## 1 Introduction
It is well known that the size of the systems of equations is directly related to the number of degrees of freedom (DOFs), and it is clear that the DOFs are associated with the nodes. The geometrically adaptive mesh discussed earlier reduces the number of DOFs by reducing that of nodes. If the number of DOFs can be reduced directly, that is, the size of equations can be reduced from the algebraic point of view, even without changing the nodes, it is clear that the time to solve the equations can be reduced. In computational mechanics, the DOF condensation method can reduce the number of DOFs in the stiffness matrix [25]. The method was first proposed by [PERSON] in 1965 and was named static condensation because it is only accurate for static problems [26]. Later, the method began to be extended to dynamic calculations [27; 28; 29]. DOF condensation methods are currently mostly used to analyze substructures where users focus on regions that have some characteristics, that is, substructure analysis [30]. This eliminates some or all of the DOFs in other regions and then allows for the detailed analysis of the localized region (e.g., the simulation of large reinforced concrete structures with localized nonlinearities [31; 32]). In fact, similarly, based on the error-control method, it is possible to eliminate some DOFs and obtain the satisfactory results with the analysis of the global region [33]. Considering that the temperature inside the core wall generally decreases and stabilizes from the construction period to the operational period, there will be no significant difference in temperature between the multiple core wall construction layers inside. In this case, an approximately accurate result can be calculated by eliminating some of the local DOFs and retaining only a small number of DOFs in the global region. Therefore, this paper proposes an adaptive DOF condensation method to automatically eliminate the temperature DOF of the core wall at a different time and then eventually achieve the reduction of the computational time and ensure the accuracy of the calculation results required. In this paper, Section 2 provides the derivation process of the method proposed in this paper and introduces the corresponding coarsening criterion and the transformation matrix used. Three examples are used in Section 3. The first and second examples verify the efficiency and accuracy of the method for the calculation of the transient temperature field in the invariant and variable computational domains, respectively. Additionally, based on an engineering problem, the third example verifies the applicability of the method to simulate the temperature field in the construction process of asphalt-concrete core wall. Similar to the simulation of the transient temperature field during the construction period of asphalt-concrete core walls, usually such problems have large differences in structural spatial scales, long computational time domains, and high model-refinement requirements. Section 4 summarizes the cost advantages and limitations of the method proposed in this paper when solving this type of problem and also describes the possible directions for further improvement.