Harvesting Model Research Articles

AoI Optimization in Multi-Source Update Network Systems Under Stochastic Energy Harvesting Model

AoI Optimization in Multi-Source Update Network Systems Under Stochastic Energy Harvesting Model

Innovative Design and Optimization of High-Quality Peanut Digging-Inverter

To rapidly dry peanut pods and effectively address mold issues resulting from rainy weather, this article provides an analysis of the current research status of global peanut digging, inverting, and harvesting technologies. Based on a two-stage peanut harvesting model, the operating principles of a high-quality peanut digging-inverter are elaborated upon, and the design of key machine components is discussed. The evaluation metrics for the operation of a high-quality peanut digging-inverter include the rate of vine inverting, the soil content rate, the rate of fallen pods, and the rate of buried pods. Utilizing theoretical analysis, the Box–Behnken experimental design is employed to investigate the operating parameters of these machines, with the tractor’s running speed, the linear speed of the inverting roller, and the linear speed of the conveyor chain serving as the experimental factors in a three-factor, three-level experimental study. A regression model is established to analyze the impact of each factor on operational quality and to comprehensively optimize the influencing factors. The experimental results indicate that all factors significantly affect the rate of vine inverting. The tractor’s running speed (X1) and the linear speed of the inverting roller (X3) significantly influence the rate of buried pods, while the linear speed of the conveyor chain (X2) does not have a significant effect on this rate. Similarly, the tractor’s running speed (X1) and the linear speed of the inverting roller (X3) significantly affect the rate of fallen pods, whereas the linear speed of the conveyor chain (X2) does not. Furthermore, the linear speed of the conveyor chain (X2) and the linear speed of the inverting roller (X3) significantly impact the soil content rate, while the tractor’s running speed (X1) does not. The optimal combination of operating parameters is a tractor running speed of 1 m/s, a conveyor chain linear speed of 1.3 m/s, and an inverting roller linear speed of 2.1 m/s. Under these conditions, the high-quality peanut digging-inverter achieves a vine inverting rate of 89.29%, a buried pod rate of 0.31%, a fallen pod rate of 0.74%, and a soil content rate of 8.11%. The experimental values for each evaluation index exhibit relative errors of 1.14%, 6.45%, 1.35%, and 0.13% compared to the optimized values provided by the Design-Expert software. The findings of this research will facilitate the development of hardware conditions for the future intelligent and information-based harvesting of peanuts, thereby establishing a solid foundation for the high-quality initial processing of oilseeds.

Semantic Segmentation Model-Based Boundary Line Recognition Method for Wheat Harvesting

The wheat harvesting boundary line is vital reference information for the path tracking of an autonomously driving combine harvester. However, unfavorable factors, such as a complex light environment, tree shade, weeds, and wheat stubble color interference in the field, make it challenging to identify the wheat harvest boundary line accurately and quickly. Therefore, this paper proposes a harvest boundary line recognition model for wheat harvesting based on the MV3_DeepLabV3+ network framework, which can quickly and accurately complete the identification in complex environments. The model uses the lightweight MobileNetV3_Large as the backbone network and the LeakyReLU activation function to avoid the neural death problem. Depth-separable convolution is introduced into Atrous Spatial Pyramid Pooling (ASPP) to reduce the complexity of network parameters. The cubic B-spline curve-fitting method extracts the wheat harvesting boundary line. A prototype harvester for wheat harvesting boundary recognition was built, and field tests were conducted. The test results show that the wheat harvest boundary line recognition model proposed in this paper achieves a segmentation accuracy of 98.04% for unharvested wheat regions in complex environments, with an IoU of 95.02%. When the combine harvester travels at 0~1.5 m/s, the normal speed for operation, the average processing time and pixel error for a single image are 0.15 s and 7.3 pixels, respectively. This method could achieve high recognition accuracy and fast recognition speed. This paper provides a practical reference for the autonomous harvesting operation of a combine harvester.

