This study investigates the early hydration characteristics and kinetics of ordinary Portland cement (OPC) and calcium sulfoaluminate cement (CSA) composite pastes. The hydration mechanisms of OPC-CSA systems with different proportions are analyzed through zonal analysis and the Krstulović–Dabić method. The experimental results show that in OPC-dominated systems, an appropriate amount of CSA promotes the rapid hydration of ye’elimite and optimizes the cumulative hydration heat and pore structure. However, excessive CSA inhibits hydration due to alkalinity imbalance. In CSA-dominated systems, 10% OPC increases the alkalinity, promoting ye’elimite to hydrate into ettringite. Higher OPC content hinders the hydration process due to ion concentration imbalance. The kinetics model indicates that CSA accelerates the interfacial reaction and diffusion in the OPC system, while OPC reduces the overall hydration rate of the CSA system. Microscopic analysis confirms that the composite system improves the pore structure through mineral interaction. In the OPC-dominated area, the pore structure is mainly composed of small and dense pores. In the CSA-dominated area, the characteristics of large pores are affected by the expansion properties of CSA and hydration heat. This study constructs a coupling mechanism of alkalinity regulation and crystal nucleus generation, providing a theoretical basis for the design of high-performance composite cement materials.

The rotational motion and orientational distribution of ellipsoidal particles in turbulent flows are of significance in environmental and engineering applications. Whereas the translational motion of an ellipsoidal particle is controlled by the turbulent motions at large scales, its rotational motion is determined by the fluid velocity gradient tensor at small scales, which raises a challenge when predicting the rotational dispersion of ellipsoidal particles using large eddy simulation (LES) method due to the lack of subgrid scale (SGS) fluid motions. We report the effects of the SGS fluid motions on the orientational and rotational statistics, such as the alignment between the long axis of ellipsoidal particles and the vorticity, the mean rotational energy at various aspect ratios against those obtained with direct numerical simulation (DNS) and filtered DNS. The performances of a stochastic differential equation (SDE) model for the SGS velocity gradient seen by the particles and the approximate deconvolution method (ADM) for LES are investigated. It is found that the missing SGS fluid motions in LES flow fields have significant effects on the rotational statistics of ellipsoidal particles. Alignment between the particles and the vorticity is weakened; and the rotational energy of the particles is reduced in LES. The SGS-SDE model leads to a large error in predicting the alignment between the particles and the vorticity and over-predicts the rotational energy of rod-like particles. The ADM significantly improves the rotational energy prediction of particles in LES.

To evaluate the characteristics of traffic noise under different network structures, an evaluation method is established to clarify the mechanism of traffic noise impacted by variational network structures. First, a stochastic user equilibrium (SUE) model considering intersection delays is developed to allocate traffic flows of different network structures, and a flow-based univariate noise prediction model is used to simulate network noise distribution. Secondly, differentiation indexes including the coefficient of inhomogeneity (COI) and the concept of Lane Area Ratio (LAR) are set to quantify the network structure differences. Finally, a structural equation model (SEM) is developed to investigate the influence mechanism of network structure differentiation on traffic noise. The following conclusions are obtained: (1) The impact of network density differentiation on traffic noise is mainly reflected in the changes of road traffic flow and speed. Traffic noise decreases as the network density increases. In this case, when network density increases by 1 km/km², traffic noise decreases by 1.6 dB. As network density increases, which means a dispensation of traffic flow, traffic noise is diminished by a reduction in traffic flow and speed. (2) The impact of road spatial location differentiation on traffic noise mainly depends on the number of noise sources. Traffic noise increases with the dense distribution of roads. In this case, when the COI increases by 1, the traffic noise increases by 3.0 dB. A higher COI indicates that the region will be exposed to more noise sources, which leads to traffic noise raises. The study can provide an effective basis for traffic noise control at the initial stage of network planning.

The single-, two- and multi-particle dispersions in isotropic turbulent flows are investigated using the direct numerical simulation (DNS), filtered DNS (FDNS) and large-eddy simulation (LES) with a spectral eddy viscosity subgrid scale (SGS) model. The contributions of filtering operation and SGS model to the dispersions are separately studied by comparing the statistics obtained from the three methods. The missing SGS motions in LES can be observed to significantly hinder two-particle and four-particle dispersions if the initial separations are less than or comparable to the filter width. A theoretical analysis of the non-monotonic behavior at short time of the one-time, two-point Lagrangian velocity correlation functions with large initial separations based on the Taylor expansion and the Kolmogorov similarity theory is derived, and the Reynolds number effect on the performance of the spectral eddy viscosity SGS model is also investigated. The results show that the SGS model used performs better with increasing Reynolds numbers. It is concluded that the particle SGS model is needed to be developed to correctly capture the Lagrangian two- and multi-point dispersion statistics of fluid particles.