Potential Source Analysis of Macrodebris in Untung Java Island by Using Trajectory Particle Modelling

Untung Java is one of the small islands in Thousand islands. One of the most highlighted problems on this island is the accumulation of macrodebris that occurs in the coastal and mangrove ecosystems. The purpose of this study is to determine the most potential source point for distributing debris to Untung Java Island by using a hydrodynamic model and particle trajectory model of MIKE 21. The scenario of the simulation is using pre-reclamation condition in 1999 and 2019. The estuary in Jakarta Bay is illustrated as the starting point for debris transport. Five other estuaries as potential source assumption are selected, namely Cisadane, Citarum, Muara Angke, Ciliwung and Cikeas. The validation data model used tidal data from Intergovernmental Oceanographic Commission (IOC) Sea Level Monitoring by utilizing Root Mean Square Error (RMSE) method. The RMSE is calculated up to 0.49-12.78%. The tidal current of Jakarta Bay is simulated up to 0.015-0.375 m/s. The Cisadane estuary is the most potential source as a supplier of macrodebris to Untung Java Island due to its debris movement pattern and the nearest distance to the island.

Implementation of a Lagrangian Stochastic Particle Trajectory Model (LaStTraM) to Simulate Concentration and Flux Footprints Using the Microclimate Model ENVI-Met

The number of studies evaluating flux or concentration footprints has grown considerably in recent years. These footprints are vital to understand surface–atmosphere flux measurements, for example by eddy covariance. The newly developed backwards trajectory model LaStTraM (Lagrangian Stochastic Trajectory Model) is a post-processing tool, which uses simulation results of the holistic 3D microclimate model ENVI-met as input. The probability distribution of the particles is calculated using the Lagrangian Stochastic method. Combining LaStTraM with ENVI-met should allow us to simulate flux and concentration footprints in complex urban environments. Applications and evaluations were conducted through a comparison with the commonly used 2D models Kormann Meixner and Flux Footprint Predictions in two different meteorological cases (stable, unstable) and in three different detector heights. LaStTraM is capable of reproducing the results of the commonly used 2D models with high accuracy. In addition to the comparison with common footprint models, studies with a simple heterogeneous and a realistic, more complex model domain are presented. All examples show plausible results, thus demonstrating LaStTraM’s potential for the reliable calculation of footprints in homogeneous and heterogenous areas.

Study on Fine Particle Flow Characteristics with Different Air Supply Parameters

With the help of FLUENT software, the flow characteristics of fine particles in the upper air supply room with different air supply parameters were studied. The particle trajectory model was established to calculate the concentration distribution characteristics of fine particles in the upper air supply room, and the optimal air supply parameters in the working area of the personnel were researched to reduce the impact of the particles on the human health. By calculating the distribution of air flow field and particle concentration under four different air supply parameters, the optimal operating conditions were obtained by comparative analysis, that is, the air supply temperature was 20°C and the air supply speed was 3m/s, which provided a theoretical basis for the setting of the air supply parameters of the upper air supply room in the future.

Marine macro debris transport based on hydrodynamic model before and after reclamation in Jakarta Bay, Indonesia

Jakarta Bay as an area with the densest population in Indonesia became one of the highest contamination level waters in the world includes pollution of debris. Reclamation activities in Jakarta Bay will change the water conditions will also affect the distribution of debris at sea. Therefore, this study conducted to determine the movement of the macro debris before and after island reclamation in Jakarta Bay. The method used is a model that simulated by the hydrodynamic model and particle trajectory model. Data needed for the hydrodynamic model were wind, tides, bathymetry, and shoreline, while for the trajectory of the particles using a data type of macro debris, debris weight, and debris flux. Hydrodynamics simulations indicate if a reclamation island formation does not change surface current patterns significantly, but causes a decrease in the flow velocity of ± 0.002 to 0.02 m/s at some point. The trajectory of particles of debris indicate if after reclamation, debris tends to accumulate in the eastern Jakarta Bay in the rainy season (January) as there are anticlockwise eddy current, as well as in the western and eastern regions during the dry season (July), because there is a clockwise eddy current in the eastern Jakarta Bay.

