Determining values for reaction parameters of reaction model for pyrolysis process

Abstract

The invention relates to a computer-implemented method for determining values of reaction parameters of a reaction model for pyrolyzing a plastic starting material into a plastic product, comprising the following steps:-providing experimental data comprising a plurality of boiling point distributions of the plastic product, each boiling point distribution being paired with a pyrolysis temperature and a pyrolysis duration, wherein each boiling point distribution is incorporated into N lumped units L1 to LN, where each lumped unit is paired with a boiling point temperature range; -determining corresponding values of the reaction parameters by fitting the reaction parameters of the reaction model to the experimental data. For each lumped unit Li from L1 to LN-1, the reaction model has a partial reaction determined by at least one reaction parameter to describe the conversion of the plastic product of the lumped unit into a plastic product of an adjacent lumped unit Li + 1 located below with respect to the boiling temperature range, where the reaction model has less than N * (N-1) / 2 partial reactions.

Description

Technical Field

[0001] The present invention relates to a computer-implemented method for determining the values ​​of reaction parameters for a reaction model used to pyrolyze a plastic starting material into a plastic product, a method for pyrolyzing a plastic starting material into a plastic product, a data processing system for performing the computer-implemented method, and a corresponding computer program product. Background Technology

[0002] Millions of tons of plastic waste are generated annually in Europe alone, with only a relatively small fraction being recycled. Consequently, large quantities of plastic waste are incinerated, landfilled, or transported out of the country. To improve recycling rates, deposit systems can be introduced, allowing plastic waste to be mechanically recycled or chemically reprocessed, for example, through depolymerization and repolymerization. A major challenge associated with plastic waste is the classification of different types of plastics and the contamination of the waste. Pyrolysis offers a relatively simple method for processing mixed plastic waste, even waste contaminated with other wastes. During pyrolysis, organic matter is converted into valuable resources under high temperature and anaerobic conditions, which can be used as starting materials for the reuse of plastic waste. During pyrolysis, long-chain hydrocarbons in plastic waste are broken down into lower molecular weight molecules through thermal energy. The pyrolysis products are liquids or gases and can be further processed in existing infrastructure, such as traditional oil refineries.

[0003] The chemical processes occurring during pyrolysis are highly complex and difficult to describe in detail theoretically. To find suitable parameters for a planned pyrolysis, such as the duration and temperature, pyrolysis can be modeled in a simplified form using a so-called lumped model. Pyrolysis products are typically grouped into so-called lumped units based on their boiling points. A lumped unit comprises pyrolysis products within a specific boiling point temperature range. Within the framework of existing lumped models, individual lumped units are typically interconnected through first-order unimolecular, irreversible reactions. As part of the lumped model, the pyrolysis products of a lumped unit with a high boiling point temperature range can decompose into pyrolysis products of any lumped unit with a lower boiling point temperature range. The reverse process, polymerization, is negligible in the pyrolysis environment and is generally not modeled in the context of a lumped model. Modeling each reaction allows us to indicate the rate or velocity of the corresponding reaction from one lumped unit to another. Experimental data from experimental reactors are typically used to determine the parameters of individual reactions.

[0004] For example, Lechleitner, AE; Schubert, T; Hofer, W.; Lehner, M. et al., "Lumped Kinetic Modeling of Polypropylene and Polyethylene Co-Pyrolysis in Tubular Reactors" Processes 2021, 9 , 34, https: / / doi.org / 10.3390 / pr9010034), shows a lumped model for the pyrolysis of polypropylene and polyethylene in a tubular reactor. To describe the pyrolysis process, a model with four lumped units is used to classify the products of plastic pyrolysis. All lumped units are interconnected via unimolecular, irreversible first-order reactions. Furthermore, an initial process step is provided, in which the starting material (“plastic”) independent of the boiling point temperature range is converted into the products of the lumped unit with the highest boiling point temperature range (“wax 420°C+”). According to this publication, this initial process step cannot be evaluated (see the last paragraph of Chapter 2.2.1). The total of six reactions k are evaluated using the Arrhenius equation. i Modeling is performed to detect the temperature dependence of the reaction. For each reaction k i The Arrhenius constant A was determined through experimental data. i and activation energy E A,i That is, there are a total of twelve parameters.

[0005] Schubert, Teresa et al. in "4-Lump kinetic model of the co-pyrolysis ofLDPE and a heavy petroleum fraction" ( Fuel An alternative model for the pyrolysis of LDPE (“low-density polyethylene”) was proposed in 262 (2020): 116597. This model has four lumped units, each of which is interconnected by a first-order unimolecular, irreversible reaction.

[0006] According to Naik, Desavath V. et al., "Kinetic modeling for catalytic cracking of pyrolysis oils with VGO in a FCC unit." Chemical Engineering Science(170(2017): 790-798) Two problems typically arise when calculating kinetic parameters. On the one hand, convergence problems occur when there are too many parameters. On the other hand, initializing parameters can lead to local minima in the optimization (which results in incorrect parameter calculations). This publication presents a model with five lumped units for catalytic cracking of pyrolysis oil. The parameters of the five-lumped model are determined sequentially using 3-lumped and 4-lumped models to keep the number of parameters to be determined simultaneously small. Summary of the Invention

[0007] The purpose of this invention is to mitigate or eliminate the disadvantages of the prior art. In particular, the objective of this invention is to provide a computer-implemented method, a system for data processing, and a computer program product for determining reaction parameter values ​​for a reaction model of the pyrolysis of plastic starting materials into plastic products. This allows for simple, robust, and efficient modeling of pyrolysis without significantly compromising the accuracy of the modeling.

