A New Exponentiated Distribution with Engineering Science Applications

2020 ◽  
Vol 9 (1) ◽  
pp. 127-137
Keyword(s):  
Engineering Science ◽  
Exponentiated Distribution

Characterization of Impressed Current Technique to Model Corrosion of Reinforcement in Concrete

2020 ◽  
Vol 11 (1) ◽  
pp. 93-99
Author(s):  
Abu Zakir Morshed ◽  
Sheikh Shakib ◽  
Tanzim Jahin
Keyword(s):  
Immersion Time ◽  
Chloride Content ◽  
Engineering Science ◽  
Coastal Regions ◽  
Faraday’S Law ◽  
Current Technique ◽  
Corrosion Cell ◽  
Impressed Current

Corrosion of reinforcement is an important durability concern for the structures exposed to coastal regions. Since corrosion of reinforcement involves long periods of time, impressed current technique is usually used to accelerate the corrosion of reinforcement in laboratories. Characterization of impressed current technique was the main focus of this research,which involved determination of optimum chloride content and minimum immersion time of specimens for which the application of Faraday’s law could be efficient. To obtain optimum chloride content, the electrolytes in the corrosion cell were prepared similar to that of concrete pore solutions. Concrete prisms of 200 mm by 200 mm by 300 mm were used to determine the minimum immersion time for saturation. It was found that the optimum chloride content was 35 gm/L and the minimum immersion time for saturation was 140 hours. Accounting the results, a modified expression based on Faraday’s law was proposed to calculate weight loss due to corrosion. Journal of Engineering Science 11(1), 2020, 93-99

Reality brings excitement to engineering education

1998 ◽  
Vol 12 (1) ◽  
pp. 83-86
Author(s):  
LARRY LEIFER ◽  
SHERI SHEPPARD
Keyword(s):  
Engineering Education ◽  
Social Activity ◽  
Thinking Skills ◽  
Engineering Practice ◽  
Engineering Science ◽  
Science And Engineering ◽  
Engineering Product ◽  
Intellectual Content ◽  
Versus Communication ◽  
Constant Source

The intellectual content and social activity of engineering product development are a constant source of surprise, excitement, and challenge for engineers. When our students experience product-based-learning (PBL), they experience this excitement (Brereton et al., 1995). They also have fun and perform beyond the limits required for simple grades. We, their teachers, experience these things too. Why, then, are so few students and faculty getting the PBL message? How, then, can we put the excitement back in engineering education? In part, we think this is because of three persistent mistakes in engineering education:1. We focus on individual students.2. We focus on engineering analysis versus communication between engineers.3. We fail to integrate thinking skills in engineering science and engineering practice.

scholarly journals The Flexible Burr X-G Family: Properties, Inference, and Applications in Engineering Science

Symmetry ◽  
2021 ◽  
Vol 13 (3) ◽  
pp. 474
Author(s):  
Abdulhakim A. Al-Babtain ◽  
Ibrahim Elbatal ◽  
Hazem Al-Mofleh ◽  
Ahmed M. Gemeay ◽  
Ahmed Z. Afify ◽  
...  
Keyword(s):  
Numerical Simulations ◽  
Exponential Distribution ◽  
Real Data ◽  
Exponential Model ◽  
Statistical Properties ◽  
Engineering Science ◽  
Data Sets ◽  
Engineering Sciences ◽  
General Statistical ◽  
Anderson Darling

In this paper, we introduce a new flexible generator of continuous distributions called the transmuted Burr X-G (TBX-G) family to extend and increase the flexibility of the Burr X generator. The general statistical properties of the TBX-G family are calculated. One special sub-model, TBX-exponential distribution, is studied in detail. We discuss eight estimation approaches to estimating the TBX-exponential parameters, and numerical simulations are conducted to compare the suggested approaches based on partial and overall ranks. Based on our study, the Anderson–Darling estimators are recommended to estimate the TBX-exponential parameters. Using two skewed real data sets from the engineering sciences, we illustrate the importance and flexibility of the TBX-exponential model compared with other existing competing distributions.

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