Performance Test System Research Articles

Simulation and Experimental Study on the Oil Circulation Rate (OCR) of R290 Electrical Vehicle Compressors

This paper establishes a simulation model for the performance of an R290 variable frequency compressor in automotive air conditioning and sets up a compressor performance testing system. It investigates the effects of different evaporation temperatures, condensation temperatures, compressor speeds, and pressure ratios on the oil circulation rate (OCR), as well as the impact of various oil circulation rates on the performance of the R290 compressor. As the comparison between simulation and experimental data shows, compressor performance predictions from the simulation model align with experimental results when the OCR is not taken into consideration. Experimental results indicate that the OCR increases with a rising evaporation temperature, decreases with a lowering condensation temperature, and increases with higher compressor speeds. The simulation model shows a minor deviation when predicting volumetric efficiency, while errors are larger when predicting isentropic efficiency and the discharge temperature. Isentropic efficiency and the discharge temperature show a notable impact from the OCR. Additionally, for system cooling capacity, power, and COP predictions, when the OCR is within the range of 2~10%, the accuracy of the simulation model proves satisfactory, with deviations within 5%.

Influences of Infrared Dye Content and Laser Energy Density on Laser Propulsion Performance of ADN-Based Liquid Propellants.

Ammonium dinitramide (ADN) is a new green oxidant, which is a kind of high-energy ionic liquid and has been widely used in the field of liquid propulsion. When it is used in laser plasma propulsion, its poor absorption coefficient significantly limits its application. To address the issue, this paper investigates the effects of the content of the infrared dye and the laser energy density on the laser propulsion performance of an ADN-based liquid propellant. The performance of the liquid propellant was tested by the light absorption performance test system and the micro-impulse test system. The results show that the addition of infrared dye can significantly improve the light absorption performance of the liquid matrix. As the content of the infrared (IR) dyes increases from 0.3 wt.% to 0.6 wt.%, the absorption coefficient of the ADN-based liquid propellant increases from 248.84 cm-1 to 463.85 cm-1, and the absorption depth decreases from 40.20 μm to 21.56 μm. At a laser energy density of 21.60 J·cm-1, when the IR dye content increases from 0.3 wt.% to 0.6 wt.%, the specific impulse increases from 26.43 s to 54.43 s and the ablation efficiency increases from 4.32% to 18.21%. Significantly luminous plasma appears in the ablation plume at higher laser energy densities, accompanied by higher-velocity plasma shock waves. Compared to the factor of the infrared dye content, the laser energy density contributes more to the ablation efficiency, especially when the increase in laser energy density promotes the full release of chemical energy from the liquid propellant, which, in turn, also enhances the impulse, impulse coupling coefficient, and the plasma detonation velocity. The results provide an important reference for the design of an energy-containing liquid propellant.

A Novel Image-Based Assessment for Pork Quality Classification via Electrochemical Impedance Combined With Sensory Evaluation.

Rapid detection of pork quality has garnered increasing attention due to its status as one of the most widely consumed meats in the world. This study developed an electrochemical impedance combined with sensory evaluation method to achieve real-time imaging and quality assessment of pork. The optimal parameters for pork detection were determined through system performance tests and a Design of Experiment, which included the use of an adjacent excitation pattern, an excitation current of 15 mA at 10 kHz, a detector diameter of 5 cm, and stainless-steel electrodes embedded in the pork. This method facilitated real-time imaging, evaluated the distribution of lean and fat, and accurately distinguished different qualities, demonstrating strong correlation with sensory assessments. Furthermore, it could assess pork with varying levels of freshness, achieving a distinguishing index of 99.93. Hence, this approach holds promising potential for applications in the domain of meat quality assessment.

Optimization of Electrospinning Temperature Control System IoT-Based with DHT21

Electrospinning is a method of making nanomaterials that has a fairly easy and flexible process that can produce nanofiber continuously. Nanofiber morphology from the electrospinning process is influenced by several parameters, one of them is temperature as an environmental parameter. If there is no temperature control system in the electrospinning system, it will be difficult to maintain the consistency of the morphology nanofiber and at certain temperatures, nanofibers are not formed. Therefore, this study aims to develop a temperature control system for electrospinning called the Electrospinning Temperature Control (ETC) System and connect it with an internet-of- things (IoT) platform to understand the dynamics of the temperature control process, upload temperature data to the cloud, and remote monitoring. The method used by designing and building system hardware and software, calibrating DHT21 as a temperature sensor and testing system performance. The results show that the calibration of the DHT21 sensor has an accuracy rate of 94.95% and a precision rate of 98.93%, while the results of the performance test show that the system can raise, maintain, and lower the temperature. Further performance testing reveals that the ETC system can operate within a temperature range of 20−40°C. The IoT system using the Blynk App allows users to remote and monitor easily, and using Google Sheets as a cloud database. The ETC system was successfully built and can be applied to electrospinning experiments.

