Tolerance Research Articles

Numerical simulation for determining the measurement uncertainty for the calibration of mass standards by transfer artefacts

Monte Carlo methods are appropriate for determining the manufacturing accuracy and measurement uncertainty for the calibration of mass standards using sorption, duplex and buoyancy artefacts that are referred to as transfer artefacts. Systematic influences and their application-specific measurement uncertainty can be calculated for the important parameters mass, surface area and volume. Since accurate volume measurements are complex, the evaluation of the uncertainty contribution is important. The input variables of the simulations result from the specified manufacturing tolerances as well as from the measurement uncertainties of the coordinate measuring machines employed. The developed model allows the transfer artefacts described to be calculated with a uniform approach according to the specifications of the GUM. Results for silicon transfer artefacts with a nominal mass of 1 kg are presented and discussed.

Electromagnetic Characteristics Analysis in Double‐Sided Permanent Magnet Linear Synchronous Motor with Asymmetrical Air‐Gap

The double‐sided permanent magnet linear synchronous motor (DS‐PMLSM) is widely used in the industrial field with high precision and long strokes due to simple construction, high instantaneous thrust and high controllability. However, parasitic issues, such as unavoidable manufacturing tolerances, might cause the symmetrical position deviation of primary or secondary components, which results in an asymmetrical air‐gap between components, affecting the motor's electromagnetic characteristics further. In this paper, it is taken into account secondary torsional or offset conditions (the secondary component is displaced sideways from a symmetrical position), and investigates the variations of electromagnetic characteristics on the 12‐solt 14‐pole short‐primary DS‐PMLSM. Based on the finite element method (FEM), the effects of secondary torsion or offset on the air‐gap flux density, the back‐EMF, the detent force, the thrust force, and the normal force are investigated and compared respectively. In addition, the analytical results of the back‐EMF considering lower secondary torsion are verified on a lower secondary torsional prototype. From the analytical results of electromagnetic characteristics, it is revealed that with the torsional angle or offset distance rising, the normal force and detent force in the Y‐axis gradually increase, while the thrust force and the back‐EMF decrease. These theoretical researches can play an important role in the operation and assembly process of the DS‐PMLSM. © 2022 Institute of Electrical Engineers of Japan. Published by Wiley Periodicals LLC.

Dynamic Modeling, Optimization and Experiment for a High-Speed Spur Gear Set

This study proposed a novel methodology for reducing the vibration of a high-speed spur gear pair (up to 30,000 rpm) by performing multi-objective optimization of the peak-to-peak loaded transmission error (PPLTE) under three assembly conditions. The optimum tip relief parameters for the high-speed spur gear set were studied by considering the practical manufacturing tolerances on the gear shaft and bearing bores. First, the PPLTE under three assembly conditions was determined by loaded tooth contact analysis. Multi-objective optimization with a genetic algorithm was used to determine the optimum linear tip relief parameters, minimizing the PPLTE under three assembly conditions by 70%. Moreover, the dynamic characteristics of the original and optimum designs were simulated and compared under ideal conditions as well as axial misalignments. The optimum design exhibited a >50% reduction in the peak RMS of acceleration at the natural frequency. Finally, dynamic experiments were performed and the RMS values of the acceleration at various speeds were computed for comparison. The results from both dynamic simulation and experiment indicated that the optimum design exhibits superior dynamic characteristics to the original design.

Statistical Analysis of Properties of Technological Charge and Manufacturing Tolerance of Thin-Walled Sections in Process of Multi-Workstations Roller Bending

Statistical Analysis of Properties of Technological Charge and Manufacturing Tolerance of Thin-Walled Sections in Process of Multi-Workstations Roller Bending

Effect of tip clearance variation in the transonic axial compressor of a miniature gas turbine at different Reynolds numbers

