Performance Verification Research Articles

Experimental and numerical studies for the performance verification of post-installed anchors used in electrical cabinet fixation

ABSTRACT Most of the electrical equipment responsible for the control within a power plant is configured in cabinet form and fixed using post-installed anchors. Shaking table testing to evaluate the seismic performance of cabinets does not simulate the same installation conditions as on-site, but simply welds the bottom of the cabinet to the top surface of the shake table to assess the structural integrity. The seismic performance evaluation of post-installed anchors is typically conducted indirectly through material testing, making it necessary to compare the performance under on-site conditions to ensure reasonable measurement. This study fabricated a structure as a replacement for the cabinet, fixed it using post-installed anchors, and applied static loads to measure the pull-out load transmitted to the anchors. The measured results were then compared with those obtained from material testing. Consequentially, the pull-out load in the test reflecting on-site conditions was approximately 10% higher than in the material test. So the current way of indirectly evaluating the performance of post-installed anchors is deemed reasonable based on the derived results. To validate the reliability of the experimental study, a numerical study was conducted, and the results showed an error range of around 1%, indicating reasonable and consistent findings.

A risk-targeted decision model for the verification of the seismic performance of RC structures against structural pounding

In this study, a novel risk-targeted decision model is introduced to verify the seismic performance of RC structures against structural pounding and then to define the minimum demand for separation gap distance (dg) between adjacent structures at a target probability Pt. The derivations are based on a linear approximation of the seismic hazard function and well-established probabilistic seismic demand models (PSDMs). New performance objectives (POs) dedicated to structural pounding risk are proposed based on engineering demand parameter (EDP) hazard curves and on the separation gap distances (dg: available or acceptable) between adjacent structures. The theoretical background in the context of the risk-targeted decision model is presented, and then the adjustment to the structural pounding risk is introduced. The minimum separation gap distance (dg,minPt) at a target Pt is defined considering a) the demand hazard curve for the maximum displacement (without pounding) at the top contact floor level of the structure (δmax), and b) the acceptable structural pounding PO of an EDP. The proposed risk-targeted decision model is then demonstrated by means of a structural pounding case study of a RC structure. Local and global EDPs at different performance levels are considered and several POs at different dg are compounded. The verification of the seismic performance of the RC structure at a target probability Pt is carried out either with or without considering the structural pounding risk. Numerical examples of the verification and the definition of the dg,minPt at different pounding risk levels (Pt) of the examined RC structure are also presented and discussed. Based on these results, a distinct PO of an EDP was identified. This PO is characterized as a critical level of structural pounding risk at the capacity level of the EDP and is associated with an explicit-critical separation gap distance between the adjacent structures. In a future research study, this PO could be the basis for providing a design solution against structural pounding risk when the estimated minimum separation gap distance at a target Pt between the adjacent structures cannot be implemented. The provided solution through the proposed decision model also indicates that the maximum demand for separation gap distance between the adjacent structures can safely be shifted to smaller values, notwithstanding that pounding risk is increased.

Honeycomb-ring hybrid random mesh design with electromagnetic interference (EMI) shielding for low stray light.

A honeycomb-ring hybrid random mesh structure is designed to achieve low stray light performance. The honeycomb-ring hybrid random mesh comprises the random honeycomb and random ring, achieving two random superpositions in the structure distribution. The stray light distribution is very low by the combination design with different random hybrid structures. In order to illustrate the advantages of the hybrid random structure, we design a random honeycomb network by randomly offsetting vertices. At the same time, for the random honeycomb structure, we replace each vertex with the ring structure with the size of the ring randomly controlled. Thus, the corresponding honeycomb-ring hybrid random structure is obtained. Compared with the random honeycomb, the maximal normalized high-order diffraction energy of the honeycomb-ring hybrid random mesh is about a 62.85% drop, and the shielding performance is increased by about 50%. At the same time, the optical transmittance remains nearly unchanged. Due to the enjoyable property of the designed honeycomb-ring hybrid random mesh, a sample was prepared for performance verification. The measurement results show that it achieves eminent diffraction pattern distribution with the maximal normalized high-order diffraction energy of about -31.8 dB. At the same time, the average optical transmittance exceeds 86%, and the electromagnetic shielding effectiveness (SE) in the Ku band is greater than 26 dB. Based on the fine photoelectric performance of the honeycomb-ring hybrid random mesh structure, it has great application potential for high-quality optical windows.