Scotch yoke structure inspired piezoelectric-electromagnetic hybrid harvester for wave energy harvesting

This paper presents a piezoelectric-electromagnetic hybrid harvester for wave energy harvesting inspired by a scotch yoke structure for obtaining energy from irregular and low-frequency waves. Through simplification of the energy harvester model, the kinematic equations of the scotch yoke are established. One of the advantages of the harvester is that the wave energy can be harvested by an up-conversion mechanism, The piezoelectric transducer (PZT) and electromagnetic generator (EMG) transform the wave excitation into electricity, and by utilizing the frequency up-conversion mechanism, the PZTs’ harvesting efficiency is increased, the influencing factors of the output power of the harvester are explored by simulation and experimental studies, The results of the experiment demonstrate that this harvester could generate an ultimate output power of 286.36 mW at ultra-low frequency (1.4 Hz) operating frequency. This study offers a practical solution for harvesting low-frequency and disordered wave energy and makes significant progress in harvesting low-frequency and irregular wave energy.

Particle motion and flow contribution in a double-row hydraulic harvesting model for deep-sea mining

The double-row hydraulic sluicing model is widely used in deep-sea mining collecting systems. However, there has been limited research focusing on its flow contributions and the relationship with particle motions. In this paper, a double-row hydraulic sluicing collector with high pickup efficiency is designed. The flow characteristics, the mechanics of the flow field, and the movement of particles in the collector are analyzed in detail through numerical calculations and experiments. The flow contributions and the collecting mechanism are clearly highlighted through aspects such as the frequency of pressure fluctuations and flow-induced vortices. The high-speed jet rolls upward after hitting the ground, forming a high-pressure area on the ground. The upwelling in the collection area is generated by the combination of the high-pressure area and the upward rolling of fluid. Regarding the particles, it is observed that particle motion can be divided into two main stages, rapid acceleration, followed by slow deceleration. Some particles may fall back when rising. Additionally, the analysis of fluid forces on the particles indicates that drag force and pressure gradient force have significant influence on particle motion.

Broadband and high-efficiency acoustic energy harvesting with loudspeaker enhanced by sonic black hole

It is well-known that acoustic energy sources can be seen as a promising alternative energy resource by using acoustic energy harvester (AEH) which can transform sound energy into usable electrical power. However, the current AEHs have been restricted by their narrow bandwidths and low energy conversion efficiencies. In this study, a broadband and high efficient AEH is presented. The proposed AEH comprises an open-end sonic black hole (SBH) structure and an electrodynamic loudspeaker. The sound pressure is amplified through the open-end SBH structure, then the loudspeaker is used as electricity generator to convert acoustic energy into electric energy. The open-end SBH is a cylindrical tube with an array of regularly-spaced rigid-walled thin rings. The inner radii of the SBH rings are quadratically decreasing and the SBH effect can be obtained. The model for energy harvesting and sound absorption performance of the proposed AEH is then presented. Finally, the open-end SBH is fabricated by 3D printing apparatus. A prototype of the AEH is designed and tested by using an impedance tube. The energy conversion efficiency and absorption coefficient from calculation and experiment show a reasonable agreement. The proposed AEH can convert 11 % of total incident sound energy from 50 Hz to 800 Hz. The maximum energy conversion efficiency can achieve 65 % at 425 Hz under optimal resistance load. Furthermore, the broadband sound absorption can also be achieved by using the proposed AEH.

Performance analysis of shared relay CR-NOMA network based on SWIPT

With the development of wireless communication technology, the number of devices accessing the communication network is increasing. This paper addresses critical issues such as low spectrum resource utilization and the energy constraints of devices. The investigation focuses on the system performance of the shared relay Cognitive Radio Non-Orthogonal Multiple Access (CR-NOMA) network based on Simultaneous Wireless Information and Power Transfer (SWIPT) network model. Unlike the existing CR-NOMA model in which the secondary network user do not participate in the transmission of information from the primary network, we consider the secondary network near user as shared relay. The shared relay utilizes SWIPT technology to harvest energy using a nonlinear energy harvesting model. Additionally, the shared relay assists in transmitting information from the primary network base station to primary user, as well as from the secondary network base station to far user of the secondary network. Subsequently, we conduct a series of simulations to analyze the effects of Signal-to-Noise Ratio (SNR), power distribution factor, interference threshold, and time-switching (TS) factor on system performance. Furthermore, we compare and analyze the performance of our proposed network model against CR-NOMA network across three dimensions: outage probability, throughput, and energy efficiency. Our results demonstrate that the proposed network model exhibits superior outage performance and enhances user throughput compared to the CR-NOMA network. Additionally, it demonstrates improved energy efficiency compared to the shared relay CR-NOMA network, leading to an overall improvement in network performance.

