Diverse Conditions Research Articles

Thermodynamic Modeling of a Solar-Driven Organic Rankine Cycle-Absorption Cooling System for Simultaneous Power and Cooling Production

Humanity is facing the challenge of reducing its environmental impact. For this reason, many specialists worldwide have been studying the processes of production and efficient use of energy. In this way, developing cleaner and more efficient energy systems is fundamental for sustainable development. The present work analyzed the technical feasibility of a solar-driven power-cooling system operating in a particular location in Mexico. The theoretical system integrates organic Rankine and single-stage absorption cooling cycles. A parabolic trough collector and a storage system integrated the solar system. Its performance was modeled for a typical meteorological year using the SAM software by NREL. The analyzed working fluids for the organic cycle include benzene, cyclohexane, toluene, and R123, while the working fluid of the absorption system is the ammonia-water mixture. The cycle’s first and second-law performances are determined in a wide range of operating conditions. Parameters such as the energy utilization factor, turbine power, COP, and exergy efficiency are reported for diverse operating conditions. It was found that the highest energy utilization factor was 0.68 when the ORC utilized benzene as working fluid at ORC and ACS condensing temperatures of 80 °C and 20 °C, respectively, and at a cooling temperature of 0 °C. The best exergy efficiency was 0.524 at the same operating conditions but at a cooling temperature of −10 °C.

Interaction of Zinc Mineral Nutrition and Plant Growth-Promoting Bacteria in Tropical Agricultural Systems: A Review.

The relationship between zinc mineral nutrition and plant growth-promoting bacteria (PGPB) is pivotal in enhancing agricultural productivity, especially in tropical regions characterized by diverse climatic conditions and soil variability. This review synthesizes and critically evaluates current knowledge regarding the synergistic interaction between zinc mineral nutrition and PGPB in tropical agricultural systems. Zinc is an essential and fundamental micronutrient for various physiological and biochemical processes in plants. Its deficiency affects plant growth and development, decreasing yields and nutritional quality. In tropical regions, where soil zinc availability is often limited or imbalanced, the PGPB, through different mechanisms such as Zn solubilization; siderophore production; and phytohormone synthesis, supports Zn uptake and assimilation, thereby facilitating the adverse effects of zinc deficiency in plants. This review outlines the impacts of Zn-PGPB interactions on plant growth, root architecture, and productivity in tropical agricultural systems. The positive relationship between PGPB and plants facilitates Zn uptake and improves nutrient use efficiency, overall crop performance, and agronomic biofortification. In addition, this review highlights the importance of considering indigenous PGPB strains for specific tropical agroecosystems, acknowledging their adaptability to local conditions and their potential in sustainable agricultural practices. It is concluded that Zn fertilizer and PGPBs have synergistic interactions and can offer promising avenues for sustainable agriculture, addressing nutritional deficiencies, improving crop resilience, and ensuring food security.

Data-driven degradation trajectory prediction and online knee point identification of battery in electric vehicles

Nonlinear degradation prediction of lithium-ion batteries is of great value in battery management systems. Knee point in degradation is a significant signal for state of health. However, large data generated by diverse aging mechanisms and dynamic operating conditions cannot be used completely in prediction. Firstly, this paper proposes a novel data-driven discrete grey model for battery degradation with knee point based on small sample modeling. Secondly, combined with four non-numerical differential methods, knee point is identified according to the predicted degradation trajectory. Then, batteries in 24 different fast charging modes are selected as a set of experimental subjects. Results show that 40% data of total cycles is sufficient to effectively predict battery degradation trajectory and identify the knee point. Finally, performance of fast charging modes is analyzed based on the predicted knee point. This work demonstrates the strong applicability of the grey model in reasonably predicting battery degradation trajectory and accurately identifying the knee point, providing a reference for fast charging schemes in complex engineering systems.

