Non-crossing Quantile Regression Neural Network as a Calibration Tool for Ensemble Weather Forecasts

Despite the maturity of ensemble numerical weather prediction(NWP),the resulting forecasts are still,more often than not,under-dispersed.As such,forecast calibration tools have become popular.Among those tools,quantile regression(QR)is highly competitive in terms of both flexibility and predictive performance.Nevertheless,a long-standing problem of QR is quantile crossing,which greatly limits the interpretability of QR-calibrated forecasts.On this point,this study proposes a non-crossing quantile regression neural network(NCQRNN),for calibrating ensemble NWP forecasts into a set of reliable quantile forecasts without crossing.The overarching design principle of NCQRNN is to add on top of the conventional QRNN structure another hidden layer,which imposes a non-decreasing mapping between the combined output from nodes of the last hidden layer to the nodes of the output layer,through a triangular weight matrix with positive entries.The empirical part of the work considers a solar irradiance case study,in which four years of ensemble irradiance forecasts at seven locations,issued by the European Centre for Medium-Range Weather Forecasts,are calibrated via NCQRNN,as well as via an eclectic mix of benchmarking models,ranging from the naïve climatology to the state-of-the-art deep-learning and other non-crossing models.Formal and stringent forecast verification suggests that the forecasts post-processed via NCQRNN attain the maximum sharpness subject to calibration,amongst all competitors.Furthermore,the proposed conception to resolve quantile crossing is remarkably simple yet general,and thus has broad applicability as it can be integrated with many shallow-and deep-learning-based neural networks.

Metagenomic Insight Reveals the Microbial Structure and Function of the Full-Scale Coking Wastewater Treatment System:Gene-Based Nitrogen Removal

Microbial communities play crucial roles in pollutant removal and system stability in biological systems for coking wastewater(CWW)treatment,but a comprehensive understanding of their structure and functions is still lacking.A five month survey of four sequential bioreactors,anoxic 1/oxic 1/anoxic 2/oxic 2(A1/O1/A2/O2),was carried out in a full-scale CWW treatment system in China to elucidate operational performance and microbial ecology.The results showed that A1/O1/A2/O2 had excellent and stable performance for nitrogen removal.Both total nitrogen(TN;(17.38±6.89)mgL1)and ammonium-nitrogen(NH4 t-N;(2.10±1.34)mg·L^(-1))in the final biological effluent satisfied the Chinese national standards for CWW.Integrated analysis of 16S ribosome RNA(rRNA)sequencing and metagenomic sequencing showed that the bacterial communities and metagenomic function profiles of A1 and O1 shared similar functional structures,while those of A2 significantly varied from those of other bioreactors(p<0.05).The results indicated that microbial activity was strongly connected with activated sludge function.Nitrosospira,Nitrosomonas,and SM1A02 were responsible for nitrification during the primary anoxic-oxic(AO)stage and Azoarcus and Thauera acted as important denitrifiers in A2.Nitrogen cycling-related enzymes and genes work in the A1/O1/A2/O2 system.Moreover,the hao genes catalyzing hydroxylamine dehydrogenase(EC 1.7.2.6)and the napA and napB genes catalyzing nitrate reductase(EC 1.9.6.1)played important roles in the nitrification and denitrification processes in the primary and secondary AO stages,respectively.The mixed liquor suspended solids(MLSS)/total solids(TS),TN removal rate(RR),total organic carbon(TOC)(RR),and NH_(4)^(+)t-N(RR)were the most important environmental factors for regulating the structure of core bacterial genera and nitrogen-cycling genes.Proteobacteria were the potential main participants in nitrogen metabolism in the A1/O1/A2/O2 system for CWW treatment.This study provides an original and comprehensive understanding of the microbial community and functions at the gene level,which is crucial for the efficient and stable operation of the full-scale biological process for CWW treatment.

