Search Results (156)

This paper proposes and experimentally validates a label-free microdroplet concentration detector based on a quad-resonator metamaterial. The device exploits the linear relationship between the dielectric constant of a binary mixed solution and its concentration, mapping concentration information to absorption frequency shifts with a sensitivity of 28.53 GHz/RIU. System modeling was performed through full-wave simulation. Experimental results demonstrate a highly linear relationship between resonance frequency shift and concentration across ethanol, water, and ethanol–water solutions. The relative deviation between simulation and measurement is less than 3%, validating the model’s reliability and the robustness of the detection principle. This detector supports rapid non-contact sample replacement without requiring chemical labeling or specialized packaging. It can be mass-produced on standard PDMS substrates, with each unit reusable for >50 cycles. With a single measurement time of <30 s, it meets high-throughput detection demands. Featuring low power consumption, high precision, and scalability, this device holds broad application prospects in point-of-care diagnostics, online process monitoring, and resource-constrained scenarios. Future work will focus on achieving simultaneous multi-component detection via multi-resonator arrays and integrating chip-level wireless readout modules to further enhance portability and system integration. Full article

In this study, an adaptive event-driven coordination paradigm is proposed for achieving consensus in nonlinear multi-agent systems (MASs) over directed networks. First, a newly dynamic event-triggered mechanism with single-point historical information is introduced to minimize unnecessary network communication. And a more general form of an event triggering mechanism with moving window historical information is designed for further saving network resources. Considering that the use of historical information over a long period of time may cause deviations, an event-triggered mechanism that can adjust the maximum memory length is proposed in this work to minimize unnecessary network communication. Secondly, the unknown nonlinearities in the MAS model are addressed using the universal approximation capability of neural networks. Then, a methodology for distributed adaptive control under event-triggered mechanisms is introduced leveraging the memory-based command-filtered backstepping methodology, and the proposed scheme resolves the complexity explosion problem. Finally, a case study is conducted to validate the feasibility of the proposed method. Full article

Estimating the mass of Oudemansiella raphanipies quickly and accurately is indispensable in optimizing post-harvest packaging processes. Traditional methods typically involve manual grading followed by weighing with a balance, which is inefficient and labor-intensive. To address the challenges encountered in actual production scenarios, in this work, we developed a novel pipeline for estimating the mass of multiple Oudemansiella raphanipies. To achieve this goal, an enhanced deep learning (DL) algorithm for instance segmentation and a machine learning (ML) model for mass prediction were introduced. On one hand, to segment multiple samples in the same image, a novel instance segmentation network named FinePoint-ORSeg was applied to obtain the finer edges of samples, by integrating an edge attention module to improve the fineness of the edges. On the other hand, for individual samples, a novel cap–stem segmentation approach was applied and 18 phenotypic parameters were obtained. Furthermore, principal component analysis (PCA) was utilized to reduce the redundancy among features. Combining the two aspects mentioned above, the mass was computed by an exponential GPR model with seven principal components. In terms of segmentation performance, our model outperforms the original Mask R-CNN; the $\mathrm{A}\mathrm{P}$, ${\mathrm{A}\mathrm{P}}_{50}$, ${\mathrm{A}\mathrm{P}}_{75}$, and ${\mathrm{A}\mathrm{P}}_{\mathrm{s}}$ are improved by 2%, 0.7%, 1.9%, and 0.3%, respectively. Additionally, our model outperforms other networks such as YOLACT, SOLOV2, and Mask R-CNN with Swin. As for mass estimation, the results show that the average coefficient of variation (CV) of a single sample mass in different attitudes is 6.81%. Moreover, the average mean absolute percentage error (MAPE) for multiple samples is 8.53%. Overall, the experimental results indicate that the proposed method is time-saving, non-destructive, and accurate. This can provide a reference for research on post-harvest packaging technology for Oudemansiella raphanipies. Full article

The increasing size and weight of deep-water topside modules necessitate reliable and efficient installation methods. The twin-barge float-over technique presents a viable alternative to conventional heavy-lift operations; however, its critical tri-vessel load transfer phase involves complex hydrodynamic interactions and continuous load redistribution that are not adequately captured by traditional staged analyses. This study develops a fully coupled time-domain dynamic model to simulate this process. The framework integrates multi-body potential flow hydrodynamics, mooring and fender systems, and Deck Support Units (DSUs). A novel continuous mass-point variation method is introduced to replicate progressive ballasting and the dynamic load transfer from single- to dual-barge support. Numerical simulations under representative sea states reveal significant narrow-gap resonance effects, direction-dependent motion amplification, and transient DSU load peaks that are overlooked in conventional quasi-static approaches. Beam-sea conditions are found to induce the largest lateral DSU loads and the highest risk of barge misalignment. The proposed framework demonstrates superior capability in predicting motion responses and load transitions, thereby providing critical technical support for the safe and efficient application of twin-barge float-over installations in complex marine environments. Full article

