Amount Of Energy Research Articles

SEISMICITY of the VOLCANIC AREAS of KAMCHATKA in 2020

The results of near real-time monitoring of the active Kamchatka volcanoes are described. Con tinuous monitoring was carried out using three remote methods: 1) seismic monitoring according to automatic telemetric seismic stations; 2) visual and video observation; 3) satellite observation of the thermal anomalies and the ash clouds. Daily information about volcanic activity is published in the Internet (http://www.emsd.ru/ ~ssl/monitoring/main.htm) since February 2000. The results of analysis of seismic activity of the Northern (Shive luch, Kluchevskoy, Bezymianny, Plosky Tolbachik, Krestovsky and Ushkovsky), Avacha (Avachinsky and Kor yaksky), Mutnovsky-Gorely volcano group and Kizimen, Zhupanovsky, Karymsky and Kambalny volcanoes for 2020 are presented. 3945 earthquakes with KS=1.6–8.6 were located for Northern volcano group, 337 earthquakes with KS=1.6–6.0 – for Avacha volcano group, 498 earthquakes with KS=1.6–6.8 – for Mutnovsky-Gorely volcano group, 55 earthquakes with KS=2.4–7.8 for Kizimen volcano, 41 earthquakes with KS=2.6–7.3 for Zhupanovsky volcano, and 4 earthquakes with KS=5.4–6.6 – for Karymsky volcano. Maps of epicenters, quantities of seismic energy and earthquake distribution according to class are given. All periods of activity were fixed and investigated by remote methods in 2020: an intensive volcanic activity of Sheveluch volcano associated with new cone, the paroxysmal explosive eruption of Bezymianny volcano and the summit explosive-effusive eruptions of Kluchevskoy volcano.

Reserve Technique in Integrating Large Sustainable Energy Sources: A Case Study of the Tunisian Grid

The increasing integration of sustainable energy sources, such as wind and solar power, into the national electricity grid presents significant challenges in terms of frequency control and grid stability. Additionally, the imbalance between electricity supply and demand introduces dynamic frequency variations. However, according to the literature, the impact of high penetration of renewable energy sources on the Tunisian grid has not been extensively analyzed using power system simulator for engineering (PSS/E). This research paper explores how the primary reserve technique participates to maintain frequency within acceptable ranges in the Tunisian electrical grid. Individual generators contribute to the total power output, thereby influencing frequency deviation. The primary frequency control action by each generator is proportional to its frequency deviation and inversely proportional to its governing drop, which measures the generator’s sensitivity to frequency changes. This paper analyzes frequency stability in the Tunisian grid under scenarios with and without different rates of sustainable energy source penetration, which barely reached 3.5% in 2023. In Tunisia, the use of sustainable energy is essential not only for ensuring grid stability but for combating climate change and reducing carbon emissions, aligning with the country’s environmental goals. The transition to sustainable energy significantly reduces the carbon footprint of the power sector, offering a sustainable solution for mitigating the adverse effects of climate change. Dynamic simulations were conducted for the isolated Tunisian system, separate from the interconnected grid, focusing on the critical scenario of the loss of a large electricity production unit. This study also examined the absence of sustainable energy integration and the effects of integration of different rates of renewable energy to evaluate the impact of reserves on the continuity of the Tunisian electrical service. Simulation results, which considered a 2023 grid model, show that with an integration trial of 20% renewable energy and, in the worst-case scenario, which represents the loss of the largest production group in the grid, the primary reserve of a given group—defined by the quantity of active energy—can be rapidly deployed to restore the balance between electricity supply and demand. Thus, reserves are a crucial solution for maintaining frequency within reasonable limits and ensuring the continuity of electrical services in Tunisia with varying rates from 10% to 20% integration of different sustainable energy sources.

Assessment of Cytotoxicity and Genotoxicity of Plasma-Treated Perfluorooctanesulfonate Containing Water Using In Vitro Bioassays

