Efficiency Calibration Research Articles

A flexible and efficient calibration method for discrete element simulations of additive manufacturing in construction

Extrusion-based 3D concrete printing (E3DCP), as one of the most advanced Additive Manufacturing processes, is a hotspot in the construction industry. Using the Discrete Element Method (DEM), the E3DCP can be investigated with reduced prototyping- and trial costs. However, DEM parameter calibration is challenging in the accurate simulation of construction materials because they are hardly typical granular matters. In addition, the introduction of a novel extrusion-based process Near-Nozzle-Mixing calls for a more flexible, efficient, and reliable calibration procedure due to the useable wide variety of material models.In this study, DEM simulation parameters of mortar and its components (e.g. Poraver® and paste) were thoroughly calibrated based on the central composite design method. Notably, the specific shape indices of related substrates were identified in the study to achieve the precise calibration of Poraver® and paste. Moreover, the European standard-based Haegermann flow table test was applied in the calibration by quantifying mortar consistency. This work provides a holistic and efficient calibration approach for three typical and physically different construction materials, which can be universally explored in the DEM simulation of most materials in E3DCP.

Characterization of Gamma Spectroscopy Setup, Efficiency Calibration of HPGe detector used for Radiological substances

Background: Contamination of radiological substances in environment is one of the most important factors and harmful for living beings if the activity is high enough with long half-life.‘Gamma Spectrometry Setup’ is comparatively better for detection and analysis of gamma radiations in any type of specimens. Initiating the data acquisition setup, it’s essential to calibrate the entire setup for accuracy measurement. Materials and Methods:The main purpose of the research work is to characterize the data acquisition setup using137Cs and 60Co point sources. 137Cs emits γ-rays of 661.66 keV and 60Coemits two different γ-rays; 1173.2 KeV & 1332.5 KeV. Setup standardization is an essential part of any research works. Results: The HPGe detector used with the setup is also good enough for γ-energy detection. Detector efficiency calibration is another major task needed for activity calculation, using gamma energy lines detected in a sample detector efficiency can be calculated. Conclusion: Initiating every research experiment, the setup calibration should be checked for accurate results

Research on metal surface specular removal algorithm based on unsupervised learning

The highlights on the surface of metal materials can seriously destroy the continuity of the image, produce certain false edges, and cause the texture details in the highlights area to weaken or even disappear, which interferes with the subsequent operations such as surface region segmentation and defect detection. Aiming at the low efficiency, high loss, easy distortion and difficult calibration of metal highlight data, an unsupervised perceptual enhancement network model based on the convolutional neural network (CNN) is proposed. Firstly, the method of generating antagonism is used to generate a large number of metal images with high-light feature information, which is used to increase the number of high-light metal image data sets in the training set. Secondly, a detail enhance model(DEM) and a color enhance model(CEM) are introduced into the context aggregation network to improve the feature detail retention rate in the low resolution weight graphs. Finally, the multi-scale structural similarity function is used to replace the original structural similarity function to solve the insensitive detail when the image size is too large. Experiments show that comparing with other multi-exposure image fusion models, the present model can improve the evaluation index of mutual information and average gradient of fused images by about 10%, and can retain more texture feature information.

An Efficient Temperature Calibration Method Based on the Improved Infrared Forward Model and Bayesian Inference

An Efficient Temperature Calibration Method Based on the Improved Infrared Forward Model and Bayesian Inference

A practical approach for calibration of MMW MIMO near-field imaging

Near-field millimeter-wave (MMW) imaging techniques typically employ multiple-input-multiple-output (MIMO) arrays to obtain high-resolution images. However, the image quality can be seriously affected by array miscalibration. In this paper, a simple and efficient calibration method for MMW MIMO arrays is proposed and validated with real data. The approach makes use of a metal plate as a reference target to collect data in the presence and absence of the reference target. By processing the two sets of received data, we can reduce the effects of inter-channel coupling and environmental interference. The method calculates the reflected position and transmission distance of the electromagnetic wave based on the transmission model of the electromagnetic wave by the metal plate. And the transmission distance difference of all transceiver pairs is eliminated. Then, the delay error and phase error between the channels are successively calculated. Numerical simulations and real measured data are processed to validate the proposed calibration method. The results demonstrate that it is an effective tool for calibrating MMW MIMO arrays.

