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  • Open Access

    ARTICLE

    Thermodynamic Performance Analysis of Geothermal Power Plant Based on Organic Rankine Cycle (ORC) Using Mixture of Pure Working Fluids

    Abdul Sattar Laghari1, Mohammad Waqas Chandio1, Laveet Kumar2,*, Mamdouh El Haj Assad3

    Energy Engineering, Vol.121, No.8, pp. 2023-2038, 2024, DOI:10.32604/ee.2024.051082

    Abstract The selection of working fluid significantly impacts the geothermal ORC’s Efficiency. Using a mixture as a working fluid is a strategy to improve the output of geothermal ORC. In the current study, modelling and thermodynamic analysis of ORC, using geothermal as a heat source, is carried out at fixed operating conditions. The model is simulated in the Engineering Equation Solver (EES). An environment-friendly mixture of fluids, i.e., R245fa/R600a, with a suitable mole fraction, is used as the operating fluid. The mixture provided the most convenient results compared to the pure working fluid under fixed operating More >

  • Open Access

    ARTICLE

    Abaca Fiber as a Potential Reinforcer for Acoustic Absorption Material at Middle-High Frequencies

    Susilo Indrawati*, Lila Yuwana, Suyatno, Mochamad Zainuri, Darminto*

    Journal of Renewable Materials, Vol.12, No.5, pp. 909-921, 2024, DOI:10.32604/jrm.2024.048452

    Abstract Recently, abaca fibers have become the focus of specialized research due to their intriguing characteristics, with their outstanding mechanical properties being a particularly notable. In the conducted study, the abaca fibers underwent a preliminary treatment process involving an alkaline solution, which was composed of 0.5% sodium hydroxide (NaOH) and 50% acetic acid (CHCOOH). This process entailed immersing each fiber in the solution for a period of one hour. This treatment led to a 52.36% reduction in lignin content compared to the levels before treatment, resulting in a dramatic decrease in the full width at half… More > Graphic Abstract

    Abaca Fiber as a Potential Reinforcer for Acoustic Absorption Material at Middle-High Frequencies

  • Open Access

    ARTICLE

    Numerical Predictions of Laminar Forced Convection Heat Transfer with and without Buoyancy Effects from an Isothermal Horizontal Flat Plate to Supercritical Nitrogen

    K. S. Rajendra Prasad1, Sathya Sai2, T. R. Seetharam3, Adithya Garimella1,*

    Frontiers in Heat and Mass Transfer, Vol.22, No.3, pp. 889-917, 2024, DOI:10.32604/fhmt.2024.047703

    Abstract Numerical predictions are made for Laminar Forced convection heat transfer with and without buoyancy effects for Supercritical Nitrogen flowing over an isothermal horizontal flat plate with a heated surface facing downwards. Computations are performed by varying the value of from 5 to 30 K and ratio from 1.1 to 1.5. Variation of all the thermophysical properties of supercritical Nitrogen is considered. The wall temperatures are chosen in such a way that two values of T are less than is the temperature at which the fluid has a maximum value of C for the given pressure), More >

  • Open Access

    ARTICLE

    MADDPG-D2: An Intelligent Dynamic Task Allocation Algorithm Based on Multi-Agent Architecture Driven by Prior Knowledge

    Tengda Li, Gang Wang, Qiang Fu*

    CMES-Computer Modeling in Engineering & Sciences, Vol.140, No.3, pp. 2559-2586, 2024, DOI:10.32604/cmes.2024.052039

    Abstract Aiming at the problems of low solution accuracy and high decision pressure when facing large-scale dynamic task allocation (DTA) and high-dimensional decision space with single agent, this paper combines the deep reinforcement learning (DRL) theory and an improved Multi-Agent Deep Deterministic Policy Gradient (MADDPG-D2) algorithm with a dual experience replay pool and a dual noise based on multi-agent architecture is proposed to improve the efficiency of DTA. The algorithm is based on the traditional Multi-Agent Deep Deterministic Policy Gradient (MADDPG) algorithm, and considers the introduction of a double noise mechanism to increase the action exploration… More >

  • Open Access

    ARTICLE

    Efficient Penetration Testing Path Planning Based on Reinforcement Learning with Episodic Memory

    Ziqiao Zhou1, Tianyang Zhou1,*, Jinghao Xu2, Junhu Zhu1

    CMES-Computer Modeling in Engineering & Sciences, Vol.140, No.3, pp. 2613-2634, 2024, DOI:10.32604/cmes.2023.028553

    Abstract Intelligent penetration testing is of great significance for the improvement of the security of information systems, and the critical issue is the planning of penetration test paths. In view of the difficulty for attackers to obtain complete network information in realistic network scenarios, Reinforcement Learning (RL) is a promising solution to discover the optimal penetration path under incomplete information about the target network. Existing RL-based methods are challenged by the sizeable discrete action space, which leads to difficulties in the convergence. Moreover, most methods still rely on experts’ knowledge. To address these issues, this paper… More >