The contamination of ground and surface waters with per- and polyfluoroalkyl substances (PFASs) is of major concern due to their potential adverse effects on human health. The carbon–fluorine bond makes these compounds extremely stable and hardly degradable by natural processes. Therefore, methods for PFAS removal from water are desperately needed. In this context, plasma treatment of water has been proposed as an effective method with reported removal rates exceeding 90%. However, the high reactivity of plasma discharge results in the formation of many reactive species, like radicals, ozone, or even solvated electrons, which lead to a complex reaction cascade and, consequently, to the generation of a wide variety of different chemical products. The toxicological properties of these PFAS breakdown products are largely unknown. The present study focuses on a toxicological assessment of PFAS-containing plasma-treated water samples. Aqueous solutions of long-chain perfluorooctanesulfonate (PFOS) were treated with various plasma-atmospheric regimes. Subsequently, plasma-treated water samples were subjected to in vitro bioassays. Cytotoxicity and genotoxicity were assessed with the MTS assay using human liver cells (HepG2) and the Ames MPFTM assay using Salmonella Typhimurium strains. Our results demonstrate varying cyto- and genotoxic properties of water containing PFAS breakdown products depending on the atmosphere present during plasma treatment. Based on the results of this study, the atmosphere used during plasma treatment affects the toxicological properties of the treated sample. Further studies are therefore needed to uncover the toxicological implications of the different treatment parameters, including the PFAS starting compound, the atmosphere during treatment, as well as the quantity of plasma energy applied.

Towards an eco-social circular economy: exploring the feasibility study of pyrolysis on agricultural feedstocks

AbstractThe agricultural sector is challenging to decarbonise due to its reliance on heavy machinery and fossil fuels, which face issues when decarbonising via methods such as electrification. However, agriculture provides opportunities to generate renewable energy via biomass sources due to their abundance within this sector. This feasibility study used a continuous auger pyrolysis system to assess how straw waste from a medium-scale arable farm could convert energy from an external electrical source into usable chemical potential. Wheat, barley, oil seed rape (OSR), and bean straw have all been processed and pyrolysed under different temperatures and auger feed rates. The syngas product was then analysed, considering its composition and the lower heating value. Results indicate that the percentage of carbon monoxide and hydrogen and the total volume of syngas increased with temperature. In addition, the syngas’ energy quantity increased despite the product’s decreasing heating value. The case study’s annual energy demand was equal to 14.4% of the 3900 GJ maximum potential contained within the syngas, and thus it can be concluded that there is potential for the application of this system towards a circular economy. The system’s cold gas, net, and electrical conversion efficiency were also assessed with maximum values of 37.1%, 30.1%, and 174.4%, respectively. Furthermore, the statistical analysis confirms high predictability for wheat, barley, bean, and OSR feedstocks, with a general linear model showing high accuracy across all.

Monte Carlo simulations of a multisource transcranial photobiomodulation helmet device: application to young and aged brains

Transcranial photobiomodulation is an emerging non-invasive technique that uses near-infrared light to stimulate brain function and offer protection against damage. Although this method is safe, there is much uncertainty concerning the optimum dosage, in particular, the quantity of energy that, when applied transcranially from a multisource helmet device, reaches the brain parenchyma and produces a change in neural activity. In this study, we used the Monte Carlo method to simulate a typical session of transcranial photobiomodulation using an existing multisource helmet device and to quantify the energy deposition region by region in the brain. We simulated two commonly used wavelengths, 670 and 810 nm, and examined light propagation in young and aged brains. Our results showed that, from the multisource helmet device, light at both wavelengths could indeed reach superficial regions of the brain parenchyma, up to 3–4 cm beneath the scalp surface. Overall, the 810 nm light penetrated deeper than the 670 nm light. From approximately 1 cm beneath the scalp, the light distribution became almost uniform for both wavelengths. However, regional analysis revealed that light penetrated better into the frontal and parietal lobes than into other regions (e.g., the temporal lobe). Furthermore, the light from this multisource device did not reach deeper structures (e.g., subcortical). Finally, the Monte Carlo simulations from the device revealed only subtle differences between the young brain and the aged brain. In summary, our results contribute to a better understanding of the quantification of regional light deposition during a typical session of transcranial photobiomodulation using a multisource helmet device.

Heat Fluxes in a Glacial Fjord: The Role of Buoyancy‐Driven Circulation and Offshore Forcing

Heat Fluxes in a Glacial Fjord: The Role of Buoyancy‐Driven Circulation and Offshore Forcing

Design of Circularly Polarized Koch Snowflake Fractal Antenna With Schottky Band Diode Rectifiers for RF Energy Harvesting Applications