Calibration HPGe detector using IAEA-U source for CBRNe

Detecting and preventing the illicit movement of radioactive materials within a country is crucial, requiring the identification of radiologic anomalies against the normal radiation background. High-purity germanium (HPGe) detectors, known for their precision and sensitivity, have become popular for analyzing radioactive materials in CBRNe scenarios. This study focused on calibrating an HPGe detector for CBRNe applications, using gamma-ray spectra from an IAEA-U reference source. Energy calibration involved identifying peaks in the spectra and creating a calibration curve for energy and channel number data. Efficiency calibration, determined using the known activity of the source, revealed a linear relationship between energy and detector response. Over four years, systematic efficiency calibrations showed a deviation of only 3% well below the recommended limit of 5%. These findings underscore the reliability of the system as a reference spectrometry method for accurate detection of radioactive materials. Graphical abstract

Synergistic Biophysics and Machine Learning Modeling to Rapidly Predict Cardiac Growth Probability.

Computational models that can predict growth and remodeling of the heart could have important clinical applications. However, the time it takes to calibrate and run current models while considering data uncertainty and variability makes them impractical for routine clinical use. This study aims to address this need by creating a computational framework to efficiently predict cardiac growth probability. We utilized a biophysics model to rapidly simulate cardiac growth following mitral valve regurgitation (MVR). Here we developed a two-tiered Bayesian History Matching approach augmented with Gaussian process emulators for efficient calibration of model parameters to align with growth outcomes within a 95% confidence interval. We first generated a synthetic data set to assess the accuracy of our framework, and the effect of changes in data uncertainty on growth predictions. We then calibrated our model to match baseline and chronic canine MVR data and used an independent data set to successfully validate the ability of our calibrated model to accurately predict cardiac growth probability. The combined biophysics and machine learning modeling framework we proposed in this study can be easily translated to predict patient-specific cardiac growth.

Implicit calibration method for underwater stereo cameras.

Underwater stereo cameras can effectively capture intricate environments with restricted accessibility, offering an appealing solution for precise perception. Stereo imaging is however susceptible to distortions caused by the refraction of incoming rays. These distortions are nonlinear and challenge the standard single viewpoint projection assumption. In this paper, we propose a data-driven implicit calibration method for underwater stereo cameras. To address the imaging characteristics and aberration distributions across different coordinates of underwater stereo cameras, we have developed the corresponding coordinates regression network and fusion strategy, thereby converting the calibration process into network-based learning. Secondly, we designed an underwater self-luminous calibration target system and the underwater corner point extraction strategy for sample dataset acquisition. We evaluated the proposed method comprehensively in terms of measurement, camera posture estimation, and 3D reconstruction, and compared it with other explicit calibration methods. The experimental results show that the proposed implicit calibration method is superior to other explicit calibration. We demonstrate with real experiments that our method enables efficient camera calibration for underwater vision applications.

Study of a method for theoretical calculation of the efficiency of a LaBr3(Ce) for detecting gamma-rays from point sources

A theoretical model for calculating the full-energy peak efficiency of scintillator detector is proposed in this paper. The effective penetration distance of gamma-rays in Ø3.81cm × 3.81 cm LaBr3(Ce) crystal, aluminum shell and MgO reflector is analyzed. The calculation model for point source detection efficiency is derived, and the attenuation of gamma-rays in the detector shell is computed by theoretical calculation method. This method is used to calculate the efficiency of LaBr3(Ce) with a size of Ø3.81 × 3.81 cm for detecting gamma-rays from point sources of 137Cs and 60Co located in different positions. Compared with experimental data and Monte Carlo (MC) simulation results, the maximum relative deviation is less than 5%. The attenuation of gamma-rays with an energy of 60 keV is more than 50%. The fitted efficiency calibration curve in the energy range of 60 keV–1500 keV is in good agreement with the simulation results. The results show that this method is suitable for calculating the efficiency of the LaBr3(Ce) detector using point sources, especially for analyzing low-energy gamma ray sources. By taking into account the attenuation of the gamma-rays by the detector shell, the measurement accuracy can be effectively improved. The proposed method can be extended for the efficiency calibration of scintillator detectors with various shapes and provides a new approach for 'source-less' efficiency calibration of detectors.

