Wind Speed Conditions Research Articles

Optimizing Wind Speed Predictions in Bangladesh: Unveiling the Power of Machine Learning Approaches

Wind speed is a naturally occurring phenomenon that arises from the intricate interplay of various atmospheric processes. Wind speed prediction is pivotal in various sectors worldwide, and Bangladesh is no exception. Beyond its impact on agriculture, water management, and disaster preparedness, wind speed also plays a crucial role in urban planning and construction projects. Architects and engineers rely on accurate wind speed forecasts to design buildings and infrastructure that can withstand local wind conditions. Furthermore, the aviation and maritime industries heavily depend on wind speed predictions to ensure the safety of flights and shipping routes. Predicting wind speeds in Bangladesh poses a significant challenge due to the region's susceptibility to frequent seasonal changes influenced by its coastal location and complex, nonlinear climate patterns. To address this important aspect, we leverage Machine Learning (ML) algorithms, including Linear Discriminant Analysis (LDA), Classification and Regression Trees (CART), Random Forest (RF), K Nearest Neighbors (K-NN), and Support Vector Machine (SVM) to forecast wind speeds at various weather stations in Bangladesh. We utilized various accuracy metrics, including precision, sensitivity, specificity, F-measure, and overall accuracy, to evaluate the performances of the algorithms. The RF model outperformed the other models with an overall accuracy of 94.73% for predicting wind speed conditions in Bangladesh. On the other hand, the LDA model exhibited the lowest performance, achieving an accuracy of 93.27% in comparison to the other models. It is noticeable that the aforementioned five models showed more than 90% accuracy for windspeed prediction. Additionally, we complement our analysis with visual representations such as box plots, density plots, dot plots, parallel plots, and scatterplot matrix plots. These empirical results also highlighted the RF as the most suitable method for predicting contemporary wind speed patterns in Bangladesh. International Journal of Statistical Sciences, Vol. 24(2), November, 2024, pp 137-154

Weathering crust formation outpaces melt-albedo feedback on blue ice shelves of East Antarctica

The penetration of shortwave radiation beneath glacier surfaces has the potential to induce melting leading to the formation of a porous white layer commonly known as weathering crust. Very little is known about its role in the Antarctic Ice Sheet. Here we provide unprecedented observational evidence for the weathering crust formation over blue ice areas of ice shelves of the Northern Victoria Land in austral summer 2022–2023, by means of in-situ and remote-sensing observations. Then, we estimated the radiative impact of the weathering crust, demonstrating a predominant negative albedo feedback over blue ice areas (on 93% of the study area), with respect to positive melt-albedo feedback (supraglacial-pond formation). Furthermore, weathering crust occurred after a period of increasing temperature, relative humidity, low wind speed and clear sky conditions. Moreover, we claim that this new process should be included in regional climate modelling of the Antarctic Ice Sheet.

Analysis of the Electric Power Monitoring System in Wind Power Plants Based on Arduino Uno

The Wind Power Plant is a renewable energy solution that can reduce dependence on fossil fuels and reduce greenhouse gas emissions. However, to ensure operational efficiency and reliability, an effective monitoring system is needed to monitor and manage the electrical power produced. This resear chaims to develop and analyzean electrical power monitoring system at PLT Busing the Arduino Uno platform. The proposed monitoring system consist sofsophisti cated sensors integrated with Arduino Unotocollect real-time data regarding wind speed, output voltage, current and turbine operational conditions. The data collectedby these sensor sissentto the Arduino Uno, which then processes andstores thedata for further analysis. Additionally,this data canbe transmitted toot her devices for remote monitoring via a wire less communication module. Algorithms were developed to analyze and display critical information about turbine performance, including anomaly detection and failure prediction. System testing was carried out on a small-scale PLTB model, and the results showed that this system was able to monitor changes in electrical power with high accuracy and fast response time. Implementation of this Arduino Uno-based monitoring system also enable searly detection of potential problems, so that preventive action can be taken to reduce downtime and increase operational efficiency. The results of this research showthat using Arduino Uno as a platform for the electrical power monitoring system at PLTBis not only effective in collecting andanalyzing data,butis also economical andeasy to implement.This system canbeeasily adaptedand expanded to suit the specific needs of various types of PLTB. In conclusion, the Arduino Uno-based monitoring system offers an innovative and practical solution to improve the performance and reliability of PLTB.