ABSTRACTRadio frequency (RF) energy harvesting has recently become an effective way of powering wireless devices, reducing the requirement of batteries along with their related storage as well as lifespan restrictions. One of the main obstacles to RF energy harvesting is the limited quantity of energy that can be obtained from wireless sources due to weak signal strength, low efficiency, and poor gain. To address these shortcomings, the proposed method is designed based on the circularly polarized Koch snowflake fractal antenna with the Jerusalem cross (JC)–based frequency‐selective surface (FSS) and Schottky diode–based rectifiers for RF energy harvesting applications at the resonance frequency of 5.8 GHz. The electromagnetic energy from the environment can effectively captured using a proposed wide band and high gain antenna designed using a Koch snowflake array based on FSSs. Flame Retardant‐4 (FR‐4) material has good dielectric qualities for electronics, and it is employed as the dielectric substrate in this model; copper serves as the ground plane. The squid game optimizer (SGO) determines the ideal outer snowflake dimensions by maximizing the resonance frequency in order to achieve high gain. The optimally selected outer snowflake length and width are 40 and 23.09 mm. The designed antenna model uses a rectifier based on Schottky diodes for RF energy harvesting applications, which involves converting electromagnetic waves into direct current. The fractal antenna model and RF energy harvesting are designed and simulated using the ANSYS HFSS and Matlab RF toolbox. The model is used to evaluate the antenna's performance by concentrating on gain radiation patterns, S11, and voltage standing wave ratio (VSWR). The Koch snowflake fractal antenna, which uses a JC–based FSS, has been measured for performance at 5.8‐GHz frequency; the values obtained for impedance bandwidth, gain, S11, and VSWR are 7.61%, 9.962 dB, −33 dB, and 1.01, respectively. The analysis of the experimental data demonstrates that the Koch snowflake fractal antenna, which is being proposed for energy harvesting applications, outperforms several other existing designs in terms of effectiveness.

Forecasting Wind–Photovoltaic Energy Production and Income with Traditional and ML Techniques

Hybrid production plants harness diverse climatic sources for electricity generation, playing a crucial role in the transition to renewable energies. This study aims to forecast the profitability of a combined wind–photovoltaic energy system. Here, we develop a model that integrates predicted spot prices and electricity output forecasts, incorporating relevant climatic variables to enhance accuracy. The jointly modeled climatic variables and the spot price constitute one of the innovative aspects of this work. Regarding practical application, we considered a hypothetical wind–photovoltaic plant located in Italy and used the relevant climate series to determine the quantity of energy produced. We forecast the quantity of energy as well as income through machine learning techniques and more traditional statistical and econometric models. We evaluate the results by splitting the dataset into estimation windows and test windows, and using a backtesting technique. In particular, we found evidence that ML regression techniques outperform results obtained with traditional econometric models. Regarding the models used to achieve this goal, the objective is not to propose original models but to verify the effectiveness of the most recent machine learning models for this important application, and to compare them with more classic linear regression techniques.

Multi-Criteria Optimization of the Paper Production Process Using Numerical Taxonomy Methods: A Necessary Condition for Predicting Heat and Electricity Output in a Combined Heat and Power (CHP) System

The subject of this study is the optimization of the paper production process in one of Poland’s leading paper mills. In addition to its primary objective of paper production, the company generates heat and electricity for internal consumption and external clients, including the local municipality. Surplus energy may be sold on the power exchange; however, this requires forecasting the quantity of energy to be sold 24 h in advance, which introduces an element of uncertainty. Production stoppages, often caused by random events such as paper breakage, force a power decrease in the CHP system, further complicating energy forecasting. To minimize the occurrence of such events, numerical taxonomy methods were employed to determine the optimal screen speed (Vs) and winding speed (Vn) for two paper machines, based on the type and weight of the paper produced. This analysis utilized detailed daily data collected by the company over the period 2015–2020. The findings contribute to minimizing the occurrence of paper roll tearing, thereby reducing the risk of inaccurate forecasts of the energy and heat produced by the CHP system. Furthermore, the methodology employed in this study may be effectively applied to other optimization problems in industrial processes.

A flow battery cell testing facility for versatile active material characterization: Features and operations

Technological development plays a fundamental role in view of the successful realization of large Flow Battery (FB) systems. This work firstly presents the design, construction and commissioning of FB-Cell Testing Facility (FB-CTF), a bench for testing electrolytes, electrodes, membrane and cell configurations under controlled conditions. Several construction aspects related to the hydraulic system, power conditioning system, and flow battery management system are described in detail. FB-CTF has been conceived and built to accurately measure the main thermal, hydraulic, electric, and energy quantities which define the performance of FBs. A comprehensive experimental campaign has been carried out on FB-CTF to characterize some widely used electrodes and membranes for Vanadium FBs (VFBs), produced by some major manufacturers. The paper presents the developed testing protocols and the test results, specifically focusing on electrical and hydraulic characterization. In addition, a methodology using FB-CTF data in the prediction of the electric and hydraulic performance of large stacks is proposed. More generally, FB-CTF measurements can be used to address the design of industrial-scale FBs. FB-CTF can provide insights for the design of large flow battery systems, to help bridge the gap between academic research and industry.