Low Costs Electrical Calibration System of SLM with the Uncertainty Measurements Compared with Primary System Platform Brūel & Kjær type 3630

Sound level meter (SLM) calibration according to IEC61672-1, 2, 3: 2013 is an essential step in the measurement process. It ensures that the SLM meets its specifications. There is a strong need for an efficient and cheap calibration system device for the electrical calibration of SLM since it avoids the body effect and angle sensitivity of the microphone membrane to the sound incidence angle for free field calibration. As well as, it avoids leakage errors due to the microphone fitting in the coupler and the coupler effect in pressure field calibration. This work gives an alternative system device used in the electrical calibration of SLM. This system consists of individual tools; PULSE signal generator, universal frequency counter, HP Dynamic signal analyzer, and DMM voltmeter. All system tools are complying with the IEC17025. The calibration procedures follow the second edition of IEC61672-2. Calibration measurements of frequency, time-weightings, and linearity of range parameters as the major features of SLMs are tested in the frequency range of 31.5 Hz to 16 k Hz. The calibration was repeated 5 times on different days and different warm-up times for devices to estimate the associated uncertainty measurement values in accordance with Part 2 and Part 3 of IEC 61672. The obtained results show that, the calibration measurement deviations are in the allowable tolerance of the IEC 61672-1 and they are comparable with that obtained from the primary Brüel & Kjær (B & K) platform 3630. The computed uncertainty of measurements is in accepted limits that are required by IEC 61672-1 which is determined to the level of confidence of 95%, using coverage factor 2.

Sensitivity analysis of hydraulic erosion and calibration of the erosion coefficient

Hydraulic erosion may pose a threat to the safety and sustainability of geo-related infrastructure, yet quantifying the intricate process of hydraulic erosion still poses a significant scientific and technical challenge. One important step in meeting this challenge is the formulation of a hydraulic erosion model with the erosion coefficient as a central controlling parameter. Calibration of the erosion coefficient (or rate) remains one of the main obstacles to improving predictive modelling, particularly in scenarios lacking long-term laboratory test data. In this study, sensitivity analysis of the key erosion indicators on the parameters controlling hydraulic erosion is conducted. A novel calibration method for the erosion coefficient is presented based on sensitivity analysis. After validating against simulation results and laboratory test findings, the proposed calibration method is applied to a hypothetical long-term hydraulic erosion case. The results show that the maximum hydraulic erosion time is sensitive to all considered parameters (erosion coefficient, initial fraction of fluidized solid particle, initial porosity and maximum porosity), while the erosion curve shape is only sensitive to the initial porosity and the maximum porosity. The validation by existing simulation results shows that the proposed calibration method is robust and internally consistent. The validation by experimental results indicates that the proposed calibration method also has high external validity. Finally, the proposed calibration method is applied to hypothetical long-term erosion in a grouted area. The results show that the hydraulic erosion effect in the grouted area becomes increasingly severe over time. This study contributes toward a more efficient calibration of the erosion coefficient, especially for scenarios in the absence of testing porosity evolution data. The research outcome provides a theoretical foundation for the safety assessment and sustainability analysis of geotechnical structures that are subject to hydraulic erosion.

Stability analysis of layered circular rock tunnels considering anchor reinforcement based on an enhanced mesh-free method

The impact of geotechnical structure and support construction on the stability of a layered circular rock tunnel was investigated based on an improved mesh-free method. The Smoothed Particle Hydrodynamics (SPH) was improved by incorporating a total bridge broken strategy into the kernel function and was validated through analysis of the mechanical behavior in circular opening problem and uniaxial compression tests. The Particle Domain Search (PDS) method is utilized to create crack pathways and implement anchor reinforcement in specific areas without the requirement for grid division. An SPH model of the Muzhailing tunnel was established to investigate the stability of the surrounding rock considering different anchor lengths and spacing. The result indicated that the enhanced SPH method provides a feasible approach for the rapid assessment of tunnel convergence displacement and damage coefficients. Furthermore, this method was validated through laboratory experiments and analytical solutions. For layered tunnels with other different dip angles, this approach offers a general optimization strategy for anchor reinforcing surrounding rock. These findings suggest that the enhanced mesh-free method, owing to its characteristics of efficient parameter calibration and computation, can be further expanded to the rapid assessment of the stability of layered slopes and foundations considering anchor reinforcement.

