DE102020000464A1 - Method for modeling and operating a process engineering device - Google Patents

Abstract

The present invention relates to a method for modeling and operating a procedural device, with a computer-implemented model of the procedural device being generated (200) as a function of theoretical and / or empirical background data, by means of which a stationary and / or dynamic simulation of the procedural device can be carried out wherein, in the course of a design phase (210) using the model, a design of the technical device is carried out, and in the course of an operating phase (220) the procedural device is operated using the model.

Description

The invention relates to a method for modeling and operating a process engineering device.

State of the art

Process engineering devices are understood to mean apparatus or systems for carrying out changes in substances and / or conversions of substances with the aid of purposeful physical and / or chemical and / or biological and / or nuclear activity processes. For example, process engineering devices can be a process engineering plant such as an air separation plant or, in general, a plant for separating mixtures of substances based on physical properties, or also components that are used in such a plant, for example heat exchangers, columns, containers for phase separation, etc.

In the course of a design phase, a process engineering device of this type can first be designed before the device is designed or set up in accordance with the corresponding selected design at a corresponding location and is finally put into operation. In the course of this design, design parameters of the device can be selected, for example the type and dimensions of individual elements and components of the process engineering device or the specific type of various components. Furthermore, in the course of the design phase, production planning can be carried out, in the course of which a plant timetable is created, according to which the process engineering device is ultimately operated. Process parameters such as educt requirements, production quantities, etc. can be specified in this plant schedule.

Disclosure of the invention

According to the invention, a method for modeling and operating a process engineering device as well as a computing unit and a computer program for its implementation are proposed with the features of the independent claims. Advantageous configurations are the subject of the subclaims and the description below.

Depending on theoretical and / or empirical background data, a computer-implemented model of the process engineering device is generated, by means of which a stationary and / or dynamic simulation of the process engineering device can be carried out. In the course of a design phase, the technical device is designed depending on the model. In the course of an operating phase, the process engineering device is operated using the model, particularly expediently with the support of information and / or data generated by the model that are usually not available in the process control system.

In this context, the design phase is to be understood in particular as a planning or plant construction phase, during which the process engineering device is planned, dimensioned, constructed or erected from the ground up and finally put into operation at a corresponding location. The operating phase is to be understood in particular as the period of time during which the process engineering device is actively operated. In this context, the design phase and the operating phase characterize the entire life cycle of the process engineering device, in particular the period from the first theoretical planning to the final shutdown after typically up to several decades.

In the course of the design phase, the model is expediently used to design the process engineering device and in particular to determine design parameters, such as the type and dimensions of individual components or the specific type of individual components. Furthermore, the model is used in the course of the design phase, in particular, to carry out production planning and to expediently create a plant timetable according to which the process engineering device is ultimately to be operated. In particular, process parameters, such as educt requirement, production quantities, etc., are determined, in particular, while observing certain boundary conditions, such as energy costs, service life consumption, etc.

In the course of the operating phase, the model is expediently used in order to monitor the corresponding procedural process and to be able to carry it out as best as possible. For example, with the aid of the model, an optimized operation of the device can be simulated and specified as a target state, with which the process actually carried out can be compared as the actual state. Furthermore, the system schedule can also be changed during the operating phase. In particular, process parameters such as educt requirement, production quantities, etc. can be adapted in order to optimize the operation of the device.

Background data in the present context are, in particular, data understand which existing process engineering devices characterize theoretically and / or empirically. The background data can for example have been collected during the design and / or operation of one or more further procedural devices which are structurally identical or identical or at least similar and comparable to the current procedural device to be designed and operated. In particular, the background data thus represent empirical values for the design and operation of the process engineering device. The model is therefore initially appropriately estimated based on empirical values and gradually adjusted over the course of the various phases and refined and improved with the aid of current data.

In the context of the present method, a theoretical computer-implemented model of the process engineering device is thus provided, which can be used consistently throughout the entire life cycle of the process engineering device during different phases. In the course of these different phases, the model can be used in particular for different purposes and in each case to achieve different, phase-specific goals.