Two‐stage stochastic energy and reserve market clearing model considering real‐time offering strategy of renewable energy

AbstractWith the introduction of decarbonization policies worldwide, renewable energy, especially wind and solar power, is gradually taking a significant share in the power system. The two‐stage stochastic optimization methods are generally adopted to address the uncertainty issues and the two‐stage stochastic market clearing models are established with the participation of renewable energy. However, most existing two‐stage stochastic market clearing models usually intuitively presume the offering quantities of renewable energy are equal to their forecast values, neglecting the potential impacts of the strategic offerings on the market results and thus affecting the secure operation of power systems. To fill the gaps, this paper incorporates the strategic offering models of renewable energy into the two‐stage stochastic energy and reserve market clearing model. Within the two‐stage framework, the first day‐ahead stage serves for energy and reserve market clearing, while the second real‐time stage considers the adjustments on offering quantities of renewable energy according to the fluctuations of renewable generations. The two‐stage stochastic market clearing model is formulated as a mixed‐integer non‐linear programming problem, and an iterative algorithm is devised to obtain market clearing results after proper linearizations. The effectiveness of the proposed method is validated using the extended IEEE‐118 test system.

Amorphous NiO nanopyramids with superior electrochromic energy storage properties

In this work, amorphous NiO nanopyramid film has been obtained by using the pulsed magnetron sputtering technique. The uniform amorphous NiO nanostructures exhibit significant electrochromic modulation efficiency in the visible and near-infrared ranges, achieving a high modulation efficiency of 60.73 % at 550 nm and 21.58 % at 1500 nm. It exhibits rapid response time (coloring takes 2.4 s, and bleaching takes 1.0 s) and significant coloring efficiency (43.23 cm2C-1). Moreover, amorphous NiO nanopyramid film displays promising properties of energy storage. The NiO nanopyramid film shows high areal capacitance (7.08 mF/cm2), along with satisfying rate capability. The alteration in the electrode color offers a convenient method for monitoring the quantity of energy stored. Furthermore, the microstructure characteristic, degree of crystallization and electrochemical performance of the NiO film are significantly influenced by both oxygen partial pressure and sputtering time. These findings highlight the potential of employing this bifunctional amorphous NiO nanopyramid film in diverse advanced nanodevices, encompassing electrochromic energy storage applications with superior performance.

The significance of biowaste drying analysis as a key pre-treatment for transforming it into a sustainable biomass feedstock.

The objective of this study is to investigate the drying kinetics of fruit and vegetable peel biowaste using a sustainable technique as a key-pretreatment for its conversion into useful feedstock. Biowaste represents a missed potential source of bioenergy and bioproducts, but moisture removal is required, and conventional drying methods are expensive since they require great quantity of energy supplied, almost always, by a non-renewable energy. In this study six batches with the same quantity of biowaste, and heterogeneous physical composition were dried under open-sun conditions. We evaluated the influence of the interaction between drying area and the initial moisture content on drying rate. Eight semi-theoretical models were fitted using Levenberg-Marquardt algorithm to predict drying rate, and their accuracy was assessed through goodness-of-fit tests. Maximum moisture content to preserve biomass (10%) was reached on 5th day and the equilibrium on 16th day of drying. According to goodness-of-fit test (R 2=0.999, χ 2=4.666×10-5, RMSE = 0.00683) the best model to predict drying rate was Two-term model. The mathematical model obtained from Fick's second law is reliable to predict drying kinetics, R2 (0.9648±0.0106); despite the variation between drying area and initial moisture content. Kruskal-Wallis test showed that drying rates between batches are not significantly different (p=0.639; 0.05); nor effective diffusion coefficient (D eff =4.97×10-11±0.3491×10-11), (p=0.723; 0.05). The study of drying kinetics is crucial for selecting the optimal biowaste treatment based on its generation context. This could enable its use as feedstock for bioproduct or bioenergy production, thereby reducing waste accumulation in landfills and environmental impact.