Experimental study on performance of 100-kW low temperature superconducting steady-state magnetoplasmadynamic thruster

Abstract Applied field magnetoplasmadynamic thrusters (AF-MPDTs), with their high specific impulse and considerable thrust, are increasingly favored for large-scale space missions. This paper presents the composition, functionality, and testing methods of a high-power electric propulsion performance testing system, along with the vacuum ignition test results of a 100 kW superconducting MPD thruster. The relationships between thruster effciency, magnetic field strength, current, and mass flow rate are analyzed. For each combination of current and flow rate in an AF-MPDT, there is an optimal magnetic field strength where the thruster effciency reaches its peak. Under conditions of 320 A current and 60 mg/s flow rate, the optimal magnetic field strength is 0.5 T, yielding the highest thruster effciency of 71%.

Multicenter Evaluation of the QIAstat-Dx and the BioFire Multiplex Panel Tests for the Detection of Respiratory Pathogens.

Syndromic multiplex panel testing enables simultaneous detection of multiple respiratory pathogens, but limited data is available on the comparative diagnostic performance of different testing systems. In this multicenter prospective study, we aimed to compare the QIAstat-Dx Respiratory Panel 2.0 (QIAstat-Dx-RP2.0) with the widely used BioFire-RP2.1, using 269 respiratory clinical specimens. Concordant test results were obtained in 232 (86.3%) cases. Discordant test results included 33 BioFire-RP2.1(+)/QIAstat-Dx-RP2.0(-) and 4 BioFire-RP2.1(-)/QIAstat-Dx-RP2.0(+) results. Discordant samples showed significantly lower pathogen loads than concordant ones (p < 0.01). Overall, the QIAstat-Dx-RP2.0 showed an analytical sensitivity of 50%-100% depending on the respiratory target, with an analytical specificity ≥ 99.0%. Most significant differences were found for the detection of adenovirus, human coronaviruses, respiratory syncytial virus, human rhinovirus/enterovirus and SARS-CoV-2 (kappa-score: 0.67-0.91). Co-detections of respiratory pathogens were identified in 47 cases by BioFire-RP2.1 and 29 by QIAstat-Dx-RP2.0. Agreement rates between the two multiplex panel tests decreased from 91.8% for single pathogen detections to 65.0% and 42.9% for co-detecting two and three pathogens, respectively. Pathogen loads were significantly lower in co-detections compared to single pathogen detections (p < 0.01), potentially explaining the lower detection rates with the QIAstat-Dx-RP2.0 in cases of multiple pathogens. In conclusion, our prospective multicenter evaluation showed good diagnostic performance of the QIAstat-Dx-RP2.0 assay, but lower detection rates for some respiratory targets compared to BioFire-RP2.1. As QIAstat-Dx-RP2.0 offers advantages in handling, noise emission, cost effectiveness, and provides semi-quantitative results compared to BioFire-RP2.1 an updated version with enhanced analytical sensitivity would be a viable alternative syndromic testing system for detecting respiratory pathogens.

Design and optimization of a source (reflector/shielding) performance test system based on (241Am-Be)-paraffin thermal neutron irradiation device

Laboratory measurements and Monte Carlo simulations were conducted to investigate the feasibility of employing a (reflector/shield) to improve the efficiency of a thermal neutron irradiator utilizing a paraffin-moderated single 241Am-Be source with an activity of 1 Ci. A multi-parameter optimization was performed to evaluate the potential of natural lead (Pb) and 90 % enriched 208Pb lead (208Pb(90 %)) in terms of increasing the neutron production while minimizing the total dose equivalent rate. The laboratory-derived optimal configuration for the (reflector/shield) assembly demonstrated that Pb significantly increased the neutron flux by approximately 58 % and reduced the total dose equivalent rate to 0.00443 mSv/h, thereby allowing for a workload of 4500 h within the annual permissible dose limit of 20 mSv. The MCNP simulations validated the potentials of Pb and confirmed the superiority of 208Pb(90 %) in terms of increasing neutron flux to about 26 % compared to that measured for Pb, while also minimizing the total dose equivalent rate to 0.0037 mSv/h. Thus, enabling a workload of approximately 5400 h, which is higher by about 20 % compared to that permitted by Pb based on measurements. The geometrical configuration and results promoted the use of the proposed TNI device primarily for prompt gamma neutron activation analysis (PGNAA).