Degradation in the service or manufacturing tolerances can cause tip clearance variation, which adversely affects the stability and performance of compressors. In particular, for a miniature gas turbine, the size of the tip clearance ratio (the ratio of tip clearance to the tip chord length) is relatively large, thus it is more likely to operate at low Reynolds number. This study, therefore, numerically investigated the effect of tip clearance variation on the aerodynamic performance of a 1.5-stage transonic compressor at high and low Reynolds numbers using a 3D Reynolds averaged Navier-Stokes (RANS) solver that incorporates the SST k-ω turbulence model coupled with the γ-θ transition model. The results show that the aerodynamic performance and the tip flow field structure of the compressor change significantly with varying tip clearance.At high Reynolds number, the performance curves are essentially negatively linear with tip clearance, but the slopes sharply increase at medium tip clearance (0.9% C, C represents the tip chord length). At low Reynolds number, the varying trends of the sensitive curves for large tip clearances (0.9% C–1.8% C) are basically the same as that at high Reynolds number. However, for small tip clearances (0.3% C–0.9% C), the aerodynamic performance parameters fluctuate, namely, there is a peak aerodynamic performance at low Reynolds number. When considering the performance and surge margin of the compressor comprehensively, the best tip clearance is 0.6% C at high Reynolds number, but 0.9% C at low Reynolds number.

ANN-predictive modeling and GA-optimization for minimizing dimensional tolerance in Polyjet Additive Manufacturing

Polyjet Additive Manufacturing (AM) is gaining attention owing to its ability to manufacture intricate parts with microscopic resolution. While extensive research and development have optimized the accuracy and strength of 3D printed structures, however, only a few prediction models exist for predicting the accuracy of the thermoplastic-based components using Polyjet technique. The study presents an accuracy-based predictive model for polyjet AM of thermoplastic structures which significantly raises the fabrication standards and reduces the number of unnecessary experimental attempts. Multivariate Regression Analysis (MVRA) statistical approach and the Generalized Regression Neural Networks (GRNN) approach is carried out to evaluate the effect of numerous significant polyjet printing parameters such as Support Material, Print Mode, Print Orientation, and Thermoplastic resin on the dimensional stability of the printed structures, examined under an ultra-compact 3D laser sensor. The outputs are optimized using the Genetic Algorithm (GA), and the findings are found consistent with experimental trials. This study sets new standards for additive manufacturing of thermoplastic components by examining the influence of polyjet printing factors on the accuracy of the manufactured fastener along the X, Y, and Z axes, respectively. The study may eventually substitute metal fasteners in certain industrial applications such as in fluidics, electronics, biomedical engineering, food packaging, and automobile industries.

Rapidly frequency-tuneable, in-vacuum, and magnetic levitation chopper for fast modulation of infrared light.

We present an in-vacuum mechanical chopper running at high speed and integrated into a magnetic levitating motor for modulating optical beams up to 200kHz. The compact chopper rotor allows fast acceleration (10kHzs-1 as standard) for rapid tuning of the modulation frequency, while 1mm diameter slots provide high optical throughput for larger infrared beams. The modulation performances are assessed using a reference visible laser and the high brightness, broadband, infrared (IR) beam of synchrotron radiation at the MIRIAM beamline B22 at Diamond Light Source, UK. For our application of IR nanospectroscopy, minimizing the temporal jitter on the modulated beam due to chopper manufacturing and control tolerances is essential to limit the noise level in measurements via lock-in detection, while high modulation frequencies are needed to achieve high spatial resolution in photothermal nanospectroscopy. When reaching the maximum chopping frequency of 200kHz, the jitter was found to be 0.9% peak-to-peak. The described chopper now replaces the standard ball-bearing chopper in our synchrotron-based FTIR photothermal nanospectroscopy system, and we demonstrate improved spectroscopy results on a 200nm thickness polymer film.

Developing Systems of Manufacturing Tolerances

Developing Systems of Manufacturing Tolerances

Performance Analysis of Logistic Model Tree-Based Ensemble Learning Algorithms for Landslide Susceptibility Mapping