  • Open Access

    ARTICLE

    Oscillatory Dynamics of a Spherical Solid in a Liquid in an Axisymmetric Variable Cross Section Channel

    Ivan Karpunin*

    FDMP-Fluid Dynamics & Materials Processing, Vol.20, No.6, pp. 1219-1232, 2024, DOI:10.32604/fdmp.2024.051062

    Abstract The dynamics of a solid spherical body in an oscillating liquid flow in a vertical axisymmetric channel of variable cross section is experimentally studied. It is shown that the oscillating liquid leads to the generation of intense averaged flows in each of the channel segments. The intensity and direction of these flows depend on the dimensionless oscillating frequency. In the region of studied frequencies, the dynamics of the considered body is examined when the primary vortices emerging in the flow occupy the whole region in each segment. For a fixed frequency, an increase in the… More >

  • Open Access

    ARTICLE

    A Novel Method for Determining the Void Fraction in Gas-Liquid Multi-Phase Systems Using a Dynamic Conductivity Probe

    Xiaochu Luo1, Xiaobing Qi2, Zhao Luo3, Zhonghao Li4, Ruiquan Liao1, Xingkai Zhang1,*

    FDMP-Fluid Dynamics & Materials Processing, Vol.20, No.6, pp. 1233-1249, 2024, DOI:10.32604/fdmp.2023.045737

    Abstract Conventional conductivity methods for measuring the void fraction in gas-liquid multiphase systems are typically affected by accuracy problems due to the presence of fluid flow and salinity. This study presents a novel approach for determining the void fraction based on a reciprocating dynamic conductivity probe used to measure the liquid film thickness under forced annular-flow conditions. The measurement system comprises a cyclone, a conductivity probe, a probe reciprocating device, and a data acquisition and processing system. This method ensures that the flow pattern is adjusted to a forced annular flow, thereby minimizing the influence of More >

  • Open Access

    ARTICLE

    Structure Optimization of a Tesla Turbine Using an Organic Rankine Cycle Technology

    Yongguo Li1,2, Caiyin Xu1,2,*, Can Qin1,2, Dingjian Zheng1,2

    FDMP-Fluid Dynamics & Materials Processing, Vol.20, No.6, pp. 1251-1263, 2024, DOI:10.32604/fdmp.2023.044804

    Abstract The so-called ORC (Organic Rankine Cycle) heat recovery technology has attracted much attention with regard to medium and low temperature waste heat recovery. In the present study, it is applied to a Tesla turbine. At the same time, the effects of the disc speed, diameter and inter-disc gap on the internal flow field and output power of the turbine are also investigated by means of CFD (Computational Fluid Dynamics) numerical simulation, by which the pressure, velocity, and output efficiency of the internal flow field are obtained under different internal and external conditions. The highest efficiency More >

  • Open Access

    ARTICLE

    Optimizing Hybrid Fibre-Reinforced Polymer Bars Design: A Machine Learning Approach

    Aneel Manan1, Pu Zhang1,*, Shoaib Ahmad2, Jawad Ahmad2

    Journal of Polymer Materials, Vol.41, No.1, pp. 15-44, 2024, DOI:10.32604/jpm.2024.053859

    Abstract Fiber-reinforced polymer (FRP) bars are gaining popularity as an alternative to steel reinforcement due to their advantages such as corrosion resistance and high strength-to-weight ratio. However, FRP has a lower modulus of elasticity compared to steel. Therefore, special attention is required in structural design to address deflection related issues and ensure ductile failure. This research explores the use of machine learning algorithms such as gene expression programming (GEP) to develop a simple and effective equation for predicting the elastic modulus of hybrid fiber-reinforced polymer (HFPR) bars. A comprehensive database of 125 experimental results of HFPR… More >

  • Open Access

    ARTICLE

    Investigation of the Damping Abilities of Sheep Wool Reinforced Expanded Polystyrene Core Layer Composites at Different Energies

    İbrahim Yavuz1,*, Ercan Şimşir1, Kenan Budak2

    Journal of Polymer Materials, Vol.41, No.1, pp. 1-14, 2024, DOI:10.32604/jpm.2024.052279

    Abstract In this study, natural fiber reinforced polymer foam core layered composites were produced for the automotive industry. Sheep wool was used as natural fiber. Polymer foam with a single layer XPS foam structure was used as the core material. XPS foams and fibers are bonded to the upper and lower sides of the foams with the help of resin. Samples were produced with one and two layers on both sides, with a total of two and four layers. Production was carried out using the vacuum bagging method using the manual laying method. After the production More >

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