IPFOA-MKSVM and BA-MLP models for predicting closed busbar temperatures in high voltage nuclear power plants in different vacuum environments

The nuclear power closed busbar is a key power transmission component in the power system, and its high temperature may cause equipment failure. In this paper, for the temperature prediction of nuclear power closed busbar under vacuum environment, a multi-core support vector machine model optimized by the improved falcon predation algorithm and a multi-layer perceptron model enhanced by the back propagation algorithm are proposed. The vacuum pump is used to reduce the air pressure in the closed space to achieve a vacuum state. The collected data are preprocessed to improve the accuracy and stability of the model. In addition, the PSO and SVM models are used to compare and verify the superiority of the proposed model. The data set is divided into a training set and a test set. The results show that under different vacuum degrees, the prediction accuracy and stability of the IPFOA-MKSVM model are better than those of other models, but its error is slightly higher than the physical calculation result. Finally, the performance of the model in wind speed prediction is verified, and compared with several models to verify the accuracy of IPFOA-MKSVM under different vacuum and wind speed conditions.

Simulation of time-invariant three-dimensional Freak waves and their scattering identification based on the JONSWAP spectrum and Donelan direction function

Abstract The results of recent maritime accident investigations show that many maritime accidents are related to the attack of freak waves, which can sink ships instantaneously with colossal energy. To identify and forecast freak waves accurately and avoid the danger of freak waves to marine structures and people, we have conducted further research on freak waves. In this paper, we propose an efficient time-invariant three-dimensional (3-D) freak wave computational model to study the scattering characteristics of time-invarian 3-D freak waves and obtain a more explicit identification of their scattering differences. First, this paper adopts linear superposition method to simulate a 3-D random rough sea surface based on the JONSWAP wave spectrum and Donelan directional distribution function. Moreover, we analyze the effect of different angular frequencies on the simulated sea surface. At the same time, the Monte Carlo method is used to further simulate the capillary waves based on the random sea surface, and this method vastly improves the computational accuracy of the random sea surface. Then, based on the two-wave train superposition wave energy focusing mode, a numerical calculation method of time-invariant 3-D freak waves is proposed, and the time-series evolution process of 3-D freak waves is simulated. Finally, the backscattering coefficients of the 3-D freak wave surface are calculated using the two-scale method, and the electromagnetic scattering characteristics of the freak wave surface under different evolution stages, wind speeds, and radar incidence angles are analyzed. By this method, we conclude that the recognition of freak waves is more accurate under medium-high wind speed and significant incidence angle conditions. The experiments show that the research in this paper can identify and predict freak waves more effectively, further improve the forecast accuracy of future freak waves, and also have some application value for freak wave risk warnings.

Performance Characteristics of Newly Developed Real-Time Wave Measurement Buoy Using the Variometric Approach

