Optimized belt dryer within an sap manufacturing process - energy and throughput optimization

Abstract

The invention is directed to a method for controlling operation of a belt dryer assembly (500) for carrying out a drying process of a superabsorbent material cake (502) that results in an output material (512). The method comprises ascertaining a belt dryer model (M) indicative of a respective effect of drying process parameters (PP1, PP2) associated to the belt dryer assembly on physical and / or chemical properties (P1, P2) of the superabsorbent material cake, ascertaining input material data (518) indicative of respective values of one or more of the material properties (PV) of the superabsorbent material cake, and using the belt dryer model and the received input material data, determining and providing control instructions (CI) for controlling operation of the belt dryer assembly for driving the values of the physical and / or chemical properties of output material towards a set of expected values of the physical and / or chemical properties (P1*, P2*).

Description

[0001] Optimized belt dryer within an SAP manufacturing process - Energy and throughput optimization

[0002] FIELD OF THE INVENTION

[0003] The invention is directed to a computer implemented method for controlling operation of a belt dryer assembly for carrying out a drying process of a superabsorbent material cake that results in an output material. The invention is further directed to a belt dryer assembly and to a computer program.

[0004] BACKGROUND OF THE INVENTION

[0005] Superabsorbent polymer, often referred to as SAP, is a water absorbent hydrophilic homopolymer or copolymer that can absorb and retain extremely large amounts of aqueous liquid relative to its own mass. They are typically produced by polymerization of a monomer solution. The polymer gel is then dried, typically using a belt dryer assembly until the residual moisture content is below a predetermined threshold amount.

[0006] US 10,1137,432 B2 describes a process for producing water absorbing polymer particles that includes drying the aqueous polymer gel in a belt dryer assembly comprising a conveyer dryer, in particular in a forced air conveyer dryer, wherein the conveyer dryer has a circulating conveyer belt and the aqueous polymer gel is conveyed on the circulating conveyer belt. According to the document, the process stability can be improved by avoiding changes in process conditions, e.g., to overcome heat exchanger fouling in the dryer which changes the drying air throughputs. In current belt dryer assemblies, the operation parameters for the drying process are set by the operator based on his or her knowledge of the process or on best product behavior. This learned behavior is cumbersome because in the drying process of gel there may be chemical degradation of the polymer observed depending on drying conditions, the morphology of the gel particles, and the composition of gel particles. Therefore, the drying step is critical to overall performance of the finished product and customer acceptance. Hence, a product specific drying operation is desirable which requires smart process control. One example of this is disclosed in WO2023 / 046583A1. As in modern production for superabsorbents it is not only necessary to enable easy switching between product grades but also to control process settings and formulation tightly to achieve target performance, prevent product loss, and enable high productivity there exists a need for better and holistic production process control.

[0007] SUMMARY OF THE INVENTION

[0008] It would be therefore beneficial to enable an improvement of the physical and / or chemical properties of the output material obtained after the drying process.

[0009] A first aspect of the present invention is formed by a computer implemented method for controlling operation of a belt dryer assembly for carrying out a drying process of a superabsorbent material cake that results in an output material, namely a dried superabsorbent material cake with lower moisture content than the superabsorbent material cake fed into the belt dryer assembly. The method of the first aspect comprises ascertaining (e.g., determining, receiving, generating or otherwise acquiring) a belt dryer model indicative of a respective effect of drying process parameters associated to the belt dryer assembly on physical and / or chemical properties of the superabsorbent material cake, ascertaining input material data indicative of respective values of one or more of the physical and / or chemical properties of superabsorbent material cake to be provided to the belt dryer assembly, and using the belt dryer model and the received input material data, determining and providing control instructions for controlling operation of the belt dryer assembly for driving the values of the physical and / or chemical properties of the output material towards a set of expected values of the physical and / or chemical properties.

[0010] Thus, the provision of the belt dryer model, which relates the operation of the belt dryer assembly to material properties of the superabsorbent material cake, in combination with the input material data obtained from the material that is going to be undergo the drying process, i.e. the superabsorbent material cake and / or its precursors, enables an adaptation of the drying process parameters to control the material properties (e.g. the chemical and / or physical properties) of the dried superabsorbent material cake. The belt dryer model refers to a description of the drying process in the belt dryer assembly using mathematical concepts including governing equations, assumptions and constraints. The control of the material properties is achieved by controlling one or more variables that affect the drying process, so that the values of the physical and / or chemical properties of the output material are driven towards the set of predetermined expected values, also referred to as target values, and which can be given as exact values or as value ranges exhibiting a certain tolerance around a respective center value.

[0011] Thus, starting from the assumption that the properties of the current output material are at the expected values and that the current output material has been obtained by drying an input material (i.e., the superabsorbent material cake to be dried) characterized by the its input material data using a set of drying process parameters, in the case that the input material data of subsequent input material to be dried is substantially similar to that pertaining to the already dried output material, no modification of the drying process is needed. If however, the values of the material properties of subsequent input material differ from those of the previous input material, the variables controlling or affecting the drying process can be varied in accordance with the belt dryer model, such that the physical and / or chemical properties of the output material resulting from drying the subsequent input material remain at, or do not significantly deviate from, the expected values.

[0012] In known belt dryer assemblies, the drying process parameters are typically not fitted to the product properties of the superabsorbent material cake that enters the drying process, and the settings are chosen from best product behavior. However, some parameters such as the particle size distribution, composition, or cake geometry and material distribution in the assembly, have a drastic impact on the drying behavior and time. Also, the composition of the material cake impacts the drying process and further post-processing. Additionally, cake height also influences the drying behavior and the drying time and can also have an impact on product quality parameters. Further, a proper distribution of the material on the belt dryer is advantageous to achieve an optimal drying process. Especially prevention or minimization of false airflows around the cake is beneficial. False airflows do not contribute to the drying of the gel cake and can negatively impact subsequent sizing of the dried cake due to left-over wet lumps from incomplete drying.

[0013] The method of the first aspect thus enables a steering of the development of material properties of the superabsorbent material cake in comparison with the commonly used belt dryer assemblies for SAP material, which is generally treated as a black box without the possibility of controlling the material properties based on the input material data. In the following, embodiments of the method of the first aspect will be disclosed.

[0014] In an embodiment, the method of the first aspect also comprises the step of determining and providing, using the belt dryer model and the ascertained input material data, control instructions for controlling operation of a pre-processing unit for processing and feeding the superabsorbent material cake to the belt dryer assembly, for driving the values of physical and / or chemical properties of the output material towards the set of expected values of the physical and / or chemical properties. Here, based on the ascertained belt dryer model and the received or otherwise acquired input material data, the pre-processing of the material to form the superabsorbent material cake and / orthe feeding of the superabsorbent material cake, can be advantageously controlled and adjusted such that the values of the material parameters out the output material converge towards the expected values. The pre-processing unit can comprise, for example, kneading reactors or belt reactors. In the kneader, the polymer gel formed during the polymerization of an aqueous monomer solution or suspension is continuously comminuted by, for example, con- or counter-rotating agitator shafts. Polymerization in a belt reactor produces a polymer gel which must be comminuted, for example in an extruder, a chopper, a cutting mill or knife or in a kneader. In an embodiment, and in order to improve the drying properties, the comminuted polymer gel obtained by means of a kneader can also be extruded in an extruder unit, whose operation can be controlled based on the output material. Alternatively, or in addition, to an extruder one can also employ any or a combination of one or more of the devices listed above to achieve an advantageous gel particle morphology by comminution. For example, a cascade of two or more choppers and extruders can be employed. Optionally one can add further post-pro-cessing ingredients in one or more comminuting steps via such devices. The pre-processing unit may also comprise a superabsorbent material cake feeder that is configured to feed the superabsorbent material cake to the belt dryer in a controlled manner. By controlling the feeder, the amount of material provided to the drying process can be adjusted, for instance in terms of the height of the cake to achieve a homogeneous distribution of the gel across the width and along the length of the belt. Properties of the gel particles (its production history), the dried cake, as well as the target performance profile of the superabsorbent may be used to control the production process and especially the drying step.

[0015] The pre-processing unit may also comprise a gel bunker that collects the polymer gel, from which it is withdrawn typically by means of a discharge screw. The operation of the gel bunker can also be controlled based on the ascertained input material data. As an alternative to a vertical gel bunker one can also employ a horizontal gel hopper with agitated stirring shafts or a similar device with an incline angle between 90° (vertical) and 0° (horizontal). Agitation of the gel contributes to shaping the gel particle morphology due to gel particle grinding and friction. In this respect, it impacts also the drying properties and the observed degradation of the gel. These effects have significant impact on final product performance.