Resistance of full-scale beams against close-in explosions.Numerical modeling and field tests

This paper explores the performances of a finite element simulation including four concrete models applied to a full-scale reinforced concrete beam subjected to blast loading. Field test data has been used to compare model results for each case. The numerical modelling has been, carried out using the suitable code LS-DYNA. This code integrates blast load routine(CONWEP) for the explosive description and four different material models for the concrete including: Karagozian & Case Concrete, Winfrith, Continuous Surface Cap Model and Riedel-Hiermaier-Thoma models, with concrete meshing based on 10, 15, and 20 mm. Six full-scale beams were tested: four of them used for the initial calibration of the numerical model and two more tests at lower scaled distances. For calibration, field data obtained employing pressure and accelerometers transducers were compared with the results derived from the numerical simulation. Damage surfaces and the shape of rupture in the beams have been used as references for comparison. Influence of the meshing on accelerations has been put in evidence and for some models the shape and size of the damage in the beams produced maximum differences around 15%. In all cases, the variations between material and mesh models are shown and discussed.

Full-Scale Isogeometric Topology Optimization of Cellular Structures Based on Kirchhoff-Love Shells

Cellular thin-shell structures are widely applied in ultralightweight designs due to their high bearing capacity and strength-to-weight ratio.In this paper,a full-scale isogeometric topology optimization(ITO)method based on Kirchhoff-Love shells for designing cellular tshin-shell structures with excellent damage tolerance ability is proposed.This method utilizes high-order continuous nonuniform rational B-splines(NURBS)as basis functions for Kirchhoff-Love shell elements.The geometric and analysis models of thin shells are unified by isogeometric analysis(IGA)to avoid geometric approximation error and improve computational accuracy.The topological configurations of thin-shell structures are described by constructing the effective density field on the controlmesh.Local volume constraints are imposed in the proximity of each control point to obtain bone-like cellular structures.To facilitate numerical implementation,the p-norm function is used to aggregate local volume constraints into an equivalent global constraint.Several numerical examples are provided to demonstrate the effectiveness of the proposed method.After simulation and comparative analysis,the results indicate that the cellular thin-shell structures optimized by the proposed method exhibit great load-carrying behavior and high damage robustness.

A real-time calibration method based on time-to-digital converter for accelerator timing system

The high-intensity heavy-ion accelerator facility(HIAF)is a scientific research facility complex composed of multiple cas-cade accelerators of different types,which pose a scheduling problem for devices distributed over a certain range of 2 km,involving over a hundred devices.The white rabbit,a technology-enhancing Gigabit Ethernet,has shown the capability of scheduling distributed timing devices but still faces the challenge of obtaining real-time synchronization calibration param-eters with high precision.This study presents a calibration system based on a time-to-digital converter implemented on an ARM-based System-on-Chip(SoC).The system consists of four multi-sample delay lines,a bubble-proof encoder,an edge controller for managing data from different channels,and a highly effective calibration module that benefits from the SoC architecture.The performance was evaluated with an average RMS precision of 5.51 ps by measuring the time intervals from 0 to 24,000 ps with 120,000 data for every test.The design presented in this study refines the calibration precision of the HIAF timing system.This eliminates the errors caused by manual calibration without efficiency loss and provides data support for fault diagnosis.It can also be easily tailored or ported to other devices for specific applications and provides more space for developing timing systems for particle accelerators,such as white rabbits on HIAF.

Wavelength calibration and spectral analysis of vacuum ultraviolet spectroscopy in EAST

A vacuum ultraviolet(VUV)spectroscopy with a focal length of 1 m has been engineered specifically for observing edge impurity emissions in Experimental Advanced Superconducting Tokamak(EAST).In this study,wavelength calibration for the VUV spectroscopy is achieved utilizing a zinc lamp.The grating angle and charge-coupled device(CCD)position are carefully calibrated for different wavelength positions.The wavelength calibration of the VUV spectroscopy is crucial for improving the accuracy of impurity spectral data,and is required to identify more impurity spectral lines for impurity transport research.Impurity spectra of EAST plasmas have also been obtained in the wavelength range of 50–300 nm with relatively high spectral resolution.It is found that the impurity emissions in the edge region are still dominated by low-Z impurities,such as carbon,oxygen,and nitrogen,albeit with the application of fulltungsten divertors on the EAST tokamak.