Landslide susceptibility prediction (LSP) is the key technology in landslide monitoring, warning, and evaluation. In recent years, a lot of research on LSP has focused on machine learning algorithms, and the ensemble learning algorithm is a new direction to build the optimal prediction. Logistic model tree (LMT) combines the advantages of decision tree and logistic regression, which is smaller and more robust than ordinary algorithms. The main aim of this study is to construct and test LMT-based random forest (RF) and selected ensemble learning algorithms including bagging and boosting algorithms to compare their performance. Firstly, taking the county of Ziyang, China, as the study area, through historical reports, aerial-photo interpretations, and field investigations, 690 inventory maps of landslide locations were constructed and randomly divided into the 70/30 ratio for a training and validation dataset. Secondly, considering geological conditions, and landslide-induced disease and its characteristics, 14 landslide-conditioning factors was selected. Thirdly, the variance-inflation factor (VIF) and tolerance (TOL) were used to analyze the 14 factors, and the prediction ability was calculated with information-gain technology. Ultimately, the receiver-operating-characteristic (ROC) curve was applied to verify and compare model performance. Results showed that the LMT-RF model (0.897) was superior to other models, and the performance of LMT single model (0.791) was the worst. Therefore, it can be inferred that the LMT-RF model is a promising model, and the outcome of this study will be useful to planners and scientists in landslide sensitivity studies in similar situations.

W-Band 4th Order Waveguide Filter Based on Double Layer SU8 Microfabrication.

This paper investigates the fabrication accuracy of the W-band SU-8 photoresist micromachined 4th order waveguide bandpass filters (BPF). The designed filter based on cylindrical resonators is excited in TM010 mode. It is ideally suitable for the layered SU-8 micromachining process as the height of the resonator is much smaller than one wavelength, the electromagnetic fields remain unchanged in the thickness direction. The filter is composed of three silver-coated SU-8 layers based on a double-layer overlay process. Excellent manufacturing tolerances can be controlled within 4 μm in the thickness direction, around 10 μm in double-layer stacking accuracy, and an average of 1° in vertical angle deviation. Various challenges encountered in the SU-8 process are investigated while corresponding general solutions are proposed for machining high-precision devices. The measured results show a return loss of 12.4 dB and a minimum insertion loss of 0.8 dB, which are in agreement with the simulated one. Stress and deformation analysis are also conducted to confirm the maximum pressure that the filter can withstand and maintain good transmission performance.

Multi-functional graphene-based tunable beam splitter in terahertz band

Two multi-functional graphene-based tunable beam splitters in terahertz band with different incidence modes are proposed in this paper. For the first time, we have achieved multiple functions of the beam splitter in the same structure only by tuning the Fermi level of the graphene layers. The optimum parameters are obtained through rigorous coupled-wave analysis, simulated annealing algorithm, and simplified modal method, which will be discussed in Section 2. At the optimum parameters, the proposed Littrow incidence beam splitter works as a polarization independent high-efficiency -1st order polarizer at and polarization independent uniform dual-port output beam splitter at . For normal incidence beam splitter, it can be transformed from a polarization independent 0th order suppressed dual-port output at to polarization-selective (transverse electric (TE)-two/transverse magnetic (TM) -three) output at . Moreover, the influence of the profile of the grating, the Fermi level, and the number of the graphene layers on diffraction efficiency are discussed in detail to reveal some manufacturing tolerances and the importance of choosing the specific appropriate parameters. The results indicate that the proposed multi-functional graphene-based tunable beam splitters in terahertz band with simple structure have great potential application values in the future.

Integrated Inductor Model Verification for Microwave LC-filters in Si and SiGe Systems on a Chip

In this paper, the conductor model that can be used to design of various inductor layout configurations for any Si and SiGe technological processes is considered. The experimental prototypes of the test inductors were produced in the standard SiGe BiCMOS 130 nm process to verify the model. The chips measuring results showed that the characteristics of the prototypes taking into account the manufacturing tolerance are in the range of model simulated values. It has been found that the proposed model has a better convergence with the prototypes characteristics than 3D modeling. The equivalent circuit simulation speed can be orders of magnitude higher than the 3D simulation speed. The proposed model accuracy is achieved by taking into account the skin-effect and edge-effects in the dielectric and substrate. Using the skin-effect equivalent circuit the model can be run in Cadence Specter Simulator. It is necessary for the microwave LC-filters development.