[0008] This objective is achieved by a computer-implemented method for determining the values ​​of reaction parameters for a reaction model used to pyrolyze plastic starting materials into plastic products. The method includes the following steps: - Provides experimental data on multiple boiling point distributions for plastic products, where each boiling point distribution is associated with pyrolysis temperature and pyrolysis duration, and the boiling point distributions are all categorized into N lumped units L1 to L2. N In this context, each lumped cell is associated with a range of boiling point temperatures; - Determine the corresponding values ​​of the reaction parameters by fitting the reaction parameters of the reaction model to experimental data; Among them, it is used for L1 to L N-1 Each ensemble model L i The reaction model has a partial reaction determined by at least one reaction parameter, used to describe the transformation of the plastic product of the lumped unit into the adjacent lumped unit L, which is located below the boiling point temperature range. i+1 The plastic product, wherein the reaction model has less than N*(N-1) / 2 partial reactions.

[0009] Reaction models known to date from the prior art, such as those described in the aforementioned publication by Lechleitner et al. (Process 2021, 9, 34), include partial reactions of each individual lumped unit down to all lumped units located below the boiling point temperature range. Therefore, the complexity of the model increases rapidly with the number of lumped units, as N*(N-1) / 2 partial reactions must be considered. Consequently, the prior art also strives to minimize the number of lumped units. Lechleitner et al. initially based their model on a 6-lumped model, which was subsequently simplified to a 4-lumped model (see Lechleitner et al., Chapter 2.2.1).

[0010] In the course of this invention, it has now been surprisingly discovered that some partial reactions can be ignored without significantly impairing the accuracy of the reaction model. Therefore, the number of partial reactions is reduced to less than N*(N-1) / 2 compared to existing techniques. By reducing partial reactions, the convergence of the fit can be improved, and generally, for the same number of lumped units, the complexity of the model can be reduced, or for the same model complexity, the number of lumped units considered can be increased. The decisive factor here is recognizing which partial reactions can be ignored without significantly reducing the accuracy of the reaction model, and which partial reactions absolutely cannot be ignored. The most critical partial reactions to accurately describe pyrolysis are those between lumped units adjacent to each other relative to the boiling point temperature range. It has been found that partial reactions between lumped units spaced apart relative to the boiling point temperature range occur less frequently in pyrolysis and are less critical to the accuracy of the reaction model. Conversely, the reaction parameters of these less critical partial reactions are more difficult to determine because experimental data are only subordinate to these partial reactions, and therefore the determination of the values ​​of the reaction parameters under discussion is affected by greater experimental and statistical uncertainty. Modeling such infrequent partial reactions negatively impacts the overall convergence of the fit. Therefore, it turns out that the overall decisive factor is the method used for transitioning from L1 to L. N-1 Each lumped unit L i The reaction model has a partial reaction, used to describe the transformation of the plastic product of the lumped unit into the adjacent lumped unit L, which is located below the boiling point temperature range. i+1 The plastic products, because these reactions are the most critical for describing pyrolysis.

[0011] As part of the pyrolysis of plastic starting materials into plastic products, thermal energy is supplied to the plastic starting materials, thereby breaking down the long-chain molecules of the starting materials to form plastic products. For example, any type of plastic waste can be used as a plastic starting material. For example, plastic starting materials can include polypropylene or polyethylene. Plastic products can include, for example, (relatively short-chain and / or lighter) hydrocarbons, such as heavy oil, spindle oil, gas oil, kerosene, naphtha, liquefied petroleum gas (LPG), or hydrocarbons that are gaseous under normal conditions.

[0012] Pyrolysis can be carried out in a pyrolysis reactor. For example, Lechleitner, AE; Schubert, T.; Hofer, W.; Lehner, M., "Lumped Kinetic Modeling of Polypropylene and Polyethylene Co-Pyrolysis in Tubular Reactors" Processes A pyrolysis reactor designed as a tubular reactor is shown in Figure 34, 2021 (https: / / doi.org / 10.3390 / pr9010034). The decisive parameters for pyrolysis are the pyrolysis temperature, i.e., the temperature to which the plastic starting material is heated, and the pyrolysis duration, indicating how long the pyrolysis temperature is maintained. Generally, higher pyrolysis temperatures and longer pyrolysis durations result in more conversion into shorter-chain plastic products.

[0013] One step of this method involves providing experimental data including multiple boiling point distributions of the plastic products. For example, experimental data can be obtained through multiple pyrolysis runs, in which the same plastic starting material is pyrolyzed in the same pyrolysis reactor at a given pyrolysis temperature and duration. Each pyrolysis run produces plastic products that can be classified according to boiling point. The boiling point distribution determined in each experiment is related to a pyrolysis temperature and a pyrolysis duration. The experimental data preferably include boiling point distributions with multiple different pyrolysis temperatures and / or multiple different pyrolysis durations. The boiling point distributions are respectively assigned to (bins) N lumped units L1 to L... NIn this model, each lumped unit is associated with a boiling point temperature range. For example, the measured boiling point distribution can initially exist continuously as a function of boiling point temperature, and lumped units are binned into them, thus ultimately existing in the form of a histogram. For example, nine lumped units L1 to L9 can be provided, with each boiling point distribution grouped into said nine lumped units. For example, the first lumped unit L1 can have a plastic starting material and a boiling point temperature range above 600°C. For example, the second lumped unit L2 has a boiling point temperature range between 450°C and 600°C and can be referred to as a bottom product or heavy product. The third lumped unit L3 can contain heavy oil with a boiling point temperature range between 400°C and below 450°C. The fourth lumped unit L4 can contain spindle oil with a boiling point temperature range between 350°C and below 400°C. The fifth lumped unit L5 can contain gas oil with a boiling point temperature range between 225°C and below 350°C. For example, the sixth lumped unit L6 may contain kerosene with a boiling point temperature range between 165°C and below 225°C. For example, the seventh lumped unit L7 may contain naphtha with a boiling point temperature range between 20°C and below 165°C. For example, the eighth lumped unit L8 may contain liquefied petroleum gas (LPG) with a boiling point temperature range between -120°C and below 20°C. In this example, the eighth lumped unit L8 may primarily comprise hydrocarbons having 2 to 4 hydrocarbon atoms (e.g., ethylene, ethane, propane, propylene, butane, and / or butene). For example, the ninth lumped unit L9 may contain gaseous hydrocarbons with a boiling point below -120°C under normal conditions. In this case, the ninth lumped unit L9 may primarily comprise methane. Alternatively, more or fewer lumped units may be provided. For example, two or more lumped units from the above examples may be combined. For example, other lumped units with different boiling point temperature ranges may be provided.