In the conventional way, it is mostly not possible to use a single model over the entire life cycle of a process engineering device. Different work steps during different phases of the life cycle are often carried out by different parties, e.g. by different companies, specialist departments, operators, etc. For example, different parties may be responsible for planning, designing and building the device than for later operation. Furthermore, the operator can also change during the operating phase if the device is sold to another operator, for example. Conventionally, each party usually creates and uses its own model tailored to the respective needs and requirements, since the different parties usually have different requirements for the accuracy or the computing time of the respective models. In the course of the life cycle of a process engineering device, a large number of different models are often developed, which are mostly not compatible with one another and cannot be used consistently. Although information is mostly communicated in the form of data between individual work steps between the respective responsible parties, models are usually always adapted and implemented anew to the task specific to the problem.

A particularly serious break usually occurs when changing from the design phase to the operating phase, with dynamic, in particular thermodynamic and hydrodynamic overall models of the device being used in the design phase, whereas completely different models are used during the operating phase, such as linear, data-driven models Models based on operational data. In addition, the requirements for the operation of the device can also change during the operating phase, for example when the device is converted or expanded. After such a conversion, a new model is often created if, for example, the accuracy and depth of detail of the previous model no longer meet the new requirements.

The present method now provides the possibility of a consistent use of the model over the entire life cycle of the process engineering device. One and the same model can expediently be used consistently as a digital twin of the process engineering device in different phases and work steps during the entire life cycle. Labor and costs for the creation of new models during the life cycle can thus be saved. The present model equally satisfies different requirements and needs during different work steps and phases of the life cycle, especially with regard to accuracy and computing time. The model can easily be adapted to different requirements.

In particular, the model can be generated at the beginning or before the start of the design phase, expediently in the course of the first theoretical planning of the process engineering device, and can then be flexibly adapted, varied and expanded to new circumstances and new requirements during the entire life cycle. For example, the model can be flexibly compared at any time with current data, for example with the results of a detailed calculation of process engineering components or parts or current operating data, and expediently continuously improved.

The present method enables significant improvements both for the construction or the design as well as the operation of process engineering devices. In particular, improved design methods or improved tools for design can be provided. Furthermore, a consistency of the design methods with operating data can be made possible.

An integration of engineering workflows through the use of a common model or common model interfaces is made possible. In particular, an improved integration between process design and process dynamics and also between process dynamics and the design of machine protection systems is made possible.

Furthermore, the operation of the process engineering device can be improved, for example, by predicting and reducing the service life consumption, by increasing the system efficiency, by supporting a load control ("Demand Side Management", DSM), that is to say controlling the demand for network-based services through use of non-linear model predictive control (NMPC) and the development of further control algorithms.

With the consistent use of a model over the entire life cycle of the process engineering device, the following advantages can also be achieved: The operation of the process engineering device can be supported by model data, which optimizes operating parameters and reduces production bottlenecks or increases production capacity (so-called . "Debottlenecking") allowed. Furthermore, model-based control algorithms and parameter estimation of non-measured variables are made possible. Furthermore, an adaptation of design methods to real system data is expediently made possible, in particular an adaptation of empirical correlations. In particular, a self-learning model is provided which can adapt parameters to operating data.

Furthermore, the use of a digital twin considerably facilitates the transfer of knowledge of parameters and measured values between design and operation. Design data can be used in operation and vice versa. The design can be accelerated through integrated, automatable workflows. Consistent data management and the avoidance of redundancy are made possible.

The model is advantageously generated composed of several partial models, which each characterize at least one component of the technical device. Individual sub-models can each describe individual components, for example. As an alternative or in addition, several components can also be combined to form a common partial model. The operation of the respective components can expediently be simulated stationary and / or dynamically by means of the partial models. The model is therefore expediently modular or composed of a large number of partial models according to the building block principle.

The use of such partial models increases the flexibility of the model and makes it possible to adapt and expand the model in a simple manner during the entire life cycle of the device. The model and in particular its sub-models can be varied flexibly in the course of the design phase and, in particular, adapted to the system actually built. Furthermore, the model or its sub-models can be flexibly adapted during the operating phase, e.g. if operating scenarios of individual components are changed or if, for example, individual components are replaced.