Accurate measurement of ocean wave parameters is critical for applications including ocean modeling, coastal engineering, and disaster management. This article introduces a novel global navigation satellite system (GNSS) drifting buoy for surface wave measurements that addresses the challenges of performing real-time, high-precision measurements and realizing cost-effective large-scale deployment. Unlike traditional approaches, this buoy uses the kinematic extension of the variometric approach for displacement analysis stand-alone engine (Kin-VADASE) velocity measurement method, thus eliminating the need for additional high-precision measurement units and an expensive complement of satellite orbital products. Through testing in the South China Sea and Laoshan Bay, the results showed good consistency in significant wave height and main wave direction between the novel buoy and a Datawell DWR-G4, even under mild wind and wave conditions. However, wave mean period disparities were observed partially because of sampling frequency differences. To validate this idea, we used Joint North Sea Wave Project (Jonswap) spectral waves as input signals, the bias characteristics of the mean periods of the spectral calculations were compared under conditions of identical input signals and gradient-distributed wind speeds. Results showed an average difference of 0.28 s between the sampling frequencies of 1.28 Hz and 5 Hz. The consequence that high-frequency signals have considerable effects on the mean wave period calculations indicates the necessity of the buoy’s high-frequency operation mode. This GNSS drifting buoy offers a cost-effective, globally deployable solution for ocean wave measurement. Its potential for large-scale networked ocean wave observation makes it a valuable oceanic research and monitoring instrument.

State-of-the-art nonstationary hypersurface damage assessment approach for energy harvesters

Since EH (Energy Harvesters) constitute nowadays a vital part of renewable energy engineering, experimental research is required in addition to numerical modeling, serving reliable structural design and ensuring prolonged device service time. The performance of GPEH (GalloPing EH) has been examined in this case study, utilizing comprehensive laboratory wind tunnel tests, carried out under realistic windspeed conditions. Novel structural multivariate risks assessment methodology, presented here, being feasible for nonstationary nonlinear GPEH dynamic systems, that had been either physically measured over a representative period, providing jointly quasi-ergodic time-series, or directly numerically MCS (Monte Carlo Simulated). Based on laboratory-measured GPEH dynamics, the presented analysis demonstrates that the proposed multivariate hypersurface methodology offers robust predictions of the structural failure/damage risks. Furthermore, when dealing with raw measured timeseries, representing the high-dimensional dynamic system, existing risk assessment techniques struggle to handle nonlinear inter-correlations between GPEH critical components. This case study's main objective has been to validate and benchmark the novel multimodal risk assessment methodology, which utilizes multivariate nonstationary lab-recorded time histories to extract relevant design information from the underlying GPEH dynamics.The proposed state-of-the-art nonstationary hypersurface reliability approach being of a generic nature, offering additional capacity for damage/failure risks prognostics for a wide range of nonlinear multidimensional nonstationary systems. Forecasted damage and failure risks have been supplied with confidence bands, demonstrating the experimental setup's robustness, as well as the useful design features of the presented nonstationary hypersurface risks assessment methodology. It should be noted that the presented reliability methodology being mathematically exact, and it does not rely on simplifying assumptions.

Ability of typical greening tree species to purify NO2 under different environmental factors

Trees can uptake nitrogen dioxide(NO2) and purify atmosphere, but the complex variation of environmental factors affects the ability of trees to purify NO2. In this study, we conducted a one-time fumigation experiment on four typical greening tree species in China, including Japanese pagoda tree (Styphnolobium japonicum), Ginkgo (Ginkgo biloba), Manchurian red pine (Pinus tabuliformis), and Bunge’s pine (Pinus bungeana), to analyze the impact of environmental factors on the ability of the trees to remove NO2 from the air by quantifying their performance under different conditions of temperature, relative humidity, and wind speed. The results showed the following: (1) Broadleaf trees were more effective at purification compared with coniferous trees. (2) With the increase of temperature, the average purification rate of each tree species showed a decreasing and then increasing trend; except Bunge’s pine, the purification amount per unit leaf area of each tree species showed an increasing and then decreasing trend. (3) With increasing relative humidity, the purification of NO2 per unit leaf area in coniferous trees increased, while the trend in broadleaf trees decreased and then increased; the average purification rate of all the tree species, except Ginkgo, also decreased and then increased. (4) Temperature inhibited plant NO2 purification capacity, relative humidity promoted plant NO2 purification capacity, and wind speed had less ability to influence. (5) Multiple linear regression equations were successfully established to predict the ability of trees to purify NO2 under different environmental factors. The study provides an important reference to purify atmosphere.

