Jerzy P. Komorowski and David S. Forsyth
The current corrosion maintenance philosophy reflected in aviation regulations and recommended practices does not stimulate progress in corrosion related technology. A US Air…
Abstract
The current corrosion maintenance philosophy reflected in aviation regulations and recommended practices does not stimulate progress in corrosion related technology. A US Air Force (USAF)‐sponsored survey has recommended re‐examination of corrosion maintenance policies and practices to identify lower cost alternatives, and has encouraged research into tools and techniques that reduce maintenance costs while preserving safety. In particular, these include models to predict the impact of existing corrosion damage on structural integrity, methods of predicting corrosion growth rates and nondestructive inspection systems capable of providing corrosion metrics. The Institute for Aerospace Research of the National Research Council Canada (IAR/NRC) has pioneered work on the application of enhanced visual methods for corrosion detection in lap joints and the assessment of the impact of corrosion on lap‐joint structural integrity. The role of these enhanced visual methods in the new corrosion management is described.
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An overview of the advances in understanding the impact of corrosion on structural integrity and the associated tools available for inspection, assessment and repair is presented…
Abstract
An overview of the advances in understanding the impact of corrosion on structural integrity and the associated tools available for inspection, assessment and repair is presented. A comprehensive set of these tools would allow for a significant shift in aircraft maintenance concepts.
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Tooraj Karimi and Jeffrey Yi-Lin Forrest
The purpose of this paper is to analyze the energy audit reports in order to define the most favorable factors affecting energy consumption of buildings. Since energy audit of…
Abstract
Purpose
The purpose of this paper is to analyze the energy audit reports in order to define the most favorable factors affecting energy consumption of buildings. Since energy audit of buildings includes assessment of occupants comfort level in addition to the technical data of buildings so some rules are extracted to model the employees thermal comfort level in organization.
Design/methodology/approach
Some tools of RST and GIA are used in this research to analyze the energy consumption of official buildings. “Average energy consumption of building per year” is selected as a system characteristic in GIA and as a decision attribute in RST to show the behavior of buildings energy consumption. Ten technical sequences of buildings are chosen as relevant factors of behavior and conditional attributes in GIA and RST. In order to model the employees thermal comfort level in organization by RST, ten technical attributes of buildings are selected as condition attributes and thermal comfort level of employees is selected as decision attribute. Due to the different algorithms of data complement, discretization, reduction, and rule generation, four rule models are constructed. Cross-validation is used for evaluation of the model results and the best model is chosen with 62 rules and 99.8 percent of accuracy.
Findings
According to the results of GIA and RST, “Uncontrolled area of the building” has been diagnosed as the most important factor between other relevant factors/attributes and it has the greatest effect on energy consumption of building. Four rule models have been extracted from deferent decision tables in order to describe the thermal comfort level of employees in organization. The maximum number of rules relates to the conditional combination/GA model with 1263 rules and average accuracy of 99.7 percent and the minimum number relates to the conditional combination/Janson model with 62 rules and average accuracy of 99.8 percent.
Research limitations/implications
The total observations for rule extraction is 81 and the results can be improved by further samples.
Originality/value
It shows that “Uncontrolled area of the building” is the most important factor/attribute to define the consumption of buildings and thermal comfort level of employees in organization.
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Tooraj Karimi, Mohammad Reza Sadeghi Moghadam and Amirhosein Mardani
This paper aims to design an expert system that gets data from researchers and determines their maturity level. This system can be used for determining researchers’ support…
Abstract
Purpose
This paper aims to design an expert system that gets data from researchers and determines their maturity level. This system can be used for determining researchers’ support programs as well as a tool for researchers in research-based organizations.
Design/methodology/approach
This study focuses on designing the inference engine as a component of an expert system. To do so, rough set theory is used to design rule models. Various complete, discretizing and reduction algorithms are used in this paper, and different models were run.
Findings
The proposed inference engine has the validity of 99.8 per cent, and the most important attributes to determine the maturity level of researchers in this model are “commitment to research” and “attention to research plan timeline”.
Research limitations/implications
To accurately determine researchers’ maturity model, solely referring to documents and self-reports may reduce the validation. More validation could be reached through using assessment centers for determining capabilities of samples and observations in each maturity level.
Originality/value
The assessment system for the professional maturity of researchers is an appropriate tool for funders to support researchers. This system helps the funders to rank, validate and direct researchers. Furthermore, it is a valid criterion for researchers to evaluate and improve their abilities. There is not any expert system to assess the researches in literature, and all models, frameworks and software are conceptual or self-assessment.