Showing 7 results for Jalali
H. Ahmadian, S. Nazari , H. Jalali ,
Volume 18, Issue 4 (International Journal of Engineering 2007)
Abstract
Abstract: The governing equations of motion for a drill string considering coupling between axial, lateral and torsional vibrations are obtained using a Lagrangian approach. The result leads to a set of non-linear equations with time varying coefficients. A fully coupled model for axial, lateral, and torsional vibrations of drill strings is presented. The bit/formation interactions are assumed to be related to the following parameters: bit motion, effects of gyroscopic moments, contact with the borehole wall, axial excitation due to bit/formation interactions, and hydrodynamic damping due to the presence of drilling mud. Simulation results show that parametric resonance and whirling may occur simultaneously within the range of operating conditions of drilling. The contact force between collar and borehole wall is calculated and its behavior is investigated. The dynamic behavior is quite complicated and may become non-periodic, suggesting a chaotic behavior.
R. Sadeghian, G.r. Jalali-Naini, J. Sadjadi, N. Hamidi Fard ,
Volume 19, Issue 4 (IJIE 2008)
Abstract
In this paper Semi-Markov models are used to forecast the triple dimensions of next earthquake occurrences. Each earthquake can be investigated in three dimensions including temporal, spatial and magnitude. Semi-Markov models can be used for earthquake forecasting in each arbitrary area and each area can be divided into several zones. In Semi-Markov models each zone can be considered as a state of proposed Semi-Markov model. At first proposed Semi-Markov model is explained to forecast the three mentioned dimensions of next earthquake occurrences. Next, a zoning method is introduced and several algorithms for the validation of the proposed method are also described to obtain the errors of this method.
S. G. Jalali Naini , M. B. Aryanezhad, A. Jabbarzadeh , H. Babaei ,
Volume 20, Issue 3 (IJIEPR 2009)
Abstract
This paper studies a maintenance policy for a system composed of two components, which are subject to continuous deterioration and consequently stochastic failure. The failure of each component results in the failure of the system. The components are inspected periodically and their deterioration degrees are monitored. The components can be maintained using different maintenance actions (repair or replacement) with different costs. Using stochastic regenerative properties of the system, a stochastic model is developed in order to analyze the deterioration process and a novel approach is presented that simultaneously determines the time between two successive inspection periods and the appropriate maintenance action for each of the components based on the observed degrees of deterioration. This approach considers different criteria like reliability and long-run expected cost of the system. A numerical example is provided in order to illustrate the implementation of the proposed approach.
M. Miranbeigi, A.a. Jalali, A. Miranbeigi ,
Volume 22, Issue 3 (IJIEPR 2011)
Abstract
supply chain network receding horizon control demand move suppression term |
Supply chain networks are interconnection and dynamics of a demand network. Example subsystems, referred to as stages, include raw materials, distributors of the raw materials, manufacturers, distributors of the manufactured products, retailers, and customers. The main objectives of the control strategy for the supply chain network can be summarized as follows: (i) maximize customer satisfaction, and (ii) minimize supply chain operating costs. In this paper, we applied receding horizon control (RHC) method to a set of large scale supply chains of realistic size under demand disturbances adaptively. Also in order to increase the robustness of the system , we added a move suppression term to cost function .
Gholam Reza Jalali Naieni, Ahmad Makui, Rouzbeh Ghousi,
Volume 23, Issue 1 (IJIEPR 2012)
Abstract
Fuzzy Logic is one of the concepts that has created different scientific attitudes by entering into various professional fields nowadays and in some cases has made remarkable effects on the results of the practical researches. However, the existence of stochastic and uncertain situations in risk and accident field, affects the possibility of the forecasting and preventing the occurrence of the accident and the undesired results of it.
In this paper, fuzzy approach is used for risk evaluating and forecasting, in accidents caused by working with vehicles such as lift truck. Basically, by using fuzzy rules in forecasting various accident scenarios, considering all input variables of research problem, the uncertainty space in the research subject is reduced to the possible minimum state and a better capability of accident forecasting is created in comparison to the classic two-valued situations. This new approach helps the senior managers make decisions in risk and accident management with stronger scientific support and more reliably.
Mehrdad Jalali Sepehr, Abdorrahman Haeri, Rouzbeh Ghousi,
Volume 30, Issue 4 (IJIEPR 2019)
Abstract
Abstract
Background: In this paper healthcare condition of 31 countries that are the members of Organization for Economic and Co-operative Development (OECD) is measured by considering 14 indicators that are relevant to three main pillars of sustainable development.
Method: To estimate the efficiency scores, Principle Component Analysis-Data Envelopment Analysis PCA-DEA additive model in both forms of envelopment and multiplier is used to determine efficiency scores and also to define benchmarks and improvement plan for the inefficient countries. Then Decision Tree Analysis is also used to realize that which factors were the most influential ones to make a county an efficient Decision Making Unit (DMU).
Results: According to the PCA-DEA additive model, among 31 OECD countries, 16 countries have become inefficient, that USA have taken the lowest efficiency score, and among efficient countries Iceland could be considered as a paragon which has the highest frequency between the countries that are defined as the benchmarks. Decision tree analysis also show that exposure to PM2.5 is an influential factor on the efficiency status of countries.
Conclusion: This research gives an insight about the sustainable development and healthcare system and show the impressive effect of environmental and social factors like: exposure to PM2.5 and water quality, population insurance coverage, and AIDS on the healthcare efficiency of OECD countries
Hessam Nedaei, Seyed Gholamreza Jalali Naini, Ahmad Makui,
Volume 32, Issue 1 (IJIEPR 2021)
Abstract
Data envelopment analysis (DEA) measures the relative efficiency of decision-making units (DMU) with multiple inputs and multiple outputs. In the case of considering a working team as a DMU, it often comprises multiple positions with several employees. However, there is no method to measure the efficiency of employees individually taking account the effect of teammates. This paper presents a model to measure the efficiency of employees in a way that they are fairly evaluated regarding their teammates’ relative performances. Moreover, the learning expectations and the effect of learning lost due to operation breaks are incorporated into the DEA model. This model is thus able to rank the employees working in each position that can then be utilized within award systems. The capabilities of the proposed model are then explored by a case study of 20 wells with 160 distinct operations in the South Pars gas field, which is the first application of DEA in the oil and gas wells drilling performance analysis.
