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Herein, we explored the impact of anticipation and asymmetric driving behavior on vehicle’s position, velocity, acceleration, energy consumption, and exhaust emissions of CO, HC, and NOx in mixed traffic flow. We present an asymmetric-anticipation car-following model (AAFVD) considering the motion information from two direct preceding vehicles (i.e., human-driving (HD) and autonomous and connected (AC) vehicles platoon) via wireless data transmission. The linear stability approach was used to evaluate the properties of the AAFVD model. Our simulations revealed that the drivers’ anticipation factor using the motion information from two direct preceding vehicles in connected vehicles environment can effectively improve traffic flow stability. The vehicle’s departure and arrival process while passing through a signal lane with a traffic light considering the anticipation and asymmetric driving behavior, and the motion information from two direct preceding vehicles was explored. Our numerical results demonstrated that the AAFVD model can decrease the velocity fluctuations, energy consumption, and exhaust emissions of vehicles in mixed traffic flow system.

Surface-enhanced Raman scattering (SERS) has been widely reported to improve the sensitivity of Raman spectra. Ordinarily, the laser is focused on the sample to measure the Raman spectrum. The size of the focused light spot is comparable with that of micro-nano structures, and the number of micro-nano structures contained in the light spot area (defined as duty cycle) will severely affect the spectrum intensity. In this study, flower-like silver nanostructures were fabricated with a soft lyotropic liquid crystal template in order to investigate the effect of duty cycle. They were observed under a scanning electron microscope, and their spectrum enhancement factor was computed with the obtained Raman spectrum. Then, their duty cycles were measured using a SERS substrate at different locations. A formula was derived to represent the relation between the duty cycle of the nanoflowers and the Raman spectral intensity. This work could promote the actual applications of SERS in high-sensitivity spectrum testing.

Weighted mean temperature (Tm) is a key parameter in Global Navigation Satellite System meteorology. In this study, European Centre for Medium‐Range Weather Forecasts Re‐Analysis product with a spatial resolution of 0.5° × 0.5° from 1999 to 2018 was used to study the spatiotemporal behaviors of Tm in China. Decomposed by Fast Fourier Transformation, Tm and lapse rate (β) variations are highly latitude‐dependent and exhibit periodicities on annual, semi‐annual, and diurnal scales. Meanwhile, Tm keeps increasing at a rate of 0.25 K per decade across China. Based on these discoveries, this study build a new grid Tm model based on feedforward neural network (FNN) with a spatial resolution of 0.5° × 0.5°, known as Grid‐FNN model. FNN is applied to each grid point to compensate the residual error of the corresponding periodic functions. And the fitting accuracy at each grid is improved by the FNN algorithm. ERA‐Interim product with a spatial resolution of 0.4° × 0.4° and Radiosonde data in 2018 are used to validate the new model, and the accuracy of Grid‐FNN model is proved 8.6% and 10.9% better than GPT2w‐Tm model, respectively. The Grid‐FNN model also shows better performance than IGPT2w, GTm‐III, and GTrop model in autumn and winter and in high‐altitude regions.

Power transformer is one of the key equipment of the power grid, and its operation reliability directly affects the safe and efficient operation of the power grid. The main cause of transformer accidents is insulation failure. Therefore, aging characteristics and mechanism of oil-filled transformer oil-paper insulation has important academic value as well as application significance. Based on the quantum chemical simulation, this paper systematically studies the physical parameters of the transformer insulating paper molecules and their dissociation process. The results showed that as for the cellulose molecule with a degree of polymerization of 10, the energy gap between the highest occupied molecular orbital and the lowest unoccupied molecular orbital was 4.2038 eV. As for its repeating unit cellobiose, the 1,4-β-glycoside bond would be broken firstly, whose equilibrium bond length was 1.41813 A. Moreover, the bond energy was 54.18 kcal/mol, and the energy of the corresponding equilibrium configuration was -1298.2662 Hartree. Subsequently, the cellulose would generate a large amount of D-monoglucose monomer and some free radicals. The results in this paper contributed to establishing the model and the mechanism of oil-paper insulation aging process, and further identifying the aging degree of transformer and improving the reliability of transformer operation.