Incorporation and Performance Verification of Hepatic Portal Blood Flow Shunting in Minimal and Full PBPK Models of Liver Cirrhosis.

Patho-physiological changes in liver cirrhosis create portacaval shunts that allow blood flow to bypass the hepatic portal vein into the systemic circulation affecting drug pharmacokinetics (PKs). The objectives of this work were to implement a physiologically-based pharmacokinetic (PBPK) framework describing shunted blood flows in virtual patients with differing degrees of liver cirrhosis; and to assess the minimal and full PBPK model's performance using drugs with intermediate to high hepatic extraction. Single dose concentration-time profiles and PK parameters for oral ibrutinib, midazolam, propranolol, and buspirone were simulated in healthy volunteers (HVs) and subjects with cirrhosis (Child-Pugh severity score (CP-A, CP-B, or CP-C)). Model performance was verified by comparing predicted to observed fold-changes in PK parameters between HVs and cirrhotic subjects. The verified model was used to simulate the PK changes for simvastatin in patients with cirrhosis. The predicted area under the curve ratios (AUCCirr :AUCHV ) for ibrutinib were 3.38, 6.87, and 11.46 using the minimal PBPK model with shunt and 1.61, 2.58, and 4.33 without the shunt, these compared with observed values of 4.33, 8.14, and 9.04, respectively. For ibrutinib, propranolol, and buspirone, including a shunt in the PBPK model improved the prediction of the AUCCirr :AUCHV and maximum plasma concentration ratios (CmaxCirr :CmaxHV ). For midazolam, an intermediate extraction drug, the differences were less clear. Simulated simvastatin dose adjustments in cirrhosis suggested that 20 mg in CP-A and 10 mg in CP-B could be used clinically. A mechanistic model-informed understanding of the anatomic and pathophysiology of cirrhosis will facilitate improved dose prediction and adjustment in this vulnerable population.

Dead-time compensation in three-phase grid-tied inverters using LQG multivariable control

Dead-time is the most important disturbance in a voltage-source inverter’s operation. It introduces low-order harmonics at the inverter’s output voltage. To compensate for the dead-time effects in three-phase grid-tied inverters, this paper proposes a Linear Quadratic Gaussian (LQG) multivariable control approach. The LQG multivariable control is known as a robust control approach while provides a high band-width for the closed-loop system. Therefore, it promises significant attenuations in the dead-time introduced harmonics. To achieve a high performance, we run the three-phase grid-tied inverter in the current-controlled mode. Based on the nominal multivariable model derived for the three-phase grid-tied inverter in a synchronous reference frame, the LQG controller is composed such that the closed-loop system exhibits robust stability while attenuates disturbances significantly. The dead-time introduced harmonics produce disturbances in the synchronous reference frame with the highest frequencies. This is the reason for considering the dead-time as the most important disturbance in an inverter’s operation. For an experimental set-up manufactured for the three-phase grid-tied inverter, we developed a detailed model in MATLAB/Simulink. It is employed for the performance verifications of designed LQG controller. Extensive results are presented for different important scenarios, based on which, the excellent performance of proposed approach is proven. In fact, by employing the proposed approach, the dead-time introduced harmonics are significantly attenuated such that a Total Harmonics Distortions (THD) of about 5% is achieved for the injected currents to grid which meets the IEEE 1547 standard.