Different partial models can be generated, for example, each with a different level of detail, depending on the specific requirements. Furthermore, individual partial models can be exchanged, for example with newly created partial models with an improved level of detail. It is therefore not necessary to create a completely new model in the course of the life cycle of the device, for example when design changes are made to the device. Instead, individual sub-models can be changed or exchanged in a simple manner.

Different versions, which characterize the respective at least one component in different ways, are preferably generated for individual partial models. The different versions of a partial model expediently each characterize different operating scenarios of the respective at least one component. It is also conceivable that the different versions of a partial model characterize the respective at least one component with different degrees of detail. The versions of the individual partial models used in the model can expediently be exchanged for a different version. The different versions of the partial models can be stored in a library for practical purposes. This library thus includes, in particular, different versions of basic procedural operations of the device, expediently in different model depths or in different degrees of detail. The use of such different versions of the partial models further increases the flexibility of the model. Individual sub-models can thus be exchanged flexibly and easily with predefined alternative versions.

According to a preferred embodiment, the individual sub-models are independent editable from each other. Each individual partial model can thus be edited and adapted individually. The individual sub-models are preferably interchangeable. Each partial model can thus be exchanged individually if necessary, expediently for a different version of the respective partial model that is stored in the library. The individual partial models can preferably be put together by means of a uniform interface. This interface makes it possible in a simple manner to assemble the model in a modular manner from a large number of individual sub-models.

The model, furthermore in particular the individual partial models, is generated as a rigorous model and / or as a reduced model and / or as a gray box model and / or as a black box model. These different model types are characterized by different levels of detail. Different partial models or different versions of partial models can therefore expediently be generated according to one of these model types depending on the accuracy requirements. Through the appropriate combination of these model types, a wide range of applications (in particular over the entire life cycle) for the simulation of the process engineering device can be represented with a uniform model platform.

Rigorous models represent a technical mechanism with exact scientific methodology. The procedural process carried out in the device or in components of the device is simulated by simulating all processes and reactions with characteristic curves, differential equations and balance equations.

A reduced model represents a simplification of a rigorous model in which partial aspects of the modeling are described or omitted by a simpler mathematical formulation. Negligible terms in the description of the procedural process are expediently not taken into account. A simpler mathematical formulation can also be obtained through measurement data and / or system data (data-driven approach).

A gray box model represents a combination of a theoretical description and the use of actually recorded data (data-driven approach). For example, a gray box model can at least partially simulate the device or its components theoretically and unknown parts using substitute models supplement from recorded data or directly using data sets.

Models that only consider external behavior, but not internal structure, are referred to as “black boxes”. A black box model mostly describes the relationship between input and output and is expediently used to describe unknown relationships or procedural operations that are difficult to describe mathematically.

A black box model is preferably generated in relation to one or more of the following factors, in particular in order to simulate corresponding unknown relationships in the process engineering device: a difference between a planned and an actual execution of a component of the process engineering device; a difference between a planned and an actual operation of the process engineering device, in particular a plant operation beyond model assumptions or design points, e.g. due to incorrect planning of the product requirement; an influence of environmental conditions; an influence of a peripheral system, in particular not precisely modeled; a malfunction of a component of the process engineering device; a change in the behavior of a component of the process engineering device due to aging effects, in particular wear and soiling; a particularly complex thermodynamic process in a component of the process engineering device.

According to an advantageous embodiment, the background data include data or design data that were collected in the course of at least one further design phase of a further process engineering device. These design data describe, in particular, prior knowledge from design methods already carried out in the past.

As an alternative or in addition, the background data preferably include data or model data that were collected with the aid of at least one further model of a further process engineering device. In particular, this model data can have been collected using empirical data-driven models.

As an alternative or in addition, the background data preferably include data or operating data that were collected in the course of the operating phase of at least one further procedural device. Background data of this type are therefore expediently empirical operating data that have been collected with the aid of already existing process engineering devices.

