Calibration Experiments Research Articles

An evaluation of source-blending impact on the calibration of SKA EoR experiments

ABSTRACT Twenty-one-centimetre signals from the Epoch of Reionization (EoR) are expected to be detected in the low-frequency radio window by the next-generation interferometers, particularly the Square Kilometre Array (SKA). However, precision data analysis pipelines are required to minimize the systematics within an infinitesimal error budget. Consequently, there is a growing need to characterize the sources of errors in EoR analysis. In this study, we identify one such error origin, namely source blending, which is introduced by the overlap of objects in the densely populated observing sky under SKA1-Low’s unprecedented sensitivity and resolution, and evaluate its two-fold impact in both the spatial and frequency domains using a novel hybrid evaluation (HEVAL) pipeline combining end-to-end simulation with an analytic method to mimic EoR analysis pipelines. Sky models corrupted by source blending induce small but severe frequency-dependent calibration errors when coupled with astronomical foregrounds, impeding EoR parameter inference with strong additive residuals in the two-dimensional power spectrum space. We report that additive residuals from poor calibration against sky models with blending ratios of 5 and 0.5 per cent significantly contaminate the EoR window. In contrast, the sky model with a 0.05 per cent blending ratio leaves little residual imprint within the EoR window, therefore identifying a blending tolerance at approximately 0.05 per cent. Given that the SKA observing sky is estimated to suffer from an extended level of blending, strategies involving de-blending, frequency-dependent error mitigation, or a combination of both, are required to effectively attenuate the calibration impact of source-blending defects.

Using Iterative Correction to Improve the Accuracy of the Blind-Hole Welding Residual Stress Test.

An iterative correction method for the stress release coefficient, leveraging numerical simulation, has been innovatively developed to address the significant error issues associated with the blind-hole method in high-stress residual stress testing of steel structures. This method effectively reduces measurement error in high residual stress regions through a discriminant iteration process. The finite element analysis technology was employed to accurately simulate the blind-hole method's test process, and additionally, Python was utilized for customizing the secondary development of ABAQUS software, thereby automating and optimizing the method. When compared with simulation and experimental data from the welding process, the efficiency, accuracy, and reliability of the correction method have been verified. The proposed method eliminates the need for tedious calibration experiments inherent in traditional methods, significantly enhancing the test's automation level and convergence speed, and ensuring measurement accuracy, which provides an innovative solution for the accurate evaluation of residual stress in steel structures.

An optimum structural design method for a torque sensor measuring the control moment of the micro flapping-wing robot

Abstract This paper presents an optimum structural design method for a sensor capable of measuring the control torque of the micro flapping-wing robot. Torque measurement in flapping-wing robots has special demands on the sensor bandwidth. The method in this paper focuses on the development of a multi-objective optimization method based on the surrogate model to solve the sensor indicator design issues, for example, increasing sensitivity while meeting bandwidth requirements. Initially, Latin hypercube sampling was applied to the choice of the characteristic parameters of the sensor. Based on finite element techniques, the surrogate models describing displacement and eigenfrequency were established to characterize the sensor indicators, and a multi-objective optimization was conducted. According to the optimization results, the sensor structure was manufactured, and a torque measurement platform was set up. Calibration experiments and frequency response experiments demonstrated a high level of consistency between the surrogate model and the experimental data. With the assistance of the eddy current displacement sensor, the actual displacement sensitivity coefficient of the torque sensor is determined to be 0.4325 mm mNm−1, consistent with the calculation of the surrogate model. The characteristic frequency is 488.5 Hz, with a relative error of 7.47% compared to the surrogate model. This indicates that the optimum structural design method can be utilized for the rapid design of torque sensors for special requirements, thus laying the foundation for the control torque measurement of micro flapping-wing robots.