[0016] In another embodiment, the method of the first aspect additionally or alternatively comprises the step of determining and providing using the belt dryer model and the ascertained input material data, control instructions for controlling operation of a post-processing unit for further processing the output material for driving the values of the physical and / or chemical properties of the output material towards the set of expected values of the physical and / or chemical properties. The post-processing unit preferably comprises a milling unit for milling the dried superabsorbent cake. After the drying process, the dried polymer gel can be crushed and optionally coarsely comminuted. The dried polymer gel is then usually ground and classified, whereby single- or multi-stage roller mills, preferably two- or three-stage roller mills, pin mills, hammer mills or vibrating mills can usually be used for grinding. For classification, sieves can be used to classify the resulting powdered product into fine material, good product, and coarse material. A good product has the intended product properties, while fine and coarse material go back to recycling loops.

[0017] In an embodiment, the belt dryer model is based on a model predictive control (MPC), which is a method of process control that is used to control a process while satisfying a set of constraints. Model predictive controllers thus rely on dynamic models of the process, for example linear empirical models obtained by system identification. The models used in MPC predict the change in the dependent variables of the drying process that will be caused by changes in the independent variables.

[0018] Additionally, or alternatively, in another embodiment, the step of determining and providing control instructions is performed using a machine learning model that has been trained using training data sets that represent a plurality of drying processes performed on superabsorbent material cakes having corresponding physical and / or chemical properties that result in output material having corresponding physical and / or chemical properties. The machine learning model represents the belt dryer model, which as every other model which is not pure white box contains some parameters that can be used to fit the model to the system it is intended to describe. If the modeling is done by an artificial neural network or other machine learning, the optimization of parameters is done by a training process, while the optimization of model hyper-parameters is done by a tuning process that often uses cross-validation. In more conventional modeling through explicitly given mathematical functions, parameters are often determined by curve fitting. Optionally, in an embodiment, the method of the first aspect further includes determining the respective values of the physical and / or chemical properties of the input material before drying process and generating and providing the input material data indicative of said values.

[0019] Preferably, the input material data indicative of the values of the physical and / or chemical properties of the input material include one or more of chemical composition data indicative of a chemical composition of the input material, moisture data indicative of a moisture content of the input material, particle size data indicative of a particle size distribution of the input material and cake geometry data indicative of spatial dimensions and distribution of the superabsorbent material cake.

[0020] The physical and / or chemical properties of the superabsorbent material cake can include gel properties determined during a pre-processing of the raw materials to form the cake before it is provided to the inlet of the belt dryer. The gel properties may include, for instance, composition or moisture content. Particularly the gel stiffness is determined by the composition (e.g., the amounts and types of gel cross-linkers, the amounts and types of initiators) and impacts how well the gel cake is aerated during the drying process. For physical parameters especially the gel particle shape, surface stickiness, and surface roughness are important for the cake formation and the achievable aeration of the cake. Hence, input material data can also refer to these categories.

[0021] The input material data can also be indicative of the particle size distribution, e.g., bed packing, which can be obtained, for instance by optical inspection. The input material data can also be indicative of a distribution of the material cake on the belt dryer and / or of a height of the material cake. The input material data can then be used, in combination with the belt dryer model, to adapt the drying process to the superabsorbent material cake that is to be dried, for instance by adapting the heat input, the drying gas flow, the drying gas direction, the drying gas humidity, the fan speed, the conveyor belt speed, etc., such that the material properties of the output material are driven towards the set of expected values.

[0022] Thus, the input material data that can include, for instance, data regarding particle size and cake height according to a measurement process at the inlet (e.g., by an optical system or a camera system), and / or data regarding the composition of the material cake at the inlet, is advantageous to adapt the drying process (e.g., in terms of drying temperatures, fan speeds, fresh air usage) according to optimal settings for the prevailing output material conditions, for instance in terms of process optimization towards a desired quality and / or process optimization towards a lower energy demand. In another embodiment, the method further comprises ascertaining output material data indicative of respective values of one or more of the physical and / or chemical properties of the output material after the drying process, and determining and providing the control instructions for controlling operation of the belt dryer assembly further in dependency of the output material data.

[0023] The output material data that are indicative of the values of the physical and / or chemical properties of the output material after the drying process can include one or more of chemical composition data indicative of a chemical composition of the output material after the drying process, moisture data indicative of a moisture content of the output material and particle size data indicative of a particle size distribution of the output material.

[0024] Thus, in the case that the output material that results from operating the belt dryer assembly under a given set of operation conditions (e.g. the values of the drying process parameters used for obtaining the output material from which the output data has been determined) already has the expected physical and / or chemical properties, no modification of the drying process is needed. If however, the received values of the material properties differ from the expected values or target values, the variables controlling or affecting the drying process can be varied in accordance with the belt dryer model, such that the gap between the received values pertaining to the output material and the expected values is reduced for subsequent output material.

[0025] Additionally, or alternatively, the method may comprise, in a particular embodiment, ascertaining material data indicative of respective values of one or more of the physical and / or chemical properties of the material cake during the drying process, that may include, for example a moisture content in the material cake, and / or an acrylic acid content in the material cake, and / or a centrifugal retention capacity of the material cake, and / or extractable content of the material cake, and / or absorption capacity of the material cake, and / or a spatial distribution of the material cake in the belt dryer assembly. The control instructions are then determined and provided further in dependence on the material data obtained during the drying process and enable a control of the drying process in-situ, thereby offering a route for immediate troubleshooting, for instance by adapting a fresh air intake, heat input, fan speed, etc.

[0026] In another embodiment, the method further comprises ascertaining environmental data indicative of respective values of one or more environmental conditions inside, or in a vicinity of, the belt dryer assembly, and, determining and providing the control instructions further in dependence on the ascertained environmental data. The environmental data can be for instance indicative of a temperature value inside the belt dryer assembly, and / or of an air humidity value inside belt the dryer assembly, and / or of drying air volume flow value inside the belt dryer assembly and / or ambient air values indicative of ambient air parameters of ambient air in the vicinity of the belt dryer assembly. For instance, the humidity of the ambient air in the vicinity can be monitored and the provision of fresh air to the belt drying assembly can depend on the determined humidity, which can depend on weather conditions or a current season (e.g. winter vs. summer).

[0027] Preferably, the drying process is performed in low pressure conditions with respect to the atmospheric pressure, to avoid or reduce dust contamination outside the belt dryer assembly.

[0028] In known belt dryer assemblies, the current state of the drying process is not known. For instance, the product may heat up in the backend, curing temperatures have an impact in properties such as the centrifugal retention capacity, or air-bypasses can be created due to an unfavorable cake laydown.

[0029] With the further ascertainment of material data indicative of the material properties during the drying process, the drying process parameters can be modified such that the values of the physical and / or chemical properties of the material cake and / or of the output material are driven towards the set of expected values of the physical and / or chemical properties. Preferably, bypasses at sidewalls (wing formation) can be detected (e.g., by a suitable camera system, in particular in combination with suitable image analysis techniques) and avoided. The formation of sidewalls is typically due to a too strong drying process at the beginning or front end of the belt dryer and can be mitigated for instance by lowering the air temperatures or volume fluxes.

[0030] In an embodiment, the control instructions for controlling operation of the belt dryer assembly are control instructions for controlling one or more of a gas inlet temperature value of a drying gas, a gas flow rate value of the drying gas, a belt dryer speed value of a belt, a fresh air inlet or an exhaust air outlet, for instance in terms of air flow rate.

[0031] Additionally, or alternatively, the control instructions for controlling operation of the preprocessing unit are control instructions for controlling one or more of a gel comminution unit, a polymerization unit, a gel bunker or an agitated hopper, or a superabsorbent material cake feeder unit for providing a desired distribution (e.g. cake height) of the superabsorbent material cake at an input of the belt dryer assembly. Additionally, or alternatively, the control instructions for controlling operation of post-pro-cessing unit are control instructions for controlling a milling unit for milling the dried superabsorbent material cake.

[0032] Optionally, the control instructions for controlling operation of post processing unit are control instructions for controlling a sieving unit for classifying the dried and ground superabsorbent material cake. The correct and product specific operation of the classifying unit affects the recycle streams and has great impact on cost and quality.

