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In order to dig out more potential of design parameters besides nameplate information, a set of pre-physical modeling methods was proposed and integrated into the dynamic thermal modeling procedure, aiming to optimize the key thermal parameters individually. In this method, a global oil momentum model was created considering the flow resistance, and for the problem of heat transfer between windings, oil flow, and radiator, a whole oil flow thermal model was established based on heat transfer principle and energy conservation. Then, the double logarithmic linear regression was applied to quantify the value of the exponents. According to the overload heat run tests, the temperature calculated by the existing models during multiple overloads is obviously different from the measured temperature, while the improved dynamic thermal modeling procedure with optimized thermal parameters attains estimates more accurately.

To quantify the non-linear variation of top-oil temperature with load current, and further investigate the key parameters in the thermal model, a model for calculating the oil exponent is proposed in this study. First, a global oil momentum model was established based on the fluid resistance characteristic. Then, based on the heat transfer coupling relationship between the winding, the oil flow, and the radiator (outside air), a set of control equations describing the oil temperature and the oil flow rate was established by using energy conservation. Simultaneously, the top-oil temperature was recorded from a field traction transformer to verify the physical part of the proposed model. The regression model parameters were identified with the ordinary least-square estimation so the oil exponent can be calculated naturally. The calculated oil exponent of the traction transformer at a wide range of load was 0.7308, so the accuracy was improved by 9.47% compared with the IEEE/IEC recommended value. Newly updated oil exponent was also verified through a dynamic overload heat run test. It is expected that the proposed oil exponent model can help in estimating top-oil temperature with more convenience and accuracy, especially in frequent overload conditions.

Thermal time constants (TTC) of a thermal dynamic model reflect the change rate of temperature, which are affected by many factors such as load current, oil temperature, etc. In this study, relative thermal time constants (RTTC) are introduced and formulated to describe the variation of thermal time constants with load current. It is verified through extensive case studies based on computational fluid dynamic (CFD) simulation and field measurements. Specific for CFD simulation, the polyhedral meshing was applied to mesh division of 3D model due to narrow part such as discs in transformer. The proposed relative thermal time constants can be integrated with dynamic thermal model to estimate the hot-spot temperature of transformers, especially in overload situations. Accuracy and adequacy metrics are used to quantify the accuracy of presented thermal model with proven thermal model.

International audience; According to the change characteristics of the subgrade moisture content and the mechanical calculation of several typical highways, the test scheme of the permanent deformation of coarse soil was formulated. The relationship between the permanent deformation of coarse-grained soil and the stress level, compaction degree, moisture content, and loading frequency was studied by cyclic loading triaxle testing. The results show that the permanent deformation of coarse-grained soil increases with the increase in partial stress and moisture content and decreases with the increase in compaction degree. The experimental data were fitted by the Tseng-Lytton model, and the correlation coefficients were 92%, which indicated that the model could be used to predict the permanent deformation of coarse soil. The relationships between the model coefficient and the moisture content and spring back modulus were obtained by the multiple regression method. Finally, the permanent deformation of the subgrade soil was calculated by using the layered summation method and a typical subgrade pavement structure.