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The ignition characteristics of nano-aluminum (nano-Al) in oxygen and steam environments were numerically studied in this work. A detailed kinetic mechanism of nano-Al combustion was developed, and the effects of initial reaction temperature, ignition pressure, the phase of reactant, and the ratio of O2 and H2O in the oxidizer on the oxidation performance of aluminum (Al) were analyzed in detail. Numerical results show that increasing the initial temperature promotes the ignition of liquid-phase Al, while the promotion is not significant for gas-phase Al ignition. The oxidation of liquid-phase Al is significantly slower than that of gas-phase Al, and the phase transition reaction of liquid-phase Al exhibits a typical endothermic process, which results in a temperature drop before ignition. The increase of initial reaction pressure can accelerate the consumption of both liquid-phase Al and gas-phase Al in the ignition process. The oxidizability of O2 is much larger than that of H2O, and the oxidation of Al becomes slower by adding H2O in the oxidizer. The rate of production (ROP) was performed to deeply realize the reaction pathways of Al consumption and main products formation. The reaction Al + O2 = AlO + O is the key reaction pathway in the Al-O2 ignition process, while the reaction Al + H2O = AlOH + O plays a more important role in the Al-H2O ignition process. In the all ignition cases, Al2O2 is a key intermediate species since it is the main precursor of gaseous Al2O3, and liquid-phase Al2O3 formed by the phase transition reaction of gaseous Al2O3 is the dominant final product.

IntroductionIn cognitive behavioral experiments, we often asked participants to make judgments within a deadline. However, the most common instruction of “do the task quickly and accurately” does not highlight the importance of the balance between being fast and accurate.MethodsOur research aimed to explore how instructions about speed or accuracy affect perceptual process, focus on event-related potentials (ERPs) and event-related oscillations (EROs) of two brain responses for visual stimuli, known as P1 and N1. Additionally, we compared the conventional analysis approach with principal component analysis (PCA) based methods to analyze P1 and N1 ERP amplitude and ERO power.ResultsThe results showed that individuals instructed to respond quickly had lower P1 amplitude and alpha ERO than those who prioritized accuracy, using the PCA-based approach. However, these two groups had no differences between groups in the N1 theta band using both methods. The traditional time-frequency analysis method could not detect any ERP or ERO distinctions between groups due to limitations in detecting specific components in time or frequency domains. That means PCA is effective in separating these components.DiscussionOur findings indicate that the instructions given regarding speed and accuracy impact perceptual process of subjects during cognitive behavioral experiments. We suggest that future researchers should choose their instructions carefully, considering the purpose of study.

Two novel heterobimetallic metal-organic frameworks (MOFs), Ba4Pb4(CH3CO2)8[(CH6CO2)4Pb](CH3CO2)4 (PbBa-MOFs) and Ba2Ni(CO2H)6(OH2)4 (NiBa-MOFs), were prepared via the solvothermal method, and their structures were characterized by X-ray diffraction (XRD) and scanning electron microscope (SEM) techniques. The pyrolysis behavior of the two MOFs and their catalytic performances on the dihydroxylammonium-5,5’-bistetrazole-1,1’-diolate (TKX-50) pyrolysis were studied by thermogravimetric-differential scanning calorimetry (TG-DSC) and thermogravimetric-fourier transform infrared spectroscopy-mass spectrum (TG-FTIR-MS) methods. Compare with the pure TKX-50, the pyrolysis peak temperature and apparent activation energy (Ea) of the TKX-50/PbBa-MOFs mixture were decreased by 3.2°C and 13.47 kJ‧mol−1 respectively. The Ea of TKX-50/NiBa-MOFs was decreased by 9.35 kJ‧mol−1. And the second pyrolysis peak disappeared in the DSC curves of TKX-50 after the addition of the two MOFs, due to that the products from MOFs pyrolysis suppress the chemical reaction pathway on the production of 5,5′-bis (2-hydroxytetrazole) (ABTOX) and accelerate the direct decomposition of 1,1’-bistetrazole diol (BTO). This resulted in the percentage of H2O decreased greatly and the percentage of NO/CH2O, CO2/N2O, NH2+/O• and NH3/OH increased during the pyrolysis of TKX-50. Finally, the relation between the pyrolysis and ignition characteristics was discussed and described. The two MOFs reduced the ignition delay time of the TKX-50 at the high power density region, and the flame becomes more luminous due to the formation of metal oxides and active free radical.

