon adsorption phase organic carbon concentration dynamic variation model, a microbial regeneration and degradation rate model, a microbial quantity dynamic variation model and an activated carbon adsorption site availability dynamic variation model.

3. The method for in-situ adsorption capacity evaluation and failure prediction of biological activated carbon based on adsorption-regeneration coupled kinetic model according to claim 1, characterized in that, The influent and effluent organic carbon concentration dynamic model comprises the following relationships:

4. The method for in-situ adsorption capacity evaluation and failure prediction of biological activated carbon based on adsorption-regeneration coupled kinetic model according to claim 3, characterized in that, The influent and effluent concentration variation relationship of the water phase biodegradable organic carbon is: The influent and effluent concentration variation relationship of the water phase non-biodegradable organic carbon is: The activated carbon adsorption phase organic carbon concentration dynamic variation model comprises the following relationships: where C B,out (t) is the concentration of biodegradable organic carbon in the effluent, t is time, Q is the influent flow rate, V is the volume of the carbon tank, C B,in (t) is the concentration of biodegradable organic carbon in the influent, k a,B is the adsorption rate constant of biodegradable organic carbon, S(t) is the availability of adsorption sites of activated carbon, θ is the contribution coefficient of microorganisms to the degradation of water-phase substrate, μ max is the maximum specific growth rate of microorganisms, K sc is the Monod half-saturation constant of water-phase biodegradable organic carbon, X(t) is the amount of microorganisms attached per unit mass of activated carbon, λ B is the re-release rate coefficient of biodegradable organic carbon, q B (t) is the biodegradable organic carbon adsorbed per unit mass of activated carbon, C N,out (t) is the concentration of non-biodegradable organic carbon in the effluent, C N,in (t) is the concentration of non-biodegradable organic carbon in the influent, k a,N is the adsorption rate constant of non-biodegradable organic carbon, λ N is the re-release rate coefficient of non-biodegradable organic carbon, q N (t) is the non-biodegradable organic carbon adsorbed per unit mass of activated carbon.

5. The method for in-situ adsorption capacity evaluation and failure prediction of biological activated carbon based on adsorption-regeneration coupled kinetic model according to claim 3, characterized in that, The mass variation relationship of the adsorption phase biodegradable organic carbon is: The mass variation relationship of the adsorption phase non-biodegradable organic carbon is: The microbial regeneration and degradation rate model is: where q B (t) is the adsorbed biodegradable organic carbon per unit mass of activated carbon, t is time, k a,B is the biodegradable organic carbon adsorption rate constant, C B,in (t) is the influent biodegradable organic carbon concentration, C B,out (t) is the effluent biodegradable organic carbon concentration, S(t) is the availability of activated carbon adsorption sites, R(t) is the biodegradable organic carbon degradation rate by microorganisms in the adsorption phase, λ B is the biodegradable organic carbon re-release rate coefficient, q N (t) is the adsorbed non-biodegradable organic carbon per unit mass of activated carbon, k a,N is the non-biodegradable organic carbon adsorption rate constant, C N,in (t) is the influent non-biodegradable organic carbon concentration, C N,out (t) is the effluent non-biodegradable organic carbon concentration, λ N is the non-biodegradable organic carbon re-release rate coefficient.

6. The method of in-situ adsorption capacity evaluation and failure prediction of biological activated carbon based on adsorption-regeneration coupled kinetic model according to claim 3, characterized in that, The microbial quantity dynamic variation model is: where R(t) is the biodegradation rate of the adsorbed phase biodegradable organic carbon by the microorganisms, Y is the bio-yield coefficient, μ max is the maximum specific growth rate of the microorganisms, q B (t) is the amount of adsorbed biodegradable organic carbon per mass of activated carbon, K sq is the Monod half-saturation constant for the adsorbed phase biodegradable organic carbon, and X(t) is the amount of microorganisms attached per mass of activated carbon.

7. The method of in-situ adsorption capacity evaluation and failure prediction of biological activated carbon based on adsorption-regeneration coupled kinetic model according to claim 3, characterized in that, The activated carbon adsorption site availability dynamic variation model is: where X(t) is the amount of microorganism attached on unit mass of activated carbon, t is time, Y is the biological yield coefficient, μ max is the maximum specific growth rate of microorganism, η is the dependency coefficient of microorganism on adsorbed-phase biodegradable organic carbon as substrate, q B (t) is the adsorbed biodegradable organic carbon on unit mass of activated carbon, K sq is the Monod half-saturation constant of adsorbed-phase biodegradable organic carbon, C B,out (t) is the biodegradable organic carbon concentration in effluent, K sc is the Monod half-saturation constant of water-phase biodegradable organic carbon, k decay is the natural decay coefficient of microorganism.

8. The method for in-situ adsorption capacity evaluation and failure prediction of biological activated carbon based on adsorption-regeneration coupled kinetic model according to claim 3, characterized in that, The method comprises the following steps: where S(t) is the availability of activated carbon adsorption sites, t is time, k d,B is the biodegradable organic carbon adsorption site loss coefficient, C B,in (t) is the biodegradable organic carbon concentration in the influent, C B,out (t) is the biodegradable organic carbon concentration in the effluent, S(t) is the availability of activated carbon adsorption sites, k d,N is the non-biodegradable organic carbon adsorption site loss coefficient, C N,in (t) is the non-biodegradable organic carbon concentration in the influent, C N,out (t) is the non-biodegradable organic carbon concentration in the effluent, a is the reactivation efficiency of adsorption sites, and R(t) is the microbial degradation rate of adsorbed biodegradable organic carbon.

9. The method for in-situ adsorption capacity evaluation and failure prediction of biological activated carbon based on adsorption-regeneration coupled kinetic model according to claim 1, characterized in that, Based on the adsorption-regeneration coupling kinetics model, the instantaneous adsorption flux of the target biological activated carbon, the adsorbed biodegradable organic carbon and non-biodegradable organic carbon on the unit mass target biological activated carbon and the organic matter removal rate are continuously calculated; According to the continuous calculation results, the adsorption capacity variation trend of the target biological activated carbon is dynamically evaluated, and the failure state and failure time are judged according to the preset threshold. ​

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