Development of the WRF-CO2 4D-Var assimilation system v1.0

Regional atmospheric CO2 inversions commonly use Lagrangian particle trajectory model simulations to calculate the required influence function, which quantifies the sensitivity of a receptor to flux sources. In this paper, an adjoint-based four-dimensional variational (4D-Var) assimilation system, WRF-CO2 4D-Var, is developed to provide an alternative approach. This system is developed based on the Weather Research and Forecasting (WRF) modeling system, including the system coupled to chemistry (WRF-Chem), with tangent linear and adjoint codes (WRFPLUS), and with data assimilation (WRFDA), all in version 3.6. In WRF-CO2 4D-Var, CO2 is modeled as a tracer and its feedback to meteorology is ignored. This configuration allows most WRF physical parameterizations to be used in the assimilation system without incurring a large amount of code development. WRF-CO2 4D-Var solves for the optimized CO2 flux scaling factors in a Bayesian framework. Two variational optimization schemes are implemented for the system: the first uses the limited memory Broyden–Fletcher–Goldfarb–Shanno (BFGS) minimization algorithm (L-BFGS-B) and the second uses the Lanczos conjugate gradient (CG) in an incremental approach. WRFPLUS forward, tangent linear, and adjoint models are modified to include the physical and dynamical processes involved in the atmospheric transport of CO2. The system is tested by simulations over a domain covering the continental United States at 48 km × 48 km grid spacing. The accuracy of the tangent linear and adjoint models is assessed by comparing against finite difference sensitivity. The system's effectiveness for CO2 inverse modeling is tested using pseudo-observation data. The results of the sensitivity and inverse modeling tests demonstrate the potential usefulness of WRF-CO2 4D-Var for regional CO2 inversions.

Development of the WRF-CO2 4DVar assimilation system

Regional atmospheric CO2 inversions commonly use Lagrangian particle trajectory model simulations to calculate the required influence function. To provide an alternative, we developed an adjoint based four-dimensional variational (4DVar) assimilation system, WRF-CO2 4DVar. This system is developed based on the Weather Research and Forecasting (WRF) model system, including WRF-Chem, WRFPLUS, and WRFDA. In WRF-CO2 4DVR, CO2 is modeled as a tracer and its feedback to meteorology is ignored. This configuration allows most WRF physical parameterizations to be used in the assimilation system without incurring a large amount of code development. WRF-CO2 4DVar solves for the optimized CO2 emission scaling factors in a Bayesian framework. Two variational optimization schemes are implemented for the system: the first uses the L-BFGS-B and the second uses the Lanczos conjugate gradient (CG) in an incremental approach. We modified WRFPLUS forward, tangent linear, and adjoint models to include CO2 related processes. The system is tested by simulations over a domain covering the continental United States at 48 km × 48 km grid spacing. The accuracy of the tangent linear and adjoint models are assessed by comparing against finite difference sensitivity. The system's effectiveness for CO2 inverse modeling is tested using pseudo-observation data. The results of the sensitivity and inverse modeling tests demonstrate the potential usefulness of WRF-CO2 4DVar for regional CO2 inversions.

Injection Performance of a Gas-Solid Injector Based on the Particle Trajectory Model

Gas-solid injectors are widely used feeding equipment in pneumatic conveying systems. The performance of a gas-solid injector has a significant influence on the type of application it can be employed for. To determine the key factors influencing the injection performance and address clogging problems in a gas-solid injector during a pneumatic conveying process, the particle trajectory model has been utilised as a means to perform simulations. In the particle trajectory model, the gas phase is treated as a continuous medium and the particle phase is treated as a dispersed phase. In this work, numerical and experimental studies were conducted for different nozzle positions in a gas-solid injector. A gas-solid injector test-bed was constructed based on the results of the simulations. The results show that the nozzle position is the key factor that affects the injection performance. The number of extrusive particles first increases and then decreases with the change in the nozzle position from left to right. Additionally, there is an optimum nozzle position that maximises the injection mass and minimises the number of particles remaining in the hopper. Based on the results of this work, the injection performance can be significantly increased and the clogging issues are effectively eliminated.

Study of the Optimal Design for the Gliding Trajectory

The optimal design for the gliding trajectory is studied. The particle trajectory model in the longitudinal plane is established. Aiming at solving the problems in numerical solution ,the direct shooting method based on the interpolating function of Akima is put forward .In direct collocation method, the parameters of the trajectory with approximate maximum lift-drag ratio is adopted as the starting value of the optimal variables. The trajectory with approximate maximum lift-drag ratio could be obtained by the search method. The transfer approach of turning the problem of trajectory optimization to the problem of parameter optimization by the direct shooting method is illustrated. To one kind of guided vehicles in simulation, the simulation results prove the practicability of the direct shooting method.