Study and Analysis on the Influence Degree of Particle Settlement Factors in Pipe Transportation of Backfill Slurry

In this study, we developed a pipeline transport model to investigate the influence of particle sedimentation factors on slurry transportation through pipelines. The particle tracking module of the software was used to simulate the transport process, and the influences on the sedimentation rate were analyzed considering the slurry concentration, particle size, and flow velocity. The established model exhibited small calculation errors. In addition, the results revealed that the proposed model is reliable for calculating the degree of influence of various factors on particle sedimentation. The effect of the particle sedimentation rate on the pipeline slurry was explored considering the particle size, slurry concentration, and flow velocity. The sedimentation rate was positively related to particle size and adversely related to the slurry concentration and flow velocity. Indeed, study on the sedimentation rate requires considering a reasonable range of particle sizes, preparing a slurry with an appropriate concentration, and adjusting an appropriate flow velocity. Numerical simulations were performed using the filling data as the background for a sample mining area. The experimental results showed optimal slurry concentration and particle size of 60% and 25.25 µm, respectively.

Pipeline slugging and mitigation: Production strategy challenge at the tail of production in Medco E and P

There are many challenging issues toward the tail of the oil and gas production period. An integrated solution is needed considering the economics of the asset. The North Belut field, located at Block B South Natuna Sea, operated by Medco E & P Indonesia has been in operation since 2009. During the current tail of production period, one of the operations challenges is the slugging phenomenon which causes wells shut-in due to high back-pressure and sudden surge of liquid which causes process upset to the downstream facilities. The mitigation program to be implemented should be integrated with the operations strategy to maintain the production and prolong the asset life. This paper summarises the study of the multiphase flowline system at its current operations condition, the impact of lowering plant pressure to the slugging phenomena, and the prediction of slugging tendency in the remaining years of the asset life. The simulation results are based on analysis using the multiphase pipeline simulation tool OLGA with slug tracking module. The results showed that the lowering of the plant pressure can reduce the slugging tendency. However, since the gas will naturally continue to decrease in the end-of-life period, the slugging phenomenon will potentially occur again in the future. The result also shows that the multiphase pipeline behaviours can be modelled with excellent agreement between actual data and simulation results. The result is beneficial in enriching the strategy to reduce slugging in the tail of the production period.

EXCHANGE CHARACTERISTICS OF AN ANTHROPOGENICALLY MODIFIED LAGOON: AN EULERIAN-LAGRANGIAN MODELING CASE STUDY WITH AN EMPHASIS ON THE NUMBER OF PARTICLES

The transport pathways and exchange characteristics of the Kamil Abdüş Lagoon in Istanbul, Turkey, are simulated using a finite element model with a Lagrangian particle tracking module. The lagoon is in the process of being reconfigured. The simulations are performed using a draft configuration. The effect of winds and the number of particles on the e-folding time is simulated. Results show that the lagoon is strongly dominated by winds with a correlation coefficient of 0.897 between the wind and residual current magnitudes. The lagoon e-folds in 9.1 days under realistic winds and in 14.3 days when there is no wind with confidence levels of 5%. The Lagrangian study uses six simulations with particle numbers ranging between 65073 and 2730486. A methodology based on confidence levels is proposed. It is observed that approximately 784 000 particles are necessary to obtain 5% level of confidence. With a problematic history and new planning options, the lagoon has a potential to be used as an example setting, all-field study ground for anthropogenically engineered coastal ecosystems.

Smart Bran Dispenser for Animal Husbandry Purpose

The creation of technology in this century changes people’s life. Technology plays an important role that benefits young people and has increased agriculture production’s efficiency and profitability. Innovative technology mainly involved in animal feeding automation is currently one of Smart Bran Dispensers’ new inventions. This project approaches an innovative animal husbandry management system to improve the agricultural system’s efficiency, particularly livestock nutrition and feed resources. The benefit of this project is to facilitate animal feeding for breeders, which can be remotely controlled and detected by a tracking module that transmits a signal to the user and informs them of the status of the bran dispenser through the Blynk server. NodeMCU ESP8266 and Arduino UNO were implemented as the main controller.

Autonomous Repeat Image Feature Tracking (autoRIFT) and Its Application for Tracking Ice Displacement