Dielectric barrier discharge (DBD) can generate low temperature plasma under atmospheric pressure, with great research value and bright application prospect. Compared with filamentary DBD, homogeneous DBD has obvious advantages such as the mildness and uniformity of discharge. This paper provided a brief review of DBD research history and paid considerable attention to homogeneous DBD at atmospheric pressure. By summarizing the latest diagnostic technology and numerical simulation methods, this paper reported some of the most important results of DBD characteristics and mechanism in recent decades. In addition, typical DBD plasma applications in biomedical fields, food safety, environmental pollution control were introduced. Technical problems that came up in present DBD research and application development were analysed. And the outlook for the DBD technology was given.

Based on COMSOL Multiphysics, dielectric barrier DISCHARGE (DBD) at atmospheric pressure in nitrogen and oxygen environment was investigated in detail. Due to the geometric symmetry of discharge, a one-dimensional model was introduced to simplify the simulation process. The results showed that compared with nitrogen, the discharge current in oxygen displayed more symmetric waveform, which indicated simultaneous existence of positive ions and negative ions owing to the gas electronegativity. And at the maximal discharge current, there are obvious minimum point of electrical field curve in oxygen discharge, owing to the density difference of positive and negative ions at different position of discharge gap. It also proves that the gas electronegative could lead to greater electron density gradients, higher discharge power and less uniform discharge. The electrical field curve at the moment of maximal current is selected as the characteristic parameter to distinguish gas property, electropositivity or electronegativity gas. The electrical field appear a minimum point in discharge gap, presented the shape of letter V, in electronegative gas discharge. According the mentioned characteristic curve, it is useful to determine the electronegativity of working gas.

Air pollution has attracted much attention worldwide. Sulfur dioxide (SO 2 ) is a major air pollutant in cities and affects human health seriously. The purpose of this paper is to examine how foreign direct investment affects SO 2 emissions and whether the pollution haven hypothesis exists in eastern China. On basis of the detailed data, we performed the spatial autocorrelation analysis and the spatial regression analysis. The results show that an increase in the foreign direct investment in a city is associated with a decline in SO 2 emissions in the same city, indicating that the pollution haven hypothesis does not hold in eastern China. But the spillover effect of the foreign direct investment is positive, indicating that a larger foreign direct investment in neighboring cities tends to raise SO 2 emissions in the local city.

We correct some errors and give some more research for our paper published in Survey Review, 2016, 48(351), 385–391. This note is a correction owing to the use of the questionable surface meteorolo...

The weighted mean temperature T m is a variable parameter in the Global Navigation Satellite System (GNSS) meteorology and the Askne-Nordius zenith wet delay (ZWD) model. Some parameters about the T m seasonal variation (e.g. the annual mean value, the annual range, the annual and semi-annual amplitudes, and the long-term trend) were discussed before. In this study, some additional results about the T m seasonal variation on a global scale were found by using the T m time series at 309 global radiosonde sites. Periodic signals of the annual and semi-annual variations were detected in these T m time series by using the Lomb-Scargle periodogram. The annual variation is the main component of the periodic T m in non-tropical regions, while the annual variation or the semiannual variation can be the main component of the periodic T m in tropics. The mean annual T m almost keeps constant with the increasing latitude in tropics, while it decreases with the increasing latitude in non-tropical regions. From a global perspective, T m has an increasing trend of 0.22 K/decade on average, which may be caused by the global warming effects. The annual phase is almost found in about January for the non-tropical regions of the Southern Hemisphere and in about July for the non-tropical regions of the Northern Hemisphere, but it has no clear symmetry in tropics. Unlike the annual phase, the geographical distributions of semi-annual phase do not follow obvious rules. In non-tropical regions, the maximum and minimum T m of the seasonal model are usually found in respective summer and winter days while the maximum and minimum T m are distributed over a whole year but not in any fixed seasons for tropical regions. The seasonal model errors increase with the increasing value of annual amplitude. A primary reason for the irregular seasonal variation in tropics is that T m has rather small variations in this region.