Investigation of dynamic stall models on the aeroelastic responses of a floating offshore wind turbine

Dynamic stall effects significantly affect the aerodynamic load prediction of wind turbines. In order to investigate the dynamic stall effects on the loads and responses of a 15 MW floating offshore wind turbine (FOWT), a novel dynamic stall model, namely IAG, is implemented within the widely-used simulation software package OpenFAST in this study. The superiority and accuracy of the IAG model are verified by comparisons against experimental data and numerical results from the Beddoes-Leishman (B-L) model. The results have shown that the IAG model is able to more accurately capture edges of the hysteresis loops of aerodynamic coefficients corresponding to various airfoils and operation states. The aeroelastic responses of a 15 MW floating offshore wind turbine under normal and extreme environmental conditions are calculated by employing the IAG model. The impact of dynamic stall models on blade loads and displacements has been analyzed. It is found that the B-L model produces larger loads and displacements under high wind speed and yaw error conditions, attributed to the insufficiently computational robustness of the B-L model under deep stall situations and the seriously dynamic stall circumstances. The 1st-order and 2nd-order bending modes of the blade are expected to be enhanced by the aerodynamic loads that are predicted using the B-L model. Consequently, the bending-torsional coupling effects would be enhanced, leading to an increase up to 64.7 % on the in-plane bending moment. This study has confirmed that the dynamic stall model should be properly selected properly for the fully coupled analysis of FOWTs.

Development of a method for evaluating fabric surface contamination by particulate matter using fluorescent particles

Functional clothing products are being developed to prevent the attachment of particulate matter (PM). However, currently, PM-blocking performance of such products cannot be quantitatively evaluated. This study developed a method for measuring fabric surface contamination by PM by contaminating textile fabrics with PM and using an image processing technique. Silicate particles exhibiting fluorescence characteristics with a suitable size distribution were selected as PM simulants. The fabric surface contamination was calculated by contaminating textile fabrics under wind speed and PM concentration conditions similar to actual atmospheric environment. The number of pixels was obtained in the black and white binary images converted from the images of the textile fabrics captured under an ultraviolet (UV) light source. Experiments were performed using finished nylon fabric with PM-blocking performance and raw nylon fabric without PM-blocking performance. Comparison of the fabric surface contamination shows that it is possible to evaluate the PM-blocking performance of fabrics.

Grapevine, peach, and plum response to simulated florpyrauxifen-benzyl drift

Abstract Off-target movement of rice herbicides is a concern in California, where sensitive crops are often grown nearby. Florpyrauxifen-benzyl and triclopyr are auxin-mimics commonly used in rice systems. To steward florpyrauxifen-benzyl around the time of its initial registration in the state, research was conducted to compare the onset of foliar symptoms from simulated florpyrauxifen-benzyl and triclopyr drift onto grapevine, peach, and plum. The rates were 1/200X, 1/100X, 1/33X, and 1/10X of the 29.4 g ai ha–1 florpyrauxifen-benzyl and 1/200X, 1/100X, and 1/33X of the 420.3 g ae ha–1 triclopyr rice use rates. Herbicides were applied on one side of one- to two-year-old peach and plum trees and one side of established grapevines in 2020 and 2021. The general symptoms for florpyrauxifen-benzyl and triclopyr were similar and included chlorosis, leaf curling, leaf distortion, leaf malformation, leaf crinkling, necrosis, and twisting on leaves. The symptoms from herbicides were observed on both sides of the grapevine canopy, whereas florpyrauxifen-benzyl symptoms on peach and plum were mostly observed on the treated side of the tree. Florpyrauxifen-benzyl and triclopyr symptoms were observed three days-after-treatment (DAT) for grapevines and seven DAT for peach and plum. In all crops, most symptoms persisted through 42 DAT. Some grape clusters showed deformation and dropping of berries. All treated crops gradually recovered during the season regardless of application rates. Because symptoms were relatively minor in peach and plum, this research suggested that application precautions that reduce off-site drift are likely to minimize the occurrence of significant injury. However, grapevines were more sensitive and showed injury symptoms up to 71% at 14 DAT with a 1/10X florpyrauxifen-benzyl simulated drift rate. Therefore, extra precautions such as using drift-management agents and proper wind speed conditions at the time of florpyrauxifen-benzyl applications may be necessary if there are nearby vineyards.

