Tao Wang¹, Zhen Tian¹, Chen Gao¹, Quanfu Gao¹, Kewei Song^1,*

The International Conference on Computational & Experimental Engineering and Sciences, Vol.27, No.4, pp. 1-3, 2023, DOI:10.32604/icces.2023.8880

Abstract With the rapid development of the economy and the increasing consumption of fossil energy, energysaving becomes imperative [1,2]. Improving the heat transfer efficiency of heat exchangers, which are widely applied in many fields, is important for energy utilization [3,4]. Twisted tube can produce secondary flow, increase turbulence and thin thermal boundary layer, and hence the enhancement of heat transfer [5-9]. However, the mixture of the fluid between the center of the twisted tube and the region around the tube is still not effectively improved. Thus, the heat transfer of the twisted tube can be further… More >

Jiahao Lu¹, Fangfang Zhang¹, Weilong Guang¹, Yanzhao Wu¹, Ran Tao^1,2,*, Xiaoqin Li^1,2, Ruofu Xiao^1,2

Energy Engineering, Vol.120, No.12, pp. 2819-2837, 2023, DOI:10.32604/ee.2023.042287 - 29 November 2023

Abstract Savonius hydrokinetic turbine is a kind of turbine set which is suitable for low-velocity conditions. Unlike conventional turbines, Savonius turbines employ S-shaped blades and have simple internal structures. Therefore, there is a large space for optimizing the blade geometry. In this study, computational fluid dynamics (CFD) numerical simulation and genetic algorithm (GA) were used for the optimal design. The optimization strategies and methods were determined by comparing the results calculated by CFD with the experimental results. The weighted objective function was constructed with the maximum power coefficient C_p and the high-power coefficient range R under multiple… More >

J. S. Manjaly, T. Subbulakshmi^*

Computer Systems Science and Engineering, Vol.47, No.3, pp. 3083-3108, 2023, DOI:10.32604/csse.2023.036320 - 09 November 2023

Abstract The default scheduler of Apache Hadoop demonstrates operational inefficiencies when connecting external sources and processing transformation jobs. This paper has proposed a novel scheduler for enhancement of the performance of the Hadoop Yet Another Resource Negotiator (YARN) scheduler, called the Adaptive Node and Container Aware Scheduler (ANACRAC), that aligns cluster resources to the demands of the applications in the real world. The approach performs to leverage the user-provided configurations as a unique design to apportion nodes, or containers within the nodes, to application thresholds. Additionally, it provides the flexibility to the applications for selecting and… More >

Rachedi Khadraoui¹, Latra Boumaraf^1,*, Philippe Haberschill²

FDMP-Fluid Dynamics & Materials Processing, Vol.19, No.5, pp. 1115-1128, 2023, DOI:10.32604/fdmp.2022.022674 - 30 November 2022

Abstract A theoretical investigation is presented about a double evaporator ejector refrigeration cycle (DEERC). Special attention is paid to take into account the influence of the sub-cooling and superheating effects induced by an internal heat exchanger (IHX). The ejector is introduced into the baseline cycle in order to mitigate the throttling process losses and increase the compressor suction pressure. Moreover, the IHX has the structure of a concentric counter-flow type heat exchanger and is intentionally used to ensure that the fluid at the compressor inlet is vapor. To assess accurately the influence of the IHX on More > Graphic Abstract

Guibin Liu¹, Meinan Wang², Qi Yu¹, Qiuyi Li², Liang Wang^2,*

Journal of Renewable Materials, Vol.9, No.11, pp. 2051-2065, 2021, DOI:10.32604/jrm.2021.015398 - 04 June 2021

Abstract The strength and durability of concrete will be significantly reduced at high volume of mineral admixture, and the poor early strength of concrete also still needs to be solved. In this investigation, a highly active alkaline electrolyzed waters was used as mixing water to improve the early strength and enhance the durability of green concrete with high volume mineral admixture, the influences of alkaline electrolyzed water (AEW) on hydration activity of mineral admixture and durability of concrete were determined. The results showed that compared with natural tap water, AEW can accelerate early hydration process of… More > Graphic Abstract

Nandhini Jembu Mohanram^1,2,*, Gnanasekaran Thangavel³, N. M. Jothi Swaroopan⁴

Computer Systems Science and Engineering, Vol.38, No.2, pp. 215-228, 2021, DOI:10.32604/csse.2021.015027 - 23 April 2021

Abstract Fault tolerance (FT) schemes are intended to work on a minimized and static amount of physical resources. When a host failure occurs, the conventional FT frequently proceeds with the execution on the accessible working hosts. This methodology saves the execution state and applications to complete without disruption. However, the dynamicity of open cloud assets is not seen when taking scheduling choices. Existing optimization techniques are intended in dealing with resource scheduling. This method will be utilized for distributing the approaching tasks to the VMs. However, the dynamic scheduling for this procedure doesn’t accomplish the objective… More >

Syed Mustajar Ahmad Shah¹, Hongwei Ge^1,*, Sami Ahmed Haider², Muhammad Irshad³, Sohail M. Noman⁴, Jehangir Arshad⁵, Asfandeyar Ahmad⁶, Talha Younas⁷

Computer Systems Science and Engineering, Vol.36, No.2, pp. 369-382, 2021, DOI:10.32604/csse.2021.014234 - 05 January 2021

Abstract The data generated from non-Euclidean domains and its graphical representation (with complex-relationship object interdependence) applications has observed an exponential growth. The sophistication of graph data has posed consequential obstacles to the existing machine learning algorithms. In this study, we have considered a revamped version of a semi-supervised learning algorithm for graph-structured data to address the issue of expanding deep learning approaches to represent the graph data. Additionally, the quantum information theory has been applied through Graph Neural Networks (GNNs) to generate Riemannian metrics in closed-form of several graph layers. In further, to pre-process the adjacency… More >

Jae-Hyun Ro¹, Won-Seok Lee¹, Min-Goo Kang², Dae-Ki Hong³, Hyoung-Kyu Song^{1, *}

CMC-Computers, Materials & Continua, Vol.64, No.1, pp. 181-191, 2020, DOI:10.32604/cmc.2020.09998 - 20 May 2020

Abstract In this paper, the supervised Deep Neural Network (DNN) based signal detection is analyzed for combating with nonlinear distortions efficiently and improving error performances in clipping based Orthogonal Frequency Division Multiplexing (OFDM) ssystem. One of the main disadvantages for the OFDM is the high Peak to Average Power Ratio (PAPR). The clipping is a simple method for the PAPR reduction. However, an effect of the clipping is nonlinear distortion, and estimations for transmitting symbols are difficult despite a Maximum Likelihood (ML) detection at the receiver. The DNN based online signal detection uses the offline learning More >

Amnart Boonloi^a, Withada Jedsadaratanachai^b,*

Frontiers in Heat and Mass Transfer, Vol.12, pp. 1-9, 2019, DOI:10.5098/hmt.12.1

Abstract Numerical examinations on flow and heat transfer behaviors in a square channel heat exchanger equipped with various configurations of V-wavy plate are performed. The pitch-to-channel height ratios, wavy height-to-channel height ratios and flow directions of the test section are investigated for the Reynolds number in the range of 100 – 1000 (laminar flow regime). The finite volume method is selected for the present investigation. The results are reported in terms of flow and heat transfer mechanisms in the channel. The thermal performance assessments of the square channel fitted with the V-wavy plate are also concluded. More >