[0014] In the next step, the values ​​of the reaction parameters are determined by fitting the reaction parameters of the reaction model to experimental data. The reaction model describes the transformation of the plastic products and plastic starting materials of each lumped unit into the plastic products of other lumped units. According to the model, lumped units are preferably associated with first-order unimolecular, irreversible partial reactions. For example, lumped unit L1 undergoes a partial reaction r 12 Connect to lumped unit L2, where the following relation applies: r 12 =k 12 *X Lump1 k 12 X is the reaction rate between lumped unit L1 and lumped unit L2. Lump1 This represents the mass fraction of the plastic product in lumped cell L1 (relative to the total mass of all lumped cells). To account for the dependence on the pyrolysis temperature T, the reactions in each part can be described by the Arrhenius equation:

[0015] It is the Arrhenius constant (also known as the exponential pre-factor or frequency factor). E A12 The activation energies for the corresponding transformations are described; in this case, they are the activation energies for the transformation of the plastic product from lumped unit L1 to lumped unit L2. R is the universal gas constant, and T is the (absolute) pyrolysis temperature. If each partial reaction is modeled using the Arrhenius equation, each partial reaction is ultimately described by two reaction parameters. In this case, from lumped unit L... i To lumped unit L j The reaction parameters for each part of the reaction are and .

[0016] For L1 to L N-1 Each lumped unit L i The reaction model has a partial reaction determined by at least one reaction parameter, used to describe the transformation of the plastic product of the lumped unit into the lumped unit L located below and adjacent to the boiling point temperature range. i+1 The plastic product. i is an exponent that can take positive integer values ​​between 1 and the number of lumped units N. The reaction model refers to pyrolysis in a pyrolysis reactor. Experimental data are obtained through the pyrolysis reactor. The reaction model is a function of pyrolysis temperature and pyrolysis duration.

[0017] For example, a pyrolysis model with three lumped units L1, L2 and L3 can have the following form, which takes into account partial reactions from lumped unit L1 to lumped unit L2 and partial reactions from lumped unit L2 to lumped unit L3.

[0018]

[0019]

[0020]

[0021]

[0022]

[0023] X1, X2, and X3 represent the corresponding mass fractions in lumped units L1, L2, and L3, respectively. t represents the pyrolysis duration. The reaction rate k... 12 and k 23This can be described by the Arrhenius equation, which also includes the pyrolysis temperature T. In this case, X1, X2, and X3 are functions of the pyrolysis duration t and the pyrolysis temperature T, therefore, for example, X1 = X1(t, T). In this simplified case, the pyrolysis model has a total of four reaction parameters: and ,as well as and Its value can be determined by the method of the present invention.

[0024] Experimental data represent experimental data from pyrolysis runs using single-value pairs of pyrolysis temperature and pyrolysis duration. Reaction models allow for interpolation between or extrapolation of these experimental data pairs. The boiling point distribution of pyrolyzed plastic products with any pyrolysis temperature and duration can be estimated using reaction models. Typically, pyrolysis temperatures range from 300°C to 650°C. Pyrolysis durations typically range from minutes to hours. For example, pyrolysis durations can range from 3 minutes to 100 minutes.

[0025] The values ​​of the reaction parameters are determined by fitting the reaction parameters of a reaction model to experimental data. In this case, fitting means selecting the values ​​of the reaction parameters in a way that allows the reaction model to reproduce the experimental data as accurately as possible. For example, the least squares sum of the reaction model and the experimental data can be minimized (also known as the least squares method). For example, fitting may include minimizing the distance from the experimental data to the reaction model. For example, the distance can be calculated using an objective function. For example, as part of the fitting, the reaction parameters may be varied to find the minimum distance between the experimental data and the reaction model. The values ​​of the reaction parameters determined in this way result in the minimum distance between the reaction model and the experimental data.

[0026] In existing techniques, reaction models with N*(N-1) / 2 partial reactions are known, meaning partial reactions across all lumped units are considered. Compared to existing techniques, the number of partial reactions is reduced to less than N*(N-1) / 2. By reducing the number of partial reactions, the convergence of the fit can be improved, and the complexity of the model can generally be reduced. The decisive factor here is which partial reactions can be ignored without significantly reducing the accuracy of the reaction model, and which cannot be ignored under any circumstances. As described in more detail above, the overall decisive factor is, for L1 to L... N-1 Each lumped unit L i The reaction models all involve partial reactions, used to describe the transformation of the plastic product of the lumped unit into an adjacent lumped unit L located below the boiling point temperature range. i+1 The plastic products, because these reactions are the most critical for describing pyrolysis.