Development and Validation of an Instrument for Wave Height Measurement with Encoder Sensors and Accelerometer

Ocean waves play a significant role in coastal dynamics and the management of coastal development activities. However, there are limited instruments to measure the wave height, particularly in developing countries. This study introduces a novel instrument design for simple and cost-effective wave height measurement. The proposed instrument combines a Hall-effect sensor and an accelerometer to capture the rise and fall of a buoy in response to wave movements. The Hall-effect sensor as a rotary encoder detects the rotation of the buoy while the accelerometer measures the tilt of the instrument caused by ocean waves. The instrument is constructed using PVC pipes and incorporates long-range (LoRa) communication technology for real-time monitoring. Experimental tests were conducted at a study site in Banyuwangi Regency, Indonesia, where the performance of the instrument was compared with an ultrasonic sensor-based instrument. The results validate the effectiveness of the proposed instrument design for wave height measurement. The collected data were transmitted via the LoRa communication system, enabling convenient monitoring and analysis of sea-level changes. The valuable contribution of the instrument to the field stems from its precision in measuring the wave height, adaptability to diverse conditions, and potential applicability in shallow waters.

Effect of Genotype, Environment, and Their Interaction on the Antioxidant Properties of Durum Wheat: Impact of Nitrogen Fertilization and Sowing Time

In this study, the influence of genotype (G), environment (E), and their interaction (G × E) on the content of total free phenolic compounds (TPC) and the antioxidant capacity (AC) was investigated, using sixteen durum wheat genotypes cultivated under seven crop management systems in Mediterranean environments. Possible correlations between TPC and AC with protein content (PC) and vitreous kernel percentage (VKP) were examined. Gs that exhibited stability across diverse conditions were studied through a comprehensive exploration of G × E interaction using a GGE biplot, Pi, and 𝘒R. The results indicated significant impacts of E, G, and G × E on both TPC and AC. Across E, the mean values of G for TPC, ABTS (2’-azino-bis-3-ethylbenzothiazoline-6-sulfonic acid), DPPH (2,2-diphenyl-1-picrylhydrazyl), and FRAP (ferric reducing antioxidant power) values were 48.8 mg Trolox equivalents (TE)/100 g, 121.3 mg TE/100 g, 23.0 mg TE/100 g, and 88.4 mg TE/100 g, respectively. E, subjected to splitting top-dressing N fertilization, consistently showed low values, while the late-sowing ones possessed high values. Organic crop management maintained a stable position in the middle across all measurements. The predominant influence was attributed to G × E, as indicated by the order G × E > E > G for ABTS, DPPH, and FRAP, while for TPC, it was E > G × E > G. For TPC, the superior Gs included G5, G7 and G10, for ABTS included G3, G5 and G7, and for protein included G1, G9, and G16. G7 and G5 had a high presence of frequency, with G7 being the closest genotype to the ideal for both TPC and ABTS. These results suggest that the sowing time, nitrogen fertilization, and application method significantly impact the various antioxidant properties of durum wheat. This study holds significant importance as it represents one of the few comprehensive explorations of the impact of various Es, Gs, and their interactions on the TPC and AC in durum wheat, with a special emphasis on crop management and superior Gs possessing stable and high TPC and AC among them, explored by GGE biplot, Pi and 𝘒R. Further experimentation, considering the effect of the cultivation year, is necessary, to establish more robust and stable conclusions.

Comparative study of single-phase multilevel cascaded transformerless inverters with different modulation methods

This paper presents an in-depth exploration of a single-phase multilevel cascaded H5 (CH5) transformerless inverter employing both phase-shifted PWM (PS-PWM) and level-shifted PWM (LS-PWM) methodologies. A comparative analysis is conducted with the conventional multilevel inverter (MLI) topologies, specifically the cascaded H-bridge (CHB) and H5 inverter configurations. The investigation delves into the impact of modulation index variations, load fluctuations, and modulation methods on the inverter's operational performance.While switches in the CHB-MLI operate continuously at the carrier frequency state using PS-PWM and LS-PWM methods, the CH5-MLI exhibits a unique behavior with some switches toggling at high frequency, while others synchronize with the grid frequency. The CH5-MLI topology demonstrates efficiency improvements and a reduction in total harmonic distortion (THD). Notably, employing the LS-PWM method yields more significant efficiency enhancements and THD reduction compared to the PS-PWM method. To analyze power loss characteristics under diverse operating conditions, the PLECS simulation environment is leveraged for calculating conduction and switching losses.The application of phase-shifted and level-shifted carrier-based pulse width modulation strategies to high and low-frequency switching switches results in minimized output harmonics, elevated operator safety, and enhanced overall reliability and efficiency. This work contributes significantly to the field by offering a detailed exploration of the CH5-MLI topology's dynamic behavior, modulation strategies, and their collective impact on performance metrics such as efficiency, THD, and power losses.

