Accurate weather data is essential for building energy modeling (BEM), yet the actual urban local weather condition is often overlooked. This study developed an approach to generate local weather data using ERA5, a global atmospheric reanalysis dataset as input for two urban land surface models, Urban Tethys-Chloris (UT&C) and Urban Weather Generator (UWG). The generated datasets (UT&C-ERA5 and UWG-ERA5) are compared to locally measured weather data for a university campus in Singapore. Results show that the original ERA5 underestimates the diurnal temperature range. UT&C-ERA5 significantly improves hourly dry bulb temperature, reducing Mean Absolute Error (MAE) from 1.73 to 1.32 and Root Mean Square Error (RMSE) from 2.31 to 1.67, while UWG-ERA5 shows modest improvements (MAE from 1.73 to 1.70, RMSE from 2.31 to 2.22). UT&C-ERA5 also improves wind speed, lowering MAE from 2.85 to 1.54 and RMSE from 3.23 to 1.79. Subsequently, these weather datasets are employed as inputs for a calibrated BEM. Compared to the original ERA5, UT&C-ERA5 reduces CV (RMSE) of building cooling load from 17.13 % to 15.45 %. By leveraging the global availability of atmospheric reanalysis datasets, this approach can support building energy design and improve energy efficiency in tropical cities.

Accurate prediction of train-induced settlement in railway transition zones is of paramount importance for ensuring the safety and serviceability of high-speed railway (HSR) infrastructure. The inherent complexity of mechanical properties and settlement distribution in these zones stems from the significant stiffness variation between different track structures. This study presents a novel iterative framework for long-term settlement prediction specifically tailored to ballastless track transition zones of HSR systems. The framework couples a dynamic Train-Track-Transition Zone (TTTZ) model with a plastic strain prediction model for soil, enhanced by a jump-step iterative algorithm that improves computational efficiency while maintaining accuracy. The model's validity has been verified through comprehensive comparisons with in-situ measurements and existing analytical solutions. Numerical results demonstrate that the iterative updating of track irregularities is crucial for accurate settlement prediction, as it accounts for the time-dependent dynamic characteristics of the TTTZ system. Furthermore, a wavelet transform-short energy method is developed to identify high-density vibration energy distributions in the spatial domain, establishing a robust correlation between dynamic responses and settlement evolution. This study underscores the importance of iterative modeling and advanced time-frequency analysis in settlement prediction and track quality assessment, offering valuable insights for the design, maintenance, and evaluation of HSR transition zones.

The dynamic response of a railway bridge can be affected by the properties of its foundations, particularly if founded on soft soils. Thus, this work aims to establish a coupled dynamic model to investigate the vibration of train-track-bridge systems considering piled foundations embedded in soft soil. Firstly, to construct the simulation framework, the finite element and multi-body methods are used to model the dynamic behavior of a train-track-bridge interaction (TTBI) system and a pier-cap-pile-soil interaction system. The equilibrium of the two sub-systems is maintained through the bridge's bearing force and a multi-time-step integration strategy is introduced to improve computational efficiency. The proposed model is validated by comparing it to the results from commercial finite element software ABAQUS. Then results are computed using the proposed model and the conventional TTBI model without piles. It is concluded that when considering the piled foundations, the low-frequency vibration of the TTBI system is dominant. Moreover, the vibration energy in the track and bridge below 7 Hz is larger compared with the conventional TTBI model. The influence of train speed on the vibration characteristics of the pile and soil is analyzed. It is found that higher train speeds cause increased pile and soil accelerations at the frequencies associated with the train axle spacing. The novelty of the analysis is providing a new insight into the coupled vibration properties of TTBI systems considering the participation of piled foundations in soft soil.

The dynamic performance of a railway track subjected to moving trains depends strongly on track support conditions. In reality, even for the well-constructed and well-maintained tracks, sleeper support stiffness and global track stiffness vary substantially along the track, which affects the train-track dynamic interactions, causing rapid track geometry degradation as well as the riding comfort and safety issues. Consequently, track stiffness irregularity (TSI, the spatial variation of track stiffness along the track) is important for railway construction and maintenance in addition to track geometry irregularities. So far, extensive research has been published on the TSI whereas the relevant issues have not been paid sufficient attention. In this paper, a summary and comments have been made in the field of TSI about the current research status and future trends from a critical point of view. Novel concepts of the critical values of TSIs and the integrated management of the track geometry and stiffness irregularities are proposed. The review presented in this work is valuable to advance the research on TSI and can help guide the design, construction and maintenance of railway tracks.

Modelling slab track-bridge interaction subject to a moving train usually involves solving complex high-dimensional matrix equations which is time-consuming. This research works to optimize the auto-assembling process in the slab track-bridge coupling matrices formulation and improve the computational efficiency by truncating the dynamic matrices used in time integral scheme. To achieve the above goals, the key issue is to appropriately couple the systems’ dynamic matrices in conditions where the elemental sizes of the track slab and the bridge are inconsistent in 3-D space. Besides, by firstly clarifying the degrees of freedom vector of the rail, the track slab and the bridge girder participated in each time step, dynamic matrices characterizing the train-slab track-bridge interaction are truncated with time to reduce the matrix size. This present study has demonstrated the solutions for above problems. Apart from model validations, some numerical examples are presented to show applicability of the proposed methods.