In this paper, we build on past efforts with regard to the implementation of an efficient feature tracking algorithm for the mass processing of satellite images. This generic open-source feature tracking routine can be applied to any type of imagery to measure sub-pixel displacements between images. The routine consists of a feature tracking module (autoRIFT) that enhances computational efficiency and a geocoding module (Geogrid) that mitigates problems found in existing geocoding algorithms. When applied to satellite imagery, autoRIFT can run on a grid in the native image coordinates (such as radar or map) and, when used in conjunction with the Geogrid module, on a user-defined grid in geographic Cartesian coordinates such as Universal Transverse Mercator or Polar Stereographic. To validate the efficiency and accuracy of this approach, we demonstrate its use for tracking ice motion by using ESA’s Sentinel-1A/B radar data (seven pairs) and NASA’s Landsat-8 optical data (seven pairs) collected over Greenland’s Jakobshavn Isbræ glacier in 2017. Feature-tracked velocity errors are characterized over stable surfaces, where the best Sentinel-1A/B pair with a 6 day separation has errors in X/Y of 12 m/year or 39 m/year, compared to 22 m/year or 31 m/year for Landsat-8 with a 16-day separation. Different error sources for radar and optical image pairs are investigated, where the seasonal variation and the error dependence on the temporal baseline are analyzed. Estimated velocities were compared with reference velocities derived from DLR’s TanDEM-X SAR/InSAR data over the fast-moving glacier outlet, where Sentinel-1 results agree within 4% compared to 3–7% for Landsat-8. A comprehensive apples-to-apples comparison is made with regard to runtime and accuracy between multiple implementations of the proposed routine and the widely-used “dense ampcor" program from NASA/JPL’s ISCE software. autoRIFT is shown to provide two orders of magnitude of runtime improvement with a 20% improvement in accuracy.

Numerical simulation study of oil diffusion at low tide near the port area of Ma’ao, Zhoushan

In this paper, the numerical hydrodynamic simulation has been carried out by using measured topographic data and related tidal information. The oil particle tracking module of MIKE21 is adopted to study the processes of drifting and turbulent diffusion of oil particles on the water surface, where four working conditions, namely, static wind, dominant wind direction, maximum wind direction and most unfavourable wind direction, are applied. Results show that Xiushan Island will be the apparent ‘victim’ in the cases of oil spill in all wind directions. Meanwhile, due to the existence of Changbai Island and Xiushan Island, the diffusion process of oil particles is obviously retarded to impact the protected marine areas.

A Wireless Multisensor Node for Long-Term Environmental Parameters Monitoring

Environmental quality is a great concern to everyone, in order to realize the collection, upload, management, and visualization of parameters of atmospheric environment in real time. We propose a cheap, low-power, and fast deployment wireless sensor node for environmental monitoring, consisting of STM32 MCU, ESP8266, light sensor, rain sensor, UV sensor, seven-in-one sensor (including temperature, humidity, PM2.5, PM10, CO2, formaldehyde, and TVOC), and solar automatic tracking module. A customized μC/OS-III runs on the node, which controls the transmission of environment parameters collected by each sensor to the cloud server through the wireless network, and then the server receives, stores, and visualizes the data. In actual test, the node collects data once an hour, and the running power of the node is low and stable. Experimental results show that the node could achieve accurate collection and transmission and display the environmental data, and solar automatic tracking module could meet long-term running of the node in the night and continuous rainy days.

Global Infectious Disease Surveillance and Case Tracking System for COVID-19: Development Study

Background COVID-19 has affected more than 180 countries and is the first known pandemic to be caused by a new virus. COVID-19’s emergence and rapid spread is a global public health and economic crisis. However, investigations into the disease, patient-tracking mechanisms, and case report transmissions are both labor-intensive and slow. Objective The pandemic has overwhelmed health care systems, forcing hospitals and medical facilities to find effective ways to share data. This study aims to design a global infectious disease surveillance and case tracking system that can facilitate the detection and control of COVID-19. Methods The International Patient Summary (IPS; an electronic health record that contains essential health care information about a patient) was used. The IPS was designed to support the used case scenario for unplanned cross-border care. The design, scope, utility, and potential for reuse of the IPS for unplanned cross-border care make it suitable for situations like COVID-19. The Fast Healthcare Interoperability Resources confirmed that IPS data, which includes symptoms, therapies, medications, and laboratory data, can be efficiently transferred and exchanged on the system for easy access by physicians. To protect privacy, patient data are deidentified. All systems are protected by blockchain architecture, including data encryption, validation, and exchange of records. Results To achieve worldwide COVID-19 surveillance, a global infectious disease information exchange must be enacted. The COVID-19 surveillance system was designed based on blockchain architecture. The IPS was used to exchange case study information among physicians. After being verified, physicians can upload IPS files and receive IPS data from other global cases. The system includes a daily IPS uploading and enhancement plan, which covers real-time uploading through the interoperation of the clinic system, with the module based on the Open Application Programming Interface architecture. Through the treatment of different cases, drug treatments, and the exchange of treatment results, the disease spread can be controlled, and treatment methods can be funded. In the Infectious Disease Case Tracking module, we can track the moving paths of infectious disease cases. The location information recorded in the blockchain is used to check the locations of different cases. The Case Tracking module was established for the Centers for Disease Control and Prevention to track cases and prevent disease spread. Conclusions We created the IPS of infectious diseases for physicians treating patients with COVID-19. Our system can help health authorities respond quickly to the transmission and spread of unknown diseases, and provides a system for information retrieval on disease transmission. In addition, this system can help researchers form trials and analyze data from different countries. A common forum to facilitate the mutual sharing of experiences, best practices, therapies, useful medications, and clinical intervention outcomes from research in various countries could help control an unknown virus. This system could be an effective tool for global collaboration in evidence-based efforts to fight COVID-19.