Evaluating the contribution of satellite measurements to the reconstruction of three-dimensional ocean temperature fields in combination with Argo profiles

Assimilation systems absorb both satellite measurements and Argo observations.This assimilation is essential to diagnose and evaluate the contribution from each type of data to the reconstructed analysis,allowing for better configuration of assimilation parameters.To achieve this,two comparative reconstruction schemes were designed under the optimal interpolation framework.Using a static scheme,an in situ-only field of ocean temperature was derived by correcting climatology with only Argo profiles.Through a dynamic scheme,a synthetic field was first derived from only satellite sea surface height and sea surface temperature measurements through vertical projection,and then a combined field was reconstructed by correcting the synthetic field with in situ profiles.For both schemes,a diagnostic iterative method was performed to optimize the background and observation error covariance statics.The root mean square difference(RMSD)of the in situ-only field,synthetic field and combined field were analyzed toward assimilated observations and independent observations,respectively.The rationale behind the distribution of RMSD was discussed using the following diagnostics:(1)The synthetic field has a smaller RMSD within the global mixed layer and extratropical deep waters,as in the Northwest Pacific Ocean;this is controlled by the explained variance of the vertical surface-underwater regression that reflects the ocean upper mixing and interior baroclinicity.(2)The in situ-only field has a smaller RMSD in the tropical upper layer and at midlatitudes;this is determined by the actual noise-to-signal ratio of ocean temperature.(3)The satellite observations make a more significant contribution to the analysis toward independent observations in the extratropics;this is determined by both the geographical feature of the synthetic field RMSD(smaller at depth in the extratropics)and that of the covariance correlation scales(smaller in the extratropics).

Temperature Field Reconstruction in High-Temperature Gas by Using the Colored Background Oriented Schlieren Method

A 3D temperature field reconstruction method using the colored background oriented schlieren(CBOS)method is proposed to address image blurring due to the different refractive index of the multi-wavelength light and significant errors produced when the traditional background oriented schlieren(BOS)method is applied to high-temperature gas.First,the traditional method is employed to reconstruct the non-uniform 3D temperature field.Second,the CBOS method is applied to correct the distortion.Then,by analyzing the correlation coefficient among different color points of the colored background pattern,the non-uniform temperature field is reconstructed much more accurately.Finally,the experimental results are verified by applying the Runge-Kutta ray-tracing method and the thermocouple contact measurement method.The maximum average temperature error of the CBOS-reconstructed temperature field is 12.92°C,compared with the thermocouples.Therefore,an accurate three-dimensional reconstruction of the temperature field can be achieved by the proposed method effectively.

Reconstruction of Temperature Field in 3-D, Absorbing, Emitting, and Anisotropically Scattering Medium

The soft measurement technology of flame temperature field is an efficient method to learn the combustion status in furnace. Generally, it reconstructs the temperature field in furnace through the image of flame, which is a process to solve radiative inverse problem. In this paper, the flame of pulverized coal is considered as 3-D, absorbing, emitting, and anisotropically scattering non-gray medium. Through the study on inverse problem of radiative heat transfer, the temperature field in this kind of medium has been reconstructed. The mechanism of 3-D radiative heat transfer in a rectangular media, which is 2 m×3 m× 5 m and full of CO2, N2 and carbon particles, is studied with Monte Carlo method. The 3-D temperature field in this rectangular space is reconstructed and the influence of particles density profile is discussed.

Variational Reconstruction and Simulation Experiments of Sea Surface Wind Field for Ocean Data Buoy

The sea surface wind field is an important physical parameter in oceanography and meteorology.With the continuous refinement of numerical weather prediction,air-sea interface materials,energy exchange,and other studies,three-dimensional(3D)wind field distribution at local locations on the sea surface must be measured accurately.The current in-situ observation of sea surface wind parameters is mainly achieved through the installation of wind sensors on ocean data buoys.However,the results obtained from this single-point measurement method cannot reflect wind field distribution in a vertical direction above the sea surface.Thus,the present paper proposes a theoretical framework for the optimal inversion of the 3D wind field structure variation in the area where the buoy is located.The variation analysis method is first used to reconstruct the wind field distribution at different heights of the buoy,after which theoretical analysis verification and numerical simulation experiments are conducted.The results indicate that the use of variational methods to reconstruct 3D wind fields is significantly effective in eliminating disturbance errors in observations,which also verifies the correctness of the theoretical analysis of this method.The findings of this article can provide a reference for the layout optimization design of wind measuring instruments in buoy observation systems and also provide theoretical guidance for the design of new observation buoys in the future.

