Despite their potential as a sustainable energy technology, the operation of proton exchange membrane fuel cells (PEMFCs) in sub-freezing conditions remains a critical challenge due to the risk of ice formation and performance degradation. This study introduces a new passive thermal management technique using strategically arranged multi-layer phase change materials (PCMs) to address this challenge. A numerical model was developed to evaluate the thermal behavior across various PCM configurations, incorporating one, two, and three layers arranged both in parallel and series with distinct melting points ranging from 55 to 65 ◦C. The results show that multi-layer PCM configurations provide significant improvements over the single-layer baseline. The parallel three-layer arrangement extended the thermal management duration by 48.8 % compared to the single-layer system, maintaining PEMFC temperatures above 55 ◦C for over 12 h in an ambient at − 20 ◦C. This configuration also demonstrated superior temperature stability, with a temperature differential of only 3 ◦C. The series three-layer design achieved a 39 % increase in duration but maintained the same 3 ◦C temperature differential. The novelty of this work lies in the systematic analysis of parallel and series PCM layer configurations, each designed for specific operating conditions. These passive solutions can effectively manage the energy demand of PEMFCs during cold startup, overcoming the limitations of conventional methods.
Big data analysis has important applications in many areas such as sensor networks and connected healthcare. High volume and velocity of big data bring many challenges to data analysis. One possible solution is to summarize the data and provides a manageable data structure to hold a scalable summarization of data for efficient and effective analysis. This research extends our previous work on developing an effective technique to create, organize, access, and maintain summarization of big data and develops algorithms for Bayes classification and entropy discretization of large data sets using the multi-resolution data summarization structure. Bayes classification and data discretization play essential roles in many learning algorithms such a
... Show MoreThis paper tackles with principal component analysis method (PCA ) to dimensionality reduction in the case of linear combinations to digital image processing and analysis. The PCA is statistical technique that shrinkages a multivariate data set consisting of inter-correlated variables into a data set consisting of variables that are uncorrelated linear combination, while ensuring the least possible loss of useful information. This method was applied to a group of satellite images of a certain area in the province of Basra, which represents the mouth of the Tigris and Euphrates rivers in the Shatt al-Arab in the province of Basra.
... Show MorePure SnSe thin film and doped with S at different percentage (0,3,5,7)% were deposited from alloy by thermal evaporation technique on glass substrate at room temperature with 400±20nm thickness .The influences of S dopant ratio on characterization of SnSe thin film Nano crystalline was investigated by using Atomic force microscopy(AFM), X-ray diffraction (XRD), energy dispersive spectroscopy (EDS), Hall Effect measurement, UV-Vis absorption spectroscopy to study morphological, structural, electrical and optical properties respectively .The XRD showed that all the films have polycrystalline in nature with orthorhombic structure, with preferred orientation along (111)plane .These films was manufactured of very fine crystalline size in the ra
... Show More4-Amino-N-(5-methyl-isaxazol-3-yl)-benzenesulfonamide, a new azo (LH) ligand, was synthesized by reacting the diazonium salt of Sulfamethoxazole with coupling compound 3-amino phenol. Spectroscopic techniques (UV-Vis, FTIR, 1H &13C-NMR, and LC-Mass) as well as micro elemental analyses (C.H.N.O) and TGA and SDC were used to identify the azo ligand. Complexes of (Zn(II), Cr(III), Cu(II) and VO(II)) were produced and characterized by atomic absorption, elemental microanalysis, infrared, LC-Mass, TGA, DSC and UV-Vis spectral techniques, as well as conductivity and magnetic quantifications. All the complexes had a 1:2 metal-ligand ratio, and non-electrolytes at all complexes and tetrahedral geometry suggested except Cr-complex, which demonstrate
... Show MoreTo reduce the effects of discharging heated water disposed into a river flow by a single thermal source, two parameters were changed to get the minimum effect using optimization. The first parameter is to distribute the total flow of the heated water between two disposal points (double source) instead of one and the second is to change the distance between these two points. In order to achieve the solution, a two dimensional numerical model was developed to simulate and predict the changes in temperature distribution in the river due to disposal of the heated water using these two points of disposal.
MATLAB-7 software was used to build a program that could solve the governing partial equations of thermal pollution in rivers by using t
This article deals with the impact of including transverse ribs within the absorber tube of the concentrated linear Fresnel collector (CLFRC) system with a secondary compound parabolic collector (CPC) on thermal and flow performance coefficients. The enhancement rates of heat transfer due to varying governing parameters were compared and analyzed parametrically at Reynolds numbers in the range 5,000–13,000, employing water as the heat transfer fluid. Simulations were performed to solve the governing equations using the finite volume method (FVM) under various boundary conditions. For all Reynolds numbers, the average Nusselt number in the circular tube in the CLFRC system with ribs was found to be larger than that of the plain abs
... Show MorePurpose: aims the study to show How to be can to enhance measurement management by incorporating a risk-based approach and the six sigma method into a more thorough assessment of metrological performance. Theoretical framework: Recent literature has recorded good results in analyzing the impact of Six Sigma and risk management on the energy sector (Barrera García et al., 2022) (D'Emilia et al. 2015). However, this research came to validate and emphasize the most comprehensive assessment of metrological performance by integrating Risk management based approach and Six Sigma analysis. Design/methodology/approach: This study was conducted in Iraqi petroleum refining companies. System quality is measured in terms of sigmas, and t
... Show MorePurpose: aims the study to show How to be can to enhance measurement management by incorporating a risk-based approach and the six sigma method into a more thorough assessment of metrological performance. Theoretical framework: Recent literature has recorded good results in analyzing the impact of Six Sigma and risk management on the energy sector (Barrera García et al., 2022) (D'Emilia et al. 2015). However, this research came to validate and emphasize the most comprehensive assessment of metrological performance by integrating Risk management based approach and Six Sigma analysis. Design/methodology/approach: This study was conducted in Iraqi petroleum refining companies. System quality is measured in terms of sigmas, and t
... Show MoreThis article presents a new cascaded extended state observer (CESO)-based sliding-mode control (SMC) for an underactuated flexible joint robot (FJR). The control of the FJR has many challenges, including coupling, underactuation, nonlinearity, uncertainties and external disturbances, and the noise amplification especially in the high-order systems. The proposed control integrates the CESO and SMC, in which the CESO estimates the states and disturbances, and the SMC provides the system robustness to the uncertainty and disturbance estimation errors. First, a dynamic model of the FJR is derived and converted from an underactuated form to a canonical form via the Olfati transformation and a flatness approach, which reduces the complexity of th
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