[0033] In an embodiment, for belt dryer assemblies comprising a plurality of drying zones along a drying route, the method includes determining and providing respective control instructions for controlling the different drying zones along the drying route.

[0034] Regarding the belt dryer model, preferred input parameters include one or more of cake height, homogeneity of the cake, airflow permeability of the cake, particle size distribution, particle composition, acrylic acid content, extractables, residual initiator (if any), CRC-development, temperature, humidity and volume flux of the air inside the belt dryer, and preferred control parameters include one or more of temperature profile, fan settings (air volume fluxes), drying air humidity, throughput, and fresh air inlet

[0035] In a particular embodiment of the method of the first aspect, the belt dryer model comprises a gas-phase model including balance equations and constitutive equations for a gas phase, a solid phase model including balance equations and constitutive equations for a solid phase, an exchange flow model including heat exchange equations and mass exchange equations and a gas-solid interface model. Balance equations describe the probability flux associated with a Markov chain in and out of states or set of states. Constitutive equations define a relation between two or more physical quantities that is specific to a material or substance and approximates its response to external stimuli, usually as applied fields or forces.

[0036] In another preferred embodiment of the present invention the belt dryer model includes -in addition- at least one model describing the kinetics and optionally the statistics of the gel polymer network degradation. Gel polymer networks can degrade when heated for a prolonged period, unavoidable in the drying step. This degradation impacts the product quality as it is irreversible. For some products the effect may be desired and necessary to accomplish a certain target performance while for other products it may be detrimental to achieve their respective target performance. It is experimentally found (e.g., WO2023 / 046583A1) that extruded gels are more loosely packed and better aerated. Gels without extrusion are more densely packed with poorer aeration and consequently more degradation effects observed. Without wishing to be bound by theory, gel degradation can be caused by polymer chain scission, crosslinker degradation or a mixture of both effects.

[0037] In gels such as polyacrylate gel cross-linked with bifunctional polyacrylates (e.g. Polyeth-ylenglycoldiacrylate) it is believed to find a large cross-linked and entangled insoluble polymer network which is swellable in water and aqueous liquids. This network comprises polymer chains with one or more crosslinks in each chain keeping the chain connected. In the case of at least one crosslink the chain contributes to osmotic swelling (free swell absorption capacity, e.g., CRC) of the gel as it cannot diffuse out from the gel. However, several crosslinks are needed to enable a polymer chain to affect stiffness which is related to the ability to swell under external pressure while resisting or reducing mechanical deformation of the gel (absorption capacity under pressure, e.g. AUL).

[0038] Also, what is believed to be present in the polymer are extractable (soluble) polymer chains which may vary in amount and molecular weight distribution. These extractables do not have crosslinks that keep them inside the swollen gel for long. Depending on their molecular weight (Mw), their chain structure (linear or branched), and their amount present in the gel they exhibit profound impact on the final product performance. When swelling, these extractables tend to thicken the pore fluid inside the gel while water molecules are diffusing into the gel, wetting the gel slowly from its outside to its inside. The extractables tend to migrate counter current to the water inflow following their concentration gradient. This is a slow process but is believed to depend on the amount (concentration) of extractables and their molecular weight. Therefore, initially such extractables may temporarily contribute to free swell absorption capacity while after long time they will have migrated out of the swollen polymer gel network.

[0039] These soluble polymer chains can be uncrosslinked leftovers from the polymerization, or crosslinks can get destroyed by mechanical treatment before drying. It is evidenced by experiment that chemical degradation of crosslinkers and / or polymer chain-scission during the drying process do significantly affect the amount and molecular weight distribution of extractables present. Both processes may already start during the polymerization step when polymer chains are present but underthe conditions in the drying step they are known to proceed more rapidly. Besides these two processes, it is also visible that other processes with trace impurities present in the ingredients can lead to generation of extractables (e.g., chain transfer agents, oxidation agents). For a simulation of the band-drying process and its effects on the quality of the superabsorbent polymer product as well as throughput productivity of the band dryer it is necessary to model such degradation processes with equations and models that can be implemented together with the equations for modeling the drying process as given in the present invention. As the degradation processes take place in the wet state but have also been shown to occur after drying at elevated temperature it is necessary to model all situations that can reasonably occur during drying. This also encompasses the effect that small gel particles dry faster than big ones. Irregular shaped particles (e.g., after extrusion or other mechanical treatment) form a more loosely packed gel bed and dry faster than non-extruded gel particles. In practice of production, one will find a bed of gel particles with different sizes and shapes, drying histories, and temperatures in a gel bed. It is an objective of the present invention to optimize production results even considering this complexity.

[0040] For the generation of suitable models as a first method one can obtain the necessary model information experimentally. For example, polymerizations with varying formulations can be carried out. The gels obtained can be cured in an autoclave at the desired temperature and after pre-defined times can be shock-frosted and / or freeze-dried. The same can be done under band-dryer conditions where samples of drying gel can be extracted after pre-defined times or in case of a continuous process at different spots along the band dryer. The amount of extractables can then be determined by the EDANA method (WSP 270.2(05)) and the molecular weights can be investigated by size exclusion chromatography. The required methods for determination of relevant product- or gel-properties (such as, for instance, water content, CRC, absorption under pressure and / or extractables) are found in WO2023 / 046583A1 This model may be created by a design of experiments that delivers the needed experimental function as a mathematical model (multiple linear regression or other machine learning regression).

[0041] For instance, the molecular weight distribution can be determined using gel permeation chromatography (GPC) or size exclusion chromatography (SEC). Gel permeation chromatography is a type of size-exclusion chromatography, which separates high molecular weight or colloidal analytes on the basis of size or diameter, typically in organic solvents. The technique is often used for the analysis of polymers. GPC is often used to determine the relative molecular weight of polymer samples as well as the distribution of molecular weights. GPC is used to measure the molecular volume and shape function as defined by the intrinsic viscosity. If comparable standards are used, this relative data can be used to determine molecular weights within ± 5% accuracy. As a second method one can set up a chemical-physical-mathematical model and, after validation with selected experimental data, can use such a model instead. One embodiment is to generate a polymer network by simulating a molecular weight distribution using data from experiments to set the required parameters. The polymer network may be initially not crosslinked, and crosslinks can be distributed after its generation by random sampling (Monte Carlo method). The model will create an inventory of all polymer chains with their crosslinks. In a next step the model will calculate based on polymer chain scission rules and crosslinker degradation rules (e.g., random sampling method) how a number of such events will impact the structure of the remaining insoluble gel-network and the amount and molecular weight distribution of the extractables. The results of this part of the model are static (not time dependent) as they depend only on the amount of degradation events that take place. Degradations take place sequentially and after each event the model inventory is refreshed. The number of degradation events is computed with Arrhenius equations for each reaction path (chain scission, crosslinker degradation) and the combination of these Arrhenius equations with the static Monte-Carlo model equations yields the final model capable of simulating the polymer network degradation.

[0042] Preferably, in the belt dryer model, the superabsorbent material cake is modelled as a discretized cake comprising, in particular per drying zone, one or more cake elements in a horizontal direction along a direction of transport and one or more layers of cake elements in a vertical direction, perpendicular to the direction of transport. In the model, each cake element is preferably associated to a size class that is indicative of the mean particle size in said cake element.

[0043] In particular, the goal of the belt dryer model is to accurately describe the drying process of the cake along the belt dryer. It is preferred that the model describes the drying process depending on the particle size. As the drying gas changes the temperature and the humidity of its way through the cake, the vertical location may also have a large impact on the actual drying progress of the particles. For instance, particles at the top of the cake may dry at different speeds compared to particles that lie directly on the belt. Further, the drying progress of the solids also impacts the actual temperature of the cake, which in turn may lead to decomposition or different reactions in the cake, which can be solved after the solution of the drying progress. In a further step, the resulting composition can be linked to material specific quality parameters.

[0044] The belt dryer is divided into one or more zones, which are divided by walls. The cake moves in a substantially horizontal direction through the assembly and the different zones. In each zone, gas may be either provided from the bottom upwards or from the top downwards. According to the preferred belt dryer model, the cake is discretized both in the horizontal (longitudinal direction) and in the vertical direction into single cake elements. In an embodiment, each cake element has the width of the belt dryer, in a horizontal direction perpendicular to the longitudinal direction. In an alternative embodiment, the cake elements have a width that is a fraction of the total width of the belt dryer and the model includes several cake elements along the width direction.