The effect of the compound slope spillway on air entrainment and total kinetic energy using computational fluid dynamics

Abstract The spillway is a hydraulic structure used for managing discharge, dissipating energy, and aeration purposes. The objective of this CFD analysis was to compare the ways in which water moved over various slanted spillways. Both the turbulence and the air–water interface were located using the volume of fluid (VOF) technique and a realizable k-model. Five different spillway models with varying slopes (normal = 30°, compound1 = 20° and 39°, and compound2 = 39° and 20°) were modelled and simulated in ANSYS Fluent. Computational data have been compared to the experimental results, and the findings were astonishing – the CFD model precisely captured the all-important flow facets. The numerical model pinpointed the inception point that occurred due to changes in slope and structure. In comparison to the normal slopes of (30°) and the compound slopes of (39°/20°), the surge in the location of the inception point was around 58%. The results of the research indicate a significant increase in turbulent kinetic energy as a result of the introduction of the compound slope. The study conducted has effectively achieved a crucial objective of the project, which is to enhance the operational efficiency and reliability of the spillway under diverse flow conditions.

Improving cryo-EM grids for amyloid fibrils using interface-active solutions and spectator proteins

Preparation of cryoelectron microscopy (cryo-EM) grids for imaging of amyloid fibrils is notoriously challenging. The human islet amyloid polypeptide (hIAPP) serves as a notable example, as the majority of reported structures have relied on the use of nonphysiological pH buffers, N-terminal tags, and seeding. This highlights the need for more efficient, reproducible methodologies that can elucidate amyloid fibril structures formed under diverse conditions. In this work, we demonstrate that the distribution of fibrils on cryo-EM grids is predominantly determined by the solution composition, which is critical for the stability of thin vitreous ice films. We discover that, among physiological pH buffers, HEPES uniquely enhances the distribution of fibrils on cryo-EM grids and improves the stability of ice layers. This improvement is attributed to direct interactions between HEPES molecules and hIAPP, effectively minimizing the tendency of hIAPP to form dense clusters in solutions and preventing ice nucleation. Furthermore, we provide additional support for the idea that denatured protein monolayers forming at the interface are also capable of eliciting a surfactant-like effect, leading to improved particle coverage. This phenomenon is illustrated by the addition of nonamyloidogenic rat IAPP (rIAPP) to a solution of preaggregated hIAPP just before the freezing process. The resultant grids, supplemented with this “spectator protein”, exhibit notably enhanced coverage and improved ice quality. Unlike conventional surfactants, rIAPP is additionally capable of disentangling the dense clusters formed by hIAPP. By applying the proposed strategies, we have resolved the structure of the dominant hIAPP polymorph, formed in vitro at pH 7.4, to a final resolution of 4 Å. The advances in grid preparation presented in this work hold significant promise for enabling structural determination of amyloid proteins which are particularly resistant to conventional grid preparation techniques.