A novel ionospheric tomography technique based on variable pixel size was developed for the tomographic reconstruction of the ionospheric electron density (IED) distribution. In variable pixel size computerized ionospheric tomography (VPSCIT) model, the IED distribution is parameterized by a decomposition of the lower and upper ionosphere with different pixel sizes. Thus, the lower and upper IED distribution may be very differently determined by the available data. The variable pixel size ionospheric tomography and constant pixel size tomography are similar in most other aspects. There are some differences between two kinds of models with constant and variable pixel size respectively, one is that the segments of GPS signal pay should be assigned to the different kinds of pixel in inversion; the other is smoothness constraint factor need to make the appropriate modified where the pixel change in size. For a real dataset, the variable pixel size method distinguishes different electron density distribution zones better than the constant pixel size method. Furthermore, it can be non-chided that when the effort is spent to identify the regions in a model with best data coverage. The variable pixel size method can not only greatly improve the efficiency of inversion, but also produce IED images with high fidelity which are the same as a used uniform pixel size method. In addition, variable pixel size tomography can reduce the underdetermined problem in an ill-posed inverse problem when the data coverage is irregular or less by adjusting quantitative proportion of pixels with different sizes. In comparison with constant pixel size tomography models, the variable pixel size ionospheric tomography technique achieved relatively good results in a numerical simulation. A careful validation of the reliability and superiority of variable pixel size ionospheric tomography was performed. Finally, according to the results of the statistical analysis and quantitative comparison, the proposed method offers an improvement of 8% compared with conventional constant pixel size tomography models in the forward modeling.

The adaptive optics system (AOS) has been used to eliminate the effect of atmospheric turbulence for free-space optical communications. The AOSs are designed based on the statistical average performance of the turbulence. In reality, the amplitude of turbulence changes drastically, and the AOS cannot always detect and correct the aberrations appropriately. To prevent the amplitude of turbulence from exceeding the designed range of the Shack–Hartmann wavefront sensor (SH WFS), the combination of the wavefront sensorless and SH WFS methods is proposed to extend the detection range. First, the control scheme is demonstrated, and the numerical simulation is performed. Then, the validation experiments are performed with static and dynamic turbulence. Results show that the proposed method is valid and that the effective communication time is greatly lengthened.

Tropospheric delay has a major effect on the accuracy of navigation and positioning when using the Global Navigation Satellite System (GNSS). Zenith tropospheric delay (ZTD) modelling has been used to weaken the influence of the atmosphere. The work reported here focused on ZTD modelling based on real-time surface meteorological parameters, traditionally represented by the Saastamoinen model. However, Saastamoinen accuracy only reaches scale of centimetres, even to scale of centimetres when the water vapour is active, whereas the scale of ground-based GNSS-ZTD data (i.e. ZTD derived from ground GNSS data) is on the millimetre scale and is considered to be the ‘true’ value. An important direction in GNSS studies is how to make good use of ground-based GNSS-ZTD data to improve the accuracy of the Saastamoinen model. Authors studied the residuals in the Saastamoinen model using high-precision GNSS-ZTD data provided by the International GNSS Service (IGS) product and then carried out modelling based on a back...

In this contribution, according to the critical frequency of the F2 layer (foF2) from the ionosonde station and the International Reference Ionosphere 2012 (IRI2012) model [the International Radio Consultative Committee (CCIR) coefficient], a single station model (called the Fusion model) for predicting the hourly value of foF2 over Lycksele (64.69°N, 18.80°E) is developed by the back-propagation neural network (BPNN) technology compensated for the model-deviation of the IRI2012 model. The input parameters of this BPNN-based foF2 prediction model include day number (day of the year), universal time, solar zenith angle, solar cycle information, geomagnetic activity (a 3-day running mean of the 3-h planetary magnetic index Ap and Kp) and the foF2 values from the IRI2012 model; the output parameter is the model-deviation. The data sets employed in this model are obtained from the National Geophysical Data Centre and National Aeronautics and Space Administration (NASA), about 215 614 sets, which are derived d...