A Bidirectional Charger for Low-Voltage-Powered Battery Vehicles

A battery charger with bidirectional operability for a low-voltage battery-powered vehicle is discussed in this work. A notable advantage of the presented charger is the effective performance with a wide output voltage range. Hence, this charger facilitates the user to charge a 48 V battery-powered vehicle as well as a 120 V battery-powered vehicle from a single-phase AC supply. Keeping this in view, the presented battery charger utilizes a modified single-ended primary inductor converter (SEPIC) as the back-end DC/DC converter. The modified SEPIC has significantly improved bidirectional operation with a wide voltage ratio of the output voltage and the input voltage. Hence, it effectively regulates the battery current of both a 48 V battery-powered vehicle and a 120 V battery-powered vehicle. Unlike the conventional SEPIC, the modified SEPIC utilizes switches with identical ratings. Thus, the manufacturing complexity reduces. Performance verification is carried out through the experimental analysis of the designed battery charger on a 1.1 kW hardware setup in the laboratory environment. The effectiveness of the battery charger is tested amid diverse operating conditions. Moreover, the conduct of the battery charger during the vehicle-to-grid (V2G) operation is discussed. Lastly, a comparison of the modified SEPIC with its counterparts, based on operational features, is made.

Experimental performance verification of rubber friction bearing

Experimental performance verification of rubber friction bearing

Three-Dimensional Printing of Large Objects with High Resolution by Dynamic Projection Scanning Lithography.

Due to the development of printing materials, light-cured 3D printing is playing an increasingly important role in industrial and consumer markets for prototype manufacturing and conceptual design due to its advantages in high-precision and high-surface finish. Despite its widespread use, it is still difficult to achieve the 3D printing requirements of large volume, high resolution, and high speed. Currently, traditional light-cured 3D printing technologies based on stereolithography, such as regular DLP and SLA, can no longer meet the requirements of the processing size and processing rate. This paper introduces a dynamic projection of 3D printing technology utilizing a digital micro-mirror device (DMD). By projecting the ultraviolet light pattern in the form of "animation", the printing resin is continuously cured in the exposure process to form the required three-dimensional structure. To print large-size objects, the three-dimensional model is sliced into high-resolution sectional images, and each layer of the sectional image is further divided into sub-regional images. These images are dynamically exposed to the light-curing material and are synchronized with the scanning motion of the projection lens to form a static exposure pattern in the construction area. Combined with the digital super-resolution, this system can achieve the layering and fine printing of large-size objects up to 400 × 400 × 200 mm, with a minimum feature size of 45 μm. This technology can achieve large-size, high-precision structural printing in industrial fields such as automobiles and aviation, promoting structural design, performance verification, product pre-production, and final part processing. Its printing speed and material bending characteristics are superior to existing DLP light-curing 3D printing methods.

Verification of the analytical performance of the serum total cholesterol assay on Abbott Architect ci8200

Serum total cholesterol measurement is an essential aspect of preventive healthcare as high levels of cholesterol are linked to various diseases such as atherosclerosis, heart attacks, and strokes. Serum cholesterol measurement is a simple blood test that assesses the levels of cholesterol in the bloodstream. It is an important diagnostic tool that helps healthcare professionals evaluate a patient's risk of developing cardiovascular disease and make decisions regarding treatment and lifestyle changes. Our study aims to verify the analytical performance of the serum total cholesterol assay method using an Abbott kit on the Architect ci8200 automated system in the biochemistry laboratory of the Mohammed VI University Hospital of Oujda. The analytical performance of the kit was verified through flexible scope A by performing a performance study on the Architect ci8200. We evaluated the repeatability, the reproducibility, the imprecision of the measurements and the comparison between two Architect ci8200 automatons. All the results obtained are in conformity with the acceptability criteria recommended by the supplier and the Valtec protocol of the ‘Société Française de Biologie Clinique’ (SFBC), and the study is globally satisfactory. The analytical performance of the Architect ci8200 automated system was satisfactory for a reliable determination of total cholesterol. Verification of methods of dosage in the medical laboratory is crucial to ensure the accuracy, precision, and reliability of laboratory test results. Verification involves confirming that the test method employed is appropriate for the intended use, produces results that are consistent with the claimed performance characteristics, and meets the laboratory's quality control and quality assurance requirements.