Optimisation of microstructures from filament extrusion additive manufacturing based on numerical simulation with VOLCO-X

The mechanical properties of parts built with material extrusion additive manufacturing are highly dependent on the material distribution within parts’ microstructure. This varies with the choice of process parameters. Therefore, when designing a functional printed part, one must tailor the printing parameters in order to obtain the desired properties, such as minimal voids. The present work proposes an optimisation method that designs printing parameters to minimise manufacturing time while keeping the void volume fraction at very low values (hence improving mechanical properties), keeping dimensions within tight tolerances and guaranteeing structural integrity. The new optimisation method utilises the authors’ previously developed software VOLCO-X, which is capable of efficiently predicting material distribution from filament extrusion within printed parts, including print track dimensions and microstructure geometry, without the need for any experimental calibration. In order to validate the proposed optimisation scheme, optimised printed parts using the scheme and parts using printing parameters determined by a commercial slicing software were manufactured and compared for different printing speeds and deposition strategies. At printing speed of 16 mm/s, it was possible to decrease the manufacturing time by more than 20% and structural mass by more than 5% in comparison to the commercial slicer printed part, whilst maintaining similar mechanical properties. At printing speed of 96 mm/s, due to the high printing speed, the commercial printed part presented gap faults between deposited strands, while the optimised part had structural integrity. At this printing speed, the optimised printed part presented significant improvements in terms of mechanical properties. The proposed optimisation methodology, in conjunction with VOLCO-X, is a powerful tool that can be used to improve manufacturing by filament extrusion. This innovative tool allows the identification of printing parameters without experiments and trial-and-error approaches, thus saving time and expense.

Research on the measurement mechanism of a six-axis force sensor based on a flexible hinge series–parallel hybrid

Abstract Addressing the common limitations of current six-axis force sensors, including the degradation of strain gauge accuracy due to environmental influences and the necessity for a complete replacement when damaged, this paper proposes an innovative six-axis force sensor that integrates a hybrid serial–parallel structure featuring flexible hinges. The sensor’s bracket is designed using a combination of serial–parallel flexible hinges, which confer load distribution capabilities, are lightweight, have high strength, and facilitate replacement. The static force model and the overall stiffness model of the sensor were developed based on the 3-universal–prismatic–universal parallel mechanism theory, providing a theoretical foundation for evaluating the sensor’s performance. To validate the accuracy of the stiffness model, finite element software is utilized for simulation-based verification. Subsequently, a calibration experiment is performed on the sensor, yielding results that conclusively show an error margin of less than 5% between experimental and theoretical values, satisfying the design criteria for sensor measurement.

External parameter calibration of laser scanner based on the combination of plane-control-based and plane-constraints-based methods

Accurate calibration of the external parameters of a laser scanner is crucial to ensure consistency in data representation from multiple sources. Plane features, known for their simplicity and ease of extraction, are widely used in external parameter calibration. The use of control planes with known plane parameters enables the simultaneous estimation of both translation and rotation parameters, while the use of planes with unknown parameters allows for efficient self-calibration. In this paper, we introduce a novel method that combines the strengths of both types of plane calibration methods to calibrate the external parameters of a laser scanner. The approach, with the help of a Gauss-Helmert adjustment model, integrates control and constraint planes to calibrate the external parameters. The method boasts the ease and accessibility offered by the plane constraint method, utilizing fewer control features while successfully estimating the external parameters of the laser scanner. To evaluate the feasibility of this method, two sets of 12 calibration experiments were conducted on the mobile measurement system platform. Notably, the residual Root Mean Square Errors (RMSE) obtained from these experiments were comparable to those achieved using traditional plane-control-based method. Furthermore, the external parameter correlation aligns with that obtained using the plane-control-based method, while the plane parameter correlation exhibits similarity to that obtained using the plane-constraint-based method. These results confirm that our method effectively minimizes the requirement for control features and enables more convenient calibration of the external parameters of the laser scanner.

