Thermal Effects for Shaft-Pre-Stress on Rotor Dynamic System

This Paper outlines study behaviour of rotating shaft with high speed under thermal effects. The method of obtaining the frequency response functions of a rotor system with study whirl effect in this revision the raw data obtained from the experimental results (using Smart Office program) are curve-fitted by theoretical data regenerated from some of the experimental data and simulating it using finite element (ANSYS 12). (FE) models using the Eigen analysis capability were used to simulate the vibration. The results were compared with experimental data show analysis data with acceptable accuracy and performance. The rotating effect causes un-symmetry in the system matrices, resulting in complexity in decoupling the mathematical models of the system for the purpose of modal analysis. Different method is therefore required, which can handle general system matrices rather than symmetrical matrices, which is normal for passive structures. Mathematical model of the system from the test data can be assembled. The frequency response functions are extracted, Campbell diagram are draw and simulated. (FE) is used to carry out such as simulation since it has good capability for Eigen analysis and also good graphical facility. Keywords: Thermal effects, Modelling, Campbell diagram, Whirl, Rotor dynamics.Comment: Published by: Academic Research Publishing Agency. All rights reserved, 6 pages, 4 figures, 1 pictur

Defect Diagnosis in Rotors Systems by Vibrations Data Collectors Using Trending Software

Vibration measurements have been used to reliably diagnose performance problems in machinery and related mechanical products. A vibration data collector can be used effectively to measure and analyze the machinery vibration content in gearboxes, engines, turbines, fans, compressors, pumps and bearings. Ideally, a machine will have little or no vibration, indicating that the rotating components are appropriately balanced, aligned, and well maintained. Quick analysis and assessment of the vibration content can lead to fault diagnosis and prognosis of a machine's ability to continue running. The aim of this research used vibration measurements to pinpoint mechanical defects such as (unbalance, misalignment, resonance, and part loosening), consequently diagnosis all necessary process for engineers and technicians who desire to understand the vibration that exists in structures and machines. Keywords- vibration data collectors; analysis software; rotating components.Comment: 11 pages,6 figures,1 pictuer,1 schem

Nonlinear free vibration analysis of the functionally graded beams

Nonlinear natural oscillations of beams made from functionally graded material (FGM) are studied in this paper. The equation of motion is derived according to the EulerBernoulli beam theory and von Karman geometric nonlinearity. Subsequently, Galerkin’s solution technique is applied to obtain the corresponding ordinary differential equation (ODE) for the FGM beam. This equation represents a kind of a nonlinear ODE containing quadratic and cubic nonlinear terms. This nonlinear equation is then solved by means of three efficient approaches. Homotopy perturbation method is applied at the first stage and the corresponding frequency-amplitude relationship is obtained. Frequency-amplitude formulation and Harmonic balance method are then employed and the consequent frequency responses are determined. In addition, Parameter Expansion Method is utilized for evaluating the nonlinear vibration of the system. A parametric study is then conducted to evaluate the influence of the geometrical and mechanical properties of the FGM beam on its frequency responses. Different types of material properties and boundary conditions are taken into account and frequency responses of the system are evaluated for different gradient indexes. The frequency ratio (nonlinear to linear natural frequency) is obtained in terms of the initial amplitude and compared for different materials and end conditions

Modeling Barriers to Social Responsibility Accounting (SRA) and Ranking its Implementation Strategies to Support Sustainable Performance – a study in an emerging market

Purpose Today, with the increasing involvement of the environment and human beings business units, paying attention to fulfilling social responsibility obligations while making a profit has become increasingly necessary for achieving sustainable development goals. Attention to profit by organizations should not be without regard to their social and environmental performance. Social responsibility accounting (SRA) is an approach that can pay more attention to the social and environmental performance of companies, but it has many barriers. Therefore, the purpose of this study is to identify barriers to SRA implementation and provide strategies to overcome these barriers. Design/methodology/approach In this study, the authors identify barriers to social responsibility accounting implementation and provide strategies to overcome these barriers. By literature review, 12 barriers and seven strategies were identified and approved using the opinions of six academic experts. Interpretive structural modeling (ISM) has been used to identify significant barriers and find textual relationships between them. The fuzzy technique for order performance by similarity to ideal solution (TOPSIS) method has been used to identify and rank strategies for overcoming these barriers. This study was undertaken in Iran (an emerging market). The data has been gathered from 18 experts selected using purposive sampling and included CEOs of the organization, senior accountants and active researchers well familiar with the field of social responsibility accounting. Findings Based on the results of this study, the cultural differences barrier was introduced as the primary and underlying barrier of the social responsibility accounting barriers model. At the next level, barriers such as “lack of public awareness of the importance of social responsibility accounting, lack of social responsibility accounting implementation regulations and organization size” are significant barriers to social responsibility accounting implementation. Removing these barriers will help remove other barriers in this direction. In addition, the results of the TOPSIS method showed that “mandatory regulations, the introduction of guidelines and social responsibility accounting standards,” “regulatory developments and government incentive schemes to implement social responsibility accounting,” as well as “increasing public awareness of the benefits of social responsibility accounting” are some of the essential social responsibility accounting implementation strategies. Practical implications The findings of the study have implications for both professional accounting bodies for developing the necessary standards and for policymakers for adopting policies that facilitate the implementation of social responsibility accounting to achieve sustainability. Social implications This paper creates a new perspective on the practical implementation of social responsibility accounting, closely related to improving environmental performance and increasing social welfare through improving sustainability. Originality/value Experts believe that the strategies mentioned above will be very effective and helpful in removing the barriers of the lower level of the model. To the best of the authors’ knowledge, for the first time, this study develops a model of social responsibility accounting barriers and ranks the most critical implementation strategies