Costs of ribosomal RNA stabilization affect ribosome composition at maximum growth rate

Ribosomes are key to cellular self-fabrication and limit growth rate. While most enzymes are proteins, ribosomes consist of 1/3 protein and 2/3 ribonucleic acid (RNA) (in E. coli).Here, we develop a mechanistic model of a self-fabricating cell, validated across diverse growth conditions. Through resource balance analysis (RBA), we explore the variation in maximum growth rate with ribosome composition, assuming constant kinetic parameters.Our model highlights the importance of RNA instability. If we neglect it, RNA synthesis is always cheaper than protein synthesis, leading to an RNA-only ribosome at maximum growth rate. Upon accounting for RNA turnover, we find that a mixed ribosome composed of RNA and proteins maximizes growth rate. To account for RNA turnover, we explore two scenarios regarding the activity of RNases. In (a) degradation is proportional to RNA content. In (b) ribosomal proteins cooperatively mitigate RNA instability by protecting it from misfolding and subsequent degradation. In both cases, higher protein content elevates protein synthesis costs and simultaneously lowers RNA turnover expenses, resulting in mixed RNA-protein ribosomes. Only scenario (b) aligns qualitatively with experimental data across varied growth conditions.Our research provides fresh insights into ribosome biogenesis and evolution, paving the way for understanding protein-rich ribosomes in archaea and mitochondria.

Veterinary Pathology Diseases and Disorders in Domestic and Wild Animals

Veterinary pathology plays a crucial role in understanding and managing diseases and disorders in both domestic and wild animals. This field encompasses the study of various pathologies, from infectious diseases like the Spanish Goat Encephalitis Virus, which causes severe neurological symptoms and high mortality in goats, to toxicological conditions such as oleander poisoning in horses, characterized by renal and cardiac lesions. It also includes the investigation of neoplastic conditions, as seen in canine apocrine gland adenocarcinoma of the anal sac and various tumors in African pygmy hedgehogs. The integration of clinical and histopathological findings is essential for accurate diagnosis, treatment, and management of these diverse conditions, highlighting the importance of veterinary pathology in animal health and welfare. Veterinary pathology, a vital branch of veterinary medicine, is instrumental in diagnosing, understanding, and managing a wide array of diseases and disorders in both domestic and wild animals. It encompasses the study of various pathologies, including infectious diseases, toxicological conditions, and neoplastic diseases. For instance, research into the Spanish Goat Encephalitis Virus sheds light on its neurological impact and high mortality rates in goats, while studies on oleander poisoning in horses focus on its renal and cardiac implications. Additionally, the field addresses neoplastic conditions such as canine apocrine gland adenocarcinoma of the anal sac and various tumors in African pygmy hedgehogs. This discipline is not only pivotal in diagnosing and treating these conditions but also plays a significant role in advancing our understanding of animal health and welfare, emphasizing the need for continuous research and collaboration between veterinary clinicians and pathologists.

Novel applications of various neural network models for prediction of photovoltaic system power under outdoor condition of mountainous region

The geography and landscape of mountainous locations are frequently varied, which causes uneven solar radiation exposure in different places which leads to photovoltaic (PV) power generation variation drastically. Therefore accurate PV power prediction is essential for industries in optimize energy production, Energy Planning and Grid Integration, Energy Storage Integration in such diverse conditions. This study aims to predict the power produced by a 2.680 kWp PV under outdoor condition in mountainous region at different time intervals of 10 seconds, 1 minute, 30 minutes, 1 hour and 1 day using different data analytics models. The results show that the radial basis neural network was the most effective model for the intervals of 10 seconds, 1 minute, 30 minutes, and 1 day. Its RMSE was 19.11 W for the 10-second interval, 22.83 W for the 1-minute interval, 25.94 W for the 30-minute interval, and 9.08 W for the 1-day interval. With an RMSE of 23.22 W, the Kernel Ridge Regressor had the best performance for the 1-hour period. This suggests that the model with only two parameters such as temperature and irradiance predict PV power more accurately. The findings can be applied to improve PV system design and performance by precisely forecasting the systems' power output in different weather scenarios.

Copper-Cystine Biohybrid-Embedded Nanofiber Aerogels Show Antibacterial and Angiogenic Properties.