The article is devoted to the issues of designing the exploitation of a seam deposit in the boundary areas of underground mines in terms of minimizing the risk of dynamic phenomena. Its main goal was to attempt to demonstrate the relationship between the method of extracting resources trapped in the boundary pillar and the magnitude of the induced seismicity of the rock mass accompanying this process. The substantive considerations concerned the single-wall model and were divided into two main parts—theoretical and verification. As part of the theoretical piece, based on model studies, a geomechanical assessment of the impact of the working face advance on changes in the stress–strain behaviour occurring in the burst-prone layer in terms of the possible loss of continuity of its original structure was carried out. The starting point for the key analyses were the results of numerical simulations based on the algorithms of S. Knothe and W. Budryk’s theories in combination with classical solutions of the mechanics of deformable bodies. Two variants of mining operations in a two-sided environment of goaf were considered, differing in the direction of progress, the degree of constraint of the start and end of the face advance, and mining circumstances in the vicinity of both sides of the advancing face. As part of the verification piece, the results of model analyses were related to an example polygon of a crossing longwall in one of the functioning, rockburst USCB hard coal mines. The scope of the research included a comparison of the experimentally indicated zones of occurrence of tremor-favourable effort processes in the roof of the seam with the actual location of the seismic phenomena foci recorded during the ongoing exploitation. The considerations included in the work formed the basis for formulating conclusions of a cognitive and applicable nature. Full article

The successful implementation of an airborne propulsion system based on hydrogen-powered fuel cell technology highly depends on the development of an efficient, lightweight and compact air supply compressor. Meeting these requirements by designing the compressor using conventional single-point preliminary design methods can be challenging, due to the very wide range of corrected mass flow rate and pressure ratio values that the air supply compressor must be able to accommodate. This article presents a multi-point design methodology for the preliminary design of centrifugal compressors of air supply systems. The method is implemented in an in-house code, called TurboSim, and allows to perform single- and multi-objective constrained optimization of vaneless centrifugal compressors. Furthermore, an automatic design point selection method is also available. The accuracy of the compressor lumped-parameter model is validated against experimental data obtained on a high-pressure-ratio single-stage vaneless centrifugal compressor from the literature. Subsequently, the design methodology is applied to optimize the compressor of the air supply system of an actual fuel cell powertrain. The results, compared to those obtained with a more conventional single-point design method, show that the multi-point method provides compressor designs that feature superior performance and that better comply with the specified constraints at the target operating points. Full article

Background: Sarcopenia and metabolic deterioration are major health concerns in adults aged ≥ 75 years with type 2 diabetes (T2DM), a population characterized by anabolic resistance, reduced dietary intake, and limited renal reserve. Optimizing protein nutrition may support muscle maintenance in this high-risk group, but clinical evidence for individualized high-protein guidance in the oldest-old population remains limited. Objective: We investigated whether an 18-month dietary intervention improves muscle mass and strength in adults aged ≥ 75 years with T2DM and whether serum amino acid (AA) and hormonal profiles reflect these changes. Methods: In this 18-month, single-arm, prospective intervention study, 44 community-dwelling adults aged ≥ 75 years with T2DM received individualized, dietitian-led nutritional guidance targeting a protein intake of approximately 1.4 g/kg ideal body weight (IBW)/day. Assessments at baseline and every 6 months included body composition, muscle strength, renal function, and fasting serum amino acid and hormonal profiles. Longitudinal changes were analyzed using paired t-tests and linear mixed-effects models. This trial was registered in the UMIN Clinical Trials Registry (UMIN000044687). Results: Skeletal muscle index and grip strength showed significant improvements at specific time points during follow-up (both p < 0.05), while gait speed improved at 6 months. Renal function remained clinically stable (eGFRcreat slope: +0.18 mL/min/1.73 m²/year; eGFRcys slope: −2.97 mL/min/1.73 m²/year), with no significant increase in CKD stage. Changes in glucagon correlated positively and C-peptide negatively with changes in skeletal muscle index, whereas glucagon was inversely associated with grip strength. Serum fibroblast growth factor 21 (FGF21) levels decreased over time, suggesting metabolic adaptation to the intervention. Conclusions: Individualized high-protein nutritional guidance for 18 months improved sarcopenia-related parameters, including skeletal muscle index and grip strength, without clinically significant deterioration of renal function in adults aged ≥ 75 years with T2DM. These findings support the feasibility and safety of protein-focused dietary counseling as a strategy to preserve muscle health in advanced age. Full article