[0027] For example, for the first lumped unit L1 and the last lumped unit L N The reaction model may not represent part of the reaction r. 1N This part of the reaction has the greatest distance between the boiling point temperatures of the two lumped units involved, and is therefore particularly irrelevant to the description of pyrolysis. Instead, in particular, this part of the reaction r 1N The response parameters are not easy to initialize in the context of fitting, and can also negatively affect the convergence of the fit.

[0028] Generally, a reaction model can have N lumped units and less than N*(N-1) / M partial reactions, where M is a natural number greater than 2 and less than the number of lumped units N (i.e., N>M). For example, a reaction model can have at least 4 lumped units N and less than N*(N-1) / 3 partial reactions.

[0029] The number of lumped units N is preferably at least three, more preferably at least four, even more preferably at least five, more preferably at least six, more preferably at least seven, more preferably at least eight, most preferably at least nine, more preferably at least ten, more preferably at least eleven, and even more preferably at least twelve. For example, the number of lumped units N can be at least seven. For example, the number of lumped units can be at least twenty. Because the ratio of some reactions or reaction parameters in the reaction model to the number of lumped units is small compared to the prior art, a relatively large number of lumped units can be used without compromising fitting convergence. This allows for increased prediction granularity without significantly reducing prediction quality.

[0030] For example, a reaction model may have exactly (N-1) partial reactions. In this case, the reaction model only considers the partial reactions between adjacent lumped units relative to the boiling point temperature range. In this case, the reaction model can be called a sequential reaction model, and only the sequential partial reactions are considered. In this case, the reaction model maps from the first lumped unit L1 to the last lumped unit L... NThe reaction model represents a single reaction path. For example, the transition from the first lumped unit L1 to the third lumped unit L3 can only be achieved by converting lumped unit L1 to the second lumped unit L2 and further converting lumped unit L2 to lumped unit L3, where lumped unit L2 lies between lumped units L1 and L3 with respect to the boiling point temperature range and is adjacent to both lumped units L1 and L3. No alternative path is provided in the context of the sequential reaction model, such as a direct transition from lumped unit L1 to lumped unit L3 (which is discontinuous with respect to the boiling point temperature range), and therefore is not possible in the context of the reaction model. For an accurate description of pyrolysis, the sequential partial reactions are the most decisive partial reactions between lumped units. By restricting the reaction model to (N-1) sequential partial reactions, convergence problems can be avoided as much as possible; furthermore, the fitting, and therefore the values ​​of the reaction parameters, do not depend on the initial values ​​of the reaction parameters used for fitting. Although simplified compared to existing, more complex reaction models, the reaction model still accurately maps pyrolysis. Furthermore, restricting the reaction model to (N-1) sequential partial reactions allows for the consideration of a significantly larger number of lumped units without increasing the overall model complexity.

[0031] The present invention also relates to a method for determining reaction parameter values ​​for a reaction model used to pyrolyze a plastic starting material into a plastic product. This method employs a computer-implemented method according to the present invention to determine reaction parameter values ​​for a reaction model used to pyrolyze a plastic starting material into a plastic product, wherein providing experimental data includes the following steps: - Perform multiple pyrolysis runs in the pyrolysis reactor at different pyrolysis temperatures and / or pyrolysis durations; - Measure the boiling point distribution of the plastic products in each pyrolysis run, where each boiling point distribution is correlated with the pyrolysis temperature and pyrolysis duration; -Assign each boiling point distribution to N lumped units L1 to L2 N In this study, the boiling point temperature range is associated with each lumped cell to obtain experimental data.

[0032] The experimental data were obtained through multiple pyrolysis runs, in which the same plastic starting material was pyrolyzed in the same pyrolysis reactor at a single pyrolysis temperature and duration under each condition. Each pyrolysis run produced plastic products that could be classified according to their boiling points.

[0033] For each pyrolysis run, the boiling point distribution of the plastic products was measured, thereby classifying the plastic products according to their boiling points. Lechleitner, AE; Schubert, T; Hofer, W.; Lehner, M. et al., "Lumped Kinetic Modeling of Polypropylene and Polyethylene Co-Pyrolysis in Tubular Reactors" (… Processes 2021, 9 34. (https: / / doi.org / 10.3390 / pr9010034) shows, for example, an experimental reactor (“experimental apparatus”) with a flash vessel (also called an evaporator) downstream of a pyrolysis reactor. With the aid of the flash vessel, plastic products existing in gaseous form can be separated. For this purpose, the temperature and pressure within the flash vessel can be set to influence the separation (so-called separation cut). Under the appropriate conditions (i.e., pressure and temperature) within the flash vessel, the gaseous plastic products can exit the evaporator and can be directed to one or more cold traps. The plastic products removed in this way can be weighed, cooled, and mixed, for example, with the product at the bottom of the flash vessel, to form a liquid final product that can then be analyzed. For example, gaseous plastic products below 0°C can be collected using balloons for further analysis.

[0034] For example, gaseous plastic products can be analyzed by gas chromatography according to DIN 51666:2007-01. The results, for example, can determine the calorific value, specific gravity, and / or detailed molecular composition of the plastic product. For example, according to ASTM D7169-20e1, the boiling point distribution of collected liquid plastic products and any carrier medium can be analyzed by simulated distillation. The boiling point distribution is mass-weighted.

[0035] The boiling point distribution determined in each experiment is related to the pyrolysis temperature and pyrolysis duration of their respective pyrolysis operations.

[0036] The boiling point distribution is divided into N lumped units L1 to L2. N In this process, each lumped cell is associated with a boiling point temperature range to obtain experimental data. Binning refers to dividing the boiling point distribution into different categories; in this case, these categories are the lumped cells.

