In this work, a new development of predictive voltage-tracking control algorithm for Proton Exchange Membrane Fuel Cell (PEMFCs) model, using a neural network technique based on-line auto-tuning intelligent algorithm was proposed. The aim of proposed robust feedback nonlinear neural predictive voltage controller is to find precisely and quickly the optimal hydrogen partial pressure action to control the stack terminal voltage of the (PEMFC) model for N-step ahead prediction. The Chaotic Particle Swarm Optimization (CPSO) implemented as a stable and robust on-line auto-tune algorithm to find the optimal weights for the proposed predictive neural network controller to improve system performance in terms of fast-tracking desired voltage and less energy consumption through investigating and comparing under random current variations with the minimum number of fitness evaluation less than 20 iterations.
In this research, the nonparametric technique has been presented to estimate the time-varying coefficients functions for the longitudinal balanced data that characterized by observations obtained through (n) from the independent subjects, each one of them is measured repeatedly by group of specific time points (m). Although the measurements are independent among the different subjects; they are mostly connected within each subject and the applied techniques is the Local Linear kernel LLPK technique. To avoid the problems of dimensionality, and thick computation, the two-steps method has been used to estimate the coefficients functions by using the two former technique. Since, the two-
... Show MoreSAPO-11 is synthesized from silicoaluminophosphate in the presence of di-n-propylamine as a template. The results show that the sample obtained has good crystallinity, 396m2/g BET surface area, and 0.35 cm3/g pore volume. The hydroisomerization activity of (0.25)Pt (1)Zr (0.5)W/SAPO-11 catalyst was determined using n-decane and base oil. All hydroisomerization experiments of n-decane were achieved at a fixed bed plug flow reactor at a temperature range of 200-275°C and LHSV 0.5-2h-1. The results show that the n-decane conversion increases with increasing temperature and decreasing LHSV, the maximum conversion of 66.7 % was achieved at temperature 275°C and LHSV of 0.5 h-1. Meanwhile, the same catalyst was used to improve base oil spec
... Show MoreThe main purpose of the research is to diagnose the importance of the role that strategic memory plays with its three variables (content, structure, and processes) in helping the human resource department to use the COSO model with its five components (culture and governance, strategy and objectives, performance, communications and information, and feedback) in auditing activities and tasks Her own. As the research problem emphasized the existence of a lack of cognitive perception, of the importance of strategic memory, and the investment of its components in the rationalization of the application of the COSO model. and therefore it can be emphasized that the importance of the research is to provide treatments for problems relate
... Show MoreSAPO-11 is synthesized from silicoaluminophosphate in the presence of di-n-propylamine as a template. The results show that the sample obtained has good crystallinity, 396m2/g BET surface area, and 0.35 cm3/g pore volume. The hydroisomerization activity of (0.25)Pt (1)Zr (0.5)W/SAPO-11 catalyst was determined using n-decane and base oil. All hydroisomerization experiments of n-decane were achieved at a fixed bed plug flow reactor at a temperature range of 200-275°C and LHSV 0.5-2h-1. The results show that the n-decane conversion increases with increasing temperature and decreasing LHSV, the maximum conversion of 66.7 % was achieved at temperature 275°C and LHSV of 0.5 h-1
... Show MoreGenerally, statistical methods are used in various fields of science, especially in the research field, in which Statistical analysis is carried out by adopting several techniques, according to the nature of the study and its objectives. One of these techniques is building statistical models, which is done through regression models. This technique is considered one of the most important statistical methods for studying the relationship between a dependent variable, also called (the response variable) and the other variables, called covariate variables. This research describes the estimation of the partial linear regression model, as well as the estimation of the “missing at random” values (MAR). Regarding the
... Show MoreThis study included isolation and characterization of extremely halophilic bacteria from Al-Massab Al-Aam region in South of Iraq Fifty isolates were identified by using numerical taxonomy 40 strains belonged to the genus Halobacterium which inclucted Hb. halobium Hb. cutirubrum Hb. salinarium Hb. saccharovorum Hb. valismortis and Hb. volcanii. Ten strains belonged to the genus Halococcus which included Hc. morrhuae Hc. saccharolyticus. Growth curves were sensitive mutants determined for wild type and salt Generation time in logarthmic phase was measured and found to be (10.37 2hr 7 0.59) for Hb. salinarium / 18 (6.490 hr 0.24) for Hb. cutirubrum / 32, (6.700 hr + 0.488) for Hb. valismortis / 20, (11.243 hr + 0.96) for Hb. volcanii / 7. (7
... Show MoreThe optimization of artificial gas lift techniques plays a crucial role in the advancement of oil field development. This study focuses on investigating the impact of gas lift design and optimization on production outcomes within the Mishrif formation of the Halfaya oil field. A comprehensive production network nodal analysis model was formulated using a PIPESIM Optimizer-based Genetic Algorithm and meticulously calibrated utilizing field-collected data from a network comprising seven wells. This well group encompasses three directional wells currently employing gas lift and four naturally producing vertical wells. To augment productivity and optimize network performance, a novel gas lift design strategy was proposed. The optimization of
... Show MoreThe present work aims to study the combustion characteristics related to syngas-diesel dual-fuel engine operates at lambda value of 1.6 operated by five different replacement ratios (RR) of syngas with diesel, which are (10%, 20%, 30 %, 40 % and 50%). ANSYS Workbench (CFD) was used for simulating the combustion of the syngas-diesel dual-fuel engine. The numerical simulations were carried out on the Ricardo-Hydra diesel engine. The simulation results revealed that the diesel engine’s combustion efficiency was enhanced by increasing the diesel replacement with Syngas fuel. The diesel engine’s combustion efficiency The peak in-cylinder temperature was enhanced from 915.9K to 2790.5K