Development and verification of subgrade service performance test system considering the principal stress rotation

Development and verification of subgrade service performance test system considering the principal stress rotation

MDM System Performance Test Recommendations

The paper provides detailed guidance for a Performance Test Process and Recommendations for a Master Data Management System, focusing on the IBM Infosphere MDM Server. And outlines the Importance of early involvement of the Business and systems owners in setting performance benchmarks, and the stakeholders’ collaboration, during the test and the steps to establish monitoring, change control, and document the test results and the performance test processes and system scalability Testing recommendations.

Cellular Vehicle-to-Everything Automated Large-Scale Testing: A Software Architecture for Combined Scenarios

As the commercialisation of Intelligent Connected Vehicles (ICVs) accelerates, Vehicle-to-Everything (V2X)-based general testing and assessment systems have emerged at the forefront of the research. Current field testing schemes mostly follow the norms of traditional vehicle tests. In contrast, Original Equipment Manufacturers (OEMs) have increasingly focused on the potential influence of V2X communication performance on the application response characteristics. Our previous work resulted in a C-V2X (Cellular-V2X) large-scale testing system (LSTS) for communication performance testing. However, when addressing the need to combine application and communication, the system software faces confronts heightened technical challenges. This paper proposes a layered software architecture for the automated C-V2X LSTS, which is tailored to combined scenarios. This architecture integrates scenario encapsulation technology with a large-scale node array deployment strategy, enabling communication and application testing under diversified scenarios. The experimental results demonstrate the scalability of the system, and a case study of Forward Collision Warning (FCW) validates the effectiveness and reliability of the system.

On the Issue of Constructing Spatial Isolines for Irregular Monitoring Networks

The article examines spatial isolines construction based on data on an irregular grid. In particular, a possible solution to the problem of contour breaks is explored. Measurements of the magnetic field parameters taken from variation stations are used as data. The paper presents a description of the algorithm for constructing isolines and describes the software system that implements this algorithm. The results of system performance testing are given in the last chapter.

Soil Moisture Detection and Linear Deceleration Control Strategy Enhancing Trenching Depth Precision and Stability for Rapeseed Sowing

Sowing depth significantly affects the germination of rapeseed, and different soil moisture conditions require corresponding sowing depths. However, most current trenching devices do not account for soil moisture content, and commonly used hydraulic or constant-force trenching equipment also exhibits deficiencies in stability and consistency. To address these challenges, this study developed an automatic depth adjustment control system based on soil moisture content. A soil moisture detection device and an innovative sliding mechanism that maintained the soil moisture sensor in a relatively stationary position relative to the soil during seeder movement were introduced. An automatic sowing depth adjustment device was designed to modulate the sowing depth. A control strategy that incorporated the Kalman filtering algorithm and linear deceleration equations was conducted. At an observation noise covariance matrix (Q/R) of 0.001, a deceleration range of 40 mm and a minimum speed of 10, the control system exhibited minimal overshoot (approximately 4%) and steady-state error (approximately 3.2 mm). It effectively adjusted the trenching depth while operating at speeds ranging from 2 to 3.6 km/h, successfully adapting to variations in soil topography. The system performance tests revealed that the control system adjustment time (ts) was 534 ms and the steady-state error remained within 1 mm. Under three different soil moisture content conditions, the sowing depth qualification rate and stability coefficients consistently surpassed 90% and 80%, respectively. This research offers a sowing depth adjustment control system based on soil moisture content, contributing to more precise depth regulation for rapeseed sowing.