Design of nonlinear locking mechanism for shape memory alloy archwire of miniature orthodontic device

The locking mechanism between bracket and shape memory alloy (SMA) archwire in the newly developed domestic orthodontic device is the key to controlling the precise alignment of the teeth. To meet the demand of locking force in clinical treatment, the tightening torque angle of the locking bolt and the required torque magnitude need to be precisely designed. For this purpose, a design study of the locking mechanism is carried out to analyze the correspondence between the tightening torque angle and the locking force and to determine the effective torque value, which involves complex coupling of contact, material and geometric nonlinear characteristics. Firstly, a simulation analysis based on parametric orthogonal experimental design is carried out to determine the SMA hyperelastic material parameters for the experimental data of SMA archwire with three-point bending. Secondly, a two-stage fine finite-element simulation model for bolt tightening and archwire pulling is established, and the nonlinear analysis is converged through the optimization of key contact parameters. Finally, multiple sets of calibration experiments are carried out for three tightening torsion angles. The comparison results between the design analysis and the calibration experiments show that the deviation between the design analysis and the calibration mean value of the locking force in each case is within 10%, and the design analysis method is valid and reliable. The final tightening torque angle for clinical application is determined to be 10° and the rated torque is 2.8 N∙mm. The key data obtained can be used in the design of clinical protocols and subsequent mechanical optimization of novel orthodontic devices, and the research methodology can provide a valuable reference for force analysis of medical devices containing SMA materials.

Photothermal-driven soft actuator capable of alternative control based on coupled-plasmonic effect

Recent advancements in small-scale soft actuators have showcased their ability to respond to various stimuli, making them ideal for biomedical engineering and robotics. Light-responsive actuators constructed from photothermal materials such as carbon-based materials have received great attention for their remote wireless control ability. However, conventional carbon-based actuators typically exhibit uniform responses to different light wavelengths, limiting the complexity of their control. To address this limitation, this study develops light-driven soft actuators utilizing gold nanorods (Au NRs) to enhance selective photo-responsiveness. Au NRs are incorporated given their superior ability to convert light energy into localized heat through localized surface plasmon resonances, with efficiency varying based on their size and the wavelength of incident light. By adjusting the specifications of the Au NRs and the wavelength of the optical field, tunable actuation efficiency can be achieved. Experimental calibration confirms that the actuator exhibits differential performance across various wavelengths, enabling more precise control over its behavior. Demonstrations of application devices highlight the actuator’s versatility in flexible robotics, showcasing its potential for advanced applications. This innovation represents a considerable step towards achieving more adaptable and functional soft robotic systems, paving the way for future developments in this area.

Mechanistic modeling of minute virus of mice surrogate removal by anion exchange chromatography in micro scale

Biopharmaceutical products are often produced in Chinese hamster ovary (CHO) cell cultures that are vulnerable to virus infections. Therefore, it is a regulatory requirement that downstream purification steps for biopharmaceuticals can remove viruses from feedstocks. Anion exchange chromatography (AEX) is one of the downstream unit operations that is most frequently used for this purpose and claimed for its capability to remove viruses. However, the impact of various process parameters on virus removal by AEX is still not fully understood. Mechanistic modeling could be a promising way to approach this gap, as these models require comparatively few experiments for calibration. This makes them a valuable tool to improve understanding of viral clearance, especially since virus spiking studies are costly and time consuming.In this study, we present how the virus clearance of a MVM mock virus particle by Q Sepharose FF resin can be described by mechanistic modeling. A lumped kinetic model was combined with a steric mass action model and calibrated at micro scale using three linear gradient experiments and an incremental step elution gradient. The model was subsequently verified for its capability to predict the effect of different sodium chloride concentrations, as well as residence times, on virus clearance and was in good agreement with the LRVs of the verification runs. Overall, models like this could enhance the mechanistic understanding of viral clearance mechanisms and thereby contribute to the development of more efficient and safer biopharmaceutical downstream processes.

A Novel Soft and Inflatable Strain-based Tactile Sensing Balloon for Enhanced Diagnosis of Colorectal Cancer Polyps Via Colonoscopy.

