Test Bench Research Articles

Study on a Novel Reseeding Device of a Precision Potato Planter

In order to address the problem of a high miss-seeding rate in mechanized potato planting work, a novel reseeding device is designed and analyzed. Based on dynamic and kinematic principles, the seed potato’s motion analysis model in the seed preparation process was constructed. The analysis results indicate that the seed preparation performance is positively related to the seed preparation opening length l1 and inclination angle of the seed-returning pipe θ. Then, the potato’s motion analysis model in the reseeding process was constructed. The analysis showed that the displacement of seeding potatoes in the horizontal direction ds is influenced by the initial seeding potato’s speed , dropping height hs, and the angle between the seeding pipe and the horizontal ground βs. The horizontal moving distance xr of the reseeding potatoes is influenced by the angle between the bottom of the reseeding pipe and horizontal ground βs2, the distance from its centroid to the reseeding door d, and the dropping height of the potato hr. The analysis results indicated that the reseeding potato can be effectively discharged into the furrow. Then, a prototype of a reseeding control system was constructed based on the STM32 microcontroller, electric pushers, and through-beam laser sensors. The simulation analysis was conducted to verify the theoretical analysis by using EDEM2020 software. The simulation results indicated that with the increase in the seeding chain speed, the seed preparation success rate initially increased slowly and then decreased gradually. The seed preparation performance can be increased by increasing the seed preparation opening length or decreasing the seed-returning pipe inclination angle. The impact on the successful seed preparation rate is ranked by significance as follows: seed preparation opening length > seed-returning pipe inclination angle > chain speed. Then, the prototype reseeding device and the corresponding seed metering device were manufactured and a series of bench tests and field tests were conducted. The bench test results showed an average successful seed preparation rate of 93.6%. The average qualified-seeding rate, miss-seeding rate, and multi-seeding rate in the field test were 89.6%, 2.46%, and 7.94%, respectively. This study can provide a theoretical reference for the design of potato reseeding devices.

Theoretical and experimental study of the dynamic and vibratory behavior of gears

AbstractThis study is devoted to condition-based maintenance using vibration analysis. It proposes a numerical and experimental methodology to assist in the detection and vibratory monitoring of chipping faults on gear teeth.The aim of this work is to model the dynamic behavior of the gear link and to treat the vibration behavior of gear flaws theoretically and experimentally. This article is going to study the case of a breast gear, a defect located on the wheel, another defect on the pinion and the wheel and the insufficient center distance defect based on experiments carried out on a test bench manufactured in the laboratory.

Enhancing SRM Performance through Multi-Platform Optimization and FPGA-Based Real-Time Simulation

This paper proposes a multi-platform algorithm methodology in order to define firing angles of torque sharing functions (TSFs) for the indirect torque control of switched reluctance motors (SRM) through a hardware-in-the-loop (HIL) system. This proposal is used to achieve optimal levels of torque ripple and losses with accuracy and reliability, while taking advantage of real-time simulation. The analysis is performed assuming steady-state conditions of speed and torque reference for levels below the base speed, aiming to obtain firing angles ensuring optimal tracking performance. A novel methodology is proposed by using a grid search algorithm that handles the communication between Python, Code Composer, and the Typhoon HIL device. For that, an experimental data FPGA-based model with 500~ns of simulation time step is used to ensure highly accurate dynamic responses of current and electromagnetic torque. Moreover, controller-HIL (C-HIL) is used to have a safe and high fidelity testing environment, allowing rapid testing before transitioning to an experimental test bench. The simulation results are experimentally validated, demonstrating that the proposed strategy is effective and ensures optimal performance, taking into account peripheral systems of A/D, signal conditioning, PWM, and sensor emulation.

The Research of Diesel Engine Assembly Consistency Influence NOx Emission Based on Uniform Design Method

ABSTRACT Diesel engines need to meet the higher emission requirement according to the Euro VI emission standards, and changes in the assembly tolerance of diesel engines will affect the consistency of nitrogen oxides(NOx) emissions. To study the influence of assembly tolerance on NOx emission, a heavy diesel engine was used as the research prototype. The combustion model of the diesel engine was simulated by the Converge software and calibrated with the bench test data. Because the combustion system parameters have a significant impact on emissions, a three-factor eleven-level uniform design is arranged with three parameters, including compression ratio, fuel injection nozzle extension height and injection advance angle. The regression analysis method is used to obtain the relationship between the parameters and NOx emissions. The R2 test value of the regression equation is 0.916 and the F test value is 43.5, which shows that the results of the analysis are very effective. Then the single factor test method is applied to analyze the varying laws of compression ratio, nozzle extension height and fuel injection advance angle on NOx emissions, and the results reveal the inherent law similar to the regression equation. According to the Euro VI emission standards and the law of diesel engine emission performance consistency, the tolerance variation range of the key dimensions of the assembly parameters is obtained.