Study and Experimental Verification on Anti-Disturbance Control Strategy for Electro-Mechanical Servo Systems

With technological advances and industrial upgrading, electro-mechanical actuators (EMAs) have gradually replaced traditional hydraulic actuation systems. During operation, force servo systems inevitably suffer from external force or position disturbances, thus affecting the output performance of the system. Therefore, it is of significant engineering application value to develop EMA anti-disturbance control strategies that exhibit strong robustness and are more easily applicable to engineering practice. In this study, an open-loop transfer function of the system with command signals and disturbance signals as inputs was established based on the nonlinear mathematical models built for the core components of EMAs. To overcome the impact of external position disturbances on the motion performance of the force servo system, a proportional integral derivative (PID) controller was introduced and a high-order transfer function associated with various parameters such as speed and acceleration was derived and obtained as feedforward compensation based on the mathematical model. By incorporating a three-loop PID controller, the impact of external disturbance forces on the motion performance of the position servo system was overcome and the tracking accuracy of the system was also improved. Finally, simulation models were built using AMESim software (AMESim 2020, LMS Imagine.Lab, Roanne, France) and a dual-channel EMA performance testing system was developed. Simulation and test results indicated that both anti-disturbance control methods exhibited strong robustness and excellent anti-disturbance performance, with the control accuracy and dynamic performance almost unaffected by disturbances. This verified the correctness of the single-channel EMA anti-disturbance control strategy and the usability of the simulation model.

Development of Nutrient Control System in Plant Factory based on Growth Phases of Romaine Lettuce (Lactuca sativa var. longifolia)

Nutrient is one of the conditions controlled in a plant factory. Nutrient control must be based on the plant growth phase, but previous research has shown shortcomings in this area. This study aims to develop a nutrient control system in a plant factory based on the plant growth phase, specifically using Romaine lettuce. The research method used is the experimental method, with research stages including system design (controller modification, programming, and TDS sensor calibration testing) and system performance testing. The TDS sensor calibration test results showed an R² of 0.9999, indicating that the TDS sensor readings are very close to those of the TDS meter. The system performance test results showed that the developed system works well in controlling nutrient levels based on the growth phase of Romaine lettuce. The planting process lasted 30 days, from October 13, 2023, to November 11, 2023, with a total of 2,697 data points recorded by Antares. Nutrient requirements were adjusted per the growth phase of Romaine lettuce, with set points in the first to fourth weeks being 500 PPM, 600 PPM, 700 PPM, and 800 PPM, respectively. The average nutrient levels recorded in the first week were 518 PPM, 623 PPM in the second week, 721 PPM in the third week, and 820 PPM in the fourth week. The TDS sensor accuracy test results showed an R² of 0.9998, indicating that the TDS sensor performed well in controlling nutrient levels during the system testing, with an average TDS sensor reading error of only 1.17%. During the planting process, the total amount of nutrients added for each of nutrients A and B was 210.10 ml, with the total operating time of the control components being 314.34 seconds for each peristaltic pump of nutrients A and B.

Effect of blade length on unsteady cavitation characteristics of hydrodynamic torque converter

Hydrodynamic torque converters (HTC), as power transmission component for high-power machinery, achieve flexible and energy saving transmission by circulating viscous oil through multi-stage impellers, involving cavitation at high flow speeds. To achieve cavitation suppression and performance enhancement, this study analyzed the mechanism of HTC blade length on cavitation effects. The Computational Fluid Dynamics (CFD) model of cavitation in the internal flow field of HTCs with different blade length were established, a hydraulic performance and flow-induced vibration test system was set up, and experimental prototypes with different blade lengths were designed and manufactured. The macroscopic and microscopic transient cavitation characteristics of different blade length were studied. The results show that shortening the length of pump and turbine blades has a significant suppression effect on cavitation. Due to changes in the impeller outlet flow field and circulation flow, the cavitation attachment range has changed significantly. Additionally, the significant impact of blade length on the flow-induced vibration influent the evolution characteristics of transient cavitation. Shorter blades reduce the amplitude of pressure oscillations, improving the attachment stability of cavitation. This study has important implications for improving the performance of HTCs and reducing the occurrence of cavitation.

Design and research of fuzzy PID-based liquid pump performance testing platform

Abstract The pump is a crucial component of agricultural sprayer machinery, directly impacting its operational quality. This paper designs a performance testing platform for pumps. Utilizing a brushless DC motor as the power source for the pump, a closed-loop mathematical model for the brushless DC motor is established. Simulation experiments and indoor experimental tests are conducted. Simulation results indicate that the motor control system exhibits fast response, no overshooting, and excellent dynamic and static performance. Experimental tests on the platform show that the error range of motor speed is less than 0.3%, achieving excellent control performance. The constructed pump performance testing system achieves precise measurement of pump flow rates at different speeds, demonstrating outstanding performance.