In this paper, with the goal of addressing the lack of tactile feedback in colorectal cancer (CRC) polyps diagnosis using a colonoscopy procedure, we propose the design and fabrication of a novel soft and inflatable strain-based tactile sensing balloon (SI-STSB). The proposed soft sensor features a unique stretchable sensing layer - that utilizes a liquid metal injected within spiral-shape microchannels of a stretchable substrate - and is integrated with a unique inflatable balloon mechanism. The proposed SI-STSB has been thoroughly characterized through different calibration experiments. Results demonstrate a phenomenal adjustable sensitivity with low hysteresis behavior under different experimental conditions for this sensor making it a great candidate for enhancing the existing diagnosis procedures.

Experimental characterisation and calibration of hyperelastic material models for finite element modelling of timber-glass adhesive connections under shear and tensile loading

Experimental characterisation and calibration of hyperelastic material models for finite element modelling of timber-glass adhesive connections under shear and tensile loading

Bayesian optimization algorithms for accelerator physics

Accelerator physics relies on numerical algorithms to solve optimization problems in online accelerator control and tasks such as experimental design and model calibration in simulations. The effectiveness of optimization algorithms in discovering ideal solutions for complex challenges with limited resources often determines the problem complexity these methods can address. The accelerator physics community has recognized the advantages of Bayesian optimization algorithms, which leverage statistical surrogate models of objective functions to effectively address complex optimization challenges, especially in the presence of noise during accelerator operation and in resource-intensive physics simulations. In this review article, we offer a conceptual overview of applying Bayesian optimization techniques toward solving optimization problems in accelerator physics. We begin by providing a straightforward explanation of the essential components that make up Bayesian optimization techniques. We then give an overview of current and previous work applying and modifying these techniques to solve accelerator physics challenges. Finally, we explore practical implementation strategies for Bayesian optimization algorithms to maximize their performance, enabling users to effectively address complex optimization challenges in real-time beam control and accelerator design. Published by the American Physical Society 2024

Enhancing precision of chromatic confocal measurement through linear interpolation based centroid algorithm

In chromatic confocal measurement (CCM), the accuracy and precision of the results rely on the robustness of the spectral power distribution (SPD) signal resolution. However, traditional centroid algorithms struggle with the inherent discretization of the SPD signal, leading to significant measurement errors. To address this issue, a linear interpolation based centroid algorithm is proposed to improve the robustness of the results. In the precision calibration experiment conducted with the in-house developed chromatic confocal sensors, the proposed algorithm demonstrates good robustness. Moreover, it achieves a 50% enhancement in the accuracy of a 4 mm range, improving from 1 μm to 0.5 μm.

Hydrodynamic force characterization and experiments of underwater piezoelectric flexible structure

The unsteady hydrodynamics of underwater flexible structures internally actuated by smart materials are drawing growing attention. In this study, the dynamic measurement and characterization of hydrodynamic forces acting on flexible structures actuated by macro fiber composites (MFC) are performed. A measurement system composed of a cantilevered transducer and a laser sensor is proposed for dynamically acquiring the induced hydrodynamic force. The parameter indexes of the measurement system are carefully determined to achieve the requirements of high resolution, high sensitivity and good anti-interference of the designed measurement system. Calibration experiments demonstrate the good measuring performances. Then, the relationship between the hydrodynamic force and the actuation frequency is explored using the data obtained from the designed measurement system. Moreover, by decomposing the measured hydrodynamic force, it is found that the added mass component shares similar behaviors with the hydrodynamic force, whereas the hydrodynamic damping component initially increases and then decreases across the explored ranges. Finally, manageable formulas for these components in the forms of hydrodynamic function are developed, and explicit expressions for the Morison’s formula are obtained. These findings are meaningful for the realization of flexible structures with the actuation of smart materials in marine applications.