[0037] This invention also relates to a method for pyrolyzing plastic starting materials into plastic products, comprising the following steps: - The reaction parameter values ​​of the pyrolysis reaction model are determined by a computer-implemented method according to the present invention; -Specify the intended boiling point distribution; - The pyrolysis temperature and duration are determined by minimizing the distance between the calculated boiling point distribution, obtained using a reaction model and previously determined reaction parameter values, and the expected boiling point distribution; and - Pyrolysis is carried out at a predetermined pyrolysis temperature and for a predetermined pyrolysis duration.

[0038] The pyrolysis model is a function of the pyrolysis duration and the pyrolysis temperature. Using a pyrolysis model with pre-determined reaction parameters for a portion of the reaction, the (theoretical) boiling point distribution of the plastic product can be calculated for each numerical pair based on the pyrolysis duration and temperature. The calculated boiling point distribution has the same lumped cells as the pyrolysis model.

[0039] In subsequent steps, the desired boiling point distribution is specified. The predetermined boiling point distribution can be continuous or in the form of a histogram. For example, the predetermined boiling point distribution can have the same lumped cells as the reaction model. The specified boiling point distribution indicates the ideal boiling point distribution of the plastic products after pyrolysis of the plastic starting material. The desired boiling point distribution can indicate which lumped cells the plastic products preferably transform into through pyrolysis.

[0040] In the next step, the pyrolysis temperature and pyrolysis duration are determined by minimizing the distance between the boiling point distribution calculated using the reaction model and previously determined reaction parameter values ​​and the expected boiling point distribution. For example, the predetermined boiling point distribution and the calculated boiling point distribution can each be represented as histograms with the same lumped cells. In this example, the distance can be the sum of the differences between the predetermined cumulative values ​​of the lumped cells of the predetermined boiling point distribution and the corresponding calculated cumulative values ​​of the lumped cells of the calculated boiling point distribution in each case. The distances can be weighted; for example, one lumped cell can have a stronger weight than others, so that the model can describe the lumped cells with larger weights particularly accurately. The pyrolysis temperature and pyrolysis duration are variables in the reaction model (and in the pyrolysis). Predefined pyrolysis temperatures and predefined pyrolysis durations are the values ​​of these variables that result in a minimum distance between the specified boiling point distribution and the calculated boiling point distribution.

[0041] In the final step, pyrolysis is carried out at a predetermined pyrolysis temperature and for a predetermined pyrolysis duration. For this purpose, the pyrolysis reactor is operated in a manner that reaches and maintains the predetermined pyrolysis temperature and duration. For example, the same plastic starting material used in the previous pyrolysis run to determine the reaction parameters of a portion of the reaction can be used. For example, the same pyrolysis reactor used in the previous pyrolysis run to determine the reaction parameters can be used for pyrolysis.

[0042] Another method for pyrolyzing plastic starting materials into plastic products includes the following steps: - The reaction parameter values ​​of the pyrolysis reaction model are determined by a computer-implemented method according to the present invention; - Calculate multiple boiling point distributions using the reaction model and previously determined reaction parameter values, with each calculated boiling point distribution associated with the pyrolysis temperature and pyrolysis duration; - Select one of the calculated boiling point distributions to determine the pyrolysis temperature and pyrolysis duration; and - Pyrolysis is carried out at a predetermined pyrolysis temperature and for a predetermined pyrolysis duration.

[0043] For example, the calculated boiling point distribution can be selected based on predefined criteria. For instance, the boiling point distribution with the maximum value in a predetermined lumped cell can be selected. Pyrolysis at a predetermined pyrolysis temperature and a predetermined pyrolysis duration can result in a boiling point distribution of the plastic product that substantially corresponds to the selected boiling point distribution.

[0044] The present invention also relates to a system for data processing, comprising means for performing steps of a computer-implemented method according to the present invention. For example, the data processing system may be a computer, such as a laptop computer. For example, the data processing system may include a processor and a hard disk.

[0045] The data processing system apparatus can also be configured to perform the following steps: - The pyrolysis temperature and pyrolysis duration are calculated using a reaction model and previously determined reaction parameter values, where the pyrolysis temperature and pyrolysis duration are defined as minimizing the distance between the boiling point distribution calculated by the reaction model and the expected boiling point distribution.

[0046] The present invention also relates to a computer program product comprising instructions that, when executed by a computer, cause the computer to perform the steps of a computer-implemented method according to the present invention. Attached Figure Description

[0047] The invention will be explained in more detail with reference to the exemplary embodiments shown in the accompanying drawings; however, the invention is not limited thereto.

[0048] Figure 1 The structure of the pyrolysis reactor is shown schematically.

[0049] Figure 2 The diagram schematically illustrates the reaction scheme between two lumped units in the context of kinetic reaction modeling of lumped units.

[0050] Figure 3 A schematic diagram of a reaction model for pyrolysis with nine lumped units is shown.

[0051] Figure 4 The comparison of the kinetic decay rates of different plastic starting materials is shown.

[0052] Figure 5A-5I The deviation of a single lumped cell in the reaction model as a function of the average pyrolysis temperature is shown.

[0053] Figure 6 The measured boiling point distribution (dashed line) is shown compared to the boiling point distribution calculated using the reaction model (solid line).

[0054] Figure 7A-7I The study shows the parameters of various pyrolysis temperatures and mass flow rates in the pyrolysis reactor. Detailed Implementation

[0055] Example 1 Example 1 relates to a sequential reaction model with nine lumped units for the co-pyrolysis of a plastic mixture with heavy oil fractions, and determines the reaction parameters of the sequential reaction model. In this case, the plastic starting material is a plastic mixture with heavy oil fractions.

[0056] In this example, a nine-lump kinetic reaction model was used. This model only includes the sequential partial reactions and does not include alternative reaction pathways. This simplifies the implementation of the reaction model. The model is based on experimental data collected in a laboratory-scale pyrolysis reactor—a tubular reactor with a maximum throughput of 2500 g / h.