Model Predictive Control and Service Life Monitoring for Molten Salt Solar Power Towers

A two-component system for control and monitoring of solar power towers with molten salt receivers is proposed. The control component consists of a model predictive control application (MPC) with a flexible objective function and on-line tunable weights, which runs on a Industrial PC and uses a reduced order dynamic model of the receiver’s thermal and flow dynamics. The second component consists of a service-life monitoring unit, which estimates the service-life consumption of the absorber tubes depending on the current mode of operation based on thermal stresses and creep fatigue in the high temperature regime. The calculation of stresses is done based on a detailed finite element study, in which a digital twin of the receiver was developed. By parallelising the model solver, the estimation of service-life consumption became capable of real-time operation. The system has been implemented at a test facility in Jülich, Germany, and awaits field experiments. In this paper, the modeling and architecture are presented along simulation results, which were validated on a hardware-in-the-loop test bench. The MPC showed good disturbance rejection while respecting process variable constraints during the simulation studies.

Assessing energy savings and visual comfort with PDLC-based smart window in an Istanbul office building: A case study

Lighting applications in architectural structures have a high share in energy consumption. Inefficient lighting applications and technologies will increase energy consumption and do not guarantee the visual comfort desired by users. Recognizing the importance of user comfort, this study takes a deeply user-centric approach in proposing feasible lighting control methods that can improve energy efficiency in smart and carbon-neutral future buildings and change daylight's benefits in favor of the user. Smart glass technology, which can adjust the color and transmittance of the light in response to external stimuli (applied voltage) and can be dynamically modulated, changing window and door characteristics, has high potential in the market for modern societies. This paper develops an innovative lighting control method to improve energy efficiency and visual comfort and reduce energy consumption. The daily performance of the proposed control methods regarding illuminance, uniformity factor, and energy consumption is experimentally analyzed in a test bench modeling an office environment with IG80 glass (for comparison), artificial lighting source (LED lamp), and polymer-dispersed liquid-crystal (PDLC)-based smart window. The research methodology involved a detailed analysis of the relationship between performance metrics and dimmer percentages and comparing the energy consumption performance of the lighting methods with other design parameters and technological advances. This algorithm prioritizes user comfort and considers the PDLC-based smart window light transmittance and LED lamp dimmer control depending on daylight. The results show that the proposed algorithm can increase energy savings by up to 22 %. While efficient lighting control is closely related to weather conditions and indoor specifications, it has similar energy consumption performance compared to research into design parameters and technological advances, eliminating further efforts.

EMA fault diagnosis method based on multi-information fusion of GRU and improved attention mechanism

Aiming at the problems of time series feature loss and fault information loss in traditional electromechanical servo system (EMA) fault diagnosis methods based on machine learning and deep learning, a multi-information fusion EMA fault diagnosis method based on gated recurrent unit (GRU) and improved attention mechanism is proposed. Firstly, the collected different sensor signals are divided into different channels, and the time series features of each channel signal are extracted by GRU. Then, the self-attention mechanism is introduced to further distinguish the important relationship between different time points of the signal. The multi-channel attention mechanism is further introduced to adaptively fuse the features of different channels, and finally the fault diagnosis is realized through the classifier. The experimental results based on the test bench data set show that: compared with the single sensor model, the diagnosis rate is improved 10%; compared with the model without the introduction of the attention mechanism, the diagnosis rate is improved 5.2%; compared with the classic machine learning, deep learning and the improved algorithm based on deep learning in the past two years, the diagnosis rate of the diagnosis model designed in this paper is 98.5%above, and the diagnosis effect is the best.

Biomechanical Performance of 4-Leg Sustained Dynamic Compression Staples in First Tarsometatarsal Arthrodesis.