Verification of the analytical performance of the serum gamma-glutamyl transferase assay on the Abbott Alinity ci®: Experience of the biochemistry laboratory of the Mohammed VI university hospital of Oujda

Introduction: As part of our study, we set out to evaluate the analytical performance of the gamma-glutamyl transferase (GGT) assay using an Abbott kit on the Alinity ci® automated system in the biochemistry laboratory of the CHU Mohammed VI in Oujda. Materials and methods: This study assessed the repeatability and reproducibility of Alinity ci® and compared the results obtained by the Alinity ci® and Architect ci-8200® automated systems. Results: The results obtained met the acceptability criteria recommended by the supplier and the Valtec protocol of the Société Française de Biologie Clinique (SFBC), demonstrating overall satisfaction with the study. The Alinity ci® automated system demonstrated the analytical performance required for accurate and reliable determination of GGT levels. Discussion: Validation of an analytical method is an essential step in guaranteeing that the result obtained is as close as possible to the reference value of a sample. Several standards and technical guides set out requirements for the performance criteria of an analytical method, notably NF EN ISO 15 189. Conclusion: the verification study of the GGT assay method produced satisfactory results, providing a high level of reliability for analysis results from the central laboratory of the CHU Mohammed VI d'Ouja. This work forms an essential basis for developing an accreditation procedure, which is part of the quality approach to which our laboratory is committed.

Structural design and self-locking performance verification of the snap-fit spatial self-locking energy absorption system under the impact loading

There are increasingly high performance requirements of energy-absorbing systems in aerospace, defense and military, transportation and other fields, especially in the field of emergency protection where the study of self-locking characteristics is of great significance. In this paper, an energy absorption system is designed by snap-fit thin-walled tubes, which can be edited, easy to assemble quickly and spatial omnidirectional self-locking, and the spatial self-locking characteristic of the system was verified by numerical simulation under the uniform/concentrated impact loadings. The results show that the energy-absorbing system can withstand the uniform/concentrated impact loadings in all directions in space. Furthermore, the good comprehensive performance of the loading condition in direction 3 (α = 90 deg, β = 0 deg) was verified by the quantitative analysis of the complex proportional assessment (COPRAS) method and the qualitative analysis of Radar Diagram method.

Application of improved bubble entropy and machine learning in the adaptive diagnosis of rotating machinery faults

This paper proposes an improved bubble entropy algorithm called Improved Hierarchical Refined Composite Multiscale Multichannel Bubble Entropy (IHRCMMCBE) to characterize the fault characteristics of rotating machinery. By introducing the refined composite multiscale analysis algorithm, the improved hierarchical decomposition algorithm, and the multi-channel data analysis method, the bubble entropy algorithm can more fully characterize the fault characteristics. Then, this method is combined with the machine learning algorithm to realize automatic fault diagnosis of rotating machinery. Multi-Cluster Feature Selection (MCFS) is used for feature selection to screen out useless features and improve feature extraction efficiency and feature quality. The MCFS method has excellent performance and does not need parameters, so it is suitable for adaptive fault diagnosis. Meanwhile, the EigenClass classifier using the concept of generalized eigenvalue is used to realize fault recognition. Besides, the recently proposed Gorilla Troops Optimizer (GTO) algorithm is used to improve EigenClass, and a GTO-optimized EigenClass (GTO-EigenClass) classifier is proposed to adaptively select parameters and achieve adaptive fault identification. The proposed fault diagnosis method of rotating machinery based on the improved bubble entropy is independent of data and application scenarios and is hardly affected by subjective factors. The ablation experiment proves the effectiveness of each improvement of bubble entropy. Also, the performance verification experiments and the comparative experiments prove that the method can effectively characterize different types of rotating machinery, different fault types, fault degrees, and composite faults, and it can achieve higher calculation efficiency and classification accuracy. When the sample length is 1024, the average accuracy of bearing and gearbox fault identification can reach 97.85 % and 97.57 % respectively, and when the sample length is 2048, the identification accuracy can reach 100 %.