Prediabetes and diabetes prevalence and risk factors comparison between ethnic groups in the United Arab Emirates

The economic growth has paralleled the rise of diabetes and its complications in multiethnic population of United Arab Emirates (UAE). Previous studies have shown that characteristics of diabetes is variable across different ethnicities. The objective of this study was to compare diabetes prevalence and risk factors between UAE nationals and different expatriate's ethnic groups in UAE using data from UAE National Diabetes and Lifestyle Study (UAEDIAB). The UAE nationals made one-fourth (n = 797, 25%) of total cohort and the remaining 75% belonged to immigrants. Across different ethnicities, adjusted prevalence of prediabetes ranged from 8% to 17%, while adjusted prevalence of newly diagnosed diabetes ranged from 3% to 13%. UAE nationals, Arabs non-nationals and Asians had the highest number of pre-diabetic as well as newly diagnosed diabetic patients. Adjusted prevalence of diabetes was highest in UAE nationals (male 21% and female 23%) as well as Asian non-Arabs (male 23% and female 20%), where 40% of both groups fell under the range of either prediabetes or diabetes conditions. Multivariate factors of diabetes versus non-diabetes included older age, ethnicities of Asian non-Arabs and local UAE nationals, family history of diabetes, obesity, snoring, decreased level of high density lipoprotein, elevated levels of triglycerides and blood pressure. In conclusion, diabetes prevalence and risk factors vary across the different ethnic groups in UAE, and hence interventions towards identification and prevention of diabetes should not treat all patients alike

Production Scheduling and Waste Disposal Planning for Oil Sands Mining Using Goal Programming

In oil sands mining, timely provisions of ore and tailings containment with less environmental footprints are the main drivers of profitability and sustainability. The recent Alberta Energy Resources Conservation Board Directive 074 requires oil sands waste disposal planning to be an integral part of mine planning. This requires the development of a well integrated strategy of directional mining and tailings dyke construction for in-pit and ex-pit tailings storage management. The objectives of this paper are to: 1) determine the order and time of extraction of ore, dyke material and waste that maximizes the net present value; 2) determine the destination of dyke material that minimizes construction cost; and 3) minimize deviations from the production goals of the mining operation. We have developed, implemented, and verified a theoretical optimization framework based on mixed integer linear goal programming (MILGP) to address these objectives. This study presents an integration of mixed integer linear programming and goal programming in solving large scale mine planning optimization problems using clustering and pushback techniques. Application of the MILGP model was presented with an oil sands mining case. The MILGP model generated a smooth and uniform mining schedule that generates value and provides a robust framework for effective waste disposal planning. The results show that mining progresses with an ore to waste ratio of 1:1.5 throughout the mine life, generating an overall net present value of $14,237M. This approach improves the sustainable development of oil sands through better waste management

A Pilot Study on Facial Expression Recognition Ability of Autistic Children Using Ryan, a Rear-Projected Humanoid Robot

Rear-projected robots use computer graphics technology to create facial animations and project them on a mask to show the robot’s facial cues and expressions. These types of robots are becoming commercially available, though more research is required to understand how they can be effectively used as a socially assistive robotic agent. This paper presents the results of a pilot study on comparing the facial expression recognition abilities of children with Autism Spectrum Disorder (ASD) with typically developing (TD) children using a rear-projected humanoid robot called Ryan. Six children with ASD and six TD children participated in this research, where Ryan showed them six basic expressions (i.e. anger, disgust, fear, happiness, sadness, and surprise) with different intensity levels. Participants were asked to identify the expressions portrayed by Ryan. The results of our study show that there is not any general impairment in expression recognition ability of the ASD group comparing to the TD control group; however, both groups showed deficiencies in identifying disgust and fear. Increasing the intensity of Ryan’s facial expressions significantly improved the expression recognition accuracy. Both groups were successful to recognize the expressions demonstrated by Ryan with high average accuracy