scholarly journals Simulation Experiment Analysis and Verification of Ship Resonance for Shipboard Helicopter

2021 ◽  
Vol 2029 (1) ◽  
pp. 012015
Author(s):  
Yan Zhu ◽  
Yuhui Lu ◽  
Fengnan Sun ◽  
Qiyou Cheng ◽  
Siwen Wang ◽  
...  
Author(s):  
A. Koto

The objective of this paper is to determine the optimum anaerobic-thermophilic bacterium injection (Microbial Enhanced Oil Recovery) parameters using commercial simulator from core flooding experiments. From the previous experiment in the laboratory, Petrotoga sp AR80 microbe and yeast extract has been injected into core sample. The result show that the experiment with the treated microbe flooding has produced more oil than the experiment that treated by brine flooding. Moreover, this microbe classified into anaerobic thermophilic bacterium due to its ability to live in 80 degC and without oxygen. So, to find the optimum parameter that affect this microbe, the simulation experiment has been conducted. The simulator that is used is CMG – STAR 2015.10. There are five scenarios that have been made to forecast the performance of microbial flooding. Each of this scenario focus on the injection rate and shut in periods. In terms of the result, the best scenario on this research can yield an oil recovery up to 55.7%.


Author(s):  
M. Safrudin ◽  
Sutaryat Trisnamansyah ◽  
Tb. Abin Syamsuddin Makmun ◽  
Deni Darmawan

The aimed of this studied was developed learning through computer-assisted as BCBL. Result of this studied have been stated that: (a) the potential of five high schools in Karawang districts supported the implementation of BCBL development, (b) planning of BCBL development through a systematic development stages from preparation, production, simulation, experiment, and publication, (c) the implementation result of BCBL learning through revision tested were learner activity and higher autonomy. Keywords: BCBL; Independence Self-reliance; Student Competence.


2006 ◽  
Author(s):  
Steve Elgar ◽  
Britt Raubenheimer ◽  
R. T. Guza
Keyword(s):  

Author(s):  
Gang Li ◽  
Binren Zhang

Background: Electromagnetic detection is an important method of geophysical exploration. The transmitting system is an important part of the electromagnetic detection equipment. Methods: The general topologies of a transmitting system for EM instrument are analyzed. The basic principle of EM detection is interpreted. In order to improve the output power and give consideration to the dynamic performance, an electromagnetic transmitting system based on the tri-state boost converter is proposed in this paper. Results: The principle of the proposed transmitting system is analyzed. The topology of the proposed transmitting system is illustrated and the working modes of tri-state boost converter are given. Conclusion: The simulation model is established and the simulation experiment is carried out to verify the feasibility of the new electromagnetic transmitting system.


Author(s):  
B. Mathura Bai ◽  
N. Mangathayaru ◽  
B. Padmaja Rani ◽  
Shadi Aljawarneh

: Missing attribute values in medical datasets are one of the most common problems faced when mining medical datasets. Estimation of missing values is a major challenging task in pre-processing of datasets. Any wrong estimate of missing attribute values can lead to inefficient and improper classification thus resulting in lower classifier accuracies. Similarity measures play a key role during the imputation process. The use of an appropriate and better similarity measure can help to achieve better imputation and improved classification accuracies. This paper proposes a novel imputation measure for finding similarity between missing and non-missing instances in medical datasets. Experiments are carried by applying both the proposed imputation technique and popular benchmark existing imputation techniques. Classification is carried using KNN, J48, SMO and RBFN classifiers. Experiment analysis proved that after imputation of medical records using proposed imputation technique, the resulting classification accuracies reported by the classifiers KNN, J48 and SMO have improved when compared to other existing benchmark imputation techniques.


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