CFD simulation and experimental investigation of a Magnus wind turbine with an improved blade shape

With the advancement of technology and growing concern for environmental issues, the demand for energy derived from renewable sources is expected to increase. It is well established that traditional bladed wind turbines exhibit inefficiency in low wind speed conditions. To address this, Magnus wind turbines, featuring cylindrical blades, have been developed specifically for regions with predominantly low-speed winds. However, these turbines present a significant drawback, as they require electric drives to rotate the blades. This study aims to conduct a three-dimensional numerical and experimental investigation of the aerodynamics around a wind turbine with a geometrically complex blade design. The scientific contribution of this work lies in the introduction of a deflector to the cylindrical blades, intended to eliminate the need for an electric drive to initiate blade rotation. A laboratory prototype of a wind turbine with the proposed blade configuration was constructed, and numerical simulations were performed using Ansys Fluent, based on the Reynolds-averaged Navier—Stokes (RANS) equations. The results demonstrate that the turbine's power coefficient (Cp) is approximately 20 % higher than that of traditional Magnus wind turbines. These findings underscore the enhanced efficiency provided by the addition of a deflector to the cylindrical blades.

Experimental performance investigation on a desiccant-assisted two-stage evaporative cooling system in hot and humid areas

The escalating demand for energy-efficient and eco-friendly air conditioning systems in buildings has spurred the development of comfortable, efficient, and cost-effective air handling system configurations. Desiccant cooling has shown a higher coefficient of performance (COP) compared to traditional vapor compression refrigeration (MVCR) systems. However, current desiccant cooling facilities struggle to decouple and efficiently handle indoor heat and moisture loads. The complexity of these facilities has kept intricate cooling systems remaining theoretical, requiring simplification and experimental investigation. This paper presents an experimental study on a compact, two-stage evaporative cooling system assisted by a liquid desiccant. A key innovation of this system is the inclusion of a two-stage heat exchanger that adeptly manages the decoupling of indoor heat and moisture loads under challenging high-temperature and high-humidity conditions. Performance analysis was conducted experimentally under three hot and humid climatic conditions using an optimized operating parameter scheme. Starting from an initial condition of 36.22 °C and a humidity ratio of 0.028 kg/kg, the proposed system achieves COP values ranging from 11.3 to 18.4 without compromising indoor comfort or facility compactness. Under high heat and high humidity conditions, the optimized system extracts 20 % of the product air as the secondary air source. It can reach a minimum supply air temperature of 18.44 °C, achieved under optimized conditions of low wind speed (1.0 m/s), high desiccant concentration (35 %), and substantial desiccant flow (0.09 kg/s). Experimental studies of this new system provide the possibility of achieving high efficiency in air handling over a wide range of temperatures and humidity.

ПОВТОРЯЕМОСТЬ АДВЕКТИВНО-РАДИАЦИОННЫХ ТУМАНОВ НАД АПШЕРОНСКИМ ПОЛУОСТРОВОМ (АЗЕРБАЙДЖАН)

The article examines the physical and meteorological characteristics of advective-radiation fogs formed on the Apsheron Peninsula and nearby islands, including the dependence of atmospheric elements that influence the formation of fogs on the meteorological visibility range, monthly and long-term fog trends. For this purpose, the initial data of aviation meteorological stations in the water area for 1999...2022 were used. The absence of a large morphometric unit on the Apsheron Peninsula and the archipelago, surroundings by the sea, and air masses affecting the area throughout the year determine its synoptic conditions. With the help of physical-meteorological and mathematical-statistical analyses, it has been established that the bulk of advective-radiation fogs formed in the Apsheron waters are repeated in march...april. With this type of fog, it has been established that the range of meteorological visibility varies depending on wind speed and sky conditions. During the period of advective-radiation fogs, south-eastern winds are most often observed in the water area. Analyzes show that an increase in average monthly and annual air temperatures on the peninsula has recently affected the frequency of advective-radiation fogs. Studying the spatiotemporal distributions of fogs can create conditions for the effective organization of aviation work.

