Background-oriented Schlieren tomography using gated recurrent unit.

Current Background-oriented schlieren tomography (BOST) methods rely primarily on iterative algorithms for reconstruction. Before reconstruction, a weight projection matrix was generated by performing 3D ray tracing using the projection relationship between the cameras, depending on the camera calibration parameters and large weight projection matrix which introduce artifacts and greatly reduce computational efficiency in the reconstruction. Considering that CT reconstruction uses spatial projection sequences from multiple directions, this study draws inspiration from the Recurrent Neural network(RNN) and utilizes spatial correlation between adjacent projection data to propose a background-oriented schlieren reconstruction method based on a gated recurrent unit (GRU) neural network. First, the model architecture is designed and implemented. Subsequently, numerical simulations were conducted using a methane combustion model to evaluate the proposed method, which achieved an average mean relative error (MRE) of 0.23%. Finally, reconstruction experiments were performed on the actual flow-field data above a candle flame, with a reprojection correlation coefficient of 89% and an average reconstruction time of only 1.04 s per frame. The results demonstrate that the proposed method outperforms traditional iterative reconstruction methods in terms of reconstruction speed and accuracy. This provides a feasible solution for the real-time reconstruction of three-dimensional instantaneous flow fields.

Displacement extraction of background-oriented schlieren images using Swin Transformer.

Displacement extraction of background-oriented schlieren (BOS) is an essential step in BOS reconstruction, which directly determines the accuracy of the results. Typically, the displacement is calculated from the background images with and without inhomogeneous flow using the cross-correlation (CC) or optical flow (OF) method. This paper discusses the disadvantages of the CC and OF methods, and an end-to-end deep neural network was designed to estimate the BOS displacement. The proposed network is based on a Swin Transformer, which can build long-range correlations. A synthetic dataset used for training was generated using the simulated flow field by computational fluid dynamics. After training, the displacement can be obtained using the BOS image pair without additional parameters. Finally, the effectiveness of the proposed network was verified through experiments. The experiments illustrate that the proposed method performs stably on synthetic and real experimental images and outperforms conventional CC or OF methods and classic convolutional neural networks for OF tasks.

Fractal two-scale method for calculating the laser scattering distribution of asphalt pavement.

The laser scattering characteristic of pavement is one of the important factors that affect the detection performance of optical sensors such as lidars. Because the wavelength of laser does not match the roughness of the asphalt pavement, the common analytical approximation model of electromagnetic scattering is not applicable in this case, so it is difficult to calculate the laser scattering distribution of the pavement accurately and effectively. According to the self-similarity of the asphalt pavement profile, a fractal two-scale method (FTSM) based on fractal structure is proposed in this paper. We used the Monte Carlo method to obtain the bidirectional scattering intensity distribution (SID) and the back SID of the laser on the asphalt pavement with different roughness. Then we designed a laser scattering measurement system to verify the simulation results. We calculated and measured the SIDs of s-light and p-light of three asphalt pavements with different roughness (σ=0.34 mm; 1.74 mm; 3.08 mm). The results show that, compared with the traditional analytical approximation methods, the results of FTSM are closer to the experimental results. Compared with the single-scale model based on the Kirchhoff approximation, FTSM has a significant improvement in computational accuracy and speed.

Application of well logging technology in geothermal resource evaluation: A case study of geothermal water wells in the Qianjiang sag, Jianghan Basin.

Geothermal resources are green and environmentally friendly renewable energy. An accurate evaluation of geothermal resources will help subsequent efficient exploitation. However, to save costs and improve efficiency, core-free drilling and without mud logging are adopted in the actual exploration, which results in an inability to directly obtain the relevant evaluation parameters of a geothermal reservoir for exploration and evaluation. Well logging technology can effectively delineate the geothermal reservoir and determine the location of the major aquifer, while also allowing for the accurate measurement of key reservoir evaluation parameters, such as the shale content, porosity, and well temperature. Moreover, coupled with the calculated logging parameters, a volumetric method can be used to determine the regional geothermal reserves. This research takes the geothermal wells of the Guanghuasi Formation in the Qianjiang sag, Jianghan Basin as an example to conduct the application research. The findings can be of reference for similar geothermal wells in China and facilitate the development of "carbon neutrality."

Direct background-oriented schlieren tomography using radial basis functions.

Background-oriented schlieren tomography (BOST) is effective for flow field measurement; however, different from general computed tomography (CT), the BOST utilizes the deflection of rays passing through an inhomogeneous field for measurement. It is sensitive to the refractive index gradient. Therefore, an additional integration step is typically employed to obtain the refractive index. In this article, a calculation method of projection matrix is proposed based on the radial basis function (RBF). The 3D distribution of the refractive index can be reconstructed directly. This method was first verified by numerical simulation. Then, the 3D instantaneous refractive index field above a candle flame was measured. The reprojection error was calculated by ray tracing. The results illustrate the accuracy and stability of the proposed method. This research provides a new and complete solution for the 3D instantaneous flow field (refractive index, density, or temperature) measurement.

Three-dimensional rapid flame chemiluminescence tomography via deep learning.