Evaluating the application of K-mean clustering in Earthquake vulnerability mapping of Istanbul, Turkey

Performing the most up-to-date and accurate vulnerability assessment is key to an effective earthquake disaster management. In cities like Istanbul (Turkey) with a high rate of urban expansion, the safety of the residents must not be neglected. The challenges in such studies are related to the lack of a training dataset. Some areas are highly prone to earthquakes, however, there have been no earthquakes in those areas recently. This research proposes and tests the ability of the k-mean clustering method to create the training dataset for earthquake vulnerability analysis. Subsequently, the derived sample dataset was used in four state-of-the-art models i.e. Decision Tree (DT), Support Vector Machine (SVM), Self-Organizing Map (SOM) and Logistic Regression (LR) for assessing earthquake vulnerability in Istanbul, Turkey. The multicollinearity among the variables was determined using tolerance (TOL) and variance inflation factor (VIF) which revealed no multicollinearity among the variables. The highest VIF belonged to the “distance to faults” factor. Vulnerability related variables were classified, weighed and using k-mean clustering, a training database was constructed. Then, the standardized variables were keyed in as input alongside the training site maps into DT, SVM, SOM and LR to construct an Earthquake Vulnerability Map (EVM). EVMs were created for all the four samples and graded as very-low, relatively-low, moderate, high, or extremely-high. Several statistical metrics such as Area under the ROC curve (AUC), sensitivity (SST), specificity (SPF), root-mean-squared-errors (RMSE), positive predictive value (PPV), and negative predictive value (NPV) were used to evaluate the accuracy of the resultant maps. The highest and lowest AUC prediction rates were 0.962 and 0.912 from the K-means-SOM and K-means-LR models, respectively. The lowest RSME results using the testing dataset (0.329) belonged to K-means-SVM model. The region's most prone vulnerability maps were found to be in the districts 9, 13, 20, 21 and 35. Finally, an analysis of the buildings and population distribution was carried out among the 39 districts of Istanbul considering the SOM outcomes. The research outcome could help in laying strategies for earthquake preparedness in the Istanbul city.

Influence of Rotor Eccentricity on Cogging Torque of 12-slot/10-pole PM Machines with Tooth Bulge

Cogging torque is usually very sensitive to the manufacturing tolerances, especially tooth bulge and rotor eccentricity in the modular permanent magnet (PM) machines. This paper investigates the cogging torque worst-case scenario due to interaction between static/dynamic rotor eccentricity and tooth bulge in the 12-slot/10-pole PM machine. Firstly, the tooth bulge worstcase scenario of the machine is predicted by vector analysis. Secondly, the worst-case scenario due to interaction between static/dynamic rotor eccentricity and tooth bulge is investigated through the finite element analysis, considering different rotor eccentricity ratio and angle. It is found that the interaction between two tolerances has a significant influence on the cogging torque. Under static rotor eccentricity and tooth bulge, cogging torque depends on the eccentricity ratio that decides which tolerance is dominant and the eccentricity angle that decides whether the effect of the non-dominant tolerance is cancelling or strengthening. Specifically, the cogging torque due to both tolerances is weakened when the eccentric rotor is close to the outward tooth, whilst the cogging torque is strengthened when the eccentric rotor is close to the inward tooth. Under dynamic rotor eccentricity and tooth bulge, cogging torque solely depends on the eccentricity ratio.

Analysis and experimental verification of static tilting behaviour of CTC in transformer windings

This paper presents a numerical model and experimental verification of the critical tilting force calculation for transformer winding conductors under static axial pressure. For the purposes of this investigation a structural finite element method model of a non-epoxy bonded continuously transposed conductor used for the construction of transformer windings was developed. The mechanical behaviour of two different transformer winding conductors under static axial pressure was simulated. The radial position of CTCs was varied according to manufacturer tolerances in order to closer correspond to the actual physical models. The displacements, stresses and strains obtained from the simulation are presented and analysed. This calculation is compared to existing analytical and empirical calculations in the IEC 60076-5:2006 and available literature. The results of these calculations were experimentally checked by pressing three physical winding models in a hydraulic press with the force corresponding to calculated critical tilting force and above. The resulting deformations of the winding conductors were photographed and compared to the results of the simulations.