CLDASSD:Reconstructing Fine Textures of the Temperature Field Using Super-Resolution Technology

Before 2008,the number of surface observation stations in China was small.Thus,the surface observation data were too sparse to effectively support the High-resolution China Meteorological Administration’s Land Assimilation System(HRCLDAS)which ultimately inhibited the output of high-resolution and high-quality gridded products.This paper proposes a statistical downscaling model based on a deep learning algorithm in super-resolution to research the above problem.Specifically,we take temperature as an example.The model is used to downscale the 0.0625°×0.0625°,2-m temperature data from the China Meteorological Administration’s Land Data Assimilation System(CLDAS)to 0.01°×0.01°,named CLDASSD.We performed quality control on the paired data from CLDAS and HRCLDAS,using data from 2018 and 2019.CLDASSD was trained on the data from 31 March 2018 to 28 February 2019,and then tested with the remaining data.Finally,extensive experiments were conducted in the Beijing-Tianjin-Hebei region which features complex and diverse geomorphology.Taking the HRCLDAS product and surface observation data as the"true values"and comparing them with the results of bilinear interpolation,especially in complex terrain such as mountains,the root mean square error(RMSE)of the CLDASSD output can be reduced by approximately 0.1℃,and its structural similarity(SSIM)was approximately 0.2 higher.CLDASSD can estimate detailed textures,in terms of spatial distribution,with greater accuracy than bilinear interpolation and other sub-models and can perform the expected downscaling tasks.

Investigation and optimization of sampling characteristics of light field camera for flame temperature measurement

It is essential to investigate the light field camera parameters for the accurate flame temperature measurement because the sampling characteristics of the flame radiation can be varied with them. In this study, novel indices of the light field camera were proposed to investigate the directional and spatial sampling characteristics of the flame radiation. Effects of light field camera parameters such as focal length and magnification of the main lens, focal length and magnification of the microlens were investigated. It was observed that the sampling characteristics of the flame are varied with the different parameters of the light field camera. The optimized parameters of the light field camera were then proposed for the flame radiation sampling. The larger sampling angle(23 times larger) is achieved by the optimized parameters compared to the commercial light field camera parameters. A non-negative least square(NNLS) algorithm was used to reconstruct the flame temperature. The reconstruction accuracy was also evaluated by the optimized parameters. The results suggested that the optimized parameters can provide higher reconstruction accuracy for axisymmetric and non-symmetric flame conditions in comparison to the commercial light field camera.

Flow Field and Temperature Field of Water-Cooling-Type Magnetic Coupling

At present, the water-cooling simulation of the water-cooled magnetic coupler is based on the water-cooled motor and the hydraulic coupler, which cannot accurately characterize the temperature distribution of the rotating watercooled coupling of the coupler. Focusing on rotating water cooling radiating, the present paper proposes simulating the water cooling temperature field as well as the flow field through the method of combining fluid-solid coupled heat transfer and MRF(Multiphase Reference Frame). In addition, taking an 800 kW magnetic coupling as an example, the paper optimizes the shape, number, cooling water inlet speed? and so on? of the cooling channel. Considering factors such as the complete machine’s temperature, and drag torque, it is proved that the cooling e ect is best when there are 36 involute curved channels and when the inlet speed is 3 m/s. Further, through experiments, the actual temperature values at six di erent positions when 50 kW and 70 kW thermal losses di er are measured. The measured values agree with the simulation results, proving the correctness of the proposed method. Further, data have been collected during the entire experimental procedure? and the variation in the coupling’s temperature is analyzed in depth, with the objective of laying a foundation for the estimation of the inner temperature rise as well as for the optimization of the structural design.