[0045] The solid particles in each cake element are divided into different size classes k. Each size class is preferably described by a mean particle size, which is for example defined using the minimum and maximum particle size of the respective size class. Particles in each size class may have a distinct composition. For instance, particles with a size of 1 mm may have a different composition than particles with a size of 5mm. The composition is preferably defined by the mass fraction of the different compounds I.

[0046] The particle size distribution, which directly effects the effective heat and mass transfer, is set at the belt dryer inlet and may be defined as equal or different for each height element I layer of the cake to account for possible segregation effects. This information of the particle size distribution is subsequently transported along the longitudinal direction of the belt for each vertical layer of the cake. Additionally, a shrinkage of the gel particles during the drying which results in a decrease in the overall particle size distribution can be considered in the model. This shrinkage directly influences the flowability, i.e. the specific pressure drop of the cake through an increase in the overall cake porosity.

[0047] Preferably, the model includes the following model parameters.

[0048] A first group of model parameters comprises belt-dryer parameters, that include one or more of residence time of the cake in the assembly (associated to a belt velocity), cake height inside the belt dryer assembly, bed porosity, and belt dryer width for the calculation of the gas velocity.

[0049] A second group of model parameter comprises material parameters that include, for instance, parameters associated to the primary solvent component (e.g., critical moisture content, equilibrium moisture content, parameter for a characteristic drying curve), parameters associated to the secondary solvent component and parameters associated to the inert components. A third group of model parameters comprise parameters associated to the inlets and / or the boundary conditions, both in terms of solid (e.g., mass flow rate, temperature, composition) as in terms of gas, typically specified for each dryer zone, and that include mass flow rate (or volume flow rate or fan speed or any other parameter associated thereto), temperature, composition (in particular in terms of water content), direction (e.g., from top to bottom, from bottom to top), pressure.

[0050] A fourth group of parameters is directed to heat and mass transfers and includes, in particular, an exponent for the Lewis number.

[0051] A fifth group of parameters include numeric parameters of the model such as horizontal discretization (e.g., number of cake elements in the longitudinal direction), vertical discretization (number of cake layers in the vertical direction), number of particle size classes, as well as solver parameters, such as the solver strategy (e.g., Newton / fixed point), solver specific parameters, and maximum number of iterations.

[0052] In one embodiment of the model, it is assumed that for the properties of the components the specific heat capacity, the thermal conductivity, the dynamic viscosity, and the solid density are functions of the drying progress and the associated changes of the drying gel (composition of the gel and mass-flow / heat-flow gradients within the drying gel) as well as the drying apparatus (drying gas-flow, drying gas humidity, drying gas temperature),

[0053] In a particular embodiment, for the model, the following simplified assumptions are preferably taken into account. Regarding the properties of the components, it is preferably assumed that the values of the specific heat capacity, thermal conductivity, the dynamic viscosity and the solid density are constant.

[0054] Regarding the components in the solid phase, the superabsorbent material cake is assumed to include 5 components, namely water, acrylic acid, polyacrylic acid, initiator, in particular sodium persulfate (NAPS), and sodium acrylate. Instead of or in addition to NAPS, one or more residual initiators from the polymerization process may be present if they are stable enough not to completely decompose during polymerization or if they have been added post-polymerization in the gel comminution step. As solvent component water is preferred. Optionally, a second evaporating component is acrylic acid. Further, optionally, gas properties in terms of dynamic viscosity and heat conductivity are assumed to be temperature independent. Finally, it is preferably assumed that there is no temperature gradient within a given particle. However, these parameters and assumptions are only exemplary. Other belt dryer models can include other parameters or use different assumptions.

[0055] A second aspect of the invention is formed by a belt dryer assembly that is configured to carry out a drying process of a superabsorbent material cake. The belt drying assembly of the second aspect of the invention comprises a belt dryer having an input unit for receiving the superabsorbent material cake to be dried and comprising a belt that is configured to transport the superabsorbent material cake from the input unit to an output unit for providing a dried superabsorbent material cake as output material.

[0056] The belt dryer comprises one or more drying zones along a drying route of the belt dryer, each drying zone comprising a respective drying unit configured to generate and provide a drying gas for drying the superabsorbent material cake currently on the belt dryer.

[0057] Further, the belt dryer assembly comprises a controller unit that is configured to ascertain a belt dryer model indicative of a respective effect of drying process parameters associated to the belt dryer assembly on physical and / or chemical properties of the superabsorbent material cake. The controller is also configured to ascertain input material data indicative of respective values of one or more physical and / or chemical properties of the superabsorbent material cake that will undergo the drying process.

[0058] The controller is also configured, using the belt dryer model and the ascertained input material data, to determine and provide control instructions for controlling operation of the belt dryer assembly, in particular of the belt and / or the drying units, for driving the values of the physical and / or chemical properties of the output material towards a set of expected values of the physical and / or chemical properties.

[0059] The belt dryer assembly of the second aspect thus shares the advantages of the computer implemented method of the first aspect of the invention or of any of its embodiments.

[0060] In the following, embodiments of the belt dryer assembly of the first aspect of the invention will be disclosed.

[0061] In an embodiment, the controller unit is further configured to implement a machine learning model that has been trained using training data sets that represent a plurality of drying processes performed on superabsorbent material cakes having corresponding physical and / or chemical properties that result in output material having corresponding physical and / or chemical properties.

[0062] Preferably, in an embodiment, the one or more drying units comprise at least a heat exchanger and a fan respectively.

[0063] In a preferred embodiment, the belt dryer assembly further comprises a parameter determination unit that is configured to determine the respective values of physical and / or chemical properties of the output material after the drying process and to generate and provide, to the controller unit, the output material data indicative thereof. The same parameter determination unit, or an alternative parameter determination unit can be provided to determine the respective values of physical and / or chemical properties of the input material. The same parameter determination unit, or an alternative parameter determination unit can be provided to determine the respective values of physical and / or chemical properties of the material inside the belt dryer assembly.

[0064] In another embodiment, the belt dryer assembly further comprises a pre-processing unit for processing and feeding the superabsorbent material cake to the belt dryer. Here, the controller unit is further advantageously configured to determine and provide control instructions for controlling operation of the pre-processing unit for driving the values of the physical and / or chemical properties of subsequent output material towards the set of expected values of the physical and / or chemical properties.

[0065] Additionally, or alternatively, the belt dryer assembly may comprise a post-processing unit for further processing the output material. Here, the controller unit is further configured to determine and provide control instructions for controlling operation of the post-processing unit fordriving the values of the physical and / or chemical properties of the output material towards the set of expected values of the physical and / or chemical properties.

[0066] In another embodiment, the controller unit can be configured to ascertain output material data indicative of respective values of one or more of the physical and / or chemical properties of the output material after the drying process, and to determine and provide the control instructions for controlling operation of the belt dryer assembly further in dependency of the output material data.

[0067] Additionally, or alternatively, in another embodiment, the controller unit is further configured to ascertain material data indicative of respective values of one or more of the physical and / or chemical properties of the material cake during the drying process, that may include, for example a moisture content in the material cake, and / or an acrylic acid content in the material cake, and / or a centrifugal retention capacity of the material cake and / or a spatial distribution of the material cake in the belt dryer assembly. The control instructions are then determined and provided further in dependence on the material data obtained during the drying process and enable a control of the drying process in-situ, thereby offering a route for immediate troubleshooting, for instance by adapting a fresh air intake, heat input, fan speed, etc.

[0068] A third aspect of the invention is formed by a computer program comprising instructions that, when executed by a controller unit of a belt dryer assembly, cause the belt dryer assembly to carry out the method of the first aspect.

[0069] It shall be understood that the methods described above, the devices described above and the computer program product described above have similar and / or identical preferred embodiments, in particular, as defined in the dependent claims.

[0070] It shall be understood that a preferred embodiment of the present invention can also be any combination of the dependent claim or above embodiments with a respective independent claim.

[0071] These and other aspects of the present invention will be apparent from and elucidated with reference to the embodiments described hereafter.