Detection efficiency measurement of an up-conversion single-photon detector at 3.39μm based on SPDC.

Up-conversion single-photon detector (UCSPD) is promising in weak light radiometry at mid-infrared spectrum. This paper proposed a method to measure the detection efficiency of UCSPD at 3.39μm based on the visible-infrared correlated photons generated by spontaneous parametric down-conversion (SPDC). No infrared standard light source or standard detector was used in measurement and calibration result was insensitive to ambient thermal radiation. An experimental facility was established to obtained a detection efficiency of 0.0085 with a relative uncertainty of 2.8% (k = 1). Factors affecting measuring uncertainty were analyzed and corrected. Bandwidth matching between trigger channel and channel under test is a key problem in detection efficiency calibration. By measuring the bandwidth of the trigger channel and analyzing the bandwidth of the optical elements in the channel under test, we confirm that the acceptance bandwidth of up-conversion crystal is the narrowest. The two channels meet the bandwidth matching conditions, and the detection efficiency can be obtained directly without the bandwidth correction algorithm. Measured detection efficiency agreed well with the result obtained by a continuous laser measurement facility within a difference about 4.7%.

A closed-loop calibration method for serial robots based on position constraints and local area measurement

This paper presents a cost-effective and efficient closed-loop calibration method to enhance the absolute positioning accuracy of industrial robots. The method utilizes an economical and highly accurate set of simple measurement devices, including a device mounted on the robot's end effector and a spherical constraint device positioned within the robot's workspace. A novel local area measurement method is employed for the spherical constraint device, effectively converting position errors into the errors in the sphere center position of the constraint device. Furthermore, the error model considers both kinematic parameter deviations of the robot itself as well as those of the measurement device, along with non-kinematic errors caused by link self-weight. The closed-loop calibration model relies on position constraints, enabling identification and compensation of all error parameters using Levenberg Marquardt method after substituting measured data. The effectiveness of this proposed method is demonstrated through simulation and experimentation. In simulations, average position error reduces from 8.249 mm to 0.8384 mm, while absolute mean difference in sphere center positions obtained using our measurement equipment decreases from 1.206 mm to 0.1027 mm. Significant reductions in both position error and difference in sphere center position are indicated after calibration. This proves that the absolute mean value of the sphere center position difference can be used as the basis for judging the size of the robot's end position error. Experimental results show that absolute mean difference in sphere center position decreases from 0.4319 mm to 0.02869 mm, leading to substantial improvement in overall positioning accuracy.

Sequence-agnostic motion-correction leveraging efficiently calibrated Pilot Tone signals.

This study leverages externally generated Pilot Tone (PT) signals to perform motion-corrected brain MRI for sequences with arbitrary k-space sampling and image contrast. PT signals are promising external motion sensors due to their cost-effectiveness, easy workflow, and consistent performance across contrasts and sampling patterns. However, they lack robust calibration pipelines. This work calibrates PT signal to rigid motion parameters acquired during short blocks (˜4 s) of motion calibration (MC) acquisitions, which are short enough to unobstructively fit between acquisitions. MC acquisitions leverage self-navigated trajectories that enable state-of-the-art motion estimation methods for efficient calibration. To capture the range of patient motion occurring throughout the examination, distributed motion calibration (DMC) uses data acquired from MC scans distributed across the entire examination. After calibration, PT is used to retrospectively motion-correct sequences with arbitrary k-space sampling and image contrast. Additionally, a data-driven calibration refinement is proposed to tailor calibration models to individual acquisitions. In vivo experiments involving 12 healthy volunteers tested the DMC protocol's ability to robustly correct subject motion. The proposed calibration pipeline produces pose parameters consistent with reference values, even when distributing only six of these approximately 4-s MC blocks, resulting in a total acquisition time of 22 s. In vivo motion experiments reveal significant ( ) improved motion correction with increased signal to residual ratio for both MPRAGE and SPACE sequences with standard k-space acquisition, especially when motion is large. Additionally, results highlight the benefits of using a distributed calibration approach. This study presents a framework for performing motion-corrected brain MRI in sequences with arbitrary k-space encoding and contrast, using externally generated PT signals. The DMC protocol is introduced, promoting observation of patient motion occurring throughout the examination and providing a calibration pipeline suitable for clinical deployment. The method's application is demonstrated in standard volumetric MPRAGE and SPACE sequences.