The accurate prediction of train acceleration is an essential requirement for Automatic Train Operation (ATO) in urban railways. While traditional single-point mass models fail to capture the distributed dynamics of coupled vehicles, multi-point models are rarely practical due to their computational cost. In this paper, we propose an enhanced single-point mass model based on Long Short-Term Memory (LSTM) networks. The model is trained on Train Control and Monitoring System (TCMS) data from Busan Metro Line 3. By averaging the coupled dynamics of sequence-cars, we obtain a realistic single-point representation. The input data undergoes kinematic preprocessing and feature engineering, including lagging, cross, and statistical measurements. The key innovation of this paper is the physics-based feedback loop mechanism, which is built into the LSTM. This mechanism uses the predicted train acceleration at each time step to update systematically the acceleration-dependent features and make new predictions. This maintains physical consistency and causal relationships without requiring future measurements, reflecting the real-world ATO operational limits. Results demonstrate very high accuracy (R² = 0.9993, MAE = 0.0083 km/h²) without error accumulation, suggesting benefits for both ATO control accuracy and energy efficiency. Full article

The control of a biped robot is a challenging task due to the hard-to-stabilize dynamics. Generating a suitable walking reference trajectory is a key aspect of this problem. This article proposes a novel method of generating walking patterns for biped robots. The method integrates the double support phase and the single support phase into one step, and uses this step as the unit for trajectory generation through quadratic optimization with terminal constraints based on the Linear Inverted Pendulum Model, enabling us to shorten the optimization horizon while still generating natural walking trajectories. Moreover, by restricting the position and acceleration of the center of mass (COM) in the vertical direction, an excessive constraint is formed on the Zero Moment Point (ZMP) to offset the nonlinear effects of the COM’s vertical motion on the ZMP. This allows the COM of the robot to change in the vertical direction while maintaining the linearity of the optimization problem. Finally, the performance of the proposed method is validated by simulations and experiments of walking on flat ground and stairs using a position-controlled biped robot, Neubot. Full article

The molten salt reactor (MSR) is a prominent Generation IV nuclear reactor concept that offers substantial advantages over conventional solid-fueled systems, including enhanced fuel utilization, inherent passive safety features, and significant reductions in long-lived radioactive waste. Central to its safety strategy is a reliance on natural circulation (NC) mechanisms, which eliminate the need for active pumping systems and enhance system reliability during normal and off-normal conditions. However, the challenges associated with molten salts, such as their high melting points, corrosivity, and material compatibility issues, render experimental investigations inherently complex and demanding. Therefore, the use of high-Pr-number surrogate fluids represents a practical alternative for studying molten salt behavior under safer and more accessible experimental conditions. In this study, a single-phase natural circulation loop setup at the University of Idaho’s Thermal–Hydraulics Laboratory was employed to investigate NC behavior under various operating conditions. The RELAP5-3D code was initially validated against water-based experiments before employing Therminol-66, a high-Prandtl-number surrogate for molten salts, in the natural circulation loop for the first time. The RELAP5-3D results demonstrated good agreement with both steady-state and transient experimental results, thereby confirming the code’s ability to model NC behavior in a single-phase flow regime. The results also highlighted certain experimental limitations that should be addressed to enhance the NC loop’s performance. These include increasing the insulation thickness to reduce heat losses, incorporating a dedicated mass flow measurement device for improved accuracy, and replacing the current heater with a higher-capacity unit to enable testing at elevated power levels. By identifying and addressing the main causes of these limitations and uncertainties during water-based experiments, targeted improvements can be implemented in both the RELAP5 model and the experimental setup, thereby ensuring that tests using a surrogate fluid for MSR analyses are conducted with higher accuracy and minimal uncertainty. Full article

The swinging sticks pendulum is an intriguing physical system that exemplifies the intersection of Lagrangian mechanics and chaos theory. It consists of a series of slender, interconnected metal rods, each with a counterweighted end that introduces an asymmetrical mass distribution. The rods are arranged to pivot freely about their attachment points, enabling both rotational and translational motion. Unlike a simple pendulum, this system exhibits complex and chaotic behavior due to the interplay between its degrees of freedom. The Lagrangian formalism provides a robust framework for modeling the system’s dynamics, incorporating both rotational and translational components. The equations of motion are derived from the Euler–Lagrange equations and lack closed-form analytical solutions, necessitating the use of numerical methods. In this work, we employ the Bulirsch–Stoer method, a high-accuracy extrapolation technique based on the modified midpoint method, to solve the equations numerically. The system possesses four fixed points, each one associated with a different level of energy. The fixed point with the lowest energy level is a center, around which small perturbations are studied. The other three fixed points are unstable. The maximum energy used for the perturbations is $0.001\%$ larger than the lowest equilibrium energy. When the system’s total energy is low, nonlinear terms in the equations can be neglected, allowing for a linearized treatment based on small-angle approximations. Under these conditions, the pendulum oscillates with small amplitudes around a stable equilibrium point. The resulting motion is analyzed using tools from nonlinear dynamics and Fourier analysis. Several trajectories are generated and examined to reveal frequency interactions and the emergence of complex dynamical behavior. When a small initial perturbation is applied to one rod, its motion is characterized by a single frequency with significantly greater amplitude and angular velocity compared to the second rod. In contrast, the second rod displayed dynamics that involved two frequencies. The present study, to the best of our knowledge, is the first attempt to describe the dynamical behavior of this pendulum. Full article

