Abstract: A steel volume is modeled in a computer by means of a plurality of volume elements. The state of the steel volume at a given time comprises, for each volume element, characteristic quantities of an enthalpy existing at said time in the respective volume element and percentages, in which the steel is available in the respective volume element at the time in austenite, ferrite and cementite phases. For at least one volume element, the computer determines the time gradient of the characteristic quantities by resolving thermal conductivity and phase transition equations. One of the characteristic quantities is a locally invariable mean interstitial element concentration within the volume element in the austenite phase thereof.

Abstract: The invention relates to a method for controlling and regulating the temperature of a metal strip in a finishing train of a hot rolling mill. A target function is formed by comparing a desired temperature gradient with an actual temperature gradient. The target function measures deviations from desired indications positioned in various places on the finishing train. The speed of the strip and the flow of the cooling agent are adjusted by predicting with the aid of a method of non-linear optimization with auxiliary conditions and are regulated and controlled online by solving a quadratic optimization problem with linear auxiliary conditions, preferably with the aid of an active set strategy.

Abstract: According to a method, initial temperatures (T1) of strip points (101) are detected when the hot-rolled strip (6) is fed to the production line. The strip points (101) are monitored on their way through the production line. The hot-rolled strip (6) is subjected to temperature influences (delta T) in the production line (3). The strip points (101), the initial temperatures (T1), the monitored values (W(t)) and the temperature influences (delta T) are supplied to a model (9) for the production line (3). The model (9) determines expected actual temperatures (T2) of the strip points (101) in real time and allocates them to the strip points as the new actual temperatures (T2).

Abstract: The invention relates to a method for controlling and regulating the temperature of a metal strip in a finishing train of a hot rolling mill. A target function is formed by comparing a desired temperature gradient with an actual temperature gradient. The target function measures deviations from desired indications positioned in various places on the finishing train. The speed of the strip and the flow of the cooling agent are adjusted by predicting with the aid of a method of non-linear optimization with auxiliary conditions and are regulated and controlled online by solving a quadratic optimization problem with linear auxiliary conditions, preferably with the aid of an active set strategy.

Abstract: According to a method initial temperatures (T1) of strip points (101) are detected when the hot-rolled strip (6) is fed to the production line at the latest. The strip points (101) are monitored on their way through the production line. The hot-rolled strip (6) is subjected to temperature influences (delta T) in the production line (3). The strip points (101), the initial temperatures (T1), the monitored values (W(t)) and the temperature influences (delta T) are supplied to a model (9) for the production line (3). The model (9) determines expected actual temperatures (T2) of the strip points (101) in real time and allocates them to the strip points as the new actual temperatures (T2).

Abstract: A method and a device are provided for calculating in advance the process variables of an industrial process. The method, which consists of at least one empirical model and a core model, is subsequently adapted and optimized using a model that has a partial inverse structure in relation to the core model. The empirical models are optimized by means of adaption or training algorithms, which, in addition to known process parameters, have the empirical variables calculated by the partial inverse core model as basic input variables.