A Novel Medium Access Policy Based on Reinforcement Learning in Energy-Harvesting Underwater Sensor Networks.

Underwater acoustic sensor networks (UASNs) are fundamental assets to enable discovery and utilization of sub-sea environments and have attracted both academia and industry to execute long-term underwater missions. Given the heightened significance of battery dependency in underwater wireless sensor networks, our objective is to maximize the amount of harvested energy underwater by adopting the TDMA time slot scheduling approach to prolong the operational lifetime of the sensors. In this study, we considered the spatial uncertainty of underwater ambient resources to improve the utilization of available energy and examine a stochastic model for piezoelectric energy harvesting. Considering a realistic channel and environment condition, a novel multi-agent reinforcement learning algorithm is proposed. Nodes observe and learn from their choice of transmission slots based on the available energy in the underwater medium and autonomously adapt their communication slots to their energy harvesting conditions instead of relying on the cluster head. In the numerical results, we present the impact of piezoelectric energy harvesting and harvesting awareness on three lifetime metrics. We observe that energy harvesting contributes to 4% improvement in first node dead (FND), 14% improvement in half node dead (HND), and 22% improvement in last node dead (LND). Additionally, the harvesting-aware TDMA-RL method further increases HND by 17% and LND by 38%. Our results show that the proposed method improves in-cluster communication time interval utilization and outperforms traditional time slot allocation methods in terms of throughput and energy harvesting efficiency.

Multi-Variable Optimization to Enhance the Performance of a Cantilevered Piezoelectric Harvester

Over the past decade, various researchers have shown the practicality of extracting electrical energy from vibrating structures. The primary objective of this research was to optimize the parameters of a basic cantilever harvester to maximize the energy production of electricity from surrounding mechanical energy. A distributed parameter model and its modal solution were utilized to determine the design variables via a parametric investigation. It is important to ensure sufficient power generation when there is a wide range of frequencies being excited, without any specific frequency being emphasized. The cost function for the optimization problem was defined as the average power within a specific frequency range, considering geometric and physical restrictions. It was discovered that different parameters’ values can be utilized to generate varying maximum power levels for different frequency ranges. Furthermore, a comparative analysis was performed between the finite element method (FEM) using ANSYS and the current harvesting model. The comparison demonstrated a high level of concordance, enabling the utilization of the finite element method (FEM) for subsequent investigation.

Multi-scale modeling of fog harvesting using thin-fiber grids – Towards new design rubrics

Fog collectors with fibers thinner than 1 mm harvest fog droplets more effectively at a low airflow velocity around 1 m s-1 than thicker fibers. However, existing models and design rubrics are restricted to thick fibers at higher velocity. This paper reports a multi-scale numerical model for fog harvesting at airflow velocity of 1 m s-1 using thin-fiber grids with different fiber spacing and diameter. The numerical model can simulate fog harvesting at two extreme length scales that are comparable to collector scale at the large end and fiber scale at the small end. The results confirm two new and important effects of fiber grid geometries on water collection efficiency, which are not included in existing theories and design rubrics. First, dense thin-fiber grids negatively influence the collection efficiency because of wall effect caused by viscous boundary layers. Second, the sparse thin-fiber grids can benefit from isolated clogging waterdrops and maintain relatively high efficiency when clogging blocks multiple grid openings. The two identified effects are then included to develop a new performance map for fog collectors, thereby shaping new design rubrics for fog harvesting. This work extends the existing theories of fog harvesting and sheds light on the design of novel fog collectors.