MATHEMATICAL MODEL OF MILLING TEMPERATURE AND TEMPERATURE FIELD ANALYSIS FOR THREE-DIMEN-SIONAL COMPLEX GROOVE MILLING INSERT

The mathematical model on the temperature of the waved-edge is constructedaccording to Jaeger's theory of moving solid and based on the used temperature model of the flatinsert. It is possible to forecast the milling temperature through programming. The comparableexperiments have been done between the two new three-dimension groove inserts (waved-edge insert,great edge insert) and flat fake insert. The theoretic forecast is in good agreement with theexperimental result. According to the cutting conditions, the boundary condition of finite elementanalysis on cutting temperature field is established, and the three-dimensional temperature fieldsof inserts with grooves are analyzed by FEM, so as to offer a reference basis for the design andoptimization of insert grooves.

Study on the computation method of temperature field of RCC dam

According to the construction characteristic of RCC dam cast by layers, three-dimensional finite element relocating mesh method is developed to simulate construction process and compute temperature field. The computation model of relocating mesh method is expatiated in detail; based on the thermodynamic properties of RCC materials, the feasibility and error of relocating mesh method are analyzed and demonstrated; The computation results in this article are verified by means of the temperature observation data of certain RCC gravity dam. The results show that the temperature field computed by three-dimensional finite element relocating mesh method can not only ensure the computation precision, but also improve the calculation efficiency greatly. This provides an effective method for simulating construction process and computing temperature field of RCC dam.

Preliminary multiproxy surface air temperature field reconstruction for China over the past millennium

We present the first millennial-length gridded field reconstruction of annual temperature for China, and analyze the reconstruction for spatiotemporal changes and associated uncertainties, based on a network of 415 well-distributed and accurately dated climatic proxy series.The new reconstruction method is a modified form of the point-by-point regression (PPR) approach.The main difference is the incorporation of the "composite plus scale" (CPS) and "Regularized errors-in-variables" (EIV) algorithms to allow for the assimilation of various types of the proxy data.Furthermore, the search radius is restricted to a grid size; this restriction helps effectively exclude proxy data possibly correlated with temperature but belonging to a different climate region.The results indicate that: 1) the past temperature record in China is spatially heterogenic, with variable correlations between cells in time; 2) the late 20th century warming in China probably exceeds mean temperature levels at any period of the past 1000 years, but the temperature anomalies of some grids in eastern China during the Medieval climate anomaly period are warmer than during the modern warming; 3) the climatic variability in the eastern and western regions of China was not synchronous during much of the last millennium, probably due to the influence of the Tibetan Plateau.Our temperature reconstruction may serve as a reference to test simulation results over the past millennium, and help to finely analyze the spatial characteristics and the driving mechanism of the past temperature variability.However, the lower reconstruction skill scores for some grid points underline that the present set of available proxy data series is not yet sufficient to accurately reconstruct the heterogeneous climate of China in all regions, and that there is the need for more highly resolved temperature proxies, particularly in the Tibetan Plateau.

Temperature field reconstruction of 3D luminous flames based on light field tomography theory

Standard plenoptic camera can be used to capture multi-dimensional radiation information of high temperature luminous flame to reconstruct the temperature distribution. In this study, a novel method for reconstructing three-dimensional temperature field is proposed. This method is based on the optical tomography combined with standard plenoptic camera. The flame projection information from different planes is contained in one radiation image. In this model, we introduced the effective concept of the nearest neighbor method in the frequency domain to strip the interference of redundant information in the projection and to realize three-dimensional deconvolution. The flame emission intensity received by the pixels on the charge-coupled device sensor can be obtained according to the optical tomographic model. The temperature distributions of the axisymmetric and nonaxisymmetric flames can be reconstructed by solving the mathematical model with the nearest neighbor method. The numerical results show that three-dimensional temperature fields of high temperature luminous flames can be retrieved, proving the validity of the proposed method.