Copper-cystine-based high aspect ratio structures (CuHARS) possess exceptional physical and chemical properties and exhibit remarkable biodegradability in human physiological conditions. Extensive testing has confirmed the biocompatibility and biodegradability of CuHARS under diverse biological conditions, making them a viable source of essential Cu2+. These ions are vital for catalyzing the production of nitric oxide (NO) from the decomposition of S-nitrosothiols (RSNOs) found in human blood. The ability of CuHARS to act as a Cu2+ donor under specific concentrations has been demonstrated in this study, resulting in the generation of elevated levels of NO. Consequently, this dual function makes CuHARS effective as both a bactericidal agent and a promoter of angiogenesis. In vitro experiments have shown that CuHARS actively promotes the migration and formation of complete lumens by redirecting microvascular endothelial cells. To maximize the benefits of CuHARS, they have been incorporated into biomimetic electrospun poly(ε-caprolactone)/gelatin nanofiber aerogels. Through the regulated release of Cu2+ and NO production, these channeled aerogels not only provide antibacterial support but also promote angiogenesis. Taken together, the inclusion of CuHARS in biomimetic scaffolds could hold great promise in revolutionizing tissue regeneration and wound healing.

Buoyancy-Driven Dissolution Instability in a Horizontal Hele-Shaw Cell.

The dissolution of minerals within rock fractures is fundamental to many geological processes. Previous research on fracture dissolution has highlighted the significant role of buoyancy-driven convection leading to dissolution instability. Yet, the pore-scale mechanisms underlying this instability are poorly understood primarily due to the challenges in experimentally determining flow velocity and concentration fields. Here, we integrate pore-scale simulations with theoretical analysis to delve into the dissolution instability prompted by buoyancy-driven convection in a radial horizontal geometry. Initially, we develop a pore-scale modeling approach incorporating gravitational effects, subsequently validating it through experiments. We then employ pore-scale numerical simulations to elucidate the 3D intricacies of flow-dissolution dynamics. Our findings reveal that a simple criterion can delineate the condition for the onset of buoyancy-driven dissolution instability. If the characteristic length falls below a critical threshold, dissolution remains stable. Conversely, exceeding this threshold leads to two distinct regimes: the unstable regime of the confined domain affected by the initial aperture and the unstable regime of the semi-infinite domain independent of the initial aperture where the instability is no longer influenced by the lower boundary. We demonstrate that the pore-scale mechanism for this instability is due to the concentration boundary layer attaining a gravitationally unstable critical thickness. Through theoretical analysis of this layer and the time scales of diffusion and advection, we establish a theoretical model to predict where the dissolution instability occurs. This model aligns closely with our numerical simulations and experimental data across diverse conditions. Our work improves the understanding of buoyancy-driven dissolution instability in radial horizontal geometry. It is also of practical significance in understanding cavity formation in karst hydrology and preventing leaks in geological CO2 storage.

An Explanatory Model of Red Lentil Seed Coat Colour to Manage Degradation in Quality during Storage

This study presents an explanatory biophysical model developed and validated to simulate seed coat colour traits including CIE L*, a*, and b* changes over time for stored lentil cultivars PBA Hallmark, PBA Hurricane, PBA Bolt, and PBA Jumbo2 under diverse storage conditions. The model showed robust performance for all cultivars, with R2 values ≥ 0.89 and RMSE values ≤ 0.0019 for all seed coat colour traits. Laboratory validation at 35 °C demonstrated a high agreement (Lin’s Concordance Correlation Coefficient, CCC ≥ 0.82) between simulated and observed values of all colour traits for PBA Jumbo2 and strong agreement (CCC ≥ 0.81) for PBA Hallmark in brightness (CIE L*) and redness (CIE a*), but not in yellowness (CIE b*). At 15 °C, both cultivars exhibited moderate to weak agreement between simulated and observed values of all colour traits (CCC ≤ 0.47), as very little change was recorded in the observed values over the 360 days of storage. Bulk storage system validation for PBA Hallmark showed moderate performance (CCC ≥ 0.46) between simulated and observed values of all colour traits. Modelling to simulate changes in seed coat colour traits of lentils over time will equip growers and traders to make informed managerial decisions when storing lentils for long periods.