Identification of dominant DEM parameters for multi-component segregation during heap formation, hopper discharge and chute flow

Segregation of granular materials is a critical phenomenon in various industries, such as food processing, pharmaceuticals, and mining. The Discrete Element Method (DEM) is an effective tool for gaining insight into granular segregation by providing particle-level information and the freedom to model mixtures that are often difficult or impossible to achieve through experiments. To ensure realistic material behaviour and correct representation of segregation, it is essential to calibrate the model parameters systematically. However, in the context of multi-component segregation, it is extremely challenging and computationally expensive to consider all parameters in the calibration procedure since interaction parameters between components must also be considered. This work aims to identify the dominant DEM parameters for modelling multi-component segregation during hopper discharge, chute flow and heap formation in a mixture of pellet and sinter. Utilising a representative example of a multi-component mixture with different sizes, densities and shapes used in blast furnaces, the investigation is done for various initial configurations as well as various mass ratios of the mixture. Our findings revealed that, while only particle-geometry interaction parameters dominate the segregation after the hopper and chute flow, particle-particle parameters are also significant for segregation in the heap. We also demonstrated that the downstream segregation is significantly influenced by the segregation upstream. Moreover, we found that the effect of pellet-sinter interactions is negligible. This research provides insights into the dominant DEM parameters, facilitating more efficient and robust calibration of multi-component models in future research endeavours.

Mass dependence of the sensitivity factors in the efficiency calibration of clearance monitors

Context:The radioactivity level of waste materials from the decommissioning of nuclear power plants and particle accelerators must be measured to classify the materials by comparing the obtained activity value with the legal exemption levels set by the regulatory authorities. Clearance monitors (CMs), commonly used for this purpose, require a scenario-dependent efficiency calibration (e.g. efficiency as a function of mass of the material to be measured) using sensitivity factors related to a reference nuclide called the key (or leading) nuclide. In commercial CMs, however, these factors are typically fixed for a given nuclide, regardless of the different measurement scenarios. Objective:The objective of this study was to determine the dependence of the sensitivity factors on the mass of measured material for a specific scenario (copper parts placed inside a stainless steel drum), with the goal of defining a general recommendation on how to select the appropriate sensitivity factor for a given measurement scenario. Approach:Monte Carlo simulations of the CM were performed for this specific scenario to obtain the sensitivity factor for five nuclides (22Na, 133Ba, 137Cs, 152Eu and 232Th) and various geometries. Measurements were carried out with certified sources of those nuclides for four specific geometries to validate the Monte Carlo calculations. Additionally, clearance measurements using the manufacturer-provided sensitivity factors and the factors calculated in this work were compared to determine in which situations one single sensitivity factor could be used for various geometries. Results:The results show that, in case of measurements with the same material but mass varying from 10.0 kg to 40.0 kg, the use of a single sensitivity factor for monoenergetic nuclides (e.g. 137Cs), if not selected properly, leads to an over- or underestimation of the activity level of the measured materials. If overestimation is not an issue, the lowest sensitivity factor can be used for all possible measurement configurations. Otherwise, a situation-dependent sensitivity factor should be estimated and implemented. The use of a single fixed sensitivity factor can be easily justified in the case of nuclides emitting gammas in a wide energy range (e.g. 152Eu), where the dependence of these factors in the studied mass range is small. Significance:These findings facilitate more accurate decisions regarding the calibration of CMs with the aim of classifying waste from the dismantling of nuclear power plants and particle accelerators, with potential logistic and economic implications.

A SGS efficiency calibration method for measuring the radioactive waste drum based on Monte Carlo simulation and function model

A SGS efficiency calibration method for measuring the radioactive waste drum based on Monte Carlo simulation and function model

Efficient and effective calibration of numerical model outputs using hierarchical dynamic models

Efficient and effective calibration of numerical model outputs using hierarchical dynamic models

SenDaL: An Effective and Efficient Calibration Framework of Low-Cost Sensors for Daily Life

SenDaL: An Effective and Efficient Calibration Framework of Low-Cost Sensors for Daily Life