A robust two-node, 13 moment quadrature method of moments for dilute particle flows including wall bouncing

For flows where the particle number density is low and the Stokes number is relatively high, as found when sand or ice is ingested into aircraft gas turbine engines, streams of particles can cross each other’s path or bounce from a solid surface without being influenced by inter-particle collisions. The aim of this work is to develop an Eulerian method to simulate these types of flow. To this end, a two-node quadrature-based moment method using 13 moments is proposed. In the proposed algorithm thirteen moments of particle velocity, including cross-moments of second order, are used to determine the weights and abscissas of the two nodes and to set up the association between the velocity components in each node. Previous Quadrature Method of Moments (QMOM) algorithms either use more than two nodes, leading to increased computational expense, or are shown here to give incorrect results under some circumstances. This method gives the computational efficiency advantages of only needing two particle phase velocity fields whilst ensuring that a correct combination of weights and abscissas are returned for any arbitrary combination of particle trajectories without the need for any further assumptions. Particle crossing and wall bouncing with arbitrary combinations of angles are demonstrated using the method in a two-dimensional scheme. The ability of the scheme to include the presence of drag from a carrier phase is also demonstrated, as is bouncing off surfaces with inelastic collisions. The method is also applied to the Taylor-Green vortex flow test case and is found to give results superior to the existing two-node QMOM method and in good agreement with results from Lagrangian modelling of this case

Simulation of particle flow in an inertial particle separator with an Eulerian velocity re-associated two-node quadrature-based method of moments

This paper presents research into practical simulations of particle flow in inertial particle separators (IPS) for helicopters and tilt rotor aircraft. The flow field of the carrier gas is predicted by means of the two-equation k-ϵ turbulence model. An Eulerian methodology is used to trace the particle trajectories of foreign particles such as droplets, ice and sand. To predict the characteristics of particle wall bouncing in dilute particle flow, the velocity re-associated two-node quadrature-based method of moments (VR-QMOM) is used. The particle distribution in the IPS is predicted for various particle sizes and these are compared with results from a Lagrangian particle tracking method. The particle-wall interactions and the separation efficiencies are studied for solid particles bouncing off perfectly elastic walls and an IPS shell coated with the M246 alloy which changes the coefficients of restitution. The simulated separation efficiencies predicted by the Eulerian method are compared with the simulation using the Lagrangian method over a range of particle sizes. The VR-QMOM method is seen to reproduce the particle bouncing and trajectory crossing behavior and to agree well with the Lagrangian method for predicted separation efficiencies. The new VR-QMOM method is shown to be an accurate and convenient alternative to established Lagrangian approaches

Smart city pilots and firm earnings management.

Smart cities improve services for businesses, among many other benefits. A comprehensive understanding and effective utilization of these advantages is crucial for promoting business development. Using panel data from Chinese listed companies (2010–2020), this study employs a multi-stage DiD model to investigate the impact of smart cities on corporate earnings management. The findings indicate that the smart city pilot policy has significantly reduced corporate earnings management. Further analysis suggests that smart cities primarily reduce earnings management by improving firms’ external information environments. Additionally, the results show that the policy impact of smart cities is more significant in regions with lower regulatory intensity or higher marketization levels, compared to regions with higher regulatory intensity or lower marketization levels. Similarly, firms in less concentrated markets or those more closely related to smart city development tend to experience greater reductions in earnings management due to smart city construction, unlike firms in more concentrated markets or those less involved. Finally, this paper offers several brief suggestions.</div

Robustness test.

Smart cities improve services for businesses, among many other benefits. A comprehensive understanding and effective utilization of these advantages is crucial for promoting business development. Using panel data from Chinese listed companies (2010–2020), this study employs a multi-stage DiD model to investigate the impact of smart cities on corporate earnings management. The findings indicate that the smart city pilot policy has significantly reduced corporate earnings management. Further analysis suggests that smart cities primarily reduce earnings management by improving firms’ external information environments. Additionally, the results show that the policy impact of smart cities is more significant in regions with lower regulatory intensity or higher marketization levels, compared to regions with higher regulatory intensity or lower marketization levels. Similarly, firms in less concentrated markets or those more closely related to smart city development tend to experience greater reductions in earnings management due to smart city construction, unlike firms in more concentrated markets or those less involved. Finally, this paper offers several brief suggestions.</div

Industry characteristics and corporate earnings management.

(a) Heterogeneity in market concentration. (b) Heterogeneity across industries.</p

Distribution of propensity scores before and after matching for pilot smart cities.

(a) Distribution of propensity scores before matching for pilot smart cities. (b) Distribution of propensity scores after matching for pilot smart cities.</p

Regulatory intensity, marketization level, and corporate earnings management.

(a) Heterogeneity in regulatory intensity. (b) Heterogeneity in marketization level.</p

The results of the placebo test.

(a) Distribution of coefficients. (b) Distribution of t-values.</p

Parallel trend test.

Smart cities improve services for businesses, among many other benefits. A comprehensive understanding and effective utilization of these advantages is crucial for promoting business development. Using panel data from Chinese listed companies (2010–2020), this study employs a multi-stage DiD model to investigate the impact of smart cities on corporate earnings management. The findings indicate that the smart city pilot policy has significantly reduced corporate earnings management. Further analysis suggests that smart cities primarily reduce earnings management by improving firms’ external information environments. Additionally, the results show that the policy impact of smart cities is more significant in regions with lower regulatory intensity or higher marketization levels, compared to regions with higher regulatory intensity or lower marketization levels. Similarly, firms in less concentrated markets or those more closely related to smart city development tend to experience greater reductions in earnings management due to smart city construction, unlike firms in more concentrated markets or those less involved. Finally, this paper offers several brief suggestions.</div

Mechanism test.

Smart cities improve services for businesses, among many other benefits. A comprehensive understanding and effective utilization of these advantages is crucial for promoting business development. Using panel data from Chinese listed companies (2010–2020), this study employs a multi-stage DiD model to investigate the impact of smart cities on corporate earnings management. The findings indicate that the smart city pilot policy has significantly reduced corporate earnings management. Further analysis suggests that smart cities primarily reduce earnings management by improving firms’ external information environments. Additionally, the results show that the policy impact of smart cities is more significant in regions with lower regulatory intensity or higher marketization levels, compared to regions with higher regulatory intensity or lower marketization levels. Similarly, firms in less concentrated markets or those more closely related to smart city development tend to experience greater reductions in earnings management due to smart city construction, unlike firms in more concentrated markets or those less involved. Finally, this paper offers several brief suggestions.</div