Calculation of exergy losses, exergy efficiency and cooling coefficient of refrigerant R22

This study presents a detailed analysis of the exergy losses, exergy efficiency, and cooling coefficient of performance (COP) for the refrigerant R22 in refrigeration systems. Exergy analysis, which considers both the quantity and quality of energy, is used to identify and quantify the irreversibilities within the system. The objective of this analysis is to provide insights into the areas of inefficiency and potential improvements for enhanced energy performance. Results indicate that the exergy losses in R22 systems are primarily associated with the compressor and expansion valve, highlighting these components as key targets for efficiency improvements. The exergy efficiency was found to vary significantly with operating conditions, suggesting that system performance could be optimized through appropriate design and control strategies. Additionally, the cooling COP of R22 was evaluated, demonstrating its effectiveness in converting input energy into cooling capacity under various conditions. This analysis contributes to the broader understanding of R22's thermodynamic performance and offers a foundation for developing more sustainable and efficient refrigeration technologies.

RANS Simulation of Minimum Ignition Energy of Stoichiometric and Leaner CH4/Air Mixtures at Higher Pressures in Quiescent Conditions

Minimum ignition energy (MIE) has been extensively studied via experiments and simulations. However, our literature review reveals little quantitative consistency, with results varying from 0.324 to 1.349 mJ for ϕ = 1.0 and from 0.22 to 0.944 mJ for ϕ = 0.9. Therefore, there is a need to resolve these discrepancies. This RANS study aims to partially address this knowledge gap. Additionally, it presents other flame evolution parameters essential for robust combustion design. Using the reactingFOAM solver, we predict the threshold energy required to ignite the fuel mixture. For this, the single step using the Arrhenius law is selected to model ignition in the flame kernel of stochiometric and lean CH4/air mixtures, allowing it to develop into a self-sustained flame. The ignition power density, an energy quantity normalised with volume, is incrementally varied, keeping the kernel critical radius rs constant at 0.5 mm in the quiescent mixture of two equivalence ratios ϕ 0.9 and 1.0, for varied operating pressures of 1, 5, and 10 bar at the constant initial temperature of 300 K. The minimum ignition energy is validated with twelve independent 1-bar datasets both numerically and experimentally. The effect of pressure on MIEs, which diminish as pressure rises, is significant. At ϕ = 1.0 (and 0.9), the flame temperature reached 481.24 K (457.803 K) at 1 bar, 443.176 K (427.356 K) at 5 bar, and 385.56 K (382.688 K) at 10 bar. The minimum ignition energy was validated using twelve independent 1-bar datasets from both numerical simulations and experiments. The results show strong agreement with many experimental findings. Finally, a mathematical formulation of MIE is devised; a function of pressure and equivalence ratio shows a slightly curved relationship.

Multi-Objetive Dispatching in Multi-Area Power Systems Using the Fuzzy Satisficing Method

The traditional mathematical models for solving the economic dispatch problem at the generation level primarily focus on minimizing overall operational costs while ensuring demand is met across various periods. However, contemporary power systems integrate a diverse mix of generators from both conventional and renewable energy sources, contributing to economically efficient energy production and playing a pivotal role in reducing greenhouse gas emissions. As the complexity of power systems increases, the scope of economic dispatch must expand to address demand across multiple regions, incorporating a range of objective functions that optimize energy resource utilization, reduce costs, and achieve superior economic and technical outcomes. This paper, therefore, proposes an advanced optimization model designed to determine the hourly power output of various generation units distributed across multiple areas within the power system. The model satisfies the dual objective functions and adheres to stringent technical constraints, effectively framing the problem as a nonlinear programming challenge. Furthermore, an in-depth analysis of the resulting and exchanged energy quantities demonstrates that the model guarantees the hourly demand. Significantly, the system’s efficiency can be further enhanced by increasing the capacity of the interconnection links between areas, thereby generating additional savings that can be reinvested into expanding the links’ capacity. Moreover, the multi-objective model excels not only in meeting the proposed objective functions but also in optimizing energy exchange across the system. This optimization is applicable to various types of energy, including thermal and renewable sources, even those characterized by uncertainty in their primary resources. The model’s ability to effectively manage such uncertainties underscores its robustness, instilling confidence in its applicability and reliability across diverse energy scenarios. This adaptability makes the model a significant contribution to the field, offering a sophisticated tool for optimizing multi-area power systems in a way that balances economic, technical, and environmental considerations.