To evaluate the effects of anticipative driving behavior based on the motion information of two leading vehicles, we first propose a new car-following model which integrates space and velocity changes of two leading vehicles implemented through V2X wireless communication in autonomous and connected vehicles environment. We then derive a corresponding macroscopic viscous continuum traffic flow model, more realistic and meaningful than those coming directly from an analogy of Navier–Stokes equations as the new macroscopic model does not exhibit a wrong-way travel phenomenon. It is revealed that taking into account motion information of two leading vehicles leads to a viscosity parameter in macroscopic traffic flow equation. The viscosity parameter is proportional to a unique quantity, which is featured with two parameters: the delay time of vehicle motion and the kinematic wave velocity at jam density. Linear and nonlinear stability analysis using the method of perturbation is carried out to study traffic characteristics.

This paper proposes a new car-following model by considering driver memory and derives a corresponding macroscopic continuum traffic flow model, in which the wrong-way travel phenomenon is not going to occur. We reveal that considering driver memory expressed in term of past traffic condition and headway leads to viscosity parameter in macroscopic traffic flow equation. The viscosity parameter is proportional to a unique quantity, which is featured with two parameters: the delay time of vehicle motion and the kinematic wave velocity at jam density. Linear and nonlinear stability analysis using the method of perturbation is carried out to study traffic characteristics. We showed that macroscopic models derived from microscopic models are more realistic and meaningful than those coming directly from an analogy of Navier–Stokes equations.

On-board the Landsat-8 satellite, the Thermal Infrared Sensor (TIRS), which has two adjacent thermal channels centered roughly at 10.9 and 12.0 μm, has a great benefit for the land surface temperature (LST) retrieval. The single-channel algorithm (SC) and split-window algorithm (SW) have been applied to retrieve the LST from TIRS data, which need the land surface emissivity (LSE) as prior knowledge. Due to the big challenge of determining the LSE, this study develops a temperature and emissivity separation algorithm which can simultaneously retrieve the LST and LSE. Based on the laboratory emissivity spectrum data, the minimum-maximum emissivity difference module (MMD module) for TIRS data is developed. Then, an emissivity log difference method (ELD method) is developed to maintain the emissivity spectrum shape in the iterative process, which is based on the modified Wien’s approximation. Simulation results show that the root-mean-square-errors (RMSEs) are below 0.7 K for the LST and below 0.015 for the LSE. Based on the SURFRAD ground measurements, further evaluation demonstrates that the average absolute error of the LST is about 1.7 K, which indicated that the algorithm is capable of retrieving the LST and LSE simultaneously from TIRS data with fairly good results.

A multiscale ionospheric tomography (MST) technique is developed for the tomographic reconstruction of the ionospheric electron density (IED) distribution, which is a simultaneous application of many overlapping single-scale tomographies (SSTs) with different pixel sizes. In contrast to conventional SST which parameterizes the model with non-overlapping pixel, the MST allows a decomposition of the ionosphere into a set of SSTs with different cell sizes; at each model location, the IED receives different contributions from all the MST submodels in the process of inversion. The final MST model is a post-inversion superposition of all submodels, and the final MST solution is a superposition of solutions of all submodels. In comparison with the conventional SST models, superior results of the MST are observed in a numerical simulation. A careful validation of the reliability and superiority of MST is made. According to the statistical analysis of average root mean square error, the result shows that the proposed model offers an improvement of 15 % over the conventional SST models.