This study investigates the biomechanical efficacy of new 4-leg Sustained Dynamic Compression (SDC) NiTiNOL staples, hypothesized to offer superior stability and resilience to loading before fusion completion, compared with conventional hardware. Twenty sawbones left full foot models were divided into 4 treatment groups: (1) 4-leg Inline Staple, (2) 4-leg Inline Staple + 2-leg Staple, (3) 4-leg Inline Staple + Screw, and (4) Plate + Screw. An osteotomy was performed to simulate a Lapidus procedure, and the respective fixation methods were applied. Mechanical testing was conducted using a servo-hydraulic testing machine to evaluate constructs' load, contact force, contact area, and plantar gap. The 4-leg Inline Staple + Screw group demonstrated significantly increased joint contact force, joint contact area, and decreased plantar gap compared with the Plate + Screw group, both before and after cyclic testing. All SDC-containing constructs exhibited post-cyclic joint contact areas that were 2.36×, 3.87×, and 5.49× greater than the post-cyclic plate + screw group. Most notably, the 4-leg Inline Staple + Screw group maintained a plantar gap of less than 3 mm throughout the testing, unlike other groups. The 4-leg Inline SDC Staple, particularly when combined with a static screw, demonstrated biomechanical superiority over traditional plate and screw constructs in Lapidus procedures. These findings suggest a promising avenue for enhanced post-operative stability, which could translate into quicker patient recovery, improved fusion rates, and potentially lower non-union rates. Further clinical trials are warranted to validate these biomechanical advantages in patient outcomes. Therapeutic, Level V: Bench Testing.

Usage of Machine Learning Techniques to Classify and Predict the Performance of Force Sensing Resistors

Recently, there has been a huge increase in the different ways to manufacture polymer-based sensors. Methods like additive manufacturing, microfluidic preparation, and brush painting are just a few examples of new approaches designed to improve sensor features like self-healing, higher sensitivity, reduced drift over time, and lower hysteresis. That being said, we believe there is still a lot of potential to boost the performance of current sensors by applying modeling, classification, and machine learning techniques. With this approach, final sensor users may benefit from inexpensive computational methods instead of dealing with the already mentioned manufacturing routes. In this study, a total of 96 specimens of two commercial brands of Force Sensing Resistors (FSRs) were characterized under the error metrics of drift and hysteresis; the characterization was performed at multiple input voltages in a tailored test bench. It was found that the output voltage at null force (Vo_null) of a given specimen is inversely correlated with its drift error, and, consequently, it is possible to predict the sensor’s performance by performing inexpensive electrical measurements on the sensor before deploying it to the final application. Hysteresis error was also studied in regard to Vo_null readings; nonetheless, a relationship between Vo_null and hysteresis was not found. However, a classification rule base on k-means clustering method was implemented; the clustering allowed us to distinguish in advance between sensors with high and low hysteresis by relying solely on Vo_null readings; the method was successfully implemented on Peratech SP200 sensors, but it could be applied to Interlink FSR402 sensors. With the aim of providing a comprehensive insight of the experimental data, the theoretical foundations of FSRs are also presented and correlated with the introduced modeling/classification techniques.

Engine Mass Flow Estimation through Neural Network Modeling in Semi-Transient Conditions: A New Calibration Approach

Nowadays, engine experimental research represents a very expensive field within the automotive industry, but it remains fundamental for engine and vehicle development. The present work aims to investigate a novel approach for engine control system calibration, by adopting machine learning techniques to model physical parameters of the engine starting from experimental data measured at the test bench. The main goal is to create a methodology which accelerates the calibration process without losing accuracy. A model that estimates air mass flow is created by adopting either a tree ensemble model or an artificial neural network trained on a small dataset, which was previously acquired at the test bench using a random calibration of the volumetric efficiency map. The model’s performance is first validated on a larger, random dataset. Then, the volumetric efficiency calculated from the air mass flow model estimation is used to calibrate the transfer function of the Engine Control Unit. Finally, the sensitivity of the model error correlated with the number of data points acquired is used in order to determine the best practice for a Design Of Experiment, which minimizes data acquisition. The methodology proposed can lead to reduced time and costs of the whole calibration process of the engine, without losing accuracy. The analysis was conducted on the entire vehicle, which is crucial for drivability, especially in motorcycles since they are highly sensitive to air-to-fuel ratio adjustments. This work demonstrates that machine learning models can be adopted for the fine-tuning of the calibration process, which is normally performed manually.