[0072] BRIEF DESCRIPTION OF THE DRAWINGS

[0073] In the following drawings:

[0074] Fig. 1 shows a schematic block diagram of an exemplary embodiment of belt dryer assembly according to the invention;

[0075] Fig. 2 shows a schematic block diagram of another exemplary embodiment of belt dryer assembly according to the invention;

[0076] Fig. 3 shows a schematic block diagram of another exemplary embodiment of belt dryer assembly according to the invention; Fig. 4 shows a flow diagram of an exemplary embodiment of a method for controlling operation of a belt dryer assembly according to the invention; and

[0077] Fig. 5a-c show a set of assumptions pertaining to the superabsorbent material cake used in an exemplary belt dryer model implemented in a controller unit of a belt dryer assembly in accordance with the invention.

[0078] DETAILED DESCRIPTION OF EMBODIMENTS

[0079] Fig. 1 shows a schematic block diagram of an exemplary embodiment of belt dryer assembly 500 according to the invention. The belt dryer assembly 500 of Fig. 1 is configured to carry out a drying process of a superabsorbent material cake 502. The belt drying assembly 500 comprises a belt dryer 504 having an input unit 506 for receiving the superabsorbent material cake 502 to be dried. The belt dryer 504 includes a transport unit, such as a conveyor belt 508, referred to as belt 508, that is configured to transport the superabsorbent material cake 502 from the input unit 506 to an output unit 510 for providing a dried superabsorbent material cake 512, which is the output material of the belt dryer 504.

[0080] The belt dryer 504 comprises one or more drying zones Z1-ZN distributed sequentially along a drying route 514, where the drying process of the superabsorbent material cake is carried out. Each drying zone Z1-ZN comprises a respective drying unit 515 that is configured to generate and provide a drying gas DG for drying the cake material located in the corresponding zone. The provision of the drying gas DG in each zone can be tailored independently to adapt the drying process along drying route 514.

[0081] The belt dryer assembly 500 comprises a controller unit 516 that is configured to ascertain (e.g., to receive, to generate, to determine or to otherwise acquire) a belt dryer model M. The belt dryer model is a mathematical model that is indicative of a respective effect of drying process parameters PP1, PP2 associated to the belt dryer assembly 500, in partic-ular to the belt dryer 504, on physical and / or chemical properties P1, P2 of the superabsorbent material cake and that includes governing equations, assumptions and constraints that relate the process parameters PP1, PP2 of the drying process (e.g., temperature profile, volume fluxes, drying gas humidity, drying gas direction, belt speed, etc.) to the material properties of the cake material (e.g., cake composition, moisture content, particle size distribution, cake height and homogeneity, etc.). The controller unit 516 of Fig. 1 is configured to receive input material data 518 that is indicative of respective values of one or more physical and / or chemical properties PV of the superabsorbent material cake to be provided to the belt dryer assembly 500, in particular to the belt dryer 504, also referred to as input material. The physical and / or chemical properties PV of the input material can be determined from input material right before being provided to the belt dryer, or from precursor materials and pre-processes used to produce the superabsorbent material cake 502. The material properties PV of the input material can include, for instance, a composition, a particle size distribution, a moisture content and / or a distribution of the cake on the belt 508.

[0082] The input material data 518 is received from a parameter determination unit 520 that is configured to determine the respective values of physical and / or chemical properties PV of the input material 512, and to generate and provide, to the controller unit 516, the output material data 518 indicative thereof.

[0083] The controller unit 516, using the belt dryer model M and the received input material data 518, is configured to determine and provide control instructions Cl for controlling operation of the belt dryer assembly 500, in particular of the belt 508 and / or the drying units 515, for driving the values of the physical and / or chemical properties of the output material 512 towards a set of expected values of the physical and / or chemical properties P1*, P2*. Thus, the knowledge of the material properties of the input material 502 is used in combination with the belt dryer model M to adapt the drying process such that the values of the material properties of the output material 512 provided by belt dryer assembly 500 are driven towards predefined target parameters. In particular, the control instructions Cl can comprise a set of different control instructions CI1- CIN for controlling each drying zone independently.

[0084] Fig. 2 shows a schematic block diagram of another exemplary embodiment of belt dryer assembly 500 according to the invention. The following discussion will be focused on those technical features that distinguish the belt dryer assemblies of Figs. 1 and 2. Those technical features having similar and or identical functions will be referred to using the same reference signs or reference numbers.

[0085] In the belt dryer assembly 500 of Fig. 2, each of the one or more drying units Z1 - ZN comprise at least a heat exchanger 515a and a fan 515b respectively. In Fig. 2, the fans 515b are arranged on a top section of the belt dryer 504 whereas the heat exchangers 515a are arranged on a bottom section. The location of the heat exchangers and the fans determine the flow direction of the drying gas DG. In alternative belt dryers, the positions of the heat exchanger and the fan can be swapped in one or more of the drying zones Z1-ZN (not shown).

[0086] The belt dryer assembly 500 of Fig. 2 further comprises a pre-processing unit 522 for processing and feeding the superabsorbent material cake to the belt dryer 504. The pre-processing unit 522 can comprise, for example, kneading reactors or belt reactors. In the kneader, the polymer gel formed during the polymerization of an aqueous monomer solution or suspension is continuously comminuted by, for example, counter-rotating agitator shafts. Polymerization in a belt reactor produces a polymer gel which must be comminuted, for example in an extruder or kneader. In an embodiment, and in order to improve the drying properties, the comminuted polymer gel obtained by means of a kneader can also be extruded in an extruder unit, whose operation can be controlled based on the output material. The pre-processing unit may also comprise a superabsorbent material cake feeder that is configured to feed the superabsorbent material cake to the belt dryer in a controlled manner. By controlling the feeder, the amount of material provided to the drying process can be adjusted, for instance in terms of the height of the cake. The pre-processing unit may also comprise a gel bunkerthat collects the polymer gel, from which it is withdrawn typically by means of a discharge screw. The parameter determination unit 520 that is configured to determine the respective values of physical and / or chemical properties PV of the of the superabsorbent material cake 502 and to generate and provide, to the controller unit 516, the input material data 518 indicative thereof, can be further configured to determine the values of physical and / or chemical properties PV of the materials (e.g. precursors) being processed in the pre-processing unit 522, and to provide the input material data 518 also in dependence thereof.

[0087] Using the belt dryer model M and the input material data, the controller unit 516 is further configured to determine and provide control instructions Cla for controlling operation of the belt dryer. In particular, the control instructions Cla for controlling operation of the belt dryer 504 can comprise control instructions CI1-CIN for controlling each of the drying zones independently. The controller unit is also configured to determine and provide control instructions Clb for controlling operation of the pre-processing unit 522 for driving the values of the physical and / or chemical properties of subsequent output material towards the set of expected values of the physical and / or chemical properties P1*, P2*. Additionally, or alternatively, the controller unit 516 is configured to determine and provide control instructions Clc for controlling operation of a post-processing unit 523 for driving the values of the physical and / or chemical properties of the output material towards the set of expected values of the physical and / or chemical properties. The post-processing unit 523 performs a post- processing step on the output material 512, such as a milling step carried out by a milling unit as the post-processing unit 523.

[0088] Fig. 3 shows a schematic block diagram of another exemplary embodiment of belt dryer assembly 500 according to the invention. The following discussion will be focused on those technical features that distinguish the belt dryer assemblies of Figs. 1, 2, and 3. Here again, those technical features having similar and or identical functions will be referred to using the same reference signs or reference numbers.

[0089] The belt dryer assembly 500 of Fig. 3 also comprises a second parameter determination unit 520b, which can be also part of the parameter determination unit 520 of Figs. 1 and / or 2. The second parameter determination unit 520b is configured to determine and provide, to the controller unit 516, output material data 518b indicative of respective values of one or more of the physical and / or chemical properties P1, P2 of the output material 512 after the drying process. The output material data 518b can be used in combination with the input material data 518 and the model M to drive the values PV of the physical and / or chemical properties P1, P2 of the output material towards the set of expected values of the physical and / or chemical properties P1*, P2*, by determining, generating and providing suitable control instructions Cla, Clb and / or Clc. In particular, the control instructions Cla for controlling operation of the belt dryer 504 can comprise control instructions CI1-CIN for controlling each of the drying zones independently.