A Weakly-Supervised Crowd Density Estimation Method Based on Two-Stage Linear Feature Calibration

In a crowd density estimation dataset,the annotation of crowd locations is an extremely laborious task,and they are not taken into the evaluation metrics.In this paper,we aim to reduce the annotation cost of crowd datasets,and propose a crowd density estimation method based on weakly-supervised learning,in the absence of crowd position supervision information,which directly reduces the number of crowds by using the number of pedestrians in the image as the supervised information.For this purpose,we design a new training method,which exploits the correlation between global and local image features by incremental learning to train the network.Specifically,we design a parent-child network(PC-Net)focusing on the global and local image respectively,and propose a linear feature calibration structure to train the PC-Net simultaneously,and the child network learns feature transfer factors and feature bias weights,and uses the transfer factors and bias weights to linearly feature calibrate the features extracted from the Parent network,to improve the convergence of the network by using local features hidden in the crowd images.In addition,we use the pyramid vision transformer as the backbone of the PC-Net to extract crowd features at different levels,and design a global-local feature loss function(L2).We combine it with a crowd counting loss(LC)to enhance the sensitivity of the network to crowd features during the training process,which effectively improves the accuracy of crowd density estimation.The experimental results show that the PC-Net significantly reduces the gap between fullysupervised and weakly-supervised crowd density estimation,and outperforms the comparison methods on five datasets of Shanghai Tech Part A,ShanghaiTech Part B,UCF_CC_50,UCF_QNRF and JHU-CROWD++.

A new calibration method for radon detector in seismic systems

Radon observation is an important measurement item of seismic precursor network observation.The radon detector calibration is a key technical link for ensuring radon observation accuracy.At present,the radon detector calibration in seismic systems in China is faced with a series of bottleneck problems,such as aging and scrap,acquisition difficulties,high supervision costs,and transportation limitations of radon sources.As a result,a large number of radon detectors cannot be accurately calibrated regularly,seriously affecting the accuracy and reliability of radon observation data in China.To solve this problem,a new calibration method for radon detectors was established.The advantage of this method is that the dangerous radioactive substance,i.e.,the radon source,can be avoided,but only“standard instruments”and water samples with certain dissolved radon concentrations can be used to realize radon detector calibration.This method avoids the risk of radioactive leakage and solves the current widespread difficulties and bottleneck of radon detector calibration in seismic systems in China.The comparison experiment with the traditional calibration method shows that the error of the calibration coefficient obtained by the new method is less than 5%compared with that by the traditional method,which meets the requirements of seismic observation systems,confirming the reliability of the new method.This new method can completely replace the traditional calibration method of using a radon source in seismic systems.

Behavior of transporting pipeline sections without and with hydrogen exposure based on full-scale tests

Pipeline transport of hydrogen is one of today’s economic and environmental challenges.In order to find safe and reliable application of both existing gas and build new pipelines,it is essential to carry out tests on full-scale pipeline section,including the potentially more dangerous places than the main pipe,the girth welds.For the investigations,pipeline sections of P355NH steel with girth welds were prepared and exposed to pure hydrogen at twice the maximum allowable operating pressure for 41 days.Subsequently,full-scale burst tests were carried out and specimens were cut and prepared from the typical locations of the failed pipeline sections for mechanical,and macro-and microstructural investigations.The results obtained were evaluated and compared with data from previous full-scale tests on pipeline sections without hydrogen exposure.The results showed differences in the behavior of pipeline sections loaded in different ways,with different characteristics of the materials and the welded joints,both in the cases without hydrogen exposure and in the cases exposed to hydrogen.

Kinematic calibration under the expectation maximization framework for exoskeletal inertial motion capture system

This study presents a kinematic calibration method for exoskeletal inertial motion capture (EI-MoCap) system with considering the random colored noise such as gyroscopic drift.In this method, the geometric parameters are calibrated by the traditional calibration method at first. Then, in order to calibrate the parameters affected by the random colored noise, the expectation maximization (EM) algorithm is introduced. Through the use of geometric parameters calibrated by the traditional calibration method, the iterations under the EM framework are decreased and the efficiency of the proposed method on embedded system is improved. The performance of the proposed kinematic calibration method is compared to the traditional calibration method. Furthermore, the feasibility of the proposed method is verified on the EI-MoCap system. The simulation and experiment demonstrate that the motion capture precision is significantly improved by 16.79%and 7.16%respectively in comparison to the traditional calibration method.

