【正文】 nd tempera tures at various point, sometime, phase transformation could shift outside the controlled area, which could cause serious quality problem, such as ?nal microstructure to be martensite or coarsen pearlite. Workers can do nothing only after ?nal checking. After installation of the model, workers can directly observe the production process from userfriendly interface of the model, adjust the opening volume of various fans according to requirement, control the temperatures at various points in the reasonable range, and make phase transformation occur in the exact area. According to statistics from this production line, rate of ?nal steel product with ?ne pearlite with grade or below has been increased from % to % due to installation of the CSSC model, at the same time, cases of quality argument has greatly reduced to give users enough con?dence in its ?nal product. 4. Conclusions An unique online quality prediction system for the Stelmor controlled cooling line was developed, following conclusions can be obtained based on the working experience: 1. The prehensive model the for Stelmor controlled cooling line consists three parts: the thermal model is obtained by FDTD method, phase change model is obtained by solving Avrami equation based on the experimental CCT data, and mechanical property model is physical model based on regressing the production data, three parts are coupled internally. 2. This online model is open to get the production information during production, which can municate with the material ?ow management system and Program Logic Control System (PLCs) automatically through local work. 3. No model is perfect and de?nitely accurate, so selfadapted function was designed for this online model to adjust the predicted temperature along the production line based on online pyrometers and ?nal properties based on ?nal checking. Present results prove that it is possible to predict the ?nal mechanical properties with the help of this online model with standard deviation MPa, which meet the requirement. After repeated modi?cation, this online model has been put into production for more than 2 years, which can greatly reduce the la bor work and improve the stability of product quality. References [1] S. Jaiswal, . Mclvor, Microalloyed high carbon steel rod, Ironmaking and Steelmaking 16 (1) (1989) 49–54. [2] . Mclvor, Microalloyed low carbon steel rod, Ironmaking and Steelmaking 16 (1) (1989) 55–62. [3] Prakash K. Agarwal, . Brimabe, Mathematical model of heat ?ow and austenite–pearlite transformation in eutectoid carbon steel rods for wire, Metallurgical Transactions B 12B (1981) 121–133. [4] . Morales, . Lop233。m, A. Simon, Coupled temperature, stress, phase transformation calculation model numerical illustration of the internal stresses evolution during cooling of a eutectoid carbon steel cylinder, Metallurgical Transactions A 18A (1987) 1203–1212. [9] J. Iyer, . Brimabe, . Hawbolt, Prediction of the structure and mechanical properties of controlcooled eutectoid steel rods, in: Conf. on Mechanical Working and Steel Processing, Chicago 1984, vol. XXII, ISS/AIME, Penn, 1985, p. 47. [10] A. Kumar, C. McCulloch, . Hawbolt, . Samarasekera, Modelling thermal and microstructural evolution on runout table of hot strip mill, Materials Science and Technology 7 (1991) 1211–1223. [11] M. Militzer, . Hawbolt, . Meadowcroft, Microstructural model for hot strip rolling of highstrength lowalloy steels, Metallurgical and Materials Transactions A 31A (2021) 1247–1259. 。z, . Olivares, Heat transfer analysis during water spray cooling of steel rods, ISIJ International 30 (1) (1990) 48–57. [6] Ettore Anelli, Application of mathematical modelling to hot rolling and controlled cooling of wire rods and bars, ISIJ International 32 (3) (1992)440–449. [7] . Hawbolt, B. Chau, . Brimabe, Kiics of austenite–ferrite and austenite–pearlite transformations in a 1025 carbon steel, Metallurgical Transactions A 16A (1985) 565–578. [8] S. Denis, S. J246。C. In the CSSC model, CR is modi?ed to refer to the cooling rate in the region from 700 176。C ing from the ?nishing mill quickly passes through several water tanks to the laying head at a speci?c temperature to form into loops, depositing on to a conveyor in an overlapping pattern, the speci?c cooling rate is achieved by opening of a series of fans below. The ?nal mechanical properties depend mainly on the chemical position and the cooling rate before the phase transformation for high carbon steel [1,2,6]. As the cooling rate and phase transformation cannot be observed directly during production, it is urgently required to develop an online model to predict the ?nal mechanical properties and phase transformation. Although there are several research reports in this ?eld [3–6], the online quality prediction model for Stelmor process has not found reported yet. Adopting Implicit Finite Difference Time Domain (FDTD) method,an online controlled cooling model was developed a