Semiconductor quantum dots (SQDs) exhibit optical responses that are strongly influenced by their internal level structure, relaxation pathways, and excitation intensity. This study investigates the time- and intensity-dependent population dynamics of a continuously driven single -type three-level SQD using the density-matrix formalism within the rotating-wave approximation. Dissipative processes are incorporated through Lindblad-type relaxation terms, while the transient and stationary responses are obtained, respectively, by numerical time integration and steady-state solution of the density-matrix equations. Special attention is given to the relaxation channel and the off-resonant transition dipole moment . The results show that primarily controls the transient redistribution route and the timescale required to reach the stationary regime, whereas the early oscillatory behavior remains dominated by the resonantly driven transition. In the steady-state regime, mainly determines how population leaving the upper state is partitioned between the two lower states, while governs how readily the off-resonant branch becomes active as the driving intensity increases. Consequently, the crossover from predominantly resonant two-level-like behavior to genuine three-level population redistribution is controlled by the combined action of relaxation-path asymmetry and off-resonant coupling strength. These findings provide a clearer mechanism-based interpretation of driven population redistribution in effective multilevel SQD systems.
This study presents a comprehensive simulation of the Free Water Knockout process, a prevalent technique in the petroleum industry for separating water from crude oil. Leveraging Computational Fluid Dynamics, the research employs the Euler–Euler approach integrated with an inhomogeneous population balance model and a realizable k–ε turbulence model to capture the complex multiphase dynamics within the separator. A key contribution of this study lies in its validation against field data from an oil facility in South Sumatera, Indonesia, using an independent sample t-test (p = 0.13), confirming the model's reliability. The simulation achieved a separation efficiency of up to 48.46%, which, while moderate compared to centrifuge-based systems, demonstrates competitive performance for gravity-driven Free Water Knockout units under high-throughput conditions. This work advances Computational Fluid Dynamics based of the Free Water Knockout modelling by incorporating coalescence dynamics and turbulence effects, offering a validated framework for optimizing separator design and operation in industrial settings.
The southern Java subduction zone is one of the major tsunami hazard sources in Indonesia due to its potential to generate large megathrust earthquakes. This study evaluates tsunami hazards from a Mw 8.7 megathrust earthquake worst-case scenario using numerical modeling with COMCOT v1.7. A five-layer nested grid system is applied to simulate tsunami generation, propagation, and inundation from the Indian Ocean to the Pancer - Puger coast, Jember Regency, Indonesia. Earthquake source parameters are defined using the Wells and Coppersmith empirical relationships, while initial seafloor deformation is calculated using the Okada elastic dislocation model. Tsunami wave dynamics are analyzed using Virtual Tsunami Gauges (VTGs). The results indicate that Puger Kulon and Mojosari villages experience the most severe impacts, with large wave amplitudes, strong currents, and inundation exceeding 20 m depths. Tsunami arrival time is about 21 to 27 minutes, providing a very limited evacuation window. The ETH (Estimated Tsunami Height) and ETA (Estimated Time of Arrival) maps show that low-lying, open coastal plains act as primary pathways for tsunami penetration. These findings emphasize the high vulnerability of the Pancer coast - Puger and the need for risk-based mitigation, improved evacuation planning, and strengthened local early warning systems.
Electrophoretic deposition (EPD) patterns of colloidal SiO2 particles (400 nm) in solution were analysed and demonstrated using the kinetic Monte Carlo (KMC) simulation method. The behaviour of the colloidal particles which formed electrical double layers in solution was described by the DLVO theory. The dynamic particle migrations of the EPD process were estimated by the KMC simulation to statistically determine the probable particle distribution based on thermodynamic theories. Results show that the particle distribution and deposition in solution were significantly influenced by the presence of the zeta potential value (η) in the solution, and applied voltage in the EPD system. The particles aggregated together in the solution with a small η value due to the strong Van der Waals attractive forces among the particles. If a large η value was adopted, all the particles moved away from central and scattered around the edges the system space because of the strong electrostatic (repulsive) forces among them. The external voltage applied to the EPD system in different η value can affect the formation of particle deposition pattern. The EPD pattern with little vacancy site can be fabricated using a small η value with a constant voltage operating condition. However, the vacancy sites of the EPD pattern became large by the on-off voltage operating scheme. The quality of the EPD films cannot be improved using this strategy.
This study presents an analytical framework for a generalized fractional formulation of Newton’s law of cooling based on a newly defined generalized fractional (GF) Laplace transform. The proposed formulation extends existing fractional models by incorporating both a fractional order and a non-negative continuous kernel function, thereby providing increased modelling flexibility and a more general representation of memory-dependent thermal processes. A rigorous definition of the GF Laplace transform is established, together with its fundamental properties, including linearity, existence conditions, and operational rules for generalized fractional derivatives and integrals. Within this framework, the classical Newton’s cooling equation is reformulated in terms of the GF derivative, and an explicit analytical solution is obtained using the proposed transform method. The resulting solution generalizes the classical exponential decay law and reduces to the standard model under appropriate parameter selection. In addition, the effects of the fractional order and kernel function on cooling dynamics were examined through several representative cases. The analysis showed that both parameters played a significant role in determining the rate of temperature decay. In particular, smaller fractional orders lead to stronger memory effects and slower convergence, whereas the choice of the kernel function determines the effective time scale of the system. These results demonstrate the capability of the generalized fractional framework to describe a wider range of thermal behaviors than classical and existing fractional models.