Flame chemiluminescence tomography (FCT) plays an important role in combustion monitoring and diagnostics due to the easy implementation and non-intrusion. However, on account of the high data throughput and the inefficiency of the conventional iteration methods, the 3D reconstructions in FCT are typically conducted off-line and time-consuming. In this work, we present a 3D rapid FCT reconstruction system based on convolutional neural networks (CNN) model for practical combustion measurement, which has the ability to reconstruct 3D flame distribution rapidly after training process. First, the numerical simulation has been performed by creating three cases of phantoms which are designed to mimic the 3D conical flame. Next, after the evaluation of loss function and training time, the optimal CNN architecture has been determined and certificated quantitatively. Finally, a real time FCT system consisting of 12 color CCD cameras is realized and multispectral separation algorithm is adopted to extract CH* and C2* components. Certificated by practical measurements testing, the proposed CNN model is able to reconstruct 3D flame structure from real time captured projections with credible accuracy and structure similarity. Furthermore, compared with conventional iteration reconstruction method, the proposed CNN model shows better performance on obviously improving reconstruction speed and it is expected to achieve 3D rapid monitoring of flames.

Impact of postoperative dexmedetomidine infusion on incidence of delirium in elderly patients undergoing major elective noncardiac surgery: a randomized clinical trial.

PURPOSE: Postoperative delirium is a serious and common complication, it occurs in 13-50% of elderly patients after major surgery, and presages adverse outcomes. Emerging literature suggests that dexmedetomidine sedation in critical care units (intensive care unit) is associated with reduced incidence of delirium. However, few studies have investigated whether postoperative continuous infusion of dexmedetomidine could safely decrease the incidence of delirium in elderly patients admitted to general surgical wards after noncardiac surgery. PATIENTS AND METHODS: This double-blind, randomized, placebo-controlled trial was conducted in patients aged 65 years or older undergoing major elective noncardiac surgery without a planned ICU stay. Eligible patients were randomly assigned to receive either dexmedetomidine (0.1 µg/kg/h) or placebo (0.9% normal saline) immediately after surgery though patient-controlled intravenous analgesia device. The primary outcome was the incidence of delirium during the first 5 postoperative days. Secondary outcomes included postoperative subjective pain scores and subjective sleep quality. The study dates were from January 2018 to January 2019. RESULTS: A total of 557 patients were randomly assigned to receive either dexmedetomidine (n=281) or placebo (n=276). The incidence of postoperative delirium had no difference between the dexmedetomidine and placebo groups (11.7% [33 of 281] vs 13.8% [38 of 276], P=0.47). Compared with placebo group, patients in dexmedetomidine group reported significant lower numerical rating score pain scores at 3, 12, 24, and 48 hrs after surgery (all P<0.05) and significant improved Richards Campbell Sleep Questionnaire results during the first 3 postoperative days (all P<0.0001). Dexmedetomidine-related adverse events were similar between the two groups. CONCLUSION: Postoperative continuous infusion of dexmedetomidine did not decrease the incidence of postoperative delirium in elderly patients admitted to general surgical wards after elective noncardiac surgery.

3D SAPIV particle field reconstruction method based on adaptive threshold.

Particle image velocimetry (PIV) is a necessary flow field diagnostic technique that provides instantaneous velocimetry information non-intrusively. Three-dimensional (3D) PIV methods can supply the full understanding of a 3D structure, the complete stress tensor, and the vorticity vector in the complex flows. In synthetic aperture particle image velocimetry (SAPIV), the flow field can be measured with large particle intensities from the same direction by different cameras. During SAPIV particle reconstruction, particles are commonly reconstructed by manually setting a threshold to filter out unfocused particles in the refocused images. In this paper, the particle intensity distribution in refocused images is analyzed, and a SAPIV particle field reconstruction method based on an adaptive threshold is presented. By using the adaptive threshold to filter the 3D measurement volume integrally, the three-dimensional location information of the focused particles can be reconstructed. The cross correlations between images captured from cameras and images projected by the reconstructed particle field are calculated for different threshold values. The optimal threshold is determined by cubic curve fitting and is defined as the threshold value that causes the correlation coefficient to reach its maximum. The numerical simulation of a 16-camera array and a particle field at two adjacent time events quantitatively evaluates the performance of the proposed method. An experimental system consisting of a camera array of 16 cameras was used to reconstruct the four adjacent frames in a vortex flow field. The results show that the proposed reconstruction method can effectively reconstruct the 3D particle fields.

Theoretical range precision obtained by maximum likelihood estimation in laser radar compared with the Cramer-Rao bound.

The waveform fitting technique has been a prevailing method for accurate extraction of a range of objects from an observed signal. Exploration of range precision then became a significant research topic to evaluate the performance of the technique with the corruption of noise. In this paper, we derive an analytical solution of the maximum likelihood estimation for the Gaussian model as the probability density function (PDF) of the range estimator. The variance of the linear version of the PDF is consistent with the Cramer-Rao bound (CRB). Thus, the variance of the PDF is regarded as the theoretical range precision (TRP) compared with the CRB. The verification results show the TRP can perfectly describe the variance of the simulation data while the CRB provides a lower bound. At a higher signal-to-noise ratio (SNR), both the TRP and CRB have the ability to provide an accurate description of the range precision. At a lower SNR, the TRP still performs well while the CRB is too loose to bound the variance on the unbiased estimation.