[0057] To determine the reaction model, three different types of plastics were mixed with heavy oil fractions of varying compositions as plastic starting materials for the pyrolysis reactor. The plastics were untreated polypropylene (PP), low-density polyethylene (LDPE), and high-density polyethylene (HDPE) in powder form (see Table 1). Due to the physical dimensions of the reactor, particularly the narrow inner diameter of the tubes, the maximum particle size of the plastics had to be less than 500 µm. Therefore, the plastics were ground at low temperatures before being used in the experiments. The maximum plastic-to-carrier medium ratio achievable through this system design is 30 wt%. Higher proportions of plastic would lead to clogging of the reactor's feed system.

[0058] The organic carrier medium used is a readily available byproduct of petroleum refining. It is a predominantly aliphatic medium with an aromatic content of approximately 25%, a density of 880 kg / m³, and a calorific value of 45 MJ / kg. Since the carrier medium also undergoes prevailing decomposition in the reactor, only the (kinetic) reaction parameters for the carrier medium were determined in the initial experiments.

[0059] Table 1. Types and specifications of plastics used in pyrolysis experiments (i.e., starting products of plastics)

[0060] Experimental setup and procedures The experiment was conducted in pyrolysis reactor 1 (also known as the laboratory reactor), which was specifically built for this process, such as... Figure 1 Schematic illustration. Pyrolysis reactor 1 basically corresponds to the “…” of Schubert T, Lehner M, Hofer W (2018). Experimental and modeling approach of LDPE thermal cracking for feedstock recycling ( 14th MINISYMPOSIUM CHEMICAL & PROCESS ENGINEERING and 5th PARTICLE FORUM Book of Abstracts The reactor described in the paper was used, and some adjustments were made to the experimental procedure.

[0061] Prior to the experimental run, the liquid carrier medium and plastic powder were manually mixed at a predetermined mass ratio of 0 to 30 wt% plastic. The mixture (i.e., the plastic starting material) was then loaded into storage container 2 and continuously stirred there. The plastic starting material was pumped from storage container 2 via pump 3 (in this case, an eccentric screw pump). Two reactors 4 and 5 were arranged downstream of pump 3. Reactors 4 and 5 were coils 6 heated in a sand bath 7 to the desired temperature range of 400°C to 550°C. The length of each reactor coil 6 could vary between 8 m and 24 m to further adjust the residence time (i.e., the pyrolysis duration) without altering the flow pattern. Actual pyrolysis occurred in reactors 4 and 5. After passing through reactors 4 and 5, the medium (i.e., the pyrolyzed plastic product) was cooled to approximately 90°C by air cooler 8 and oil cooler 9. The pressure in the system could be regulated using valve 10 (manual or automatic diaphragm valve) to slowly reduce the product to atmospheric pressure. For all experiments, the pressure in the system was regulated to 15 bar. Following the oil cooler 9 and valve 10 is the flash vessel 11. Under the conditions in the flash vessel 11, the gaseous plastic product exits through the head and is fed into the first cold trap 12 and the second cold trap 13. The temperature of the first cold trap 12 is set to 15°C, while the temperature of the second cold trap 13 is set to 0°C. The plastic product present at the bottom of the flash vessel 11 is called the bottom product and exits the flash vessel through the bottom line 14. The plastic product collected through the first cold trap 12 is called the top product and exits the first cold trap 12 through the top line 15. The plastic product collected through the second cold trap 13 is called the light product and exits the second cold trap 13 through the light product line 16. After the second cold trap 13, the gaseous pyrolysis product (i.e., the plastic product) below 0°C is sampled using a balloon (not shown). After the product is removed, all liquid is weighed, cooled in a freezer, and mixed into the final liquid product to be analyzed.

[0062] The experimental conditions, namely the pyrolysis temperature and pyrolysis duration, are mainly affected by the temperature of sand bath 6, the lengths of reactors 4 and 5, and the output of pump 3. The pump output regulates the mass flow rate in reactors 4 and 5, with a minimum flow rate of 300 g / h and a maximum flow rate of 2500 g / h. This results in a residence time (i.e., pyrolysis duration) ranging from 3 minutes to 60 minutes, depending on the operating conditions.

[0063]

[0064] For each reactor volume element, the residence time can be calculated and summed differently.

[0065] The primary influence on residence time (corresponding to the duration of pyrolysis) is the reactor temperature, as the vapor content of the medium and therefore its average density largely depend on it. In terms of chemical reactions, residence time and temperature are independent parameters for the reaction rate. However, physical phenomena can also occur in the flow tube, which can cause a correlation between the two parameters. For example, due to increased temperature, the boiling point may partially exceed the limit, which is why vapor forms. Furthermore, reactions with lighter products (or low-boiling-point lumped units) may occur, increasing the proportion of vapor. This can decrease the average density. This will increase the volumetric flow rate, thus shortening the residence time while keeping the reactor volume constant.

[0066] According to DIN 51666:2007-01, gaseous plastic products collected via a balloon were analyzed by gas chromatography. The results are the calorific value, specific gravity, and molecular composition of the gas phase. According to ASTM D7169-20e1, the true boiling point profiles of the liquid products and the carrier medium were analyzed by simulated distillation (SIM-Dist).

