A computational fluid dynamics study of combustion and emission performance in an annular combustor of a jet engine

This paper is a Computational Fluid Dynamics (CFD) study of the performance of a jet engine annular combustor that was subjected to various loading conditions. The aim is to comprehend the effect of various genuine working conditions on ignition and emission performance. The numerical models utilized for fuel ignition is the feasible k-ω model for turbulent stream, species transport (aviation fuel and air) with eddy-dissipation reaction modelling and pollution model for nitrogen oxides (NOX) emission. The results obtained confirm the findings described in the literature

RANCANG BANGUN ALAT PENGADUK SABUN CAIR BAHAN BAKU MINYAK SERAI WANGI

The process of making liquid soap from citronella oil is an interesting thing to know. This study aims to design, create, test and analyze the time and rpm rotation of the most efficient liquid soap mixer machine. Soap is an alkaline local salt (usually a potassium salt) of fatty acids, mainly containing C16 salt (palmitic acid) and C18 (stearic acid) but can also contain several carboxylates with lower atomic weights (Fessenden, 1994 and Ketaren, 1986). Traditionally, lemongrass is used as a flavor generator in food, drinks and traditional medicine (Wijayakusumah, 2002). Fragrant lemongrass is also used as a flavor generator used in spicy sauce, fried chili sauce, chili paste and fish sauce (Oyen, 1999). Data collection observed were device capacity, yield. From the results of the study, the effective capacity of the equipment was 397.1 L / hr.   Keywords: liquid soap, citronella oil, effective capacity of the tool, yield

Pengaruh Berat Pecahan Arang Kelapa yang berbeda sebagai Filter dalam Mempertahankan Kualitas Air pada Pemeliharaan Benih Ikan Kakap Putih (Lates calcarifer)

The research was carried out in September 2021, taking place at the Marine Aquaculture Laboratory and for water quality analysis carried out at the Marine Chemitry Laboratory of the Raja Ali Haji Maritime University, Tanjungpinang City, Riau Islands Province. The method used is an experimental method using a completely randomized design (CRD) with 4 treatments and 3 replications. The results showed that the levels of ammonia and nitrite decreased after passing through the coconut shell charcoal fragments. The best reduction in ammonia and nitrite levels was obtained in treatment C (using coconut charcoal fragments of 30 g/liter of rearing container water), resulting in total ammonia nitrogen of (11,983±0.691) and nitrite (4.14±0.01), the length of time for filter performance for 2 days the level of ammonia (0.115±0 ppm) and nitrite level of (4.448±0)Penelitian dilaksanakan pada bulan September 2021, bertempatan di Laboratorium Marine Aquaculture dan untuk analisis kualitas air dilakukan di Laboratorium Marine Chemitry Universitas Maritim Raja Ali Haji, Kota Tanjungpinang, Provinsi Kepulauan Riau. Metode yang digunakan merupakan metode eksperimen menggunakan rancangan acak lengkap (RAL) dengan 4 perlakuan dan 3 ulangan. Hasil penelitian menunjukan bahwa kadar amonia dan nitrit mengalami penurunan sesudah melewati pecahan arang batok kelapa. Penurunan kadar amonia dan nitrit terbaik didapat pada perlakuan C (menggunakan pecahan arang kelapa 30 g/liter air wadah pemeliharaan), menghasilkan Total amonia nitrogen sebesar (11,983±0,691) dan nitrit (4,14±0,01), lama waktu kinerja filter selama 2 hari tingkat amonia (0,115±0 ppm) dan tingkat nitrit sebesar (4,448±0

RTK GPS Performance Assessment for Long Baseline Deformation Monitoring

An offshore platform or correctly is a large structure with facilities to drill wells, to extract and process oil and natural gas, and to temporarily store product until it can be brought to shore for refining and marketing. For a normal GPS, after we obtained the coordinates of certain point, we have to process them and this will take time. For RTK GPS, it is real time process. It means that the data obtained can be processed on time and this can reduce time and occupation load. When a platform is hit by external forces, it will move a little bit from its original position, maybe just about 10cm. How can we measure the movement of the platform at the middle of the sea? This project work will be using the knowledge that author had learnt during the period of study. It is a method to test for the practicality of the knowledge that had been learned. In conducting this project, the author has to study about RTK GPS performance, understand the concept and the functions of RTK GPS. Next, some tests are going to be conducted, which is distance, accuracy, precision, and performance of RTK GPS single-based test