Energy-efficient maximization algorithm for energy harvesting under imperfect channel information

In this paper, we propose a novel energy-efficient resource optimization scheme in non-orthogonal multiple access (NOMA) networks with simultaneous wireless information and power transfer (SWIPT). In this system, we consider practical imperfect channel information that accounts for random channel delays and channel estimation errors. Additionally, the small cell users (SCUs) in a heterogeneous network (HetNet) can harvest energy from the small base station (SBS) signal by energy harvesting. Based on the non-linear energy harvesting (NEH) model, the problem of maximizing energy efficiency with imperfect channel state information (CSI) is formulated. Since the formulated problem is a probabilistic mixed non-convex optimization problem, a two-stage algorithm is developed to jointly optimize sub-channel matching and power allocation. In particular, the problem is first transformed into a non-probabilistic problem through the relaxation method. For the sub-channels matching problem, a low-complexity many-to-many matching algorithm is designed to achieve dynamic matching based on the preference lists. For the power allocation problem, the closed-form transmission power of SCUs can be derived by the Dinkelbach method and Lagrangian dual approach. Simulation results show that the proposed scheme can achieve higher energy efficiency than existing linear energy harvesting (LEH)-NOMA and NEH-OFDMA schemes, with improvements of 37.99% and 84.69%, respectively.

Human conflict, food security and impacts on wildlife: Importance of sustainable harvest models to inform policy

AbstractResearch Highlight discussing: Carenton, N., Defos du Rau, P., Wachoum, A. S., Ducros, D., Suet, M., Deschamps, C., Betoloum, M. R., Birard, J., Djimasngar, M. B. N., Kayser, Y., Petersen, I. K., Dias, J., Wachoum, M. A., Portier, B., Koumbraït, A. M., Le Bel, S., & Mondain‐Monval, J.‐Y. (2024). Migration of humans fleeing conflict in the Lake Chad region may increase pressures on natural resources in Lake Fitri (Chad): A case study on waterbirds, Journal of Applied Ecology, 1–13, https://doi.org/10.1111/1365‐2664.14700. Human conflict and food security have emerged as critical issues for humanity with potentially profound implications for biodiversity conservation. These interconnected challenges not only threaten human well‐being and socio‐economic stability but also have significant impacts on biodiversity, including biodiversity of conservation concern. The importance of wildlife for bushfood, particularly in regions affected by conflict, adds another layer of complexity. In such areas, reliance on wildlife for sustenance often increases, leading to overexploitation. Bushmeat serves as a crucial source of protein and livelihoods in many parts of the world particularly Africa, highlighting its significant role in local economies and food security. This dynamic not only threatens biodiversity but also exacerbates the challenges of food security and human conflict. Understanding the interplay between human conflict, food security and biodiversity conservation is essential for developing sustainable solutions that address these complex issues holistically. Modelling of wildlife exploitation has historically focussed on spatially explicit pressure maps showing how vulnerable species are to exploitation. New modelling is emerging to help better understand the specific impacts on species populations so that policymakers can help create better informed policies and strategies that balance human needs with conservation efforts.

Performance Correction and Parameters Identification Considering Non-Uniform Electric Field in Cantilevered Piezoelectric Energy Harvesters.

In the current electromechanical model of cantilevered piezoelectric energy harvesters, the assumption of uniform electric field strength within the piezoelectric layer is commonly made. This uniform electric field assumption seems reasonable since the piezoelectric layer looks like a parallel-plate capacitor. However, for a piezoelectric bender, the strain distribution along the thickness direction is not uniform, which means the internal electric field generated by the spontaneous polarization cannot be uniform. In the present study, a non-uniform electric field in the piezoelectric layer is resolved using electrostatic equilibrium equations. Based on these, the traditional distributed parameter electromechanical model is corrected and simplified to a practical single mode one. Compared with a traditional model adopting a uniform electric field, the bending stiffness term involved in the electromechanical governing equations is explicitly corrected. Through comparisons of predicted power output with two-dimensional finite element analysis, the results show that the present model can better predict the power output performance compared with the traditional model. It is found that the relative corrections to traditional model have nothing to do with the absolute dimensions of the harvesters, but only relate to three dimensionless parameters, i.e., the ratio of the elastic layer's to the piezoelectric layer's thickness; the ratio of the elastic modulus of the elastic layer to the piezoelectric layer; and the piezoelectric materials' electromechanical coupling coefficient squared, k312. It is also found that the upper-limit relative corrections are only related to k312, i.e., the higher k312 is, the larger the upper-limit relative corrections will be. For a PZT-5 unimorph harvester, the relative corrections of bending stiffness and corresponding resonant frequency are up to 17.8% and 8.5%, respectively. An inverse problem to identify the material parameters based on experimentally obtained power output performance is also investigated. The results show that the accuracy of material parameters identification is improved when considering a non-uniform electric field.

