Refrigerant R134a has been widely utilized in automotive air conditioning systems (AACSs); R134a has a high global warming potential (GWP) of 1430 despite having zero ozone depletion potential (ODP). Coming refrigeration systems must include refrigerants with low GWP and zero ODP. The aim of this experimental study is to evaluate the thermal performance of an (AAC) with different values of compressor speeds, i.e., (1000, 1700, and 2400 rpm) and two thermal loads, i.e., (500 and 1000 Watt) with the absence and presence of liquid suction heat exchanger (LSHX) using R134a. The results showed that adding LSHX enhanced the COP cycle by 7.18%, 10.7%, and 3.09% for the first, second, and third speed, respectively, at 500 Watt, while the en

The interaction of charged particles with the chemical elements involved in the synthesis of human tissues is one of the modern techniques in radiation therapy. One of these charged particles are alpha particles, where recent studies have confirmed their ability to generate radiation in a highly toxic localized manner because of its high ionization and short its range. In this work, We focused our study on the interaction of alpha particles with liquid water; since the water represents over 80% of the most-soft tissues, as well as, hydrogen, oxygen, and nitrogen ,because they are key chemical elements involved in the synthesis of most human tissues. The mass stopping powers of alpha particle with HଶO , COଶ, Oଶ, Hଶ and Nଶhave

Theoretical and experimental investigations of the transient heat transfer parameters of constant heat flux source subjected to water flowing in the downward direction in closed channel are conducted. The power increase transient is ensured by step change increase in the heat source power. The theoretical investigation involved a mathematical modeling for axially symmetric, simultaneously developing laminar water flow in a vertical annulus. The mathematical model is based on one dimensional downward flow. The boundary conditions of the studied case are based on adiabatic outer wall, while the inner wall is subjected to a constant heat flux. The heat & mass balance equation derived for specified element of bulk water within the annulu

Accurate pore and fracture pressure detection is a major step in successful drilling operations design. The overestimation of these parameters absolutely leads to serious problems throughout and after well drilling. This study is concerned with the characterization and analysis of the most significant diagenetic processes that degrade or improve the reservoir characteristics of the Mauddud Formation in the Badra oil field. The primary goal of this research is to estimate the pore pressure and fracture pressure using well logging data by Techlog 2015 software in order to assess the impact on the estimation of the mud weight window (MWW). The estimated values of formation pressures are then analyzed according to different diagenetic p

Research aimed to explore the Application Effect of the Conflict Management Strategies by the managements to solve conflict between and inside the conflicted parties within (IGEC) to increase the productivity of the workers. To collect data, 110 questioners had been distributed among managers and heads of departments of all managerial levels, 102 answered questioners regained, 5 of them were disqualify for statistical analytic, only 97 were taking in consideration   for statistical analysis presenting 93% of the retained number.

SPSS Program supported with a group of statistical tools, had been used for analysis purposes such as Kronbach Alpha test to assure the validity & stability of the t

Background/Objectives: Early and accurate discrimination of neurological conditions, dementia, stroke and healthy aging, remains a critical clinical challenge. Electroencephalography (EEG) is a non-invasive measure of brain dynamics and entropy-based features obtained from multichannel EEG have shown strong discriminative ability. However, existing deep learning approaches do not sufficiently address the combined challenges of small clinical cohorts and high-dimensional entropy feature spaces. In this study, a novel architecture is proposed for multi-class neurological EEG classification under extreme small-sample conditions. Methods: A novel dual-branch Channel-wise Transformer and Attention-Branch Network (EEG-ChTABNet) are pr to