Lithium-ion hybrid capacitors (LICs) possess the fascinating characteristics of both high power density and high energy density simultaneously. However, to design highly compatible cathode materials with a high capacity and anode materials with a high rate performance is still a major challenge because of the mismatch of dynamic mechanisms, greatly limiting the development of LICs. Herein, we report an N−doped porous carbon (N−PC) with a continuously interconnected network as the cathode, matching the dynamic mechanism of the uniquely pseudocapacitive T−Nb2O5 anode without diffusion-controlled behavior. This heteroatom-grafting strategy of the cathode can effectively control the dynamic process to adjust the ion transport efficiency, shortening the gap of kinetics and capacity with the anode. For the energy storage application, the as-prepared N−PC cathode demonstrates an appreciable capacity of 62.06 mAh g−1 under a high voltage window of 3 V to 4.2 V, which can exceed the capacity of 25.57 mAh g−1 for porous carbon without heteroatom doping at the current density of 0.1 A g−1. Furthermore, the as-developed lithium-ion capacitor possesses an outstanding electrochemical performance (80.57 Wh kg−1 at 135 W kg−1 and 36.77 Wh kg−1 at 2.7 kW kg−1). This work can provide a new avenue to design cathode materials with a highly appreciable capacity and highly compatible kinetic mechanism, further developing high-performance lithium-ion capacitors.

In this work, spherical Al-Mg-Zr alloy with intensive heat release were characterized and compared to neat Al powders. The morphology, element distribution and thermal performance were characterized by TEM, SEM, Mapping and TG-DSC. The laser-induced ignition and combustion characteristics of Al-Mg-Zr alloy powders were performed by microscopic high-speed video-recording. The effect of Al-Mg-Zr on the combustion process of HTPB-based solid propellants were carried out as well. It was observed that, the energy release process of Al-Mg-Zr is accompanied by the phenomena of gas emission and microexplosion, which is useful for improving the combustion efficiency of the alloy and reducing the combustion product particles of solid propellants. The findings in this work validate the potential of Al-Mg-Zr as an additional fuel for high aluminum content solid propellants.

Purpose – This paper aims to use active fine lane management methods to solve the problem of congestion in a weaving area and provide theoretical and technical support for traffic control under the environment of intelligent connected vehicles (ICVs) in the future. Design/methodology/approach – By analyzing the traffic capacities and traffic behaviors of domestic and foreign weaving areas and combining them with field investigation, the paper proposes the active and fine lane management methods for ICVs to optimal driving behavior in a weaving area. The VISSIM simulation of traffic flow vehicle driving behavior in weaving areas of urban expressways was performed using research data. The influence of lane-changing in advance on the weaving area was evaluated and a conflict avoidance area was established in the weaving area. The active fine lane management methods applied to a weaving area were verified for different scenarios. Findings – The results of the study indicate that ICVs complete their lane changes before they reach a weaving area, their time in the weaving area does not exceed the specified time and the delay of vehicles that pass through the weaving area decreases. Originality/value – Based on the vehicle group behavior, this paper conducts a simulation study on the active traffic management control-oriented to ICVs. The research results can optimize the management of lanes, improve the traffic capacity of a weaving area and mitigate traffic congestion on expressways.

Purpose – Heavy fog results in low visibility, which increases the probability and severity of traffic crashes, and fog warning system is conducive to the reduction of crashes by conveying warning messages to drivers. This paper aims at exploring the effects of dynamic message sign (DMS) of fog warning system on driver performance. Design/methodology/approach – First, a testing platform was established based on driving simulator and driver performance data under DMS were collected. The experiment route was consisted of three different zones (i.e. warning zone, transition zone and heavy fog zone), and mean speed, mean acceleration, mean jerk in the whole zone, ending speed in the warning zone and transition zone, maximum deceleration rate and mean speed reduction proportion in the transition zone and heavy fog zone were selected. Next, the one-way analysis of variance was applied to test the significant difference between the metrics. Besides, drivers’ subjective perception was also considered. Findings – The results indicated that DMS is beneficial to reduce speed before drivers enter the heavy fog zone. Besides, when drivers enter a heavy fog zone, DMS can reduce the tension of drivers and make drivers operate more smoothly. Originality/value – This paper provides a comprehensive approach for evaluating the effectiveness of the warning system in adverse conditions based on the driving simulation test platform. The method can be extended to the evaluation of vehicle-to-infrastructure technology in other special scenarios.

The dynamic measurement and correction of infrared radiation temperature for rocket motor exhaust plume was established based on Stefan-Boltzmann formula under the assumption that the colorimetric temperature is regarded as the real value. The relationship between the spectral emissivity of the exhaust plume and time is obtained, and the temperature distribution measured by the infrared thermal imager is corrected in real time. During the stable working period of the rocket motor, the maximum value of the infrared radiation temperature distribution curve and the average value corresponding to the time are used to represent the maximum and average infrared radiation temperature of the motor exhaust plume field. This method is applicable to the real-time determination of the spectral emissivity of the exhaust plume and the accurate measurement of the infrared radiation temperature distribution at static or rocket sled flight state, and is of great significance to the development of the low-signature rocket motor and propellant charge.