Effect of scandium concentration on the performances of cantilever based AlN unimorph piezoelectric energy harvester with silicon nitride substrate

Microelectromechanical systems (MEMS) offer its ability to sense, control and actuate on sub-micron scale and exhibit its effect on macro scale. To implement any specific MEMS system, small, efficient and long-lifespan micro power sources are required. Piezoelectric energy harvester (PEH) along with radioactive source is one of the most promising approaches to harness electrical energy at micro to millimeter range. In this report, a scandium (Sc) doped Aluminium Nitride (AlN) unimorph piezoelectric energy harvester has been demonstrated. Unimorph piezoelectric layer is built on Silicon Nitride (Si3N4) substrate platform that act as cantilever beam and that can be vibrated by inbuilt radioactive system. In particular, Si3N4 as cantilever material and the impact of Sc doping concentration on electrical and mechanical properties of AlN piezoelectric thin film materials have been studied in MATLAB simulation platform. Results obtained from numerical study suggests that the proposed energy harvester model composed of AlScN unimorph piezoelectric (with 10% Sc doping concentration, Sc-10%) layer and Si3N4 cantilever can yield a maximum power output of ~ 19.33 μW and overall mechanical energy conversion efficiency of ~ 91.07%. These are the maximum output power and mechanical energy conversion efficiency numerically obtained from Sc doped AlN piezoelectric energy harvester systems to the best of our knowledge.

On the role of sliding friction effect in nonlinear tri-hybrid vibration-based energy harvesting

This work aims to develop an experimental investigation into the effectiveness of the sliding-mode approach for hybrid vibration-based energy harvesting. A proposed sliding-mode triboelectric-electromagnetic-piezoelectric energy harvesting model involves a cantilever beam with a tip mass exposed to magnetic and frictional forces. The experimental findings indicate that the system can achieve its peak inter-well oscillation output within a low-frequency range of 4Hz–6Hz. Friction has a lesser impact on the open-circuit voltage output at an excitation acceleration of 1.5g compared with 1g. The distribution of tri-stability changes with the presence of friction. This model provides a deeper understanding of the influence of the dry friction coefficient (0.2–0.5) on the interactive behaviors of different generator units.

A semi-analytical electromechanical model for energy harvesting of plate with acoustic black hole indentations

Acoustic black hole (ABH) has been proved to be helpful for the energy harvesting of beam. Since thin plates are more widely used in practical engineering, it is of great significance to explore the energy harvesting with ABH effect applying to thin plate. Therefore, a piezoelectric plate with ABH indentations is designed and a standard full-wave rectifier circuit connected to the energy harvester in this paper. A semi-analytical electromechanical model is proposed for the energy harvesting system and Gaussian basis functions are used to solve the coupled electromechanical equations. The harvested power is calculated with the proposed method and the acceptable accuracy could be found through the validation against finite element simulation. Finally, a comprehensive analysis has been performed and numerical results show the system parameters (such as piezoelectric layer parameters, ABH parameters, and circuit parameters) have a significant influence on the energy harvesting.

Hybrid Time Series Model for Advanced Predictive Analysis in COVID-19 Vaccination

This study aims to enhance the prediction of COVID-19 vaccination trends using a novel integrated forecasting model, facilitating better public health decision-making and resource allocation during the pandemic. As the COVID-19 pandemic continues to impact global health, accurately forecasting vaccination trends is critical for effective public health response and strategy development. Traditional forecasting models often fail to capture the complex dynamics of pandemic-driven vaccination rates. The analysis utilizes a comprehensive dataset comprising over 68,487 entries, detailing daily vaccination statistics across various demographics and geographic locations. This dataset provides a robust foundation for modeling and forecasting efforts. It utilizes advanced time series analysis techniques and machine learning algorithms to accurately predict future vaccination patterns based on the Hybrid Harvest model, which combines the strengths of ARIMA and Prophet models. Hybrid Harvest exhibits superior performance, with mean-square errors (MSEs) of 0.1323, and root-mean-square errors (RMSEs) of 0.0305. Based on these results, the model is significantly more accurate than traditional forecasting methods when predicting vaccination trends. It offers significant advances in forecasting COVID-19 vaccination trends through integration of ARIMA and Prophet models. The model serves as a powerful tool for policymakers to plan vaccination campaigns efficiently and effectively.

