Search Results (402)

The stem taper function is essential in predicting diameter outside bark (DOB) variations along the tree height, contributing to volume estimation, harvest planning, and precision forestry. Traditional taper models, such as the Kozak function, offer interpretability but often fail to capture nonlinear growth dynamics and regional variability, particularly in the upper stem segments. This study aimed to evaluate and compare the prediction accuracy of conventional and machine learning-based taper models using Pinus densiflora, a representative conifer species in Korea. Field data from two ecologically distinct regions (Gangwon and Central Korea) were used to build and test four models: the Kozak taper function, random forest, extreme gradient boosting, and an artificial neural network (ANN). Model performance was assessed using the RMSE, R², and MAE, along with stem profile visualizations for representative trees. The results showed that the ANN consistently achieved the highest prediction accuracy across both regions, particularly at an upper crown zone relative height (RH) > 0.8, while maintaining smooth and stable taper curves. In contrast, the Kozak model tended to underestimate the diameter of the upper stem. This study demonstrates that machine learning models, particularly ANNs, can effectively enhance the taper prediction precision and serve as practical tools for data-driven forest management and the implementation of precision forestry in Korea. Full article

The aim of this study was to characterize the vegetative growth development of hop plants grown in the subtropics under a two-crop-a-year system with artificial supplementation lighting. The development of ‘Mapuche’ and ‘Spalter’ hops was compared during the summer 2022–2023, fall 2023, summer 2023–2024 and fall 2024 harvest seasons, considering the effects of the air temperature on the vegetative growth of plants from thermal sums in a subtropical climate region. The experiment was conducted in Palotina, Paraná, Brazil (24°17′40.05″ S, 55°50′23.16″ W, at 332 m elevation). The hops were trained on a 5.5 m high vertical trellis, using a ‘V’-shaped training system. Vegetative growth was evaluated based on the plant height development (m), hop growth rate (HGR), and classification of four growth stages based on the HGR. The phenology of the hop cultivars was determined visually according to the duration in days of the phenological stages. The development of the plant height and HGR was analyzed by nonlinear regressions of the Gompertz model and Gaussian function, respectively. ‘Mapuche’ and ‘Spalter’ hops had complete vegetative growth and phenological phases in the summer and fall seasons, with greater precocity in plant development in the summer season. The growth model based on the air temperature demonstrated that under subtropical conditions, the growth was maximized in seasons with higher temperatures. The duration of the phenological phases and the complete cycle of the plants was influenced by the vegetative growth of each cultivar in each harvest season. Therefore, double annual crop production of the hop cultivars ‘Mapuche’ and ‘Spalter’ is possible in a subtropical climate with artificial light supplementation. Full article

Integrated sensing and communication (ISAC) can improve the energy harvesting (EH) efficiency of simultaneous wireless information and power transfer (SWIPT)-assisted IoT networks by enabling precise energy harvest. However, the transmit power is increased in the hybrid system due to the fact that the sensing signals are required to be transferred in addition to the communication data. This paper aims to tackle this issue by formulating an optimization problem to minimize the transmit power of the base station (BS) under a nonlinear EH model, considering the coexistence of power-splitting users (PSUs) and time-switching users (TSUs), as well as the beamforming vector associated with PSUs and TSUs. A two-layer algorithm based on semi-definite relaxation is proposed to tackle the complexity issue of the non-convex optimization problem. The global optimality is theoretically analyzed, and the impact of each parameter on system performance is also discussed. Numerical results indicate that TSUs are more prone to saturation compared to PSUs under identical EH requirements. The minimal required transmit power under the nonlinear EH model is much lower than that under the linear EH model. Moreover, it is observed that the number of TSUs is the primary limiting factor for the minimization of transmit power, which can be effectively mitigated by the proposed algorithm. Full article

This paper aims to study a two-degree-of-freedom (2DOF) magnetic spring-based electromagnetic generator system theoretically and experimentally. The proposed linear generator system contains a nonlinear nonmagnetic shaft (nonmagnetic materials), two floating magnets, and two fixed magnets. All magnets are placed in the system in a repulsive configuration. First, the magnetic properties of the proposed system are studied to provide insight into its role in the system’s nonlinear oscillatory behavior. The magnetic restoring forces are analyzed, and both linear and nonlinear coefficients of the oscillator system are analyzed based on these forces. The mathematical model of the proposed system is presented to study the dynamic behaviors of the oscillator system. The magnetic restoring forces and dynamic behaviors for different oscillator heights are also studied. Finally, the proposed system’s energy generation capacity is examined using electromechanical coupling. Full article