Calibration of CO and CO2 Monitors Used in Periodic Inspection of Vehicles at Fixed Stations for Environmental Control

Global efforts for environmental cleanliness through the control of gaseous emissions from vehicles are gaining momentum and attracting increasing attention. Calibration plays a crucial role in these efforts by ensuring the quantitative assessment of emissions for informed decisions on environmental treatments. This paper describes a method for the calibration of CO/CO2 monitors used for periodic inspections of vehicles in cites. The calibration was performed in the selected ranges: 900 - 12,000 µmol/mol for CO and 2000 - 20,000 µmol/mol for CO2. The traceability of the measurement results to the SI units was ensured by using certified reference materials from CO/N2 and CO2/N2 primary gas mixtures. The method performance was evaluated by assessing its linearity, accuracy, precision, bias, and uncertainty of the calibration results. The calibration data exhibited a strong linear trend with R² values close to 1, indicating an excellent fit between the measured values and the calibration lines. Precision, expressed as relative standard deviation (%RSD), ranged from 0.48 to 4.56% for CO and from 0.97 to 3.53% for CO2, staying well below the 5% threshold for reporting results at a 95% confidence level. Accuracy measured as percent recovery, was consistently high (≥ 99.1%) for CO and ranged from 84.90% to 101.54% across the calibration range for CO2. In addition, the method exhibited minimal bias for both CO and CO2 calibrations and thus provided a reliable and accurate approach for calibrating CO/CO2 monitors used in vehicle inspections. Thus, it ensures the effectiveness of exhaust emission control for better environment.

Parameter calibration of the tensile-shear interactive damage constitutive model for sandstone failure

The tensile-shear interactive damage(TSID)model is a novel and powerful constitutive model for rock-like materials.This study proposes a methodology to calibrate the TSID model parameters to simulate sandstone.The basic parameters of sandstone are determined through a series of static and dynamic tests,including uniaxial compression,Brazilian disc,triaxial compression under varying confining pressures,hydrostatic compression,and dynamic compression and tensile tests with a split Hopkinson pressure bar.Based on the sandstone test results from this study and previous research,a step-by-step procedure for parameter calibration is outlined,which accounts for the categories of the strength surface,equation of state(EOS),strain rate effect,and damage.The calibrated parameters are verified through numerical tests that correspond to the experimental loading conditions.Consistency between numerical results and experimental data indicates the precision and reliability of the calibrated parameters.The methodology presented in this study is scientifically sound,straightforward,and essential for improving the TSID model.Furthermore,it has the potential to contribute to other rock constitutive models,particularly new user-defined models.

Global Calibration Method for Monocular Multi-View System Using Rotational Dual-Target

To make the problems of existing high requirements of calibration tools, complex global calibration process addressed for monocular multi-view visual measurement system during measurement, in the paper, a global calibration method is proposed for the geometric properties of rotational correlation motion and the absolute orientation of the field of view without over lap. Firstly, a dual-camera system is constructed for photographing and collecting the rotating image sequence of two flat targets rigidly connected by a long rod at different positions, and based on the known parameters, such as, target feature image, world coordinates, camera internal parameters and so on, then the global PnP optimization method is used to solve the rotation axis and the reference point at different positions;Then, the absolute orientation matrix is constructed based on the parameters of rotation axis, reference point and connecting rod length obtained by this method. In the end, the singular value decomposition method is used to find the optimal rotation matrix, and then get the translation matrix. It’s shown based on simulation and actual tests that in comparison with the existing methods, the maximum attitude and pose errors is 0.0083˚ and 0.3657 mm, respectively, which improves the accuracy by 27.8% and 24.4%, respectively. The calibration device in this paper is simple, and there are no parallel, vertical and coplanar requirements between multiple rotating positions. At the same time, in view of the calibration accuracy, the accuracy requirements of most application scenarios can be met.