Effect of Atmospheric Mixing on Spectral Reflectivity in Sentinel Images of Baghdad Province

The lowest layer of the atmosphere is called the atmospheric mixed layer, characterized by small-scale, irregular air motions defined by winds that change in speed and direction. Aerosol radiative effects impact the atmospheric boundary layer (ABL), which holds most aerosols in the lower atmosphere. Aerosol absorption and scattering both lower the quantity of solar energy that reaches the ground, which has an impact on the spectral signature of the land coverings. In this study, 51 locations in downtown Baghdad were chosen for four different types of land cover (water bodies, farms, open areas, and residential areas) for Sentinel 2 satellite imagery, and the time the pictures were taken was 8:00 am ( 22 March, 22 June, 20 September, and 22 December) 2021. Their spectral reflectance was calculated at the NIR band using a mathematical equation in the ArcGIS program for Sentinel 2 satellite images that had been processed and analyzed. Also, atmospheric boundary layer height and solar radiation values were downloaded for the same date as the satellite images and compared with the spectral reflectivity values of the land covers(agriculture area, residential area, open area, and river) and knowing the effect of the mixing layer and solar radiation on the spectral reflectance values. The highest value of spectral reflectivity, mixing layer height, and solar radiation was in June at (0.065, 1965.524629, and 897.7088) respectively. The spectral reflectivity of plants at near-infrared (NIR) was higher than the rest of the earth’s features because plants reflect near-infrared radiation and absorb the red and blue parts of the spectrum.

Enzymatic modification of cotton fibre polysaccharides as an enabler of sustainable laundry detergents

Cotton is the most common natural fibre used in textile manufacture, used alone or with other fibres to create a wide range of fashion clothing and household textiles. Most of these textiles are cleaned using detergents and domestic or commercial washing machines using processes that require many chemicals and large quantities of water and energy. Enzymes can reduce this environmental footprint by enabling effective detergency at reduced temperatures, mostly by directly attacking substrates present in the soils. In the present study, we report the contribution of a cleaning cellulase enzyme based on the family 44 glycoside hydrolase (GH) endo-beta-1,4-glucanase from Paenibacillus polymyxa. The action of this enzyme on textile fibres improves laundry detergent performance in several vectors including soil anti-redeposition, dye transfer inhibition and stain removal. Molecular probes are used to study how this enzyme is targeting both amorphous cellulose and xyloglucan on textile fibres and the relationship between textile surface effects and observed performance benefits.

Research on the characteristics of partial discharge gas generation in typical defects of oil immersed current transformers

During the operation of oil-immersed current transformers, they gradually deteriorate due to various factors. In order to study the relationship between partial discharge and gas generation characteristics under different typical defects, this paper measures the unit-time discharge energy, unit-time apparent discharge quantity, pulse repetition rate, and gas generation rate during the discharge development process of three typical defects: protrusion defect, surface defect, and gas gap defect. The study reveals that the generation of hydrocarbon gases and hydrogen in the oil mainly depends on discharges with an apparent discharge quantity above 300 pC. Among the discharge characteristics, the unit-time discharge energy and unit-time average discharge quantity significantly impact the gas generation rate. It is found that the content of C2H2 and C2H4 in the oil for protrusion and surface defects increases significantly with discharge intensity, while CH4 and H2 show significant changes for gas gap defects. Additionally, an approximately linear relationship exists between discharge energy per unit time, pulse repetition rate, and the rate of characteristic gas generation for both protrusion and surface defects, as well as for gas gap defects. These findings provide a reference for diagnosing current transformers and highlight the critical role of discharge characteristics in gas generation dynamics.

Oscillating Heat Pipe Start-up and Flow Characteristics with Water as Working Fluid

Thermal management has grown more and more problematic as electronic components continue to get faster and smaller. One of the passive two-phase cooling systems are Oscillating heat pipe (OHP) that have the capacity to transmit a significant quantity of thermal energy across long distances. Oscillating heat pipe is a device that has the potential to satisfy this developing requirement. An investigation into the effects of orientation, filling ratio, and heat load on the initiation and characteristics of oscillatory motion, combining numerical simulations with experimental validation. A copper tube with a 2 mm inner diameter and a 2 mm wall thickness is used to fabricate the OHP. The condenser, evaporator, and adiabatic sections are designed with lengths of 50 mm, 50 mm, and 150 mm, respectively. Results showed that the onset of oscillation occurs more rapidly with increasing input heat flux values compared to lower heat input conditions. The amplitude variations of the temperature of evaporator raised with the raising of heating power. The curves for the higher heat inputs (60 and 80 watts) appear to have higher average evaporator temperatures throughout the test compared to the 40-watt curve. Oscillation movement in tubes is proportional to charge ratio, and it is observed that it rises as charge ratio increases. It demonstrates that in Closed-loop oscillating heat pipe, a sufficient charge ratio is required to maintain the motion of oscillation.