[0090] Optionally, the belt dryer assembly 500 alternatively or additionally comprises a third parameter determination unit 520c that is configured to provide material data 518c that is indicative of respective values PV of one or more of the physical and / or chemical properties P1, P2 of the material cake during the drying process. These can include, for instance, one or more of a moisture content in the material cake, and / or an acrylic acid content in the material cake, and / or a centrifugal retention capacity of the material cake and / or a spatial distribution of the material cake in the belt dryer assembly. The material data 518c can be used in addition to or in combination with the output material data 518 and the input material data 518b, as well as with the model M, to drive the values PV of the physical and / or chemical properties P1, P2 of the output material towards the set of expected values of the physical and / or chemical properties P1*, P2*. In particular, environmental data 519 can be ascertained that is indicative of respective values of one or more environmental conditions E1, E2 inside or in a vicinity of the belt dryer assembly. The control instructions Cla, Clb, Clc can be provided further in dependence on the ascertained environmental data 519. The environmental data can be for instance indicative of a temperature value inside the belt dryer assembly, and / or of an air humidity value inside belt the dryer assembly, and / or of drying air volume flow value inside the belt dryer assembly and / or ambient air values indicative of ambient air parameters of ambient air in the vicinity of the belt dryer assembly.

[0091] Fig. 4 shows a flow diagram of an exemplary computer implemented method 100 for controlling operation of a belt dryer assembly 500 for carrying out a drying process of a superabsorbent material cake 502 that results in an output material 512. The method comprises, in a step 102, ascertaining (e.g., receiving, generating, determining or otherwise acquiring) a belt dryer model M indicative of a respective effect of drying process parameters PP1, PP2 associated to the belt dryer assembly on physical and / or chemical properties P1, P2 of the superabsorbent material cake 502. The method also comprises, in a step 104, ascertaining (e.g., receiving, generating, determining or otherwise acquiring) input material data 518 indicative of respective values PV of one or more of the physical and / or chemical properties (P1, P2) of the superabsorbent material cake to be provided to the belt dryer assembly. The ascertainment of some of the input material data can be carried out by a suitable camera system, preferably combined with suitable image analysis techniques. Chemical and / or physical analysis of the superabsorbent material cake can also be used to ascertain input material data. The method also comprises, in a step 106, and using the belt dryer model and the received input material data 518, determining and providing control instructions Cla for controlling operation of the belt dryer assembly for driving the values PV of the physical and / or chemical properties P1, P2 of the material cake towards a set of expected values of the physical and / or chemical properties P1*, P2*.

[0092] Optionally, as indicated by the dashed lined boxes in Fig. 4, the method 100 can comprise, in a step 104b, ascertaining output material data 518b indicative of respective values PV of one or more of the physical and / or chemical properties P1, P2 of the output material after the drying process and / or, in a step 104c, ascertaining material data indicative of respective values PV of one or more of the physical and / or chemical properties P1, P2 of the material cake during the drying process.

[0093] Also optionally, the method 100 can comprise, in a step 106b, determining and providing control instructions Clb for controlling operation of a pre-processing unit 522 for processing and feeding the superabsorbent material cake to the belt dryer assembly, for driving the values of the physical and / or chemical properties of the output material towards the set of expected values of the physical and / or chemical properties, and / or, in a step 106c, determining and providing control instructions Clc for controlling operation of a post-processing unit 523 for further processing the output material for driving the values of the physical and / or chemical properties of the output material towards the set of expected values of the physical and / or chemical properties. Figs. 5a-c schematically show a set of assumptions regarding the superabsorbent material cake that is associated to a particular exemplary belt dryer model that will be explained in the following.

[0094] According to the preferred belt dryer model, and as it is shown in Fig. 5a, the cake 502 is discretized both in the horizontal (longitudinal direction) and in the vertical direction into single cake elements (i, j). Fig. 5a shows a cross-sectional view of the cake in a direction parallel to the transport direction, i.e., it shows the whole length of the belt dryer and each cake element has the width of the belt dryer, in a horizontal direction perpendicular to the longitudinal direction. Alternatively, the cake elements (i, j) can have a width that is a fraction of the total width of the belt dryer and the model includes several cake elements along the width direction. According to Fig. 5a, the cake is discretized in Nj vertical layers and Ni horizontal elements, resulting in a total of Ni*Nj cake elements. The direction of transport is given by the reference sign T

[0095] The solid particles in each cake element are divided into different size classes k (see Fig.

[0096] 5c). Each size class is preferably described by a mean particle size, which is for example defined using the minimum and maximum particle size of the respective size class. Particles in each size class may have a distinct composition, as shown in Fig. 5b. For instance, particles with a size of 1mm may have a different composition than particles with a size of 5mm. The composition is preferably defined by the mass fraction of the different compounds I. The particle size distribution is set at the belt dryer inlet and may be defined as equal or different for each height element I layer of the cake to account for possible segregation or shrinking effects.

[0097] In particular, the belt dryer model comprises a gas-phase model including balance equations and constitutive equations for a gas phase, a solid phase model including balance equations and constitutive equations for a solid phase, an exchange flow model including heat exchange equations and mass exchange equations and a gas-solid interface model.

[0098] For the following discussion, table 1 summarizes the meaning of the different indices used in the formulas.

[0099]

[0100]

[0101] 1) Gas phase model

[0102] An exemplary gas phase model is given by the following balance equations and constitutive equations:

[0103] 1.1) Balance equations

[0104] Mass balance equation of compound (l) in a discrete cake element(i,j):

[0105]

[0106] wherein m is a mass flow rate (kg / s).

[0107] Enthalpy balance of gas in discrete cake element (i,j) and size class (k)

[0108]

[0109] wherein H is the enthalpy flow rate (J / s) and Q is the heat flow rate (J / s)

[0110] 1.2) Constitutive equations

[0111] Mass fraction of compound (l) in discrete cake element (i,j)

[0112]

[0113] wherein w is the mass fraction

[0114] Outflowing mass flow rate from discrete cake element (i,j)

[0115]

[0116] Connection of stream variables of compound (l) in vertical direction between discrete cake elements (i,j), (i,j - 1) and (i,j + 1) for:

[0117] Mass gas flow from bottom to top:

[0118]

[0119] Mass flow from top to bottom:

[0120] ^G,i,j,l,in = rflG,i -l,l,oUt. for j < Nj - 1

[0121] ṁG,i,j,l,in = ṁG,i,l,in for j = Nj - 1

[0122] wherein Nj in the number of cake layers

[0123] Specific enthalpy of gas phase and component (Z)

[0124]

[0125] wherein h is the specific enthalpy (J / kg), cp is the specific heat capacity (J / (kg*K)), T is the temperature (K), T0 is the reference temperature (K) near operating point for evaluation of material properties, ΔHv is the enthalpy of vaporization (J / kg)

[0126] Temperature of gas from specific enthalpy

[0127]

[0128] 2) Solid phase model

[0129] An exemplary solid phase model is given by the following balance equations and constitutive equations:

[0130] 2.1) Balance equations

[0131] Mass balance of compound (l) in particle size class (k) in discrete cake element (i,j).

[0132]

[0133] wherein Rmis a mass specific reaction rate of a reaction m (kg / s)

[0134] Here, reactions are considered separately after convergence of the heat and mass transfer due to drying and contact with hot gas. The reactions are preferably calculated in a separate solution step after the drying step has converged to a solution. The reaction does not contribute directly to the mass and energy balances.

[0135] Enthalpy balance of particle size class (k) in discrete volume element (i,j)

[0136]

[0137] 2.2) Constitutive equations

[0138] Mass fraction of compound (l) for particles in size class (k) in discrete cake element (i,j)

[0139] -S i jjc i out

[0140] WS,i,j,k,l = - - ''lS,iJ,k,out

[0141] Outflowing mass flow rate of particles in size class (k) from discrete cake element (i,j)

[0142]

[0143] Connection of stream variables of size class (k) and compound (l) in horizontal direction between discrete cake elements (i,j), (i,j - 1) and (i,j + 1) for

[0144]

[0145] Outflowing enthalpy flow rate of particles in size class (k) from discrete cake element (i,j)

[0146]

[0147] Specific enthalpy of gas phase and compound (l)

[0148]

[0149] Temperature of gas from specific enthalpy

[0150]

[0151] Number of particles in size class (k) in discrete cake element (i,j)

[0152]

[0153] wherein Nsis the number of particles

[0154] Solid mass of particles of size class (k) in discrete cake element (i,j)

[0155] mS,i,j,k = ṁS,i,j,k,out · τS,i

[0156] wherein m is the mass (kg), and τS,i is the residence time of particles in horizontal element (i) given by Ay

[0157] τS,i = Δy / vS

[0158] wherein Ay is the width or length of the horizontal element (m) and v is the velocity (m / s)

[0159] Length of horizontal volume elements (i)

[0160]

[0161] wherein H is the height of the cake and Ntis the number of horizontal elements

[0162] Mass of single particle of size class (k) in discrete volume element (i,j)

[0163]

[0164] Normalized / Relative drying rate for evaporating compound (lsolv)

[0165]

[0166] wherein v is the relative drying rate and is the normalized solvent content.