Performance evaluation of the SMART passive safety injection system against the SBLOCA scenario with the SMART-ITL facility

A set of system performance tests has been performed and the thermal-hydraulic behaviors were investigated for the passive safety injection system (PSIS) of the SMART design. Major thermal-hydraulic characteristics of core cooling in reactor coolant system and safety injection (SI) in PSIS were investigated using the SMART-ITL. The parametric effects of break size, break location and train number on the PSIS performance were discussed with the relevant SMART-ITL data. Compared with the 2.0 inch SI line break test, the 0.4 inch SI line break test has a milder change of system parameters. The pressure is reduced more quickly, the decrease of water level is slower and the break mass flow rate is higher during the pressurizer safety valve line break than during the SI line break. Major thermal-hydraulic parameters were compared among single, two and full train operation of the PSIS focusing on the effect of train number. It was shown that multiple trains of CMT and SIT were operated independently and the reactor vessel (RV) inventory increased proportionally with the addition of each train. Sufficient SI water was injected into the RV in a passive manner to cool down the reactor core efficiently during the full train test.

Localization and Mapping Method Based on Multimodal Information Fusion and Deep Learning for Dynamic Object Removal

Article Localization and Mapping Method Based on Multimodal Information Fusion and Deep Learning for Dynamic Object Removal Chong Ma, Peng Cheng, and Chenxiao Cai * School of Automation, Nanjing University of Science and Technology, Nanjing 210094, China * Correspondence: ccx5281@njust.edu.cn Received: 10 September 2023 Accepted: 25 December 2023 Published: 26 June 2024 Abstract: A simultaneous localization and mapping (SLAM) system is presented in this paper based on visual-inertial fusion to solve the pose estimation drift problem caused by weak texture environments or rapid robot movements. The camera and inertial measurement unit (IMU) is initialized through IMU pre-integration and visual front-end processing, and a tightly coupled residual function model is employed in the back-end to eliminate accumulated errors. To realize the real-time pose estimation in the complex loop scene, the sliding window optimization method based on the marginalization strategy is adopted to improve the optimization efficiency of the system, and the loop detection algorithm based on the bag-of-words model is exploited to solve the cumulative error problem generated during long-term operation. Furthermore, because of the interference (of complex scenes with dynamic targets) in system modeling and localization of the environment, this paper introduces a deep-learning semantic segmentation model to segment and eliminate dynamic targets. The system performance test is carried out based on the EuRoC dataset and the KITTI dataset. Finally, the experimental results illustrate that the proposed method has improved system robustness and localization accuracy compared with the pure vision algorithm and the visual-inertial fusion algorithm without removing dynamic targets.

Photovoltaic Model Parameters Estimation Via the Fully Informed Search Algorithm

Effective parameter estimation for photovoltaic (PV) systems holds significant importance for both researchers and industry professionals. An accurate understanding of PV models, achieved through modeling and simulation, plays a pivotal role in optimizing the design, control, testing, and forecasting of PV system performance. Developing a precise and robust parameter identification method significantly contributes to enhancing the modeling, control, and optimization of photovoltaic systems. In this context, our research contribution introduces a novel version of Rao metaheuristic algorithm named the Fully Informed Search Algorithm (FISA). Which demonstrate acceptable performance to solving optimization problems in several applied fields. While, maintaining the simplicity and non-parametric nature of the original algorithm. The proposed algorithm holds promise for various industrial applications, particularly in optimizing complex systems such as photovoltaic (PV) systems. For which, we used it to efficiently identifying the parameters of the single-diode model (SDM). Thus, we demonstrate its effectiveness through the application in two distinct case studies within our simulation research. in the end, we compared the results of FISA algorithm to seven other well-known algorithms, the obtained results indicate the superiority of the proposed algorithm in term of the stability of the system, a faster convergence and higher accuracy.

The study of in-situ calibration technology of redocking torque parameter of performance test system for space station redocking mechanism

Abstract The redocking manipulator performance test system is the necessary equipment in the development stage of a redocking manipulator. The measurement parameters such as redocking torque are the key parameters used by the test system to simulate the redocking process of the space station, which directly affect the simulation accuracy of the whole test system and the correctness of the test results of the redocking manipulator. In this paper, the in-situ calibration technology of redocking torque is studied. Firstly, the calibration theory is analyzed based on the sensor comparison method. Secondly, the in-situ calibration device of redocking torque is established by using a special loading mechanism and calibration tooling, and the measurement uncertainty is evaluated. Finally, the application verification test of the test system is carried out to verify the feasibility of the calibration device, which provides a metrological guarantee for the successful completion of the development and production task of the redocking manipulator of the space station.