Expert consensus on the standardization and clinical application of genotyping for human leukocyte antigens

The genes encoding human leukocyte antigens (HLA) are located in the region of 6p21.31 of the human chromosome, accounting for 1/3 000 of the human genome. The area is seen as a structurally complex, with the characteristics of multi-gene inheritance, high polymorphism, haplotype inheritance, linkage disequilibrium, racial diversity, and regional distribution. In recent years, with the continuous innovation of HLA genotyping technology, new issues and challenges have emerged in terms of the standardization of the technology platform, the implementation of the performance validation and verification plan for clinical testing projects, quality control of the entire testing process, analysis and interpretation of results, consultation and selection of donors, and clinical application. This consensus, in combination with the current status of HLA genotyping technology in clinical practice in China, systematically sorts out the key contents in the standardization and clinical application of the HLA genotyping technology platform. The first part proposes the basic requirements for the standardization of the HLA typing technology platform from the perspectives of personnel, instrumentation, reagents and consumables, experimental methods, environmental settings, and introduces the methods and performance indicators for confirming the performance of HLA genotyping with next-generation sequencing (NGS) technology. The second part elaborates on the key points of quality control during the entire process of HLA genotyping procedure, quality control of result reporting and releasing, and management of result interpretation and bioinformatics systems. The last part describes the clinical consultation and application promotion of HLA genotyping. After widely soliciting revisions and discussions from domestic experts in the field of HLA and transplantation, the consensus aims to promote the development and clinical application of the HLA gene in related medical field.

Intelligent CNC control with improved adaptive thermal error compensation model

The thermal errors (TE) of computer numerical control (CNC) in workshop production seriously reduces the productivity. Therefore, to improve the productivity of CNC and enhance production intelligence, an improved adaptive TE compensation model (TECM) is proposed. The model is based on an online temperature measurement system (OTMS), which improves the adaptive learning rate of back-propagation neural network (BPNN) for temperature prediction. Finally, the correlation value between temperature changes and TEs is used for thermal error compensation. The performance verification of the model shows that the proposed OTMS can achieve effective temperature acquisition and processing, and the prediction ability of the improved BPNN is significantly higher than that of other prediction algorithms. Finally, it is found in the test that the improved adaptive TECM can reduce the contour error of workpiece machining to within 0.02×10-3 mm, the machining accuracy of CNC is significantly improved. The above results show that using the improved adaptive TECM can promote the intelligent development of CNC and improve their machining accuracy, which is of great significance to the development of workshop manufacturing.

CloudDeepLabV3+: a lightweight ground-based cloud segmentation method based on multi-scale feature aggregation and multi-level attention feature enhancement

ABSTRACT The segmentation of ground-based cloud images is the basis for obtaining numerous cloud parameters. To achieve high-precision adaptive cloud image segmentation requirements, this study designs a lightweight ground-based cloud image adaptive segmentation method named CloudDeepLabV3+ that integrates multi-scale features aggregation and multi-level attention feature enhancement. Firstly, a novel lightweight EfficientNetV2-S is designed as a feature extraction backbone to reduce network parameters. Secondly, a heterogeneous receptive field splicing atrous spatial pyramid pooling module is designed. It enhances the correlation of information between layers, and realizes multiscale information fusion. The feature enhancement module based on the self-attention mechanism intensifies the representation of local and global features. Thirdly, the feature alignment module based on the attention mechanism is constructed to pull deep and shallow features for alignment. Finally, we implement ablation study on the key components of method and comparison experiment with other advanced methods using five evaluation metrics. Results show that the key components play an important role in multiscale information fusion. It promotes the accuracy of cloud image feature extraction while reducing the loss of detailed features. Generalization performance verification indicates the excellent performance of the proposed model in advanced cloud feature extraction and cloud-mask generation.

Design of a point-focusing lens antenna based on 3D printing for a small-area plasma

The interaction mechanism between plasmas and electromagnetic waves has not been fully defined, and experiments are helpful for investigating the mechanism and verifying the theoretical analysis. This paper proposes a point-focusing lens antenna based on three-dimensional (3D) printing technology for the experimental study of the interaction between electromagnetic waves and a small-area plasma. First, CST simulation software was used for the simulation design of the horn antenna and focusing lens. Subsequently, 3D printing technology was used to print the lens combined with the horn antenna for experimental verification of the focusing performance. Finally, an electromagnetic wave passing through a plasma was experimentally investigated, and it was mutually verified with the propagation theory of electromagnetic waves in plasmas. The experimental and theoretical data indicated that the 3D-printed point-focusing lens antenna exhibited a good focusing effect on electromagnetic waves. This method may be used by employing a variety of materials and designs, thereby considerably improving the detection of small-area plasma. It may also solve the issue of the radial diffraction effect of narrow cylindrical plasma generated by inductively coupled plasma-generation equipment and reduce the error associated with experimental data. Therefore, this method may be useful for plasma propagation measurement, plasma-environment diffraction analysis, and parameter inversion of complex plasma environments.