[0167] Normalized moisture content for evaporating compound (lsolv)

[0168]

[0169] wherein XS,i,j,k is the moisture content for evaporating compound (lsolv) given by

[0170]

[0171] 3) Exchange flow model

[0172] An exemplary exchange flow model is given by the following heat exchange equations and mass exchange equations: 3.1) Heat exchange

[0173] Heat exchange between gas and solid in discrete volume element (i,j) and size class (k)

[0174] QGS,i,j,k = NS,i,j,k · π · dp,k · αi,j,k · [TG - TS,i,j,k]

[0175] wherein N is the number of particles, dPis the particle size (m), a is the heat transfer coefficient (W / (K*m2))

[0176] wherein the heat transfer coefficient is given as

[0177]

[0178] wherein A is the thermal conductivity (W / (m*K)) and Nu is the Nusselt number

[0179] 3.2) Mass exchange

[0180] Evaporation rate for component (l) in particle size class (k) in discrete volume element (i,j):

[0181]

[0182] wherein ρ is the density (kg / m³), Y is the gas solvent moisture -dry basis- (kgsolv / kgdry) and β is the mass transfer coefficient (m / s) given by

[0183]

[0184] wherein Sh is the Sherwood number and Dvis the binary diffusion coefficient (m2 / s)

[0185] 4) Gas-solid interface model

[0186] The gas-solid interface model addresses mixture properties including the temperature at gas - solid interface according to a predetermined mixture rule around particles of size class (k) in discrete volume element (i,j)

[0187]

[0188] The model includes a set of dimensionless numbers that include the Nusselt number, defined as:

[0189] Nui,j,k = αi,j,k · dp,k / λG,i,j · Le^K

[0190] wherein Le is the Lewis number defined as:

[0191]

[0192] wherein Sc is the Schmidt number and Pr is the Prandtl number defined as:

[0193] p > PG,i,jCp, G,i,j

[0194] '■jAG,i,j

[0195] wherein η is the dynamic viscosity (Pa*s)

[0196] The Sherwood number Sh is given according to Gnielinski (Mersmann, A., Gnielinski, V., Thurner, F., Verdampfung, Kristallisation und Trocknung, Springer Verlag, Berlin, 1993):

[0197]

[0198] wherein the laminar Sherwood number is defined as:

[0199] Shlam,i,j,k,l = 0.664 · Re^(1 / 2) · Sc^(1 / 3)

[0200]

[0201] and the turbulent Sherwood number is defined as

[0202]

[0203] and wherein Re is the Reynolds number around particles of size class (k) in discrete cake element (i,j) and is defined as:

[0204]

[0205] Further, the diffusion coefficient (From Seaver et al 1989, for water) is defined as:

[0206] Dv iu = 0.211

[0207]

[0208] and the saturation pressure for water (From Stull, 1947 [255.0-373 K]) at surface of particle of size class (fc) is defined as:

[0209]

[0210] The solvent saturation loading of water at surface of particle is given by

[0211]

[0212] wherein M is the molar mass (kg / mol)

[0213] The Solvent content (dry basis) in gas is given as:

[0214]

[0215] These equations form an exemplary belt dryer model that accurately describes the drying process of the cake along the belt dryer assembly depending on the particle size and the vertical location of the material in the cake. The knowledge of the values of the one or more of the physical and / or chemical properties of the output material after the drying process can be used in combination with the model to control the operation of the belt dryer assembly, so that the material properties (e.g., physical or chemical properties) of future or subsequent output material tend toward a set of target or expected values. This is done by providing control instructions for controlling the drying process and / or the pre-processing unit, thereby controlling the way in which the superabsorbent material cake is dried inside the belt dryer and / or the properties of the material cake that is provided to the belt dryer for drying, or in other words, the input material.

[0216] In summary, the invention is directed to a method for controlling operation of a belt dryer assembly for carrying out a drying process of a superabsorbent material cake that results in an output material. The method comprises ascertaining a belt dryer model indicative of a respective effect of drying process parameters associated to the belt dryer assembly on physical and / or chemical properties of the superabsorbent material cake, ascertaining input material data indicative of respective values of one or more of the material properties of superabsorbent material cake, and using the belt dryer model and the received input material data, determining and providing control instructions for controlling operation of the belt dryer assembly for driving the values of the physical and / or chemical properties of output material towards a set of expected values of the physical and / or chemical properties.

[0217] Other variations to the disclosed embodiments can be understood and effected by those skilled in the art in practicing the claimed invention, from a study of the drawings, the disclosure, and the appended claims.

[0218] For the processes and methods disclosed herein, the operations performed in the processes and methods may be implemented in differing order. Furthermore, the outlined operations are only provided as examples, and some of the operations may be optional, combined into fewer steps and operations, supplemented with further operations, or expanded into additional operations without detracting from the essence of the disclosed embodiments.

[0219] Procedures like the ascertaining determining or receiving current values performed by one or several units or devices can be performed by any other number of units or devices. These procedures can be implemented as program code means of a computer program and / or as dedicated hardware.

[0220] A computer program product may be stored / distributed on a suitable medium, such as an optical storage medium or a solid-state medium, supplied together with or as part of other hardware, but may also be distributed in other forms, such as via the Internet or other wired or wireless telecommunication systems.

[0221] Any units described herein may be processing units that are part of a classical computing system. Processing units may include a general-purpose processor and may also include a field programmable gate array (FPGA), an application specific integrated circuit (ASIC), or any other specialized circuit. Any memory may be a physical system memory, which may be volatile, non-volatile, or some combination of the two. The term “memory” may include any computer-readable storage media such as a non-volatile mass storage. If the computing system is distributed, the processing and / or memory capability may be distributed as well. The computing system may include multiple structures as “executable components”. The term “executable component” is a structure well understood in the field of computing as being a structure that can be software, hardware, or a combination thereof. For instance, when implemented in software, one of ordinary skill in the art would understand that the structure of an executable component may include software objects, routines, methods, and so forth, that may be executed on the computing system. This may include both an executable component in the heap of a computing system, or on computer-readable storage media. The structure of the executable component may exist on a computer-readable medium such that, when interpreted by one or more processors of a computing system, e.g., by a processor thread, the computing system is caused to perform a function. Such structure may be computer readable directly by the processors, for instance, as is the case if the executable component were binary, or it may be structured to be interpretable and / or compiled, for instance, whether in a single stage or in multiple stages, so as to generate such binary that is directly interpretable by the processors. In other instances, structures may be hard coded or hardwired logic gates, that are implemented exclusively or near-exclusively in hardware, such as within a field programmable gate array (FPGA), an application specific integrated circuit (ASIC), or any other specialized circuit. Accordingly, the term “executable component” is a term for a structure that is well understood by those of ordinary skill in the art of computing, whether implemented in software, hardware, or a combination. Any embodiments herein are described with reference to acts that are performed by one or more processing units of the computing system. If such acts are implemented in software, one or more processors direct the operation of the computing system in response to having executed computer-executable instructions that constitute an executable component. Computing system may also contain communication channels that allow the computing system to communicate with other computing systems over, for example, network. A “network” is defined as one or more data links that enable the transport of electronic data between computing systems and / or modules and / or other electronic devices. When information is transferred or provided over a network or another communications connection, for example, either hardwired, wireless, or a combination of hardwired or wireless, to a computing system, the computing system properly views the connection as a transmission medium. Transmission media can include a network and / or data links which can be used to carry desired program code means in the form of computer-executable instructions or data structures and which can be accessed by a general-purpose or special- purpose computing system or combinations. While not all computing systems require a user interface, in some embodiments, the computing system includes a user interface system for use in interfacing with a user. User interfaces act as input or output mechanism to users for instance via displays.

[0222] Those skilled in the art will appreciate that at least parts of the invention may be practiced in network computing environments with many types of computing system configurations, including, personal computers, desktop computers, laptop computers, message processors, hand-held devices, multi-processor systems, microprocessor-based or programmable consumer electronics, network PCs, minicomputers, mainframe computers, mobile telephones, PDAs, pagers, routers, switches, datacenters, wearables, such as glasses, and the like. The invention may also be practiced in distributed system environments where local and remote computing system, which are linked, for example, either by hardwired data links, wireless data links, or by a combination of hardwired and wireless data links, through a network, both perform tasks. In a distributed system environment, program modules may be located in both local and remote memory storage devices.