The background data therefore expediently include empirical and theoretical data that were collected during the design and operating phase of further process engineering devices, which in particular are structurally identical or at least comparable to the device currently to be designed.

A regulation and / or control of the procedural device is advantageously carried out in the course of the operating phase using the model. With the aid of the model, in particular an optimized operation of the device can be simulated in order to determine optimized setpoint values for the actual operation.

Alternatively or additionally, a model predictive control (MPC) of the process engineering device is preferably carried out in the course of the operating phase using the model. The time-discrete, dynamic model is used for such an MPC in order to calculate the future behavior of the procedural process to be regulated in the device as a function of input signals. This expediently enables the calculation of optimal input signals, which lead to optimal output signals. The term “optimal” refers in particular to the optimality of all free process parameters while maintaining all boundary conditions to minimize all necessary operating resources.

Alternatively or additionally, planning and / or monitoring and / or optimization of the operation of the process engineering device are preferably carried out in the course of the operating phase using the model. In the course of monitoring, for example, alarm or error messages can be generated. In the course of the planning, in particular a system schedule, process and operating parameters can be specified. In the course of the optimization, these process or operating parameters as well as the plant schedule can be appropriately adapted and optimized.

As an alternative or in addition, in the course of the operating phase, the model is advantageously used to determine the remaining service life or the service life consumption of the process engineering device. With the aid of the model, it is therefore expedient to monitor the service life (“health monitoring”) online while the device is in operation.

Alternatively or additionally, a hardware-in-the-loop simulation (HIL) and / or an operator training simulation (OTS) of the process engineering device are preferably carried out in the course of the operating phase using the model.

In such an HIL simulation, an embedded system of the device, for example a control unit, is connected via its inputs and outputs to the HIL simulation, which is used to simulate the real environment of the system. Control algorithms for the operation of the process engineering device can expediently be determined by means of such HIL simulations.

By means of such an OTS, the process engineering device is simulated by means of dynamic simulation and, furthermore, in particular a control system of the device is emulated. With the help of this OTS, operating personnel can be trained in handling the process engineering device, expediently without disrupting the operation of a real plant. For example, new operating personnel can be trained and current operating personnel can complete refresher training. Furthermore, new control strategies and control algorithms can be developed and tested.

Alternatively or additionally, using the model, data mining is preferably carried out on data that are collected during the operation of the process engineering device. In the course of such data mining, the collected data are examined using statistical methods, in particular in order to be able to identify new, previously unknown relationships, trends or cross-connections.

The process engineering device is advantageously a process engineering system or at least one component of a process engineering system. In this context, a process engineering device is to be understood as meaning in particular a unit or a system of different units for carrying out a process engineering process, furthermore in particular an apparatus or a system for carrying out substance changes and / or substance conversions with the aid of appropriate physical and / or chemical and / or biological and / or nuclear action processes. Such changes and conversions typically include grinding, sieving, mixing, heat transferring, rectifying, crystallizing, drying, cooling, filling and superimposed material conversions such as chemical, biological or nuclear reactions.

The process engineering device is advantageously a process engineering system, in particular for separating and / or liquefying gases, for example a Air separation plant or, in general, a plant for separating mixtures of substances based on physical properties, a natural gas plant, a hydrogen and synthesis gas plant, an adsorption and membrane plant, e.g. a pressure swing adsorption plant, or a cryotechnical plant, e.g. for cooling superconductors and cold neutron sources, MRIs, fusion and fission applications or in the liquefaction of helium and hydrogen.

Furthermore, the process engineering device can expediently be a component that is used in such a system, furthermore in particular a process engineering apparatus through which a fluid flows. The process engineering device is advantageously a heat exchanger, e.g. a plate heat exchanger or a spiral-wound heat exchanger, or a column (hollow column with internals) or a phase separation apparatus or container for phase separation (container with internals).