A new human metabolic rate sensing model optimization and wearable sensor realization

Accurate assessment of metabolic rate is crucial for predicting human thermal comfort. However, many existing instruments are bulky, invasive, and inconvenient. Additionally, wearable metabolic rate measurements have faced long-standing challenges due to a lack of a comprehensive theoretical model with easy-to-measure parameters. This paper optimizes our previously proposed theoretical approach for wearable metabolic rate measurement that incorporates heart rate, whole-body unit heat loss, skin resistance, and body muscle percentage. We have improved the evaluation approach for whole-body unit heat loss by introducing a newly designed convective heat loss coefficient from various body segments. Regarding the wearable sensor design, a heat loss measuring system with serpentine channel was verified as the most suitable design following calibration experiments. We also integrated a modified square-wave-based skin resistance design, resulting in an upgraded integrated metabolic sensor. To validate our sensor and model performance, we conducted experiments with ten subjects of both genders at three temperature conditions (22, 25 and 28 °C) and four levels of activities (rest, tiptoe heel, slight walk, and moderate walk). First, our results demonstrate a strong positive relationship between the metabolic rate obtained by our optimized sensor and Quark CPET instrument, with high coefficients of determination (highest:0.97 from the male group, 0.98 from the female group). Our approach achieved at least 96 % accuracy and less than 2.5 % uncertainty for both groups. Second and increasingly, we found that only one metabolic rate model was required across combined temperature conditions when the person was fixed. Third, the positive relationship was further improved by incorporating whole-body unit heat loss. Finally, we obtained information from different segments on skin temperatures. In summary, our study provides a powerful methodology for predicting and evaluating human metabolic rate through an innovative wearable approach. Our approach and sensor have the potential to substantially contribute to energy-saving efforts in smart buildings.

Mass calibration of Rosetta’s ROSINA/DFMS mass spectrometer

The Double Focusing Mass Spectrometer (DFMS) onboard the Rosetta spacecraft employs an electrostatic and a magnet sector for energy and mass discrimination, resulting in a high mass resolution. A built-in feedback loop uses the measured magnet temperature to compensate for the temperature dependence of the magnet’s field strength. Still, large onboard temperature variations and other effects cause any given mass peak to move over a range of 30 pixels or more on the detector during the mission. The present paper discusses the various factors that contribute to the time variations in the mass calibration relation. A technique is developed to evaluate and correct for these factors. A mass calibration relation that is valid for the DFMS neutral high mass resolution mode measurements throughout the entire mission for the mass range m/z=13–69 is established and its accuracy is evaluated. The 1σ precision turns out to be less than a single pixel, which is excellent as full peak width at half height is about 12 pixels. The proposed approach provides an a posteriori mass calibration and is useful for all magnet-based mass spectrometers where experimental mass calibration by comparison to reference species, temperature stabilization, and/or electrostatic compensation, are not possible or fail to deliver a mass scale precision that is comparable to the mass resolution of the instrument.

Improved MTPA and MTPV Optimal Criteria Analysis Based on IPMSM Nonlinear Flux-Linkage Model

The use of interior permanent-magnet synchronous machines (IPMSMs) is prevalent in automotive and vehicle traction applications due to their high efficiency over a wide speed range. Given the high-power-density requirements of automotive IPMSMs, it is imperative to consider the effect of nonlinearities, such as saturation and cross-coupling, on the motor model. The aforementioned nonlinearities render conventional linear motor models incapable of accurately describing the operating characteristics of the IPMSM, including the maximum torque per ampere (MTPA) trajectory, the flux-weakening (FW) trajectory, and the maximum torque per volt (MTPV) trajectory. With respect to the linear motor model, the nonlinear flux-linkage model is gradually receiving attention from researchers. This modeling method represents the nonlinear behavior of the motor through the direct establishment of a bidirectional mapping relationship between flux-linkage and current. It is capable of naturally incorporating the effects of magnetic saturation and cross-coupling factors. However, the analysis of the current trajectory optimal criteria based on this model has not yet been reported. In this paper, the optimal criteria for the MTPA and MTPV current trajectories are analyzed based on the nonlinear flux-linkage model of IPMSMs. Firstly, the nonlinear flux-linkage model of the tested IPMSM is established by the experimental calibration method. The mathematical analytical expressions of the MTPA and MTPV optimal criteria are then analyzed by constructing and solving optimal problems with different objectives. Finally, the current command table applicable to actual motor control is constructed by calculating the current command for different operating conditions according to the optimal criteria proposed in this paper. The validity and feasibility of the optimal criteria proposed in this paper are verified through experimental tests on different operating conditions.