[0067] A reaction model with 9 lumped units Using lumped units for kinetic modeling is a standard approach to modeling the kinetics of hydrocarbon cracking. This approach is necessary because typical starting materials for hydrocarbon pyrolysis are mixtures of many different molecules, making it impractical to consider every individual real reaction between each molecule. In this approach, each individual component of the plastic product is associated with a specific lumped unit in the reaction network. These lumped units are partitioned according to boiling point. Alternatively, they can be partitioned according to other material properties, such as molecular structure or density. Each lumped unit functions as a pseudo-component with representative material properties derived from the molecules it contains. The cracking reactions between lumped units are modeled as irreversible, single-stage, unimolecular reactions, such as... Figure 2 As illustrated in the diagram, the reaction rate r (see equation (1)) follows the Arrhenius law (see equation (2)).

[0068]

[0069]

[0070] In the reaction model of this example, lumped units are separated by boiling point. First, the boiling point temperature range of interest to the refinery is defined, which produces the gas-to-bottom product classification shown in Table 2. All components with boiling points above 600°C are defined as plastic / wax lumped units, representing the endpoints of the boiling point temperature range for the organic carrier medium. A complete reaction network with nine lumped units (i.e., the number of lumped units N is nine), where each heavier lumped unit (i.e., each lumped unit with a higher boiling point temperature range) reacts with each lighter lumped unit (i.e., each lumped unit with a lower boiling point temperature range), will consist of N*(N-1) / 2 distinct reactions, i.e., 36 distinct reactions, each with two kinetic reaction parameters. The sequential reaction model only considers the reaction from each heavier lumped unit to the next lighter lumped unit directly next to the next lighter lumped unit relative to the boiling point. This significantly reduces the number of reactions to 8 unknown reactions with 16 kinetic parameters. Figure 3 The resulting reaction model is schematically illustrated in the figure.

[0071] The sequential reaction model takes into account the decomposition of the plastic and carrier medium mixture, so that there is no interaction between the materials. For any plastic in the carrier medium and the plastic starting material, the reaction model can be solved independently of each other. The final mass fraction of lumped cell j is the sum of all lumped cells from n individual components with the same boiling point temperature range (Equation (3)).

[0072] Table 2. Boiling temperature range and number of carbon atoms for the nine lumped units used in the reaction model.

[0073]

[0074] Simulation and Fitting of Reaction Parameters The reactor was programmed as a custom operating unit in Visual Basic within PetroSim 7.2. For simulation, the laboratory system was divided into nine sections based on its geometry. Each section was simulated as a plug flow reactor, differing from the others in geometry, ambient temperature, and pipe insulation. For example, the first section was a horizontal tube, the second a vertical tube, and the third a downward-flowing coil. All these geometries had different heat transfer coefficient formulas and different ambient temperatures. The initial conditions for integrating the first reactor section were the measured mass flow rate, the measured feed temperature, and the feed concentration in the lumped unit. The initial conditions for the next section were the solutions to the differential equations of the previous section.

[0075] In this model, the mass balance of the reaction in the lumped unit, the energy balance of the fluid temperature required for the reaction rate, and the pressure loss equations for the two-phase flow were solved. The differential equations were discretized into a one-dimensional grid along the length of the reactor tube (see equations (4), (5), and (6)). The Darcy friction coefficient for the pressure loss calculation was calculated based on the correlation between Beggs and Brill for the two-phase flow (see (1996) "Standard handbook of petroleum & natural gas engineering", Gulf Publ, Houston, Texas).

[0076]

[0077]

[0078]

[0079] The dynamic parameters of the model were tuned using Matlab and the Surrogate optimization solver from the Global Optimization Toolbox. Surrogate optimization is typically used for global optimization of expensive cost functions that do not have available derivatives. For tuning, Matlab invoked PetroSim as a COM server to write experimental parameters and measurements into the case and obtain the results after computation. The simulation results are a comparison of the composition of the lumped cells of the simulated product with the true composition of the measured lumped cells. The surrogate solver treats the model itself as a black box and does not require gradient adaptation. The objective function Obj used in this study is the sum of squared errors between the experimental composition and the calculated composition of the lumped cells according to equation (7).

[0080]

[0081] Since it is assumed that there are no interactions between the components, experiments can be conducted using only the support medium or only a single plastic (i.e., a plastic starting material with only one type of plastic), adjusting the kinetic parameters first for the support medium and then for each plastic individually. Table 3 lists the parameter ranges and number of experiments for each plastic component. Two to three experiments were randomly selected from each plastic starting material to evaluate the kinetic parameters. These selected experiments, and all experiments with mixed plastics, were used only to evaluate the model parameters, not for training the model.

[0082] Table 3: Data used to adjust kinetic reaction parameters. Results were evaluated using a mixed plastic run.

[0083]

[0084] Simulation and Fitting of Reaction Parameters Experimental results show that process parameters and the composition of the plastic starting material have a significant impact on the boiling point distribution of the plastic products after pyrolysis. Table 4 provides an overview of the experimental process data.

[0085] Table 4. Experimental parameters for the graphs.

[0086]

[0087] Decomposition kinetics of different types of plastics Since the heaviest lumped unit (i.e. the lumped unit with the highest boiling point temperature range and the longest hydrocarbon range) is composed of plastic and its heaviest wax products, the k1 part of the reaction from the corresponding kinetic network can be regarded as the decomposition rate of the plastic. Figure 4 The results show that polypropylene breaks down much faster than low-density polyethylene (LDPE) and high-density polyethylene (HDPE) across most of the studied temperature range. Within the studied temperature range, the reaction rate of LPE is twice that of HDPE. At 500°C, the reaction rates of all plastics become nearly similar, with the differences diminishing. The activation energies and frequency factors of the reactions are shown in Table 5.

[0088] Table 5. Activation energies and frequency factors of the K12 decomposition reaction of PP, LDPE and HDPE.