Nonlinear energy harvesting system with multiple stability

The nonlinear energy harvesting systems of the forced vibration with an electron-mechanical coupling are widely used to capture ambient vibration energy and convert mechanical energy into electrical energy. However, the nonlinear response mechanism of the friction induced vibration (FIV) energy harvesting system with multiple stability and stick-slip motion is still unclear. In the current paper, a novel nonlinear energy harvesting model with multiple stability of single-, double- and triple-well potential is proposed based on V-shaped structure spring and the belt conveying system. The dynamic equations for the energy harvesting system with multiple stability and self-excited friction are established by using Euler-Lagrangian equations. Secondly, the static characteristics of the nonlinear restoring force, the friction force, and the potential energy surfaces are obtained to show the nonlinear stiffness, multiple equilibrium points, discontinuous behaviors and multiple well responses. Then, the equilibrium surface of bifurcation sets for the autonomous system is given to show the third-order quasi zero stiffness (QZS3), fifth-order quasi zero stiffness (QZS5), double well (DW) and triple well (TW). The co-dimension bifurcation sets of the self-excited vibration system are analyzed and the corresponding phase portraits for the coexistent of multiple limit cycles are obtained. Furthermore, the analytical formula of amplitude frequency response of the approximated system are obtained by the complex harmonic method. The response amplitudes of charge, current, voltage and power of the forced electron-mechanical coupled vibration system for QZS3, QZS5, DW and TW are analyzed by using the numerically solution. Finally, a prototype of FIV energy harvesting system is manufactured and the experimental system is setup. The experimental works of static restoring forces, damping forcse and the electrical outputs are well agreeable with the numerical results, which testified the proposed FIV energy harvesting model.

A hybrid energy harvesting approach for transmission lines based on triboelectric nanogenerator and micro thermoelectric generator

To effectively detect faults in transmission lines, monitoring the operating status of these lines is imperative. However, providing power to monitoring devices for transmission line status presents a significant challenge. In this research, a hybrid energy harvesting approach based on micro thermoelectric generator (MTEG) and triboelectric nanogenerator (TENG) is proposed, and a theoretical model for MTEG-TENG hybrid energy harvesting is established. This study develops an integrated energy harvesting prototype, which incorporates oscillating-TENG (O-TENGs), MTEGs, and a power management control unit. This prototype not only harvests energy from the vibrations of transmission lines but also converts the lines thermal energy into electricity. The Experiment results show that the maximum open-circuit voltages of O-TENG and MTEG reach 80.3 V and 1.094 V, respectively. Compared to a single MTEG energy harvesting device, the prototype of the MTEG-TENG hybrid energy harvesting device demonstrates a 5.36% improvement in energy harvesting and battery charging performance. Consequently, this approach achieves self-powered monitoring with excellent stability and lower manufacturing costs. It provides an efficient and durable power approach for transmission line status monitoring devices.

Advances in Organic Multiferroic Junctions

Typically, organic multiferroic junctions (OMFJs) are formed of an organic ferroelectric layer sandwiched between two ferromagnetic electrodes. The main scientific interest in OMFJs focuses on the magnetoresistive properties of the magnetic spin valve combined with the electroresistive properties associated with the ferroelectric junction. In consequence, memristive properties that couple magnetoelectric functionalities, which are one of the most active fields of research in material sciences, are opening a large spectrum of technological applications from nonvolatile memory to elements in logic circuits, sensing devices, energy harvesting and biological synapsis models in the emerging area of neuromorphic computing. The realization of these multifunctional electronic elements using organic materials is presenting various advantages related to their low-cost, versatile synthesis and low power consumption functioning for sustainable electronics; green disintegration for transient electronics; and flexibility, light weight and/or biocompatibility for flexible electronics. The purpose of this review is to address the advancement of all OMFJs including not only the achievements in the charge and spin transport through OMFJs together with the effects of electroresistance and magnetoresistance but also the challenges and ways to overcome them for the most used materials for OMFJs.