Experimental and numerical investigation of heat transfer modes on pot surfaces in a power range of a cooking porous burner

The investigation of convective and radiative heat transfers to a cooking pot in a porous burner, coupled with an analysis of the pot's bottom and side contributions to total heat transfer, remains an underexplored area of research. In this study, we adopt a comprehensive approach, combining experimental measurements and 3D numerical models, to explore the practical application of a Silicon carbide porous burner fueled with natural gas in cooking pots with power ranging from 12.15 kW to 31.04 kW. Three primary aspects are examined: differentiating between radiative and convective heat transfer contributions, investigating porous mixing characteristics, and analyzing the burner's thermal and combustion efficiencies. To facilitate this investigation, a dedicated test bench is meticulously designed and constructed, equipped with state-of-the-art measuring instruments to effectively monitor the thermal behavior of the heating process. The results reveal that the higher Damköhler number at higher power, driven by the dominance of chemical time over mixing time, accentuates the importance of chemical reactions in heat transfer to the pot. Moreover, increasing the power leads to a reduction in the burner's overall thermal efficiency, from 29.2% to 18.8%, due to a higher energy waste percentage, escalating from 45.12% at P = 12.15 kW to 65.31% at P = 31.04 kW. This increase in power also strengthens the downward movement of the flame and its detachment from the pot surface. The pot's bottom contribution to total heat transfer ranged from 76.7% to 95.5%, with convection alone accounting for over 98% in all cases. Consequently, optimizing the pot bottom geometry for the purpose of enhancing convection presents promising avenues for significantly boosting thermal efficiency. These findings highlight the potential of the investigated porous burner for efficient and clean combustion in cooking appliances.

An Experimental Study of an Autonomous Heat Removal System Based on an Organic Rankine Cycle for an Advanced Nuclear Power Plant

The present study focuses on the recovery of waste heat in an autonomous safety system designed for advanced nuclear reactors. The system primarily relies on passive safety condensers, which are increasingly integrated into the design of advanced Pressurized Water Reactors (PWRs). These condensers are typically immersed in large water tanks that serve as heat sinks and are placed at sufficient heights to ensure natural circulation. Such a heat removal system can operate for an extended period, depending on the size of the tank. This research is driven by the potential to recover part of the energy stored in the boiling water volume, using it as a heat source for an Organic Rankine Cycle (ORC) system via an immersed heat exchanger. The electricity generated by the ORC engine can be used to power the system components, thereby making it self-sufficient. In particular, a pump replenishes the water tank, ensuring core cooling for a duration no longer limited by the water volume in the tank. An experimental test setup, including a boiling water pool and an ORC engine with an electrical output of approximately several hundred watts, along with an immersed evaporator, was constructed at CEA (Grenoble, France). Several test campaigns were conducted on the experimental test bench, exploring different configurations: two distinct ORC working fluids, cold source temperature variation effects, and relative positioning of the submerged evaporator and heat source within the water tank impact. These tests demonstrated the reliability of the system. The results were also used to validate both the ORC condenser and evaporator models. This article presents this innovative system, which has recently been patented. Moreover, to the best of our knowledge, the investigated configuration of an ORC that includes an immersed evaporator is original.

Research on the discrimination and classification of multi-modal fault bearing based on multi-attribute decision-making mechanism

In order to solve the problem of low fault diagnosis rate of friction torque in upright placement, this paper proposes a fault diagnosis method based on multi-attribute decision-making mechanism to accurately evaluate the fault damage degree of bearing friction torque test bench. We detect defects by utilizing non-destructive, non-contact infrared thermal imaging technology to perform data acquisition and testing in six situations, including non-destructive, damaged inner ring, damaged outer ring, marble-defect, lack of lubrication, and damaged inner and outer ring bearings. Then, the infrared data of different bearings are transformed in a standardized form, and the decision data is mapped to the Pythagorean fuzzy information space. The correlation between the decision data are considering, the PA operator and the BM operator are used for data processing to achieve the accurate distinction of different faulty bearings. Finally, qualitative and quantitative methods are used to analyze the decision results, and the effectiveness of the method is explained. The variation of the overall singular value of each object in the decision result of the proposed method is less than 0.002, while the data fluctuation of WA, WG, HM and DHM related decision methods is 0.005, and there is a singular value greater than 0.02. In addition, sensitivity analysis provides a feasible scheme for parameter optimization and optimal parameter determination.