[0089]

[0090] Accuracy of the reaction model The calculated kinetic parameters (i.e., reaction parameters) were evaluated using experimental data not used to fit the reaction parameters. A good fit of the model was defined as a maximum deviation of less than 0.05 kg / kg between the simulated data and the experimental values ​​(see Equation (8)) and no significant systematic error was observed. Figures 5A to 5I The deviations between the simulated and measured mass fractions for each evaluation experiment are shown, plotted on the average temperature in the reactor. No systematic errors were detected in any of the lumped cells and across the entire temperature range. It can also be seen that the accuracy for most lumped cells is within the accuracy criteria defined above. The least accurate lumped cell is the plastic / bottom product lumped cell. In this lumped cell, the deviations for two of the experiments are slightly above the threshold, with a maximum deviation of 0.07 kg / kg. Despite the high deviations, there are no identifiable systematic errors, so the kinetic parameters are still well-suited despite these two outliers. The larger deviations from the heaviest lumped cell can be explained by the inaccuracies of SimDist measurements, which are less accurate at higher boiling points. Figure 6 The results show that the simulated (solid) boiling point distribution matches well with the measured boiling point distribution (dashed line).

[0091] (8) Experimental series using laboratory reactors The kinetic model was used in the case study to find optimal experimental parameters for a laboratory reactor (in this case, a pyrolysis reactor). This case study used a plastic starting material consisting of 20 wt% LDPE, 10 wt% PP, and 70% support medium. Individual reaction models were determined for each different plastic starting material. The individual models can be summed (weighted according to the respective proportions of the plastic starting materials). Figure 7A Figure I shows the yield of the lumped units of the reactor across the entire temperature and mass flow range. It is clear that temperatures above 470°C have a positive impact on the yield of plastic products from more valuable lumped units with a crossover point below 350°C. Above this temperature, almost all plastics decompose into lighter fractions (or lumped units) of kerosene and gas oil, with clearly visible maximum yields of 0.14 wt% and 0.25 wt%, respectively.

[0092] Example 1 Summary Pyrolysis processes for the chemical recycling of plastics are essential technologies for achieving a fully circular economy. In this example, it has been demonstrated that a simple kinetic reaction model based on lumped units (with nine lumped units and a fully continuous partial reaction) can model the decomposition of polyolefins in a carrier medium with very high accuracy. The resolution of the boiling points of the plastic products is more accurate than other reaction models with fewer lumped units, and the number of unknown reaction parameters used for fitting is limited. For most lumped units, the maximum deviation of the modeled mass fraction from experimental results is less than 0.05 kg / kg, except for the plastic residue lumped unit, where the maximum deviation is 0.07 kg / kg. This accuracy has been shown to be detectable within the relevant temperature range for slow pyrolysis above 400°C and below 500°C. A case study from a laboratory plant demonstrates a clear temperature window between 470°C and 520°C for maximum yield of kerosene or gas oil.

[0093] List of abbreviations

[0094] Symbol list

Claims

1. A computer-implemented method for determining the values ​​of reaction parameters for a reaction model of the pyrolysis of a plastic starting material into a plastic product, the method comprising the following steps: - Provides experimental data on multiple boiling point distributions of plastic products, each of which is associated with pyrolysis temperature and pyrolysis duration, wherein the boiling point distributions are all categorized into N lumped units L1 to LN, each of which is associated with a boiling point temperature range. - Determine the corresponding values ​​of the reaction parameters by fitting the reaction parameters of the reaction model to experimental data; Among them, it is used for L1 to L N-1 Each lumped unit L i The reaction model has a partial reaction determined by at least one reaction parameter, used to describe the transformation of the plastic product of the lumped unit into the adjacent lumped unit L, which is located below the boiling point temperature range. i+1 The plastic product, wherein the reaction model has less than N*(N-1) / 2 partial reactions.

2. The computer-implemented method according to claim 1, characterized in that, The number of lumped units N is at least 7.

3. The computer-implemented method according to any one of claims 1 or 2, characterized in that, The reaction model has exactly (N-1) partial reactions.

4. A method for determining the values ​​of reaction parameters for a reaction model of pyrolysis of a plastic starting material into a plastic product using a computer-implemented method according to any one of the preceding claims, characterized in that, Providing experimental data includes the following steps: - Perform multiple pyrolysis runs in the pyrolysis reactor at different pyrolysis temperatures and / or pyrolysis durations; - Measure the boiling point distribution of the plastic products during each pyrolysis run, where each boiling point distribution is correlated with the pyrolysis temperature and pyrolysis duration; -Assign each boiling point distribution to N lumped units L1 to L2 N The boiling point temperature range is associated with each lumped cell to obtain experimental data.

5. A method for pyrolyzing plastic starting materials into plastic products, comprising the following steps: - Determine the reaction parameter values ​​of the pyrolysis reaction model by the computer-implemented method according to any one of claims 1 to 3 or the method according to claim 4; -Specify the expected boiling point distribution; - The pyrolysis temperature and duration are determined by minimizing the distance between the calculated boiling point distribution, obtained using a reaction model and previously determined reaction parameter values, and the expected boiling point distribution; and - Pyrolysis is carried out at a predetermined pyrolysis temperature and for a predetermined pyrolysis duration.

6. A system for data processing, characterized in that... A device having means for performing the steps of a computer-implemented method according to any one of claims 1 to 3.

7. The data processing system according to claim 6, characterized in that, The device is also adapted to perform the following steps: - The pyrolysis temperature and pyrolysis duration are calculated using a reaction model and previously determined reaction parameter values, where the pyrolysis temperature and pyrolysis duration are defined as minimizing the distance between the boiling point distribution calculated by the reaction model and the expected boiling point distribution.

8. A computer program product comprising instructions that, when executed by a computer, cause the computer to perform the steps of a computer-implemented method according to any one of claims 1 to 3.

Images