Multibranch Machine Learning-Assisted Optimization and Its Application to Antenna Design

To satisfy certain requirements for an antenna design, many full-wave electromagnetic (EM) simulations are required, and they involve a considerable computational burden. A multibranch machine learning-assisted optimization (MB-MLAO) method is proposed to dramatically reduce the computational complexity in this task. Then, this method is applied to antenna design and worst case performance (WCP) searching under a practical manufacturing tolerance. In the conventional Gaussian process regression (GPR)-based MLAO method, a lower confidence bound (LCB) prescreening strategy with an empirical LCB constant is used to weigh the predicted value and predicted uncertainty. Using a variable-fidelity machine learning method, an adaptive LCB variable, and a retraining and repredicting method, the proposed MB-MLAO method can strike a delicate balance between exploitation and exploration in searching. Moreover, variable-fidelity data from full-wave EM simulations are used in the multifidelity GPR machine learning method to further reduce the computational burden. Finally, two test functions and three types of antennas are selected as examples to illustrate the superiority of the proposed MB-MLAO method.

Demonstration of a Wideband and Compact Input–Output Coupling Structure for Subterahertz Sheet-Beam Traveling Wave Amplifiers

A novel methodology for the beam-wave division/combination in a sheet beam traveling wave amplifier (SB-TWT) is proposed. The design, microfabrication, and measurement of an <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">H</i> -band (220–325 GHz) input–output coupling structures, which originates from an <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">E</i> -plane Riblet coupler with one shorted port, are presented in this article. To experimentally validate the proposed methodology, the designed input–output coupling structure was manufactured by using nanocomputer numerical control milling and measured by using a vector network analyzer. A 3-dB transmission bandwidth of ∼94.0 GHz (231.0–325.0 GHz, 33.8% fractional bandwidth) was measured, over which the measured reflection and isolation coefficients were smaller than –15.3 dB and –11.6 dB, respectively. Compared with other previously reported input–output coupling structures for SB-TWTs, this structure is highlighted by its superior comprehensive performance, including compact geometry, insensitive to the manufacturing tolerance, and good electrical performance over a wide frequency bandwidth, which makes it especially applicable in the terahertz-band operation.

Anthesis and Booting: Two Critical Stages Vulnerable to Water Stress in Wheat (Triticum aestivum L.) With Respect to Yield Production

Six spring bread wheat varieties (AAS-11, BARS-09, Dharabi-11, Faisalabad-08, Chakwal-50 and Fatehjang-2016) and 4 elite lines of wheat (10FJ01, 12FJ26, 12FJ01 and 11FJS309) were analyzed with respect to water stress by providing them two types of treatments i.e., control (no stress) and strained treatment (20 days of stoppage of irrigation at booting and further 20 days of drought after anthesis) at Barani Agricultural Research Station, Fatehjang during 2017-18. Results of this study exhibited highly significant variations prevailed in all the wheat genotypes by viewing their mean performance with respect of all physiological and yield traits. AAS-11, Fatehjang-2016 and Dharabi-11 exhibited their best performance and pointed out elevated mean productivity (MP), stress tolerance index (STI), relative water content (RWC) and geometric mean productivity (GMP). Moreover, stress susceptibility index (SSI) and tolerance (TOL) was anticipated at lowest among the above-mentioned wheat varieties and lines. Based multivariate analysis (biplot) and dendrogram studies; AAS-11, Fatehjang-2016 and Dharabi-11 are most suitable wheat cultivars for drought tolerance at booting and anthesis stage. MP, STI, RWC, GMP, SSI and TOL are renowned to be favourable gauges for identification of drought tolerance wheat ideotype. Likewise, same wheat varieties also exhibited higher grain yield per plant that put them in higher ranked genotypes for making selections and recombination while improving wheat through breeding for drought resistant.

Research on the performance of foil thrust bearings under dynamic disturbances

The runner motions in a foil thrust bearing system typically consist of axial pulsations and angular wobbles as a result of manufacturing and assembly tolerances. By considering the disturbances caused by the runner, this paper established a dynamic model of a foil thrust bearing that has an angular swinging bearing pad. The influence of angular disturbance on the load-carrying capacity (LCC) of the bearing was theoretically and experimentally studied. It was found that the LCC of the bearing under angular disturbances can be enhanced by introducing a proper angular tracking ability. In this paper, the LCC of the bearing was increased by approximately 50% with the angular tracking ability provided by the swinging bearing pad.

Optimization of an induction motor for loss reduction considering manufacturing tolerances

Optimization of an induction motor for loss reduction considering manufacturing tolerances