According to a particularly advantageous embodiment, a digital twin of an air separation plant is generated as the model as part of the method. With the help of the model, the entire operating range of the air separation plant can be covered. The key component of the model is, in particular, a model or partial model of a double column of the air separation plant. The model is expediently created using a modular system for creating dynamic, pressure-driven, modular-hierarchical simulation models that cover the entire operating range for distillation columns. The accuracy of the column models is expediently adaptive. Furthermore, the modular system also allows the creation of gray box column models in such a way that thermodynamic and phenomenological components can be learned, while fundamental quantum mechanical relationships (in the course of so-called "first principle" models) are used for fluid-mechanical components.

A computing unit according to the invention is set up, in particular in terms of programming, to carry out a method according to the invention.

The implementation of the invention in the form of software is also advantageous, since this enables particularly low costs, in particular if an executing computing unit is also used for other tasks and is therefore available anyway. Suitable data carriers for providing the computer program are, in particular, magnetic, electrical and optical data carriers such as hard drives, flash memories, EEPROMs, DVDs, etc. A program can also be downloaded via computer networks (Internet, intranet, etc.).

Further advantages and embodiments of the invention emerge from the description and the accompanying drawing.

It goes without saying that the features mentioned above and those yet to be explained below can be used not only in the respectively specified combination, but also in other combinations or on their own, without departing from the scope of the present invention.

The invention is shown schematically in the drawing using exemplary embodiments and is described in detail below with reference to the drawing.

Figure list

• 1 shows schematically a process engineering device which can be modeled and operated in the course of a preferred embodiment of a method according to the invention.
• 2 shows schematically a preferred embodiment of a method according to the invention as a block diagram.

Detailed description of the drawing

In 1 a process engineering device in the form of an air separation plant is shown schematically, which can be modeled and operated in the course of a preferred embodiment of a method according to the invention.

The air separation plant has, among other things, a main air compressor 1 , a pre-cooling device 2 , a cleaning system 3 , a booster assembly 4th , a main heat exchanger 5 , an expansion turbine 6th , a throttle device 7th , a pump 8th and a distillation column system 10 . The distillation column system 10 comprises in the example shown a classic double column arrangement from a high pressure column 11 and a low pressure column 12th as well as a raw argon column 13th and a pure argon column 14th .

In the air separation plant, a feed air flow is generated by means of the main air compressor in the course of air separation 1 Sucked in and compressed via an unmarked filter element. The compressed feed air flow is the pre-cooling device operated with cooling water 2 fed. The pre-cooled feed air flow is in the cleaning system 3 purified. In the cleaning system 3 , which typically comprises a pair of adsorber vessels used in alternating operation, the precooled feed air stream is largely freed from water and carbon dioxide.

Downstream of the cleaning system 3 the feed air flow is divided into two partial flows. One of the partial flows is at the pressure level of the feed air flow in the main heat exchanger 5 completely cooled. The other partial flow is in the booster arrangement 4th recompressed and also in the main heat exchanger 5 cooled, but only to an intermediate temperature level. A part of this flow, the so-called turbine flow, is generated after cooling to the intermediate temperature level by means of the expansion turbine 6th relaxed to the pressure level of the completely cooled substream, combined with this, and into the high-pressure column 11 fed in.

In the high pressure column 11 an oxygen-enriched liquid bottom fraction and a nitrogen-enriched gaseous top fraction are formed. The oxygen-enriched liquid bottom fraction is extracted from the high pressure column 11 withdrawn, partly as a heating medium in a bottom evaporator of the pure argon column 14th used and each in defined proportions in a top condenser of the pure argon column 14th , a top condenser of the crude argon column 13th as well as the low pressure column 12th fed in. In the evaporation chambers of the top condensers of the crude argon column 13th and the pure argon column 14th Evaporating fluid is also in the low pressure column 12th convicted.

From the top of the high pressure column 11 the gaseous nitrogen-rich overhead product is drawn off in a main condenser, which is a heat-exchanging connection between the high-pressure column 11 and the low pressure column 12th produces, liquefies, and in parts as a return to the high pressure column 11 abandoned and in the low pressure column 12th relaxed.