Full-Scale Numerical Simulation of the Local Scour Under Combined Current and Wave Conditions Based on Field Data

The monopile is the most common foundation to support offshore wind turbines.In the marine environment,local scour due to combined currents and waves is a significant issue that must be considered in the design of wind turbine foundations.In this paper,a full-scale numerical model was developed and validated based on field data from Rudong,China.The scour development around monopiles was investigated,and the effects of waves and the Reynolds number Re were analyzed.Several formulas for predicting the scour depth in the literature have been evaluated.It is found that waves can accelerate scour development even if the KC number is small(0.78<KC<1.57).The formula obtained from small-scale model tests may be unsafe or wasteful when it is applied in practical design due to the scale effect.A new equation for predicting the scour depth based on the average pile Reynolds number(Rea)is proposed and validated with field data.The equilibrium scour depth predicted using the proposed equation is evaluated and compared with those from nine equations in the literature.It is demonstrated that the values predicted from the proposed equation and from the S/M(Sheppard/Melville)equation are closer to the field data.

On the calibration and verification of Voronoi-based discontinuous deformation analysis for modeling rock fracture

Since its introduction,discontinuous deformation analysis(DDA)has been widely used in different areas of rock mechanics.By dividing large blocks into subblocks and introducing artificial joints,DDA can be applied to rock fracture simulation.However,parameter calibration,a fundamental issue in discontinuum methods,has not received enough attention in DDA.In this study,the parameter calibration of DDA for intact rock is carefully studied.To this end,a subblock DDA with Voronoi tessellation is presented first.Then,a modified contact constitutive law is introduced,in which the tensile and shear meso-strengths are modified to be independent of the bond lengths.This improvement can prevent the unjustified preferential failure of short edges.A method for imposing confining pressure is also introduced.Thereafter,sensitivity analysis is performed to investigate the influence of the calculated parameters and meso-parameters on the mechanical properties of modeled rock.Based on the sensitivity analysis,a unified calibration procedure is suggested for both cases with and without confining pressure.Finally,the calibration procedure is applied to two examples,including a biaxial compression test.The results show that the proposed Voronoi-based DDA can simulate rock fracture with and without confining pressure very well after careful parameter calibration.

A machine learning approach to TCAD model calibration for MOSFET

Machine learning-based surrogate models have significant advantages in terms of computing efficiency. In this paper, we present a pilot study on fast calibration using machine learning techniques. Technology computer-aided design(TCAD) is a powerful simulation tool for electronic devices. This simulation tool has been widely used in the research of radiation effects.However, calibration of TCAD models is time-consuming. In this study, we introduce a fast calibration approach for TCAD model calibration of metal–oxide–semiconductor field-effect transistors(MOSFETs). This approach utilized a machine learning-based surrogate model that was several orders of magnitude faster than the original TCAD simulation. The desired calibration results were obtained within several seconds. In this study, a fundamental model containing 26 parameters is introduced to represent the typical structure of a MOSFET. Classifications were developed to improve the efficiency of the training sample generation. Feature selection techniques were employed to identify important parameters. A surrogate model consisting of a classifier and a regressor was built. A calibration procedure based on the surrogate model was proposed and tested with three calibration goals. Our work demonstrates the feasibility of machine learning-based fast model calibrations for MOSFET. In addition, this study shows that these machine learning techniques learn patterns and correlations from data instead of employing domain expertise. This indicates that machine learning could be an alternative research approach to complement classical physics-based research.

A Full-Scale Optimization of a Crop Spatial Planting Structure and its Associated Effects