Adaptive Integrated Thermal Management System for a Stable Driving Environment in Battery Electric Vehicles

With an increase in global warming, battery electric vehicles (BEVs), which are environmentally friendly, have been rapidly commercialized to replace conventional vehicles with internal combustion engines. Unlike traditional internal combustion engine vehicles, the powertrain system of BEVs operates with high efficiency, resulting in lower heat generation. This poses a challenge for cabin heating under low-temperature conditions. Conversely, under high-temperature conditions, the operating temperature of a high-voltage battery (HVB) is lower than the ambient air temperature, which makes cooling through ambient air challenging. To overcome these challenges, in this study, we proposed an integrated thermal management system (ITMS) based on a heat pump system capable of stable thermal management under diverse climatic conditions. Furthermore, to assess the ability of the proposed ITMS to perform thermal management under various climatic conditions, we integrated a detailed powertrain system model incorporating BEV specifications and the proposed ITMS model based on the heat pump system. The ITMS model was evaluated under high-load-driving conditions, specifically the HWFET scenario, demonstrating its capability to perform stable thermal management not only under high-temperature conditions, such as at 36 °C, but also under low-temperature conditions, such as at −10 °C, through the designated thermal management modes.

Passivating Blunt‐Ended Helices to Control Monodispersity and Multi‐Subunit Assembly of DNA Origami Structures

Deoxyribonucleic acid (DNA) origami enables the synthesis of bespoke nanoscale structures suitable for diverse applications. Effective design requires preventing uncontrolled aggregation, while still facilitating directed multi‐subunit assembly. Uncontrolled aggregation is often caused by base‐stacking interactions between arrays of blunt‐ended helices, a problem which is typically mitigated by incorporating disordered single‐stranded DNA (ssDNA) (like scaffold loops or poly‐thymine brushes) at the end of double‐stranded DNA (dsDNA) helices. Such disordered regions are ubiquitous in DNA origami structures yet their optimal design requirements in various chemical environments remains unclear. This study systematically investigates scaffold loops and poly‐nucleotide brushes for aggregation prevention and control of multi‐subunit assembly, examining length, sequence, and MgCl2 concentration dependencies. Additionally, a novel strategy is introduced using orthogonal double‐stranded DNA helices to create a steric shield against base stacking. The results reveal key considerations. Poly‐thymine brushes excel in achieving monodispersity across diverse conditions whereas scaffold loops aid directed multi‐subunit assembly. Orthogonal DNA helices remove the need for disordered regions altogether, preventing aggregation over a broad range of MgCl2 concentrations and facilitating controlled multi‐subunit assembly. This study expands the toolbox for DNA origami design and enables a more informed approach for achieving control of monodispersity and multi‐subunit assembly in DNA origami structures.

Special irregular neutrosophic graphs

Recently, the neutrosophic graph has been introduced as an extension of fuzzy graphs and intuitionistic fuzzy graphs, which offers more compatibility and flexibility than these two types in modeling and structuring many actual issues. In this article, using neutrosophic highly strong arc, the new notions of (totally) special irregular, highly special irregular, strongly special irregular, neighborly special irregular and special arc-irregular of neutrosophic graphs are stated. Finally, one of their utilizations relevant to offering a fixed optimization model in decision making in diverse conditions is presented. In fact,we present a decision-making problem in real-world applied example which discusses the factors influencing a companys efficiency. The presented model is, in fact, a factor-based model wherein the impact score of each factor is divided into two types of direct and indirect influences, in which the concept of neutrosophic special dominating set plays a significant role.

Relationship between payment problems and health: A nation-wide register study in Norway.