From Grayscale Image to Battery Aging Awareness—A New Battery Capacity Estimation Model With Computer Vision Approach

Accurate detection of capacity degradation is critical to the safe and efficient utilization of battery systems. Many datadriven capacity estimators were proposed based on emerging intelligent algorithms, but their accuracy depends on the data of complete charged/discharged process and complex algorithm structures. This paper developed a computer vision (CV)-based method, constructing battery multidimensional aging features as the key image to estimate capacity using specific charging data segment. Specifically, the designed image-aging recognition method is used to extract multidimensional aging features from the partial charging current sequence and then establish map inputs for a computer vision model that recognizes the constructed feature maps. Consequently, the mapping relationship between the charging information and capacity degradation can be obtained as the two-dimensional grayscale images which contain massive extracted features in their small size hence greatly simplify the network structure in CV model so as to improve estimation accuracy and efficiency significantly. More importantly, since the model input is a specific charging current segment rather than the data of complete charging process, the model applicability to the random and incomplete charging process of electric vehicles can be greatly improved. Battery cycling data from different types of Li-ion cells was utilized for performance verification. Compared with the conventional estimation methods proposed previously, the proposed method demonstrates the great superiority in terms of the model applicability, estimation accuracy and computational efficiency for online capacity estimation in actual battery usage.

Developing standards, metrics, and systematic approaches for improved model performance verification and validation

Developing standards, metrics, and systematic approaches for improved model performance verification and validation

Optimal Segmentation Approach for Reducing Water Outage Damage Considering Urbanization in Water Distribution Systems

Damage due to abnormal conditions in water distribution systems is attributable to direct causes, such as facility deterioration, as well as indirect causes, including inadequate management, natural disasters, and negligence of a manager. Such damage can be prevented from being spread by closing a shut-off valve to isolate the incident area, although additional damage may occur in the area isolated by the control valve due to water outage, thus requiring a structural solution. Therefore, this study proposed an optimal segment division technique that minimizes the damage due to water outage occurring in the isolated area by installing a shut-off valve at an appropriate location through an optimal valve location determination model designed based on various urban development scenarios. The proposed technique was applied to a benchmark network and J-city network in Korea for performance verification. This technique can be used to select the number of installable valves and find the optimal valve locations according to the urban development scenario.

Verification Of ballistic machine performance against load and capacity at TPST Samtaku Jimbaran Bali

Waste is the result of a shift in people's consumption habits that are not proportional to the level of their activity. Waste has no use value because it is dirty and smelly, but if it can be processed properly, it can become something valuable and boost the use value of society. Every day, 4,281 tons of waste are created on the island of Bali, according to waste data. Only 52 percent of the waste has been managed, while the rest has been controlled. This ballistic machine that can plan 10 tons per hour is already used in Jimbaran, Bali. The shaft in the study is 2350 mm in diameter and has three parts: screw conveyor input, cutting blades and supports, and screw conveyor outlets. The axial force of the screw conveyor is 513,685 N with a threaded knife cutting force of 1; 73,138 N, thread 2; 76.59 N, thread 3; 75.28 N, thread 4; 73.64 N, thread 5; 71.64 N, thread 6; 69.41N, and thread 7; 66.83 N. Highest moment load on the horizontal part is at x = 2200 mm and the vertical part is at x = 1220 mm in the calculation of the bending moment of 107,099 N/mm2. The engine ballistic produces 16.9 horsepower. The capacity of the machine is 281.7 kg of garbage, and it can produce 1.46 tons per hour after being confirmed in one hour.