In the low pressure column 12th an oxygen-rich liquid bottom fraction and a nitrogen-rich gaseous top fraction are formed. The former is partly in the pump 8th liquid pressurized in the main heat exchanger 5 heated, and made available as a product. From a liquid retention device at the top of the low-pressure column 12th a liquid nitrogen-rich stream will be withdrawn and exported as a liquid nitrogen product from the air separation plant. One from the head of the low pressure column 12th withdrawn gaseous nitrogen-rich stream is passed through the main heat exchanger 5 out and as nitrogen product on the pressure of the low pressure column 12th provided. From the low pressure column 12th a current is also drawn from an upper area and, after heating, in the main heat exchanger 5 as so-called impure nitrogen in the pre-cooling device 2 or after heating by means of an electrical heater in the cleaning system 3 used.

Overall, the column or the low pressure column 12th In the course of the air separation, air (AIR) is supplied and at least oxygen and nitrogen are withdrawn in gaseous form (GOX, GAN) and / or liquid (LOX, LIN). Furthermore, impure nitrogen (UN2) is usually removed and, if desired, noble gases such as argon etc.

In 2 a preferred embodiment of a method according to the invention is shown schematically as a block diagram, in the course of which in the present example an air separation plant as shown in FIG 1 is represented, modeled and operated.

In the context of the present procedure, step 200 generates a computer-implemented model of the air separation plant that can be used consistently over the entire life cycle in different phases of the air separation plant. The life cycle of the air separation plant refers in particular to the period from the first theoretical planning to the final shutdown of the plant after up to several decades and in particular includes a design phase 210 and an operational phase 220 .

The computer-implemented model is generated as a function of theoretical and / or empirical background data, for example design data that was collected in the course of at least one further design phase of a further process engineering device, of model data that was collected with the help of at least one further model of a further process engineering apparatus , and of operating data that were collected in the course of the operating phase of at least one further procedural device.

The model is generated in a modular manner and composed of a large number of sub-models, with individual sub-models representing one or more of the components of the air separation plant. The individual partial models can be edited and exchanged independently of one another and flexibly added to or removed from the model using a uniform interface.

The model can be flexibly expanded and adapted. Individual partial models can each be exchanged for a different version which, for example, can be more or less detailed than the version of the respective partial model currently used in the model or which, for example, describes a different operating scenario. The model can thus be flexibly adapted to during the entire life cycle of the air separation plant, for example to structural changes to the air separation plant or to new requirements with regard to the level of detail of the model.

In the course of the design phase 210 a design of the air separation plant is carried out using the model. For example, a suitable design for everyone in 1 components shown (the main air compressor 1 , the booster assembly 4th , the main heat exchanger 5 , the rectification system 11 + 12, ...) can be found, in particular which special type and which special series of these components is to be used. Furthermore, a plant schedule is to be created according to which oxygen, nitrogen and / or argon in gaseous and / or liquid form are to be produced as products in the air separation plant.

First, in step 211 carried out an offer phase, whereby cost models are used to determine the dimensions of the air separation plant and its components and a first rough thermodynamic design. The model of the air separation plant or its partial models are created according to the accuracy requirements of the offer phase. These can already be rigorous models for rectification columns, for example, or simple (linear / non-linear) regressions can also be used.

In step 212 an order phase is carried out. In the course of this, the in step 211 Generated thermodynamic rough design is refined and rigorous thermodynamic models or partial models with detailed model depth are generated. Furthermore, the hydrodynamics of individual components is calculated and a hydrodynamic design is carried out. The model is expanded to include rigorous, very detailed hydrodynamic partial models. Furthermore, a dimensioning of the equipment is carried out on the basis of the thermodynamic partial models.

In step 213 an operating concept is determined, with dynamic simulations of the air separation plant being carried out. Dynamic sub-models are generated based on the hydrodynamic design. The model is thus expanded to include rigorous, very detailed dynamic sub-models. In this step 213 the model is expanded to a complete model of the air separation plant, as it is ultimately to be built. Furthermore, a basic regulation of the air separation plant is developed and included in the model and important or safety-critical operating scenarios are calculated. The component design is optimized based on the findings of the dynamic simulations. The model is thus expanded to include a dynamic component design, which is rigorous and very detailed. The feedback from operational studies to the design decision for components can improve the overall design of a system, lower operating costs and / or increase the operating range of a system.