Geometrically nonlinear wind-induced vibration piezoelectric energy harvester based on vortex-induced vibration

This paper proposes a geometrically nonlinear wind-induced vibration piezoelectric energy harvester (WIVPEH) with a maximum size of only 80 mm. Introducing nonlinearity solely through geometric structure design reduces the overall stiffness of the system, enabling the device to excite multi-mode coupling and induce internal resonance even under low wind speed conditions, thereby broadening the bandwidth. Wind tunnel experiments demonstrated that the device could vibrate at a wind speed of 1.5 m/s. Under low wind speed, the piezoelectric output is about 4 times greater than that of ordinary devices. Our research indicates that the designed device can maintain efficient wind energy collection within a low wind speed range.

The Problem of Power Variations in Wind Turbines Operating under Variable Wind Speeds over Time and the Need for Wind Energy Storage Systems

One of the most important and efficient sources of green electricity is catching air currents through wind turbine technology. Wind power plants are located in areas where the energy potential of the wind is high but it varies. The time variation of the wind generates fluctuations in the power produced by the wind farms that is injected into the grid. This elevates, depending on the intensity, problems of network stability and the need for balancing energy, thus raising both technical and cost issues. The present paper analyzes the behavior of a wind turbine (WT) over time in varying wind speed conditions, highlighting that without automation algorithms, a WT is far from the operation at the maximum power point (MPP). However, even when it is brought to operate at MPP, there are still significant variations in the power injected into the network. These power variations can be compensated if the wind system has energy storage facilities for the captured wind. All of these assumptions are analyzed using improved mathematical models and processed in simulations, with experimental data used as input from a wind turbine with an installed power of 2.5 [MW] in operation on the Romanian Black Sea coastal area. Consequently, the paper demonstrates that during an operation in the optimal area, from an energy perspective, the wind turbine’s maximum power point requires a storage system for the captured wind energy.

Wind speed effect on infrared-image-based coal and gangue recognition with liquid intervention in LTCC

The commitment to achieving carbon neutrality by 2060 makes the clean transition of fossil energy production inevitable in China. As the primary fossil energy source, China produced approximately 4.66 billion tons of raw coal in 2023. Among them, in the fields of mining engineering and environmental science, the accurate recognition of gangue (one of the environmental pollutants produced by coal combustion is black-gray solid waste) from coal is crucial because it is a key step in reducing resource waste and environmental pollution. Hence, coal and gangue automatic recognition with high accuracy is very important for intelligent longwall top coal caving (LTCC) mining. A novel approach of “liquid intervention + infrared detection” is introduced to enhance the recognition accuracy when the exterior color of coal and gangue is similar. This study focuses on the infrared image recognition of coal and gangue after liquid intervention under varying wind speed conditions, and optimizes the image processing path. The effect of varying wind speed conditions on the recognition accuracy of coal and gangue after liquid intervention was analyzed, and the optimal wind speed range was determined. The morphological evolution characteristics of droplets under varying wind field conditions were studied by COMSOL two-phase flow interface. The results show that with the increase of wind speed, the surface contour of coal is gradually clear, and the overall recognition accuracy is also improved. When the high wind speed is 1.55 m/s, the recognition accuracy reaches 99.89%, and the recognition accuracy of other wind speed regions is also above 90% (within 7s). In addition, the numerical simulation can maintain the volume fraction of the droplet in a short time under the constant flow wind flow field, thus inhibiting the phenomenon that the recognition accuracy decreases with time. The simulation results are in good agreement with the physical experimental phenomena, which proves the reliability of the numerical simulation. This study is of great significance to the recognition of coal gangue types with low identification characteristics in LTCC, so as to ensure the primary economic benefits, ecological environment safety and sustainable development of coal mines.