[0223] Those skilled in the art will also appreciate that at least parts of the invention may be practiced in a cloud computing environment. Cloud computing environments may be distributed, although this is not required. When distributed, cloud computing environments may be distributed internationally within an organization and / or have components possessed across multiple organizations. In this description and the following claims, “cloud computing” is defined as a model for enabling on-demand network access to a shared pool of configurable computing resources, e.g., networks, servers, storage, applications, and services. The definition of “cloud computing” is not limited to any of the other numerous advantages that can be obtained from such a model when deployed. The computing systems of the figures include various components or functional blocks that may implement the various embodiments disclosed herein as explained. The various components or functional blocks may be implemented on a local computing system or may be implemented on a distributed computing system that includes elements resident in the cloud or that implement aspects of cloud computing. The various components or functional blocks may be implemented as software, hardware, or a combination of software and hardware. The computing systems shown in the figures may include more or less than the components illustrated in the figures and some of the components may be combined as circumstances warrant.

[0224] In the claims, the word "comprising" does not exclude other elements or steps, and the indefinite article "a" or "an" does not exclude a plurality. A single unit or device may fulfil the functions of several items recited in the claims. The mere fact that certain measures are recited in mutually different dependent claims does not indicate that a combination of these measures cannot be used to advantage.

[0225] Any reference signs in the claims should not be construed as limiting the scope.

Claims

CLAIMS1. Computer implemented method (100) for controlling operation of a belt dryer assembly (500) for carrying out a drying process of a superabsorbent material cake (502) that results in an output material (512), the method comprising:- ascertaining (102) a belt dryer model (M) indicative of a respective effect of drying process parameters (PP1, PP2) associated to the belt dryer assembly on physical and / or chemical properties (P1, P2) of the superabsorbent material cake;- ascertaining (104) input material data (518) indicative of respective values (PV) of one or more of the physical and / or chemical properties (P1, P2) of the superabsorbent material cake to be provided to the belt dryer assembly (500);- using the belt dryer model and the ascertained input material data, determining and providing (106a) control instructions (Cla) for controlling operation of the belt dryer assembly for driving the values (PV) of the physical and / or chemical properties (P1, P2) of the output material towards a set of expected values of the physical and / or chemical properties (P1*p2*)2. The method (100) of claim 1, further comprising:- using the belt dryer model and the ascertained input material data, determining and providing (106b) control instructions (Clb) for controlling operation of a pre-processing unit (522) for processing and feeding the superabsorbent material cake to the belt dryer assembly, for driving the values of the physical and / or chemical properties of the output material towards the set of expected values of the physical and / or chemical properties.

3. The method (100) of claim 1 or 2, further comprising: using the belt dryer model and the received input material data, determining and providing (106c) control instructions (Clc) for controlling operation of a post-processing unit (523) for further processing the output material for driving the values of the physical and / or chemical properties of the output material towards the set of expected values of the physical and / or chemical properties.

4. The method of any of the preceding claims, wherein the step of determining and providing (106a, 106b, 106c) control instructions is performed using a machine learning model that has been trained using training data sets that represent a plurality of dryingprocesses performed on superabsorbent material cakes having corresponding physical and / or chemical properties that result in output material having corresponding physical and / or chemical properties.

5. The method of any of the preceding claims, further comprising:- determining (103), the respective values of the physical and / or chemical properties of the input material.

6. The method (100) of any of the preceding claims, wherein the input material data indicative of the values of the physical and / or chemical properties of input material include one or more of chemical composition data indicative of a chemical composition of the input material, moisture data indicative of a moisture content of the input material, particle size data indicative of a particle size distribution of the input material and cake geometry data indicative of spatial dimensions of the superabsorbent material cake.

7. The method (100) of any of the preceding claims, wherein- the control instructions (Cla) for controlling operation of the belt dryer assembly are control instructions for controlling one or more of a gas inlet temperature value of a drying gas, a gas flow rate value of the drying gas, a belt dryer speed value of a belt, a fresh air inlet or an exhaust air outlet; and / or- the control instructions (Clb) for controlling operation of the pre-processing are control instructions for controlling one or more of an extruder unit, a polymerization unit, a gel bunker, or a superabsorbent material cake feeder unit for providing a desired distribution (e.g. height and homogeneity over width) of the superabsorbent material cake at an input of the belt; and / or- the control instructions (Clc) for controlling operation of post-processing unit are control instructions for controlling a milling unit for milling the dried superabsorbent material cake.

8. The method of any of the preceding claims, wherein the belt dryer assembly comprises a plurality of drying zones (Z1-ZN) along a drying route (514), and wherein the method includes determining and providing respective control instructions (CI1-CIN) for controlling the different drying zones along the drying route.

9. The method of any of the preceding claim, wherein the belt dryer model comprises a gas-phase model including balance equations and constitutive equations for a gas phase, a solid phase model including balance equations and constitutive equations for a solid phase, an exchange flow model including heat exchange equations and mass exchange equations and a gas-solid interface model.

10. The method of any of the preceding claims, wherein, in the belt dryer model, the superabsorbent material cake is modelled as a discretized cake comprising, in particular per drying zone, one or more cake elements (EI1-EIN) in a horizontal direction and one or more layers of cake elements (Lay1-LayM) in a vertical direction, and wherein each cake element is associated to a size class (k) indicative of the mean particle size in said cake element.

11. A belt dryer assembly (500) for carrying out a drying process of a superabsorbent material cake (502), the belt drying assembly comprising:- a belt dryer (504) having an input unit (506) for receiving a superabsorbent material cake (502) to be dried and comprising a belt (508) configured to transport the superabsorbent material cake (502) from the input unit (506) to an output unit (510) for providing a dried superabsorbent material cake (512) as output material (512);- wherein the belt dryer (504) comprises one or more drying zones (Z1-ZN) along a drying route (514) of the belt dryer (504), each drying zone comprising a respective drying unit (515, 515a, 515b) configured to provide a drying gas (DG);- a controller unit (516) configured:-to ascertain a belt dryer model (M) indicative of a respective effect of drying process parameters (PP1, PP2) associated to the belt dryer assembly on physical and / or chemical properties (P1, P2) of the superabsorbent material cake (502);- to ascertain input material data (518) indicative of respective values of one or more of the physical and / or chemical properties (PV) of the superabsorbent material cake (502) to be provided to the belt dryer assembly (500); and- using the belt dryer model and the ascertained input material data, to determine and provide control instructions (Cla) for controlling operation of the belt dryer assembly,in particular of the belt (508) and / or the drying units (515a, 515b), for driving the values of the physical and / or chemical properties of the output material (512) towards a set of expected values of the physical and / or chemical properties (P1*, P2*).

12. The belt dryer assembly of claim 11, wherein the controller unit is configured to implement a machine learning model that has been trained using training data sets that represent a plurality of drying processes performed on superabsorbent material cakes having corresponding physical and / or chemical properties that result in output material having corresponding physical and / or chemical properties.

13. The belt dryer assembly (500) of any of the preceding claims 11 to 13 or 10 further comprising a parameter determination unit (520) configured to determine the respective values of physical and / or chemical properties (PV) of the superabsorbent material cake (502) and to generate and provide, to the controller unit (516), the input material data (518) indicative thereof.

14. The belt dryer assembly (500) of any of the preceding claims 11 to 13, further comprising:- a pre-processing unit (522) for processing and feeding the superabsorbent material cake to the belt dryer (504), and wherein the controller unit (516) is further configured to determine and provide control instructions (Clb) for controlling operation of the pre-processing unit (522) for driving the values of the physical and / or chemical properties of subsequent output material towards the set of expected values of the physical and / or chemical properties (P1*, P2*); and / or- a post-processing unit for further processing the output material, and wherein the controller unit (516) is further configured to determine and provide control instructions (Clc) for controlling operation of the post-processing unit fordriving the values of the physical and / or chemical properties of the output material towards the set of expected values of the physical and / or chemical properties.

15. Computer program comprising instructions that, when executed by a controller unit of a belt dryer assembly, cause the belt dryer assembly to carry out the method of any of the claims 1 to 10.

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