Effect of Axial Clearance Variation on Dual-Rotor Flowmeter Performance.

This study examines the impact of axial clearance variations on the performance characteristics of a dual-rotor flowmeter (DRT-FM) through numerical simulations, with the validity of the numerical results verified by calibration experiments. The results indicate that within the range of 200 L/h to 1600 L/h, the K factors of different groups increase as clearance increases. The K factor of the 0.80 mm group is the largest, showing an average increase of around 6% compared to that of the 0.50 mm group. Additionally, Linearity E also decreased, with a minimum of 1.07% in the 0.65 mm group, significantly lower than the 3.33% in the 0.50 mm group. Furthermore, the pressure loss increased slightly, with the 0.65 mm group having the largest pressure loss; however, at a flow rate of 1600 L/h, the pressure loss only increases by 0.186 kPa compared to that of the 0.50 mm group. Flow field analysis reveals that changes in axial clearance predominantly affect pressure distribution. Larger clearances reduce low-pressure regions on upstream and downstream transition surfaces, thereby reducing energy loss due to pressure changes. Entropy analysis further demonstrates that higher axial clearance decreases energy loss in the upstream and downstream stationary domains, optimizing the DRT-FM's energy characteristics.

Bolt axial stress measurement method based on ultrasound multi-feature fusion

ABSTRACT There exist issues of ill-adaptability and low-accuracy in ultrasonic bolt stress measurement based on acoustic elasticity and scattering attenuation. Therefore, a bolt axial stress measurement method based on ultrasound multi-feature fusion is proposed in this paper. Firstly, ultrasound characteristic parameters based on the theory of acoustic elasticity are extracted, including the difference of time-of-flight (TOF) and the longitudinal wave attenuation coefficient in polycrystalline materials within the Rayleigh scattering range. Then, following the dimension reduction principle, the difference of TOF, attenuation coefficient, and clamping length are chosen as the input feature vectors for the fusion model. Subsequently, the SVR model is employed to establish a multi-feature fusion model for bolt axial stress measurement. Calibration and measurement experiments are conducted using the constructed experimental platform. Comparative analysis between the traditional measurement methods and the proposed method reveals that the SVR model can adapt to measurements of bolts with different lengths, overcoming the limitations of traditional methods. Furthermore, the measurement results of different fusion algorithms show that SVR yields significantly lower average relative errors in the measurement of the three bolts (3.35%, 4.44%, and 4.48%) compared to BP and RBF algorithms. This indicates higher measurement accuracy and immunity to low-stress effects.

Toward on-demand measurements of greenhouse gas emissions using an uncrewed aircraft AirCore system

Abstract. This paper evaluates the performance of a multirotor uncrewed aircraft and AirCore system (UAAS) for measuring vertical profiles of wind velocity (speed and direction) and the mole fractions of methane (CH4) and carbon dioxide (CO2), and it presents a use case that combines UAAS measurements and dispersion modeling to quantify CH4 emissions from a dairy farm. To evaluate the atmospheric sensing performance of the UAAS, four field deployments were performed at three locations in the San Joaquin Valley of California where CH4 hotspots were observed downwind of dairy farms. A comparison of the observations collected on board the UAAS and an 11 m meteorological tower show that the UAAS can measure wind velocity trends with a root mean squared error varying between 0.4 and 1.1 m s−1 when the wind magnitude is less than 3.5 m s−1. Findings from UAAS flight deployments and a calibration experiment also show that the UAAS can reliably resolve temporal variations in the mole fractions of CH4 and CO2 occurring over periods of 10 s or longer. Results from the UAAS and dispersion modeling use case further demonstrate that UAASs have great potential as low-cost tools for detecting and quantifying CH4 emissions in near real time.