Three-dimensional dynamic measurements of CH* and C2* concentrations in flame using simultaneous chemiluminescence tomography.

The species concentrations of flame chemiluminescence play important role in combustion diagnostics, such as CH* and C2* of hydrocarbon flame, which can provide specific characteristics in combustion control and monitoring. In order to realize both CH* and C2* chemiluminescence intensity detection in propane-air diffusion flame simultaneously, we present three-dimensional dynamic flame detecting method for species concentration determination. Firstly, quantitative flame chemiluminescence multispectral separation technique based on color cameras coupled with double-channel bandpass filters is adopted for dual channel signal division. Next, flame chemiluminescence tomography combining with multi-directional simultaneous capturing is proposed for real time three dimensional observations and detection in flame. Moreover, the proposed technique can quantitatively provide comparison of species intensity between CH* and C2* for further analysis. Considering its credible detecting accuracy and simple requirements, it is believed the proposed technique can be widely used in combustion diagnostics.

Implementation of multidirectional moiré computerized tomography: multidirectional affine calibration.

To realize three-dimensional (3D) instantaneous diagnoses for flow fields, many multidirectional optical computerized tomographic (optical CT) techniques based on laser interferometry have been proposed. Projections from different directions of these tomographic systems are captured simultaneously to reconstruct the test field. These projections are independent from each other. However, due to the inevitable errors from installation and difference between optical elements, projections will be imaged with different distortion and located at different positions on the sensors. Therefore, a multidirectional calibration should be performed to remap these projections to a unified coordinate system before CT reconstruction. As far as we know, the multidirectional calibration problem for laser interferometric CT techniques has never been discussed in previous research. In this paper, a six-directional moiré tomographic system is designed. Considering the projection characteristics of moiré deflectometry, a multidirectional affine calibration method is proposed to determine the extrinsic and intrinsic parameters of tomographic projections. With the calibration results, projections can be remapped to the unified coordinate system and the 3D distributions of flow field can be reconstructed.

Hybrid algorithm for three-dimensional flame chemiluminescence tomography based on imaging overexposure compensation.

Flame tomography of chemiluminescence is a necessary combustion diagnostic technique that provides instantaneous 3D information on flame structure and excited species concentrations. During combustion diagnostics, imaging overexposure always causes missing information, which obviously decreases the accuracy in further reconstructions. In order to compensate imaging overexposure, a hybrid algorithm combining weight correction and Tikhonov's regularization is proposed in this paper. The intensity of the overexposure region can be estimated via the accumulation of weight coefficients. Meanwhile, Tikhonov's regularization is utilized to ameliorate the quality of reconstruction. The numerical simulation quantitatively evaluates the performance of the hybrid algorithm. Additionally, an experiment system consisting of 12 cameras was established to reconstruct the 3D combustion structure of axisymmetric flame with different exposure time settings. This work further investigates dynamic nonaxisymmetric propane diffusion flame. The obtained results show that the hybrid algorithm can effectively reveal the flame structure less influenced by imaging overexposure and achieve better results.

Asymmetric Diketopyrrolopyrrole Conjugated Polymers for Field-Effect Transistors and Polymer Solar Cells Processed from a Nonchlorinated Solvent.

Newly designed asymmetric diketopyrrolopyrrole conjugated polymers with two different aromatic substituents possess a hole mobility of 12.5 cm(2) V(-1) s(-1) in field-effect transistors and a power conversion efficiency of 6.5% in polymer solar cells, when solution processed from a nonchlorinated toluene/diphenyl ether mixed solvent.

Selective Modification of Halloysite Nanotubes with 1-Pyrenylboronic Acid: A Novel Fluorescence Probe with Highly Selective and Sensitive Response to Hyperoxide.

A novel fluorescence probe based on modified halloysite nanotubes (HNTs) by using 1-pyrenylboronic acid selectively grafted onto the inner surface of lumen was successfully achieved. The solid-state nuclear magnetic resonance ((13)C and (11)B), X-ray photoelectron spectroscopy (XPS) and Fourier transform infrared (FTIR) confirmed that the boronic acid group only binds to alumina at the tube lumen and does not bind the tube's outer siloxane surface. The modified HNTs (HNTs-PY) inherit the spectroscopic properties relating to the pyrene units. Interestingly, the established Al-O-B linkage gives the H2O2-sensitivity to pyrene grafted tubes. HNTs-PY exhibits a highly specific "turn-off" response for hyperoxide over other reactive oxygen species (ROS) and oxidative ions owing to their chemoselective boronate-to-phenol switch. The "turn-off" response can even be tracked when the additional amount of H2O2 was limited to 1 × 10(-6) mol. Thus, the selective modification method under mild conditions for the design of novel organic-inorganic hybrid fluorescence probe may open up a broader application as well as for identification and diagnosis.