Frequency-independent dual-tuned cable traps for multi-nuclear MRI and MRS

Magnetic Resonance Imaging (MRI) and Magnetic Resonance Spectroscopy (MRS) of non-proton nuclei (X-nuclei) typically require additional proton imaging for anatomical reference and B0 shimming. Therefore, two RF systems exist, necessitating cable traps to block the unwanted common-mode current at both Larmor frequencies of 1H and X-nuclei. This study introduces a frequency-independent dual-tuned cable trap that combines a standard solenoid cable trap with a float solenoid trap to independently tune high and low frequencies without compromising performance. The methods involved theoretical analysis, electromagnetic simulations, and bench tests. Two design approaches were evaluated: a float cable trap for 1H, a non-float cable trap for X-nuclei, and vice versa. Results showed that the design with the float trap for X-nuclei and non-float for 1H had superior performance, with high common-mode current suppression ability at both frequencies. Bench tests confirmed these findings, demonstrating effectiveness across various static fields and X-nuclei. The proposed frequency-independent dual-tuned cable trap provides a compact and efficient solution for multinuclear MRI and MRS, enhancing safety, image quality, and flexibility.

Effect of tooth surface pitting on dynamic characteristics under mixed lubrication

The variation of tooth meshing stiffness and frictional characteristics caused by tooth surface pitting increases vibration and noise in the gear transmission system. Assuming a smooth tooth surface and a homogeneous material in studying the gear contact and dynamics is insufficient to reveal the evolution of dynamic contact performance caused by pitting faults. In the present study, we established a coupling analysis model for pitting faults to assess the effect of the tooth surface micro-morphology. The mesh stiffness and static transmission error of gears with randomly distributed pittings were calculated, and the vibration response of gears with different pitting degrees was resolved. Finally, the effectiveness of the applied dynamic response theory analysis was experimentally verified using the constructed pitting fault simulation test bench. The results indicate that pitting failure decreases the effective load-bearing capacity of gear teeth. The mesh stiffness gradually but significantly decreased with the pitting degree, also exhibiting fluctuating values. Pitting faults induced significant periodic features in the vibration response of gear transmission systems, showing complex sidebands around the meshing frequency and its harmonics.

Heat pipe-enhanced two-stage thermoelectric harvester based on phase change material

The thermoelectric generator (TEG) technology is important for improving energy efficiency. However, the TEG limited by poor thermoelectric material properties and thermal transfer strategies faces challenges in achieving excellent heat harvesting capacity, especially for large-temperature gradients. Herein, we reported a heat pipe-enhanced two-stage thermoelectric generator (HTTEG) enabled by bismuth alloy-based PCM for effective space waste thermal harvesting. We comprehensively explored the effects of different thermal-enhanced strategies on HTTEG performance. Compared with copper plate and horizontal layout, the effective thermal conductivity obtained by vertical-planar heat pipe is 1.1 × 104 W/mK enhanced by 79.2 and 33.0 times, which has outstanding advantages in achieving considerable temperature difference and excellent thermoelectric harvesting capacity of the HTTEG. We also systematically discussed the thermoelectric properties of heat pipe-enhanced one-stage TEG (HOTEG) and HTTEG by simulation and LED test bench. The results show that the bismuth alloy-based PCM with considerable latent thermal capacity and remarkable heat transfer characteristics can suppress temperature fluctuations and expand thermoelectric harvest interval, achieving excellent power output capacity. Compared with the HOTEG, the thermoelectric power achieved by HTTEG is 4.45 W enhanced by 581.8 %, because optimizing the spatial layout of stage-two thermoelectric modules to the high-temperature gradient interval achieves remarkable heat harvesting efficiency.

Lay-up design and experimental study of the multiple corrugated diaphragms of carbon fiber reinforced polymer composite

Rebound and deformation of stainless steel during processing have brought great difficulties to forming the multiple corrugated diaphragm (MCD), seriously affecting its performance. Carbon fiber reinforced polymer composite (CFRP) provides a new idea for the design and forming methods of MCD due to its excellent performance and designability. This paper uses ABAQUS finite element analysis software to analyze the influence of laying angle and laying angle ratio on the mechanical properties of composite material MCD. Finally, the axial stiffness of the designed CFRP MCD is tested using a flexible coupling stiffness test bench. The findings demonstrate that the design values are consistent with the experimental results within an acceptable margin of error. The investigation validates the feasibility of the proposed laying design method for CFRP multi-waveform membrane discs (MCDs) and establishes a theoretical foundation for their engineering design and practical application.