An improved Mass–Spring Model (iMSM) is developed by adding central springs to the conventional Mass–Spring Models (MSMs) of tubular structures. This improvement is necessary to model fibers that have enough stiffness so that they do not collapse under transverse loading. Such is the case with many pulp fibers used in papermaking. Four different types of pulp fibers (Aspen CTMP, Aspen BCTMP, Birch BCTMP, and Spruce BKP) were simulated in the study. A geometric model and iMSM of a single fiber were developed, in which the topological structure of iMSM is explained in detail. The mass of mass points and the elastic coefficient of different springs in iMSM were calculated using axial tensile and torsional responses. A dynamic simulation of transverse bending of the fiber over a rigid cylinder and subjected to a transverse pressure was used to determine the effective elastic modulus for four different single fibers and compared to experimental values with an average relative error of 8.49%. The dynamic simulations were completed in 1.04–2.64 min for the four different paper fibers representing sufficient speeds to meet the needs of most real application scenarios. The acceptable accuracy and the fast simulation speed with the developed iMSM fiber model demonstrate the feasibility of the methodology in analyzing paper structures as well as similar fiber-based materials. Full article

In this study, the impact resistance of WUF-B steel frame beam–column joints under fire was investigated using ABAQUS finite element software through a sequential thermal–mechanical coupling approach. By integrating a room-temperature impact model with a single-sided fire field applied to the lower flange of the steel beam, the multi-parameter influence mechanisms—including temperature (150–750 °C), fire area distribution, and impact momentum—were systematically analyzed. Results indicate that elevated temperatures significantly degrade structural impact resistance. At 750 °C, the peak impact force decreases by 73.3% compared to room temperature, while the mid-span bending moment increases by 63.3%. When the fire zone is near the impact point, localized thermal softening further reduces the peak impact force. Under constant impact energy, lower momentum (i.e., higher velocity) accelerates the rebound of the falling mass, revealing the role of momentum transfer efficiency in governing the transient response of high-temperature structures. Additionally, an analytical prediction model based on Timoshenko beam theory and thermo-mechanical stiffness degradation is developed. By introducing a segmented temperature reduction function, the model significantly enhances the accuracy of mid-span displacement predictions for steel structures under fire. Full article

Multirotor UAVs powered by batteries face limitations due to the low energy density of their energy source, which constitutes a significant portion of the total weight. During missions, the high battery mass remains constant, necessitating high required power. This leads to reductions in payload capacity and endurance constraints. This study developed a design tool for multirotor UAVs that sequentially detach used batteries during missions to reduce weight and extend endurance. The developed tool consists of a battery weight prediction model and a required power prediction model. It accurately predicts endurance by considering changes in weight, thrust, RPM, motor-propeller efficiency, and required power at each battery separation point. Using the developed tool, the battery separation technology was applied to a quadcopter with total weights of 7, 15, and 25 kg, and the extended endurances were quantitatively compared. The results showed endurance improvements of 127.3%, 122.0%, and 127.0% for the 7, 15, and 25 kg quadcopters, respectively, compared to using a single battery. In addition, the method was applied to the commercially available industrial UAV DJI Matrice 300 RTK. With a 2.7 kg payload, the two-stage battery configuration extended the endurance by 12.5% compared to the single-battery case. Under no-payload conditions, a three-stage configuration achieved a 16.7% improvement. These results confirm the effectiveness of staged battery detachment even in real-world UAV platforms. Full article

During drilling, different kick locations significantly impact the formation-wellbore temperature (FWT) profile under the co-existence of kick and leakage condition (CKL). To ensure safety and efficiency during drilling, we study the effect of different kick locations on the FWT under the CKL. In this paper, a full transient heat transfer model based on the first law of thermodynamics is established to obtain four distinct WFT profiles under CKL conditions, incorporating both convective heat transfer and variable mass flow effects. Compared with the actual temperature measurement data, the reliability of the developed model is verified. The case studies show that the annular temperature (AT) is lower under the single-point leakage (SL), continuous leakage (CL), and CKL conditions than that in the normal drilling condition. Wellhead temperature in CKL differs significantly from that in normal drilling (ND). As the kick location gets closer to the bottom hole, the AT gets higher, and the temperature difference between the formation and annular gets smaller. Compared with the wellbore temperature profile under ND, the kick location can be detected by real-time monitoring of the FWT profile under the CKL. Full article