Energy harvesting from ambient vibrations has received significant attention as an alternative renewable, clean energy source for microelectronic devices in diverse applications such as wearables and environmental monitoring. However, typical vibrations in remote environments exhibit ultra-low frequencies with variations and uncertainty leading to operation away from resonance and severe underperformance in terms of power output. Pendulum-based energy harvesters offer a promising solution to these issues, particularly when designed for parametric resonant response to driven displacement of the pendulum pivot. Parametric excitation has been shown to trigger fast rotational motion of the pendulum VEH that is beneficial for energy generation and the necessary space utilization. Nevertheless, low-frequency ambient vibrations typically come at very weak amplitudes, a fact that establishes significant design barriers when traditional gravitational pendula are used for rotary energy harvesting. In this paper, we propose a novel concept that utilizes permanent magnet arrays to establish pendulum dynamics. Extensive investigation of the restoring torque of the proposed magnetic pendulum concept is conducted with analytical tools and FEA verification. The resulting oscillator exhibits frequency tuning that is decoupled from gravity and adjustable via the circularly arranged magnetic fields, leading to increased flexibility in the concurrently necessary amplitude tuning. Numerical integration of the nondimensional equation of motion is performed in the system’s parameter space to identify the impact on the regions triggering rotational response to parametric excitation. Finally, a theoretical case study is numerically investigated with the device space constrained within 20 cm³, showing a multi-fold improvement in the achieved power density of over 600 μW/cm³/g²/Hz over a broad range of frequencies and driving amplitudes as low as 1.1 Hz at 0.2 g. Full article

Energy-harvesting devices utilizing the Vortex-Induced Vibration (VIV) phenomenon are gaining significant research attention due to their potential to generate energy from small water flows, where conventional hydroelectric plants are impractical. Developing effective design methods for these systems is therefore essential. This study focuses on a critical configuration of such devices where energy extraction is achieved by harnessing the oscillatory deformation of two clamped–clamped plates, positioned downstream of the bluff body and subject to the effect of the vortex street. To simplify the preliminary design process, a semi-analytical approach, based on energetic considerations, is proposed to model the non-linear oscillations of the plates, eliminating the need for numerical simulations. The accuracy of this method is assessed through comparative analyses with finite element method (FEM) analyses, under both static and dynamic deformation conditions. The results validate the effectiveness of the proposed approach, offering insights into the effect of the adopted simplifications. In this framework, potential improvements to enhance the method’s reliability are identified. Thus, the work provides a practical model to address the preliminary design of these devices and suggests pathways for its further enhancement. Full article

This paper presents an investigation into the influence of varying potential well depths on the performance of a dual−coupled beam energy harvester (DEH). Firstly, three varying potential well depths were established with different polynomial coefficients of nonlinear restoring force and analyzed in simulation. Numerical results revealed that whether the initial potential well depth is shallow or not, the optimal power output can be attained when the stiffness of the coupling spring is a half of the monostable−to−bistable coupling spring stiffness, which was also validated by an experiment. Specifically, at a deeper initial potential well depth of 0.64 mJ, the system demonstrated superior energy conversion capabilities. Compared to traditional BEH and LEH, the output RMS voltage of Beam 1 and total RMS power of the DEH increased by 103.06% and 49.6%, respectively. The RMS power increased by 16.4% at a potential well depth of 0.9 mJ. In addition, regardless of the potential well depth, the DEH can always achieve the optimal operating bandwidth when the coupling spring stiffness is near the monostable−to−bistable transition region. Full article