自燃煤矸石山火区表面温度场三维重构与实践

【目的】煤矸石山自燃灾害严重破坏生态环境,影响安全生产,已成为我国生态文明建设进程中的瓶颈问题,为科学制定灭火方法及实施灭火工程,自燃煤矸石山火区范围的准确探测至关重要。【方法】提出采用无人机热红外倾斜摄影测量技术探测高温区三维分布的思路,研发热红外图像多尺度高斯滤波细节增强技术,突出目标边缘信息;基于FLIR Tools软件开发工具包SDK (software development kit)开发热红外图像一键式批量化处理软件,利用ThreadPool高效地开展热红外图像的多线程异步处理,全局统一所有热红外图像颜色阈值与温度数值的对应关系;最后采用批量处理后的热红外图像进行自燃煤矸石山火区表面温度场三维重构,并在陕西某煤矸石山火区进行了现场应用。【结果和结论】结果表明:(1)经过多尺度高斯滤波细节增强后,热红外彩色图像细节特征得到显著增强,热红外图像信息熵由6.989提高到了7.624。(2)所开发的热红外图像批量化处理软件可在10 min内对1 000张热红外图像进行快速处理,极大提高了工作效率。(3)上述技术在陕西某煤矸石山火区现场成功构建了一区及二区煤矸石山火区三维表面温度场,分别圈定了11 693 m^(2)和10 800 m^(2)高温区,为火区发展态势评估和后续灭火方案设计提供了支撑。研究成果可应用于煤矸石山火灾、煤田火灾、垃圾填埋场火灾、森林火灾以及建筑火灾等高温场景的温度场三维重构,为火区侦查、火情调查及火源位置诊断提供详实的火场数据支持。

航空发动机叶片表面红外测温校准及温度场重构

随着我国航空业的蓬勃发展,航空发动机技术取得了长足的进步。作为航空发动机的关键组件,航空发动机叶片的研制关乎全局。对其温度进行实时、精确的测量监控有助于推动航空发动机叶片相关技术的突破。本文提出了一种基于红外测温技术的航空发动机叶片温度校准算法和温度场三维重构策略。该工作利用多层感知机网络的函数拟合能力,建立了对目标点精确温度与其周围温度分布的函数关系,并将红外测温的误差控制在1.24℃。在此基础上,采用投影法和三维点云法向量估计的创新策略,实现了二维红外图像到三维空间位置映射。该方法能从单视角红外图像得到温度场三维重构,重构过程简单,摆脱了对多视角图像的依赖。

基于压缩感知的AT温度场重建算法

为提高声学层析成像(AT)的温度场重建能力,提出了基于压缩感知(CS)的AT温度场重建算法(CS-AT算法)。算法利用信号稀疏性,减少待求数据量,降低逆问题求解难度。首先选择适当字典,构建基于CS的AT温度场重建正逆问题框架;然后以正交匹配追踪(OMP)算法进行CS重构,得到温度场重建待求量在稀疏域的解;最后将其变换回原始域,通过三次样条插值得到37×37像素的细致温度分布。通过数值仿真,分别以经典的最小二乘法(LSM)和CS-AT算法在有噪声和无噪声条件下重建了均温、单峰、双峰和四峰模型温度场;在自主研发的实验系统上重建了均温、单峰和双峰实际温度场。仿真和实验表明:CS-AT算法可有效降低温度场重建误差;四峰温度场下,CS-AT算法的最高重建误差最低,仅为LSM的25.5%。

基于先验信息的压缩感知重建温度场技术

针对利用压缩感知方法重建微处理器芯片温度场存在错失真实热点、从而影响重建精度的问题,提出了一种基于先验信息的压缩感知重建温度场方法。通过对温度场先验信息的处理,结合主成分分析和模拟退火算法有针对性地设计观测矩阵,优化温度传感器的布置,提高重建精度。实验结果表明:与基于特征图的重建方法、基于模拟退火算法布置传感器的方法和基于随机采样的压缩感知重建温度场方法相比,该方法在平均温度误差、最大温度误差和均方误差方面至少分别提升了29.9%、46.6%和53.7%,有更优越的温度场重建性能。

