scholarly journals Design of Petroleum Physical Properties Prediction Application

2021 ◽  
Vol 1 (1) ◽  
pp. 610-619
Author(s):  
Harry Budiharjo Sulistyarso ◽  
Dyah Ayu Irawati ◽  
Joko Pamungkas ◽  
Indah Widiyaningsih
Keyword(s):  
Mathematical Model ◽  
User Interface ◽  
Physical Properties ◽  
Polynomial Regression ◽  
Regression Method ◽  
User Needs ◽  
Multivariate Polynomial ◽  
Density Data ◽  
Interface System ◽  
Made In

Based on the results of previous studies regarding the modeling of the physical properties of petroleum, a mathematical model has been built to calculate the prediction of the physical properties of petroleum. The prediction is based on viscosity, interfacial tension, and density data from the EOR laboratory in UPN Veteran Yogyakarta. The model still cannot be used independently without the Python environment, so to be used easily by more users, the model must be built into an independent application that can be installed on the user's device. In this research, the application design for the physical properties of petroleum prediction application will be carried out. The application is built using the Multivariate Polynomial Regression method according to the model to predict the physical properties of petroleum, and uses Naïve Bayes to classify the petroleum, and will be the changing result of the physical properties of petroleum modeling that has been made in a previous study. The shift from model to the application requires several adjustments, including user interface, system, and database adjustments which are implemented as the designs of application. . The design is done before the application is built to suit user needs as the result of the research.

scholarly journals Petroleum Physical Properties Prediction Application in Enhanced Oil Recovery Process

2021 ◽  
Vol 10 (4) ◽  
pp. 139-147
Author(s):  
Harry Budiharjo Sulistyarso ◽  
◽  
Dyah Ayu Irawati ◽  
Joko Pamungkas ◽  
Indah Widiyaningsih ◽  
...  
Keyword(s):  
Interfacial Tension ◽  
Physical Properties ◽  
Enhanced Oil Recovery ◽  
Oil Recovery ◽  
Naive Bayes ◽  
Polynomial Regression ◽  
Laboratory Data ◽  
Naïve Bayes ◽  
Regression Equations ◽  
Multivariate Polynomial

The Enhanced Oil Recovery (EOR) process is one of the ways in the petroleum exploitation process so that thick oil can be lifted to the surface and produced. The EOR process referred to in this study is the EOR process carried out in previous studies at the EOR laboratory of UPN Veteran Yogyakarta Indonesia by adding biosurfactants and adjusting the temperature. In laboratory experiments, each time an amount of biosurfactant concentration is added and the temperature is adjusted, the calculation must be done repeatedly to determine the amount of viscosity, interfacial tension (IFT), and density. This experiments takes a long time, requires high cost and variety limitation of the condition. The previous research has succeeded in building a model with multivariate polynomial regression equations to predict the value of the physical properties of crude oil from existing data then classify it into three categories using Naive Bayes, i.e., light oil, medium oil, and heavy oil. The physical properties of petroleum measured in the research are viscosity, interfacial tension, and density. The model uses laboratory data which are taken from the test results of Pertamina's KW-55 well as validation. The validation result shows that Multivariate Polynomial Regression has succeeded in predicting the value of viscosity, interfacial tension, and density with error values ranging from 0% to 1% from the sample data. With a low error value, the application can make forecasting with more variable conditions. The model still cannot be used independently without the Python environment, so to be used easily by more users, the model must be built into an independent application that can be installed on the user's device. In this research, the prediction application of petroleum physical properties has been built. The application is made using the Multivariate Polynomial Regression method according to the model in the previous study to predict the physical properties of petroleum, then uses Naïve Bayes to classify the oil. The application completed the several adjustment to shift from model to application, including user interface, system, and database adjustments.

Imprecision of Laboratory Determinations and Diagnostic Accuracy: Theoretical Considerations

1974 ◽  
Vol 13 (03) ◽  
pp. 151-158 ◽  
Author(s):  
D. A. B. Lindbebo ◽  
Fr. R. Watson
Keyword(s):  
Mathematical Model ◽  
Diagnostic Accuracy ◽  
Diagnostic Process ◽  
Clinical Laboratories ◽  
Non Linear ◽  
Theoretical Considerations ◽  
Made In

Recent studies suggest the determinations of clinical laboratories must be made more precise than at present. This paper presents a means of examining benefits of improvement in precision. To do this we use a mathematical model of the effect upon the diagnostic process of imprecision in measurements and the influence upon these two of Importance of Diagnosis and Prevalence of Disease. The interaction of these effects is grossly non-linear. There is therefore no proper intuitive answer to questions involving these matters. The effects can always, however, be calculated.Including a great many assumptions the modeling suggests that improvements in precision of any determination ought probably to be made in hospital rather than screening laboratories, unless Importance of Diagnosis is extremely high.