Soil–water management is fundamental to plant ecophysiology, directly affecting plant resilience under both anthropogenic and natural stresses. Understanding Agricultural Soil–Water Management Properties (ASWMPs) is therefore essential for optimizing water availability, enhancing harvest resilience, and enabling informed decision-making in intelligent irrigation systems, particularly in the face of climate variability and soil degradation. In this regard, the present research develops predictive models for ASWMPs based on the grain size distribution and dry bulk density of soils, integrating both traditional mathematical approaches and advanced computational techniques. By examining 900 soil samples from the NaneSoil database, spanning diverse crop species (Avena sativa L., Daucus carota L., Hordeum vulgare L., Medicago sativa L., Phaseolus vulgaris L., Sorghum vulgare Pers., Triticum aestivum L., and Zea mays L.), several predictive models are proposed for three key ASWMPs: soil-saturated hydraulic conductivity, field capacity, and permanent wilting point. Mathematical models demonstrate high accuracy (71.7–96.4%) and serve as practical agronomic tools but are limited in capturing complex soil–plant-water interactions. Meanwhile, a Deep Neural Network (DNN)-based model significantly enhances predictive performance (91.4–99.7% accuracy) by uncovering nonlinear relationships that govern soil moisture retention and plant water availability. These findings contribute to precision agriculture by providing robust tools for soil–water management, ultimately supporting plant resilience against environmental challenges such as drought, salinization, and soil compaction. Full article

The authors present an in-depth theoretical study of two nonlinear circuits capable of transient thermal energy harvesting at one temperature. The first circuit has a storage capacitor and diode connected in series. The second circuit has three storage capacitors, and two diodes arranged for full wave rectification. The authors solve both Ito–Langevin and Fokker–Planck equations for both circuits using a large parameter space including capacitance values and diode quality. Surprisingly, using diodes one can harvest thermal energy at a single temperature by charging capacitors. However, this is a transient phenomenon. In equilibrium, the capacitor charge is zero, and this solution alone satisfies the second law of thermodynamics. The authors found that higher quality diodes provide more stored charge and longer lifetimes. Harvesting thermal energy from the ambient environment using diode nonlinearity requires capacitors to be charged but then disconnected from the circuit before they have time to discharge. Full article

To explore the nonlinear dynamics of a piezoelectric energy harvesting device, we consider the simultaneous parametric and external excitations. Based on Bernoulli–Euler beam theory, a new dynamic model is proposed taking into account the curvature of the beam, geometric and electro-mechanical coupling nonlinearities, and damping nonlinearity, with inextensible deformation. The system is discretized by using the Galerkin–Bubnov procedure and then is investigated by the optimal auxiliary functions method. Explicit analytical expressions of the approximate solutions are presented for a complex problem near the primary resonance. The main novelty of our approach relies on the presence of different auxiliary functions, the involvement of a few convergence-control parameters, the construction of the initial and first iteration, and much freedom in selecting the procedure for obtaining the optimal values of the convergence-control parameters. Our procedure proves to be very efficient, simple, easy to implement, and very accurate to solve a complicated nonlinear dynamical system. To study the stability of equilibrium points, the Routh–Hurwitz criterion is adopted. The Hopf and saddle node bifurcations are studied. Global stability is analyzed by the Lyapunov function, La Salle’s invariance principle, and Pontryagin’s principle with respect to the control variables. Full article

The digging mechanism is the component of garlic harvesters that consumes the most energy. Consequently, there are theoretical gaps in the design of resistance reduction. These gaps are due to the complexity of the interaction dynamics between the shovel and the soil, and the insufficient understanding of the evolution patterns of soil damage. To address these challenges, this study develops a finite element model of the shovel–soil system using damage mechanics to characterize nonlinear interaction mechanisms under operational loading conditions. The methodology integrates three critical phases: (1) soil damage evolution analysis was employed to identify key damage parameters for model calibration; (2) systematic finite element simulations were used to evaluate the effects of system variables—entry angle, shovel blade bevel angle, forward speed, and vibration frequency—on forward resistance; (3) orthogonal experimental optimization of these parameters was carried out. Key results include the following: (i) A nonlinear relationship was identified between variables (entry angle, forward speed, and vibration frequency) and resistance reduction. Furthermore, the threshold for optimal performance was determined. The optimal parameters were identified as an entry angle of 20°, a forward speed of 0.39 m/s, and a frequency of 2.6 Hz. (ii) Validation through soil bin experiments, demonstrating strong agreement between simulated and measured load–displacement responses, confirming the predictive accuracy of the model. The research presented in this paper may offer insights into the principles of low-resistance designs for underground fruit harvesting. Full article