Design and Testing of Electric Drive System for Maize Precision Seeder

To improve the expandability, seeding accuracy, and operating speed range of the electric drive system (EDS) of precision seeders, this study constructed an EDS based on a controller area network (CAN) bus and designed a motor controller based on a field-orientated control (FOC) algorithm. Full-factorial bench and field tests based on seed spacing (0.1, 0.2, and 0.3 m) and operating speed (3, 6, 9, 12, and 15 km/h) were carried out to evaluate the performance of the EDS. The results of bench tests showed that seeding quality varied inversely with operating speed and positively with seed spacing. The average quality of feed index (QFI) at 0.1, 0.2, and 0.3 m seed spacing in bench tests was 88.38%, 96.67%, and 97.36%, with the average coefficient of variation (CV) being 20.13%, 16.27%, and 13.20%. Analysis of variance confirmed that both operating speed and seed spacing had a significant effect on QFI and CV (p < 0.001). The analysis of motor rotational speed accuracy showed that the relative error of motor rotational speed above 410 rpm did not exceed 2.24%, and the relative error had less influence on the seeding quality. The average QFI was 85.93%, 95.91%, and 96.24%, with the average CV being 21.12%, 15.50%, and 16.49% at 0.1, 0.2, and 0.3 m seed spacing in field tests. The methods and results of this study can provide a reference for the design and optimization of the EDS in a maize precision seeder and provide an effective solution for the improvement of maize yields.

Multi-bandwidth observer-based adaptive robust pressure control for electro-hydraulic brake system with uncertainties and measurement noise

Accurate pressure regulation of electro-hydraulic brake system (EHB) is essential for enhancing braking performance in automobiles. However, component wear and pressure measurement noise can cause model parameters and controlled states to drift, resulting in system chattering. This nonlinear and uncertain state can significantly degrade pressure control performance. Motivated by this, the article presents a controlled state reconstruction-based adaptive robust pressure control technique with noise suppression. Firstly, a reduced dynamics model is established for controller design, which effectively captures the fundamental characteristic of the EHB. Secondly, a multi-bandwidth extended state observer (MBESO) capable of noise suppression is designed to reconstruct controlled states, including unknown disturbances and unmeasured pressure change rates of the EHB. Thirdly, an MBESO-based adaptive robust pressure control technique is introduced, where the control gain and robust factor are updated based on control and observation errors. In addition, the overall performance of the proposed control strategy is analyzed in the frequency domain, and close-loop stability is demonstrated via the Lyapunov method. Finally, the pressure control precision and robustness of the proposed algorithm are validated in both dynamic and static scenarios through sinusoidal and step-response experiments on a hardware-in-loop test bench. The results indicate that the proposed algorithm reduces dynamic pressure-tracking error by up to 62% compared to traditional method under sinusoidal conditions, with steady-state error remaining within 1 bar under step-response conditions.

Design, construction, and use of a tapered-spiral, quadrature 1H/23Na double-tuned coil for in ovo MRI at 7 T.

In ovo MR presents a promising and viable alternative to traditional in vivo small animal experiments. Sodium MRI complements proton MRI by providing potential access to tissue cellular metabolism. Despite its abundance, sodium MRI is challenged by lower MR sensitivity and faster relaxation times compared to proton MRI. Ensuring a high signal-to-noise ratio and effective B0 shimming is essential. Double-tuned coils combining 23Na and 1H are frequently employed to achieve structural imaging and efficient shim adjustment. This study introduces a novel, highly optimized, double-tuned coil design, specifically for MR scans of chick embryos. A tapered-spiral, double-tuned coil was designed and constructed following careful consideration of design parameters. The performance of the coil was rigorously assessed through bench tests, and final validation was conducted on a 7 T MRI scanner using a chick embryo. Bench tests demonstrated that the return losses for both 1H and 23Na coils were better than -30dB, and isolation factors were better than -21dB, indicating that the double-tuned coil was well-set, with negligible coupling between channels. MR images of chick embryos, obtained using the coil, validated the feasibility of utilizing the design concept for in ovo applications. The innovative design of the proposed double-tuned coil, characterized by its unique arrangement, offers improved performance. This design has the potential to significantly enhance the quality of in ovo 1H and 23Na measurements.