After the air separation plant is in the design phase 210 is designed and then constructed or erected at an appropriate location according to this selected layout, the system is in the operating phase 220 operated using the model.

This takes place in step 221 first a commissioning, whereby an extended control concept with (non) linear model predictive control is determined. The basis for the implementation and / or evaluation of such control strategies is the evaluation of the behavior of the overall system model. Troubleshooting and verification of the measurement technology are also carried out. The model or individual sub-models can be exchanged for other versions, which can be specified as replacement models with a coarse or detailed model depth.

In step 222 the regular operation of the air separation plant takes place, with the help of the model a detailed operational planning of individual plants or plant groups as well as an operational optimization can be carried out. Furthermore, individual components can be monitored and service life consumption can be monitored (“health monitoring”). For the model you can use this step 222 individual partial models with coarse to detailed model depth in the form of black box and / or gray box models can be used.

In step 223 After-sales management or sales follow-up management takes place, in the course of which conversions or expansions of the air separation plant and training of operating personnel can be carried out. For such training, an “Operator Training Simulation” (OTS) is carried out using the model, based on very detailed substitute models that can be developed on the basis of the model information obtained from the previous process steps. For conversions or extensions, the level of detail is adjusted by replacing partial models based on the corresponding task.

Claims (13)

Method for modeling and operating a process engineering device, depending on theoretical and / or empirical background data, a computer-implemented model of the process engineering device is generated (200), by means of which a stationary and / or dynamic simulation of the process engineering device can be carried out, in the course of a design phase (210) using the model a Design of the technical device is carried out and the procedural device is operated using the model in the course of an operating phase (220). Procedure according to Claim 1 , wherein the model is generated composed of several partial models, which each characterize at least one component of the technical device. Procedure according to Claim 2 , whereby different versions are generated for individual partial models, which characterize the respective at least one component in different ways. Procedure according to Claim 2 or 3 , whereby the individual partial models can be edited independently of one another, are interchangeable and can be put together by means of a uniform interface. Method according to one of the preceding claims, wherein the model is generated as a rigorous model and / or as a reduced model and / or as a gray box model and / or as a black box model. Procedure according to Claim 5 wherein a black box model is generated in relation to one or more of the following factors: a difference between a planned and an actual execution of a component of the process engineering device; a difference between planned and actual operation of the procedural device; an influence of environmental conditions; an influence of a peripheral system; a malfunction of a component of the process engineering device; a change in the behavior of a component of the process engineering device due to aging effects; a thermodynamic process in a component of the process engineering device. Method according to one of the preceding claims, wherein the background data comprises one or more of the following data: Data that were collected in the course of at least one further design phase of a further process engineering device; Data that have been collected with the aid of at least one further model of a further process engineering device; Data that were collected in the course of the operating phase of at least one further procedural device. Method according to one of the preceding claims, wherein one or more of the following functions are carried out in the course of the operating phase using the model: a regulation of the process engineering device; a control of the process engineering device; a model predictive control of the process engineering device; planning the operation of the process engineering device; a monitoring of the operation of the process engineering device; an optimization of the operation of the process engineering device; a determination of the remaining life of the process engineering device; a hardware-in-the-loop simulation of the process engineering device; an operator training simulation of the process engineering device; data mining of data collected during operation of the process engineering device. Method according to one of the preceding claims, wherein the process engineering device is a process engineering system or at least one component of a process engineering system. procieedings Claim 9 , the process engineering device being a process engineering apparatus through which fluid flows, in particular a heat exchanger or a column or a container for phase separation, or a process engineering plant, in particular for separating and / or liquefying gases. Computing unit which is set up to carry out all method steps of a method according to one of the preceding claims. Computer program that causes a processing unit to perform all method steps of a method according to one of the Claims 1 until 10 to be carried out when it is executed on the processing unit. Machine-readable storage medium with a computer program stored thereon Claim 12 .

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