基于正则代数重建算法的二维温度场重建

在使用代数重建算法(Algebraic Reconstruction Technique, ART)对二维非均匀温度场进行重建时,离散误差和投影噪声会随着迭代修正被引入,为了平衡离散误差,减小算法对噪声的敏感度,在ART中引入了正则化项,并使用留一交叉验证法对单位正则化参数进行了选取,根据投影穿过待测区域路径的长度和单位正则化参数动态调整每条投影的正则化权重,实现了对每条投影离散误差和噪声水平的衡量。在不同的投影分布情况下,使用该算法对高斯单峰对称和高斯单峰偏置温度场进行了仿真重建,重建结果表明相比于传统迭代算法,该算法可有效提高温度场的重建精度,并且具有较好的稳定性。

基于声学层析成像的温度场和流速场重构

为有效重构三维管道内液体的温度场和流速场,提出了一种超声飞渡时间计算表征,并基于此求解温度场和流速场反演模型。同时考虑温度梯度导致的声线弯曲效应,采用正四面体前向展开法,追踪超声弯曲路径;开展“华龙一号”反应堆主管道冷却剂温度场和流速场重构实验。实验结果表明,所提方法能有效重构管道冷却剂温度场和流速场,且考虑弯曲效应能进一步提高重构精度。

基于共焦辐射和光学层析技术重建火焰温度场

针对实际测量中设备观察口有限、对于特定位置或受背景辐射影响较大位置的温度测量问题,设计了一种共焦辐射微孔相机,将共焦技术与光学层析技术相结合,利用格林函数的双调和算子插值算法重建全场火焰温度.首先,介绍了共焦辐射微孔相机测温的基本原理,对该相机的聚焦位置及聚焦系数进行了实验标定,并用黑体炉标定了共焦辐射微孔相机的测量信号与火焰辐射强度之间的关系;最后通过层析算法和格林函数双调和插值算法对火焰温度场进行重建.结果表明:共焦辐射微孔相机测量重建结果与燃烧温度场的分布趋势大致相同,重建误差不高于10%,具有较好的灵活性和良好的抗噪性.

基于选择性卷积核CNN的声学温度场重构插值

锅炉温度反应了炉内燃烧情况。精准定位炉内高温区域,对提高燃烧效率,识别故障情况起到重要作用。传统声学温度场重构插值依赖于声波换能器的布置与径向基函数的选择,难以实现高分辨率温度场重构。为了解决该问题,本文设计基于选择性卷积核CNN的温度场重构插值网络(TRIN)对声学温度场重构中的插值问题进行优化,实现了对温度场的高精度插值。为了验证模型的有效性,在仿真温度场数据集和锅炉厂实测数据上开展实验,取得了良好的结果。

基于双向多步预测的炉管温度场重构方法

针对高温封闭的乙烯裂解环境下裂解炉炉管温度感知难的问题,提出一种融合机理和长短记忆神经网络(Long Short-Term Memory,LSTM)的裂解炉炉管表面温度场重构方法。该方法首先基于计算流体力学仿真平台fluent构建乙烯裂解反应机理模型,用来描述裂解反应与炉管温度的数学关系,然后利用工业现场数据对机理模型进行数值矫正和过程参数求解,进一步基于皮尔逊相关系数确定适用性强的主要过程参数,在此基础上,设计卷积块注意力模块(Convolu tional Block Attention Module,CBAM)对反映裂解反应与炉管温度关系的主要过程参数的特征进行提取,最后基于遗传算法和LSTM网络设计双向多步预测模型(GA-BMLSTM)对炉管温度分布进行预测。实验结果表明该方法对炉管温度场的重构有较高的准确率和较强的适用性。