Wireless Sensor Nodes (WSNs) are becoming increasingly popular in various industrial sectors due to their capability of real-time remote monitoring of assets. Powering these devices with vibrational energy harvesters (EHs) provides multiple benefits, such as minimal maintenance and ideally infinite lifespan. Among the vibrational harvesters, translational electromagnetic ones (TEMEHs) are a promising solution due to their simple and reliable architecture and their ability to harvest energy at low frequencies. However, a major challenge is achieving a high power density. In this paper, recent literature about this typology of harvesters is reviewed. Different techniques to tune the resonance frequencies to the fundamental frequencies of the ambient vibrations are analyzed, such as non-linearities and multi-DOF configurations. The harvesters are classified on the basis of the suspension type, highlighting advantages and disadvantages. A final comparison is carried out in terms of NPD and FoMv, two indexes that evaluate power density in relation to size and excitation amplitudes. Full article

Growing demands for self-powered, low-maintenance devices—especially in sensor networks, wearables, and the Internet of Things—have intensified interest in capturing ultra-low-frequency ambient vibrations. This paper introduces a hybrid energy harvester that combines elastic buckling with magnetically induced forces, enabling programmable transitions among monostable, bistable, and multistable regimes. By tuning three key parameters—buckling amplitude, magnet spacing, and polarity offset—the system’s potential energy landscape can be selectively shaped, allowing the depth and number of potential wells to be tailored for enhanced vibrational response and broadened operating bandwidths. An energy-based modeling framework implemented via an in-house MATLAB^® R2024B code is presented to characterize how these parameters govern well depths, barrier heights, and snap-through transitions, while an inverse design approach demonstrates the practical feasibility of matching industrially relevant target force–displacement profiles within a constrained design space. Although the present work focuses on systematically mapping the static potential landscape, these insights form a crucial foundation for subsequent dynamic analyses and prototype validation, paving the way for advanced investigations into basins of attraction, chaotic transitions, and time-domain power output. The proposed architecture demonstrates modularity and tunability, holding promise for low-frequency energy harvesting, adaptive vibration isolation, and other nonlinear applications requiring reconfigurable mechanical stability. Full article

A major challenge for practical magnetic energy harvesting (MEH) applications is achieving stable harvested power with high power density under a wide range of temperature variation. The amount of power harvested from the MEH is sensitive to ambient temperature because the characteristics of the magnetic material are greatly affected by temperature. From a practical point of view, previous studies have limitations because they do not consider thermal effects at all. In this paper, a novel control algorithm form maximum harvesting power in MEH is proposed by considering dynamic changes in temperature for the first time. In order to tackle this problem, a temperature-dependent B-H curve model is proposed, which considers the effect of temperature variation on the magnetic core. This study is the first to integrate thermal effects at the design stage of MEH. Theoretical analysis using the proposed B-H curve model demonstrates that the nonlinear behavior of magnetic materials can be accurately predicted under varying temperature conditions. Based on the above analysis, it was possible to extract the maximum harvested power while predicting shifts in the magnetic saturation point across a wide temperature range. Experimental results validate the effectiveness of the proposed design method, achieving a 26.5% higher power density compared to conventional methods that neglect thermal effects. Full article

In recent decades, substantial progress has been made in embedding molecules, nanocrystals, and nanograins into nanofibers, resulting in a new class of hybrid functional materials with exceptional physical properties. Among these materials, functional nanofibers exhibiting ferroelectric, piezoelectric, pyroelectric, multiferroic, and nonlinear optical characteristics have attracted considerable attention and undergone substantial improvements. This review critically examines these developments, focusing on strategies for incorporating diverse compounds into nanofibers and their impact on enhancing their physical properties, particularly ferroelectric behavior and nonlinear optical conversion. These developments have transformative potential across electronics, photonics, biomaterials, and energy harvesting. By synthesizing recent advancements in the design and application of nanofiber-embedded materials, this review seeks to highlight their potential impact on scientific research, technological innovation, and the development of next-generation devices. Full article