Tropospheric delay is a primary error source in earth observations and a variety of radio navigation technologies. However, the main problem still present is that not all strategic points around the world will have a GPS receiver. To overcome the shortcoming, a Fusion model was proposed to compensate for errors in prediction of zenith tropospheric delay (ZTD), by incorporating back propagation neural network (BPNN). The input parameters include the surface meteorological data (altitude, atmospheric pressure, absolute temperature and water vapour partial pressure) and Hopfield model predicted ZTD, the output is the difference between the Hopfield predicted and high altitude balloon derived ZTD (also called true ZTD). The datasets covered ∼250 meteorological observation stations within 8∶00 and 20∶00 for May 1st, 10th, 30th, and July 1st, August 1st and September 1st, 2010. Data from 16 uniformly distributed stations were used for training at 8∶00 on May 1st, and the remaining for validation. Modelling resu...

A new model for regional ionospheric delay correction has been developed, tested and compared with a two-dimensional polynomial ionosphere delay correction model (called 2-DPM). First, available ionospheric data have been used in the modelling of the 2-DPM. Then, artificial neural network technology is used to compensate for the model deviation Δy of the 2-DPM to obtain a new ionospheric delay correction model (called the Fusion model). Finally, an example is implemented to demonstrate the performance and efficiency of the Fusion model. According to the statistical analysis of average root mean squared errors, the Fusion model offers an improvement of 26·4% over the 2-DPM. The results show that the proposed model can give better accuracy than the 2-DPM.

In China, normal height, which is the height above the geoid calculated using the mean normal gravity along the plumb line, is used in engineering applications. However, the adjusted global positioning system (GPS) height is the height above the surface of the WGS-84 ellipsoid. Thus, it is necessary to convert a GPS height into a normal height. Normally, the conicoid fitting method (CFM) and the neural network method (NNM) are used for this purpose in China, but each has its own advantages and disadvantages. After studying these two methods, a new method (CF&NNM) is conceived. The structure of the back-propagation neural network and detailed algorithm of the CFM, NNM, and CF&NNM are discussed. The procedure of the new method is introduced. A practical engineering example is used to study these three different methods. The results by the three methods are listed. It is demonstrated that the CF&NNM could produce better results than either the CFM or the NNM in deriving the normal height from the GPS height. The theory of the CF&NNM is analyzed.

The friction stir welding (FSW) process has been evaluated for application on the Al 2195 cryogenic tank of the Space Transportation System. In the present study, the general corrosion, pitting and stress corrosion cracking (SCC) resistance of 2195 plates joined by FSW was investigated. Plates of Al 2219 joined by FSW were also tested for comparison purposes along with Al 2195 and Al 2219 plates joined by the variable polarity plasma arc welding method. The general corrosion, SCC and pitting behavior of FSW AI 2195 and AI 2219 is presented and discussed.

The purpose of this paper is to monitor the ionospheric total electron content (TEC) in real time. Firstly, the receiver differential code bias (DCB) and the satellite DCB are calculated by assuming that they are constant value during the whole day. Comparing with the satellite DCB given by the Center for Orbit Determination in Europe (CODE), this paper also analyzes the DCB stability of receiver and satellite. And secondly, according to the stability of DCB, we calibrate vertical TEC (VTEC) by using DCB of the former day, and establish the polynomial model with multi-station in single epoch to monitor the changes of ionosphere. The result of all epoches within a day shows that the average internal RMS of this method can be better than 1 TECU (1016 el/m2), and the average external RMS can be about 1 TECU.

As we all know, to predict the short-term traffic flow accurately and efficiently is the premise and key of traffic management and control. Based on these existing study, this paper selected BP neural network model in which the traffic flow difference was taken as the input parameter, applied the thought of dynamic rolling prediction to design a new short-term traffic flow prediction method, and wrote the corresponding program. Then using the actual observation data of traffic flow presented the model structure, thought and calculation steps of this new method. The results show this method is feasibility, reliability, and of some practical value.

In order to change the conventional separate mode of plane and height control network, the new method of establishing 3-dimension GPS engineering control network using gravity quasi-geoid was proposed. By computing and analyzing with GPS control network of the Remove South Water to North Engineering, the accuracy of normal heights that were computed using new method was excelled 0.050m. The 3-dimension GPS engineering control network can improve the accuracy of normal heights that are converted from GPS ellipsoid heights and replace low- grade geometrical levelling measure in some civil engineering.