Study on the Design of Series-Type All-DC Wind Farms Based on Half-Bridge Voltage Balancing Circuits

Offshore wind farms connected in series, with each wind turbine connected in series with one another, enhance the coupling between them. Significant differences in wind speeds between neighboring DC wind turbines (DCWTs) might result in a substantial disparity in the output voltage, hence posing a risk of overvoltage. Nevertheless, implementing voltage-limiting configurations for DCWTs might lead to the dissipation of wind energy, thereby diminishing the wind farm’s capacity to deliver electricity. This work introduces a half-bridge voltage balancing circuit (HVBC) topology as a solution to the issue of DCWT output voltage changes affecting the stable operation of wind farms. The proposed HVBC topology is designed specifically for large-capacity series-connected all-DC wind farms where wind speed variations occur. This design achieves power decoupling for series-connected all-DC wind farms by providing current compensation to the series-connected DCWTs. A control strategy is devised by examining the decoupling principle and operational characteristics of the HVBC. A 60 kV/48 MW tandem-type all-DC wind farm model consisting of six DCWTs in series is built in Matlab/Simulink. The model is then simulated to evaluate its performance under conditions of unequal wind speed, rapid changes in wind speed, and wind turbine failure shutdown. This research verifies the feasibility of the HVBC topology and improves the stability of the series-type all-DC wind farm.

Experimental study on the burning rate and flame dynamics of oil reservoir pool fire under cross-wind: Effect of lip height

The study of combustion characteristics and heat feedback mechanisms of liquid fuels is important for fire safety engineering, particularly in the context of energy utilization. In thiswork, the effect of lip height on the evolution of n-heptane pool fire burning rates and flame heights, as well as the thermal feedback control mechanism, were investigated in a series of experiments in the presence of cross-wind. The results showed that the lip height of pool and cross-wind speed have a significant effect on the flame characteristics and heat feedback mechanism. For a given wind speed condition, the radiative feedback fraction and the convective feedback fraction showed non-monotonic changes with an increase in the lip height of pool. With the increase of lip height and cross-wind speed, the lift off phenomenon gradually appeared inside the oil pool, while the flame height outside the oil pool gradually decreased. A new correlation is proposed, which can well describle the relationship between the flame height and the ratio of the air entrainment caused by the cross airflow to that caused by the flame buoyancy, which can provide references for the utilization and management of energy storage strategies nowadays.

Parameter effects on performance of piezoelectric wind energy harvesters based on the interaction between vortex-induced vibration and galloping

Our previous research experimentally validated that the interaction between vortex-induced vibration and galloping is an effective method for enhancing the performance of piezoelectric wind energy harvesters under low wind speed conditions. We proposed a distributed-parameter electromechanical coupling model as well. This study aims to investigate the effects of various parameters and optimize the performance of VIV-galloping interactive piezoelectric wind energy harvesters. Initially, we assessed the applicability of the model under different circuit and aerodynamic force conditions and discussed boundary and convergence conditions by replicating previous results. Further, simulations were performed to analyze the effects of the structural parameters of the bluff body and piezoelectric beam. The width or depth of the bluff body significantly influenced the low critical wind speed, interactive occurrence, and electrical output. To achieve a balance between material cost and electrical benefit, we recommend positioning the electrode length from the fixed end with a coverage ratio of at least 60%. Additionally, the output power is highly sensitive to the piezoelectric beam length, but reducing it results in a higher natural frequency and critical wind speed. We fabricated and tested four prototypes, which have demonstrated significantly higher power densities compared with previously reported values at the same wind speed.