WIELAND-SW1

Alloy Digest ◽  
2015 ◽  
Vol 64 (9) ◽  
Keyword(s):  
Corrosion Resistance ◽  
Physical Properties ◽  
Tensile Properties ◽  
Heat Treating ◽  
Lead Free ◽  
Made In

Abstract Wieland-SW1 is a lead-free special brass made in extruded and drawn products. This datasheet provides information on composition, physical properties, hardness, elasticity, and tensile properties as well as fatigue. It also includes information on corrosion resistance as well as forming, heat treating, and joining. Filing Code: Cu-841. Producer or source: Wieland Metals Inc. and Wieland-Werke AG.

MULTIMET (N-155)

Alloy Digest ◽  
1961 ◽  
Vol 10 (12) ◽  
Keyword(s):  
High Temperature ◽  
Physical Properties ◽  
Heat Treating ◽  
Age Hardening ◽  
Nickel Chromium ◽  
Cobalt Nickel ◽  
Temperature Performance ◽  
High Oxidation ◽  
Scaling Resistance ◽  
Made In

Abstract MULTIMET alloy is cobalt-nickel-chromium-iron austenitic alloy having high oxidation and scaling resistance along with good high-temperature properties. It tends to work harden but does not respond significantly to age-hardening. It is made in a wrought grade (0.08-0.16% carbon) and a casting grade (0.20% max. carbon). This datasheet provides information on composition, physical properties, elasticity, and tensile properties as well as creep and fatigue. It also includes information on high temperature performance as well as forming, heat treating, machining, and joining. Filing Code: SS-28. Producer or source: Haynes Stellite Company. Originally published May 1955, revised December 1961.

Lumped Parameter Modeling of a Magnetorheological Fluid Clutch

2006 ◽  
Author(s):  
John C. Ulicny ◽  
Daniel J. Klingenberg ◽  
Anthony L. Smith ◽  
Zongxuan Sun
Keyword(s):  
Mathematical Model ◽  
Physical Properties ◽  
Magnetorheological Fluid ◽  
Input Current ◽  
Fluid Composition ◽  
Fluid Temperature ◽  
Temperature Range ◽  
Lumped Parameter ◽  
Lumped Parameter Modeling ◽  
Fan Speed

A lumped-parameter mathematical model of an automotive magnetorheological (MR) fluid fan clutch was developed. This model is able to describe the average fluid temperature, average clutch temperature, and output fan speed as a function of time, input current, and fluid composition. The model also reproduces numerous features of fan operation observed experimentally and revealed a mechanism for some observed cases of hysteresis. However, it fails to capture certain other features which lead us to conclude that phenomena which are not included in the model, e.g., sedimentation and re-suspension, are important to the clutch behavior. In addition, the results indicate that certain physical properties need to be measured over a larger temperature range in order for the model to better predict the clutch behavior.

User Interface, System Design

2015 ◽  
pp. 1561-1565
Author(s):  
Jianjie Li ◽  
Xin Yang ◽  
Xunqiang Tao ◽  
Jie Tian
Keyword(s):  
User Interface ◽  
System Design ◽  
Interface System

scholarly journals Prototype User Interface Mobile App E-Learning

2021 ◽  
Vol 7 (1) ◽  
pp. 61-70
Author(s):  
Henderi Henderi ◽  
Praditya Aliftiar ◽  
Alwan Hibatullah
Keyword(s):  
User Interface ◽  
User Interfaces ◽  
Mobile Application ◽  
Mobile App ◽  
User Needs ◽  
High Fidelity ◽  
Application Development ◽  
E Learning ◽  
Prototype Design ◽  
People Today

Information technology has developed rapidly from time to time. One of the technologies commonly owned by many people today is smartphones with the Android and IOS platforms. By knowing this factor, mobile developers compete with each other to design applications with attractive user interfaces so that users are interested in using them. At this stage in mobile application development, starting from designing a user interface prototype. This stage aims to visualize user needs, improve user experience and simplify the coding process by programmers. In this study, researchers applied the prototype method. This research produces a prototype design for the e-learning application user interface which consists of a high fidelity prototype.

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