Previous studies have found a solid correlation between payment problems and health, and a large body of literature has recognised the impact of debt burden on ill health. However, few have looked at the reversed causality-the impact of health on over-indebtedness and payment problems. In this article, we investigate whether or not a person with mental and physical health challenges is more likely to experience debt enforcement, and we take a step further to explore the role of health status on receiving debt settlement for those with severe payment problems. The article uses register data from Statistics Norway, the Norwegian Patient Registry and the Mortgages Registry from 2009 to 2018. When using conditional logistic models and fixed-effects Poisson regressions with a one-year lagged effect, we find that mental disorders significantly contribute to individuals' financial strains, while physical health does not play a substantial role. When integrating the models with dynamic health effects, all health indicators turned out to have substantial impacts, indicating an extended delayed physical health effect on financial outcomes. Poor health leads to increased payment problems, yet individuals facing health challenges have a lower likelihood of receiving necessary assistance in debt settlement. These findings emphasise the need for tailored services to address the financial challenges of debtors with diverse health conditions.

Influence of diverse boundary conditions on SH and P-SV wave dynamics in micropolar plates

Studying wave propagation characteristics in plates is vital for comprehending the material dynamics to enhance the strength of structures and for optimizing the effectiveness of non-destructive testing devices. Micropolar elasticity displays microcontinuum behavior by integrating rotational and coupling effects through displacements and micro-rotations. The present study thoroughly investigates horizontally polarized shear waves (SH) within a thin micropolar plate by employing diverse boundary conditions namely stress-free, clamped, and mixed conditions. Shear horizontal waves propagate within a plate by shearing the material along the surface, excluding any motion in perpendicular direction. Moreover, for a more comprehensive grasp of wave behavior in a micropolar plate, the study investigates P-SV type waves under plane strain conditions. Analytical techniques are utilized to derive the dispersion relations for SH and P-SV type waves in a micropolar plate. Graphical representations are provided to showcase the impacts of various micropolar parameters such as coupling number, characteristic length, and plate thickness on the phase velocities of SH and P-SV type waves. The study also includes a dispersion analysis of the multimode aspect of SH and P-SV waves. This thorough investigation can significantly augment the comprehension of wave propagation phenomena within plate-like structures.

Optimizing Vertical-Axis Wind Turbine Performance and Determining Optimal Velocity and Deflector Configuration Based on Wind Speed

In the realm of wind energy harnessing, Vertical-axis Wind Turbines (VAWTs) have emerged as promising alternatives. However, they face persistent challenges due to their low efficiency and poor self-starting properties. This study addresses these limitations and aims to unlock the full potential of VAWTs by conducting a comprehensive investigation. The focus of this research lies in determining the optimal operating velocities to enhance the performance of Savonius-type VAWTs, leveraging advanced deflectors. The study delves into an in-depth analysis of the optimal deflector distances and angles for the turbine, taking into account different geographical areas with varying wind velocities. To achieve this, a Savonius-type VAWT equipped with advanced wind deflectors was meticulously designed and tested. Utilizing SOLIDWORKS software, sophisticated turbine models were crafted, which were then subjected to rigorous analysis using ANSYS Fluent, Computational Fluid Dynamics (CFD) software. The research methodology involved conducting simulations across a range of wind velocities, spanning from 1 ms-1 to 8 ms-1, and changing the deflector distance from 100 cm to 150 cm from the centre of the turbine, and the deflector angle from 12 to 45 degrees. During the simulations, critical indicators of turbine performance, including moment coefficient, moment, force coefficient, and force acting on the blade, were closely examined. The study uncovered significant variations in the power output of the Savonius-type vertical-axis wind turbine (VAWT) fitted with an advanced deflector system, especially at lower wind speeds. Notably, the study revealed that at different wind velocities, the optimum deflector configuration changed, with the highest energy-generating capacity observed at 1 m/s for the wind turbine equipped with advanced deflectors. Outperforming the turbine lacking a deflector system, this inventive method demonstrates the capacity to notably boost energy generation. This novel method underscores the capacity for substantial improvements in energy production. Additionally, the research offers valuable insights into customized deflector distance and angle combinations, optimizing turbine performance for specific wind velocity ranges. By strategically positioning the deflectors, higher energy output can be achieved, making the VAWT system more adaptable and efficient across diverse wind conditions
 
 Keywords: Vertical-axis wind turbine, Wind deflectors, Computational Fluid Dynamics, SOLIDWORKS, ANSYS Fluent