ENT 530 Social Media Portfolio: Happizza / Muhammad Zulfadhli Syam Md Zuber

This report aims to achieve the main objective of Happizza that to be the best homemade pizza in Kuala Lumpur. This homemade pizza is to our beloved customer with affordable price and luxurious taste of pizza. Our business was started officially on 6 June in 2021. According to the customer who have try the pizza, our product gives a very delicious taste and feels like buying from big pizza store but cheaper. This product is also like by many citizens due to the sum of Malaysia taste of pizza that different from the others. Hence, this product provides a good insight for the continuation of sale to our customers. Since early of its opening, Happizza have sold their product more than 50 pack of pizza with variety of flavour that order by customer according to their tastes. Because of increasing demand for our product result into a good profitable sale revenue to our business product. As a result, Happizza's homemade pizza is a good marketable product of choice that can be expanded into many different places as the business grows

The transmission dynamic of the COVID 19 outbreak: A predictive dashboard

COVID 19 outbreak gives a great impact worldwide. The disaster of this pandemic has resulted in a large number of human lives being lost. As all countries implemented quarantine and social distancing, the great lockdown all over the world lead to multiple crises including health, economy, financial, and collapse in industrial and educational activities. Movement Control Order (MCO) and social distancing which have been implemented as control measures in Malaysia also affected many sectors. The landscape now has successfully reduced the number of infected people. However, from the economic point of view, the Retail Group Malaysia (RGM) has projected the country’s retail industry suffers a negative growth rate for the first time in 22 years. If the epidemic continues, society will reach an impasse, a time when the lockdown will become more than some of them can tolerate. As recognized by the World Health Organization (WHO), modelling the outbreak based on the prior input data is more appropriate than the ‘risk of bias’ for decision-makers. Thus, this research is conducted to model the outbreak of the disease using the susceptible-infected-recovery-death (SIRD) compartmental model accompanying with the varying infection rate due to changes in MCO measures. The model assumes under the unavailability of the vaccine, recovered people can be reinfected. The epidemic parameters and reproduction numbers are estimated and fitted from the transmission model to the actual data using the Monte Carlo Markov Chain (MCMC) of Metropolis-Hasting. The model is solved using a numerical algorithm of the Runge-Kutta method. The predictive dashboard of a graphical user interface (GUI) is developed, hence monitoring and predicting the outbreak under the control measures of the two different types of MCO scenarios (which are called constant and alternate scenarios) can be performed. GUI for the dynamic transmission of the COVID 19 provides insight for the future outbreak, hence may help the respective stakeholders to propose the best policy of a new norm for all sectors. From the GUI, we can see that, when no or loose MCO is implemented or compliance of the public to the COVID 19 standard operating procedure (SOP), the infected case will increase rapidly up to 7.5 million. With strict MCO regulation or public obedient to the SOP, the infected case will decrease rapidly, but even after a long period of strict regulation, once the quarantine is stopped, the infected case will rise again. An alternative MCO scenario is suggested where a cyclic pattern of strict and loose MCO regulation is upheld, and it shows to flatten the curve while allow periods of less restricted lifestyle. This can be one of the alternatives to balance the life and livelihood

Predictive Analytics of the Covid-19 Outbreak Under Uncertainty of the Disease Spreading

COVID-19 pandemic was identified in Wuhan, China in 2019 and has spread at a tremendous rate affecting all countries over the world. Understanding the spreading disease is crucial; hence, the dynamic behaviour of the disease can be predicted. This paper is aimed to model the COVID-19 outbreak by extending the deterministic susceptible-infected-recovered-death (DSIRD) into a stochastic SIRD (SSIRD) model. Infectious rate parameter of the DSIRD model is perturbed with Brownian motion to reflect the uncertainty of the COVID-19 outbreak. Fourth order stochastic Runge-Kutta (SRK4) method is used to simulate the model. Parameter estimation is estimated using the Markov Chain Monte Carlo (MCMC) method. The simulated results for three ASEAN countries of Malaysia, Indonesia and Singapore indicate that SSIRD model is consistent with the infected COVID-19 data;hence, shows the model is adequate in explaining the behaviour of the infectious disease

Estimation of the Epidemiological Parameter for the COVID-19 Outbreak

The COVID-19 pandemic has affected worldwide with unprecedented catastrophes. Susceptible-Infected-Recovered-Death (SIRD) model is a well-known mathematical model to replicate the illness epidemic. Estimation of the epidemiological parameters of the SIRD model is crucial for understanding the virus's transmission and effect of the virus, thus, helping in making informed decisions about the required interventions. In this study, we propose a Metropolis-Hastings algorithm of the Markov Chain Monte Carlo (MCMC) method to estimate the epidemiological parameters of infectious rate, fatality rate, recovery rate, and reproduction numbers. An analysis is performed to investigate how the parameter changes throughout the lifespan of the pandemic. Numerical results show that the Metropolis-Hastings algorithm can adequately estimate the parameters of the COVID-19 pandemic, providing valuable insights into the spread of the virus and the changes in the pandemic behavior over time