Driven by the concept of agricultural sustainable development,crop planting structure optimization(CPSO)has become an effective measure to reduce regional crop water demand,ensure food security,and protect the environment.However,traditional optimization of crop planting structures often ignores the impact on regional food supply–demand relations and interprovincial food trading.Therefore,using a system analysis concept and taking virtual water output as the connecting point,this study proposes a theoretical CPSO framework based on a multi-aspect and full-scale evaluation index system.To this end,a water footprint(WF)simulation module denoted as soil and water assessment tool–water footprint(SWAT-WF)is constructed to simulate the amount and components of regional crop WFs.A multi-objective spatial CPSO model with the objectives of maximizing the regional economic water productivity(EWP),minimizing the blue water dependency(BWFrate),and minimizing the grey water footprint(GWFgrey)is established to achieve an optimal planting layout.Considering various benefits,a fullscale evaluation index system based on region,province,and country scales is constructed.Through an entropy weight technique for order preference by similarity to an ideal solution(TOPSIS)comprehensive evaluation model,the optimal plan is selected from a variety of CPSO plans.The proposed framework is then verified through a case study of the upper–middle reaches of the Heihe River Basin in Gansu province,China.By combining the theory of virtual water trading with system analysis,the optimal planting structure is found.While sacrificing reasonable regional economic benefits,the optimization of the planting structure significantly improves the regional water resource benefits and ecological benefits at different scales.

Design and development of the deep-rock in-situ condition-preserved coring calibration platform

To systematically validate and calibrate the theory and technology of the deep in-situ conditionpreserved coring, the in-situ conditions at different depths should be simulated, and the full-size coring tests should be carried out in this simulated environment. Therefore, a deep-rock in-situ conditionpreserved coring calibration platform was designed and developed. The self-tightening sealing structure and the quick-disassembly structure were designed on the basis of an innovative segmented nonuniformdiameter structure, which was a breakthrough from the traditional high-pressure vessel frame and was verified by finite element simulation and actual testing under extreme working conditions, respectively.To simulate the actual deep in-situ environment with a temperature of 150℃ and pressure of 140 MPa for a large Φ450 mm×H1400 mm core, temperature and pressure control systems were designed by coupling, and a pre-embedded high-pressure-resistant temperature sensor was designed. Finally, highprecision assembly automation, complex movement coordination of the coring device with the platform,and rotary dynamic sealing were achieved by utilizing the combination of adaptive cabin body servo control and an adaptive mechanical structure in a limited space, laying a solid foundation for the calibration of in-situ condition-preserved coring.

Easy to Calibrate:Marker-Less Calibration of Multiview Azure Kinect

Reconstructing a three-dimensional(3D)environment is an indispensable technique to make augmented reality and augmented virtuality feasible.A Kinect device is an efficient tool for reconstructing 3D environments,and using multiple Kinect devices enables the enhancement of reconstruction density and expansion of virtual spaces.To employ multiple devices simultaneously,Kinect devices need to be calibrated with respect to each other.There are several schemes available that calibrate 3D images generated frommultiple Kinect devices,including themarker detection method.In this study,we introduce a markerless calibration technique for Azure Kinect devices that avoids the drawbacks of marker detection,which directly affects calibration accuracy;it offers superior userfriendliness,efficiency,and accuracy.Further,we applied a joint tracking algorithm to approximate the calibration.Traditional methods require the information of multiple joints for calibration;however,Azure Kinect,the latest version of Kinect,requires the information of only one joint.The obtained result was further refined using the iterative closest point algorithm.We conducted several experimental tests that confirmed the enhanced efficiency and accuracy of the proposed method for multiple Kinect devices when compared to the conventional markerbased calibration.

On-orbit Geometric Calibration and Preliminary Accuracy Evaluation of GF-14 Satellite

GF-14 satellite is a new generation of sub-meter stereo surveying and mapping satellite in China,carrying dual-line array stereo mapping cameras to achieve 1∶10000 scale topographic mapping without Ground Control Points(GCPs).In fact,space-based high-precision mapping without GCPs is a challenging task that depends on the close cooperation of several payloads and links,of which on-orbit geometric calibration is one of the most critical links.In this paper,the on-orbit geometric calibration of the dual-line array cameras of GF-14 satellite was performed using the control points collected in the high-precision digital calibration field,and the calibration parameters of the dual-line array cameras were solved as a whole by alternate iterations of forward and backward intersection.On this basis,the location accuracy of the stereo images using the calibration parameters was preliminarily evaluated by using several test fields around the world.The evaluation result shows that the direct forward intersection accuracy of GF-14 satellite images without GCPs after on-orbit geometric calibration reaches 2.34 meters(RMS)in plane and 1.97 meters(RMS)in elevation.