Abstract In view of the benefits and a promising prospect of the emerging connected vehicles (CV), more and more vehicles will be equipped with the in‐vehicle human‐machine interface (HMI). This study aims to assess the comprehensive impacts of HMIs on individual driving performance, traffic safety, and eco‐driving behaviour based on a driving simulator. In order to explore how a driver responds to warnings when approaching a tunnel, this study divided the experimental road into five zones according to warning positions. A comparative analysis was conducted to examine the changes in driving comfort, speeding behaviour, the standard deviation of speed, time headway (THW), fuel consumption, and emissions. Results showed that the HMI could be beneficial to speed adjustment before entering a tunnel. Meanwhile, HMI may affect the THW of vehicles. Drivers were usually more cautious when the HMI was on. However, no significant effects of the HMI for driving comfort and eco‐driving behaviour can be observed. It is expected that more efficient technology and different warning strategies can be developed to enhance eco‐safe driving for different zones because they have different effects. The findings of this study are also helpful for active safety management and for evaluating the effectiveness of CV systems.

Driving speeds are higher on freeways, and the visibility reduction occurring in freeway fog zones often increases traffic accidents. This study aims at assessing the impact of different levels of connected vehicle fog warning systems on driving behavior and safety. A connected vehicle fog warning system is developed based on driving simulators, and virtual scenes are developed based on fog zones. The connected vehicle technology includes three levels: a normal level, a level including a human-machine interface, and a level with both a human-machine interface and dynamic message signs. Speed and lateral deviation are chosen as assessment indicators and combined with sample entropy to evaluate the impact of the connected vehicle fog warning system on safety. The deceleration ratio of the warning point is used to evaluate the efficiency of the connected vehicle fog warning system. Results show that the connected vehicle fog warning system can significantly reduce driving speed, and that there are differences in the speed-reduction effectiveness for different technical levels. The connected vehicle fog warning system can reduce the lateral deviation and improve the lateral driving safety. From the perspective of change stability, speed safety entropy and lateral deviation safety entropy are increased, which indicates that the connected vehicle fog warning system will negatively impact safety because of the additional workload. Drivers’ responses are more pronounced in the human-machine interface group compared to the group with dynamic message signs, where the drivers maintained a lower speed. This study provides a reference for the studies on connected vehicle technology based on driving simulators and supports the optimization, design, and evaluation of connected vehicle fog warning systems.

In order to better control the fire problem due to coal oxidations, a novel composite inorganic retarding gel material processed from sodium-based bentonite junction and kaolin, silica, hydrogen peroxide and silicon oxide is developed. For studying the gel's properties the scanning electron microscopy (SEM) and the thermogravimetry (TG-DTG) are used to characterize microscopical structures and mass losses with the temperature change process, respectively. For quantifying the inhibitory effect of the novel gel on the spontaneous combustion process of coal oxidation, laboratory tests such as temperature-programmed oxidation and infrared spectroscopy are carried out. Changes of the gases generated from the treated coal sample by the novel gel under the temperature increasing are analyzed. The inhibitory effects of mud and MgCl2 solutions on coal spontaneous combustion are compared. The results show that the surface of the gel is flat and smooth in microscopic scale. Under the a high-temperature, the gel is stable and is not easy to decompose. In detail, the quality loss is within 10%. The novel gel with a concentration of 20% has a good inhibitory effect on CO release and spontaneous combustion in coal combustion. In addition, the novel gel can significantly reduce the consumption of –OH, –CH and other functional groups in the low-temperature oxidation reaction. Hence, the novel gel is a kind of Inhibitor material with a better comprehension performance. This study provides a novel gel for better preventing and controlling the coal spontaneous combustion hazard.

In this work, Cu-substituted MgAl2O4 ceramics were prepared via solid-state reaction. The crystal structure, cation distribution, and microwave dielectric properties of Mg1−xCuxAl2O4 ceramics were investigated. Cu2+ entered the MgAl2O4 lattice and formed a spinel structure. The substitution of Cu2+ ions for Mg2+ ions contributed to Al3+ ions preferential occupation of the octahedron and changed the degree of inversion. The quality factor (Qf) value, which is correlated with the degree of inversion, increased to a maximum value at x = 0.04 and then decreased. Ionic polarizability and relative density affected the dielectric constant (εr) value. The temperature coefficient of the resonant frequency (τf) value, which was dominated by the total bond energy, generally shifted to the positive direction. Satisfactory microwave dielectric properties were achieved in x = 0.04 and sintered at 1550 °C: εr = 8.28, Qf = 72,800 GHz, and τf = −59 ppm/°C. The Mg1−xCuxAl2O4 solid solution, possessing good performance, has potential for application in the field of modern telecommunication technology.

The composition, structure, and thermal behaviors of yttrium-containing phosphate glasses were studied in this work, and the glass-ceramics were prepared via the two-step crystallization method. The XRD and SEM-EDS results show the forming range of the phosphate glass system and the formation of YPO4 (xenotime) due to the addition of excessive Y2O3. The spectroscopic characterization of these glasses presented shifts of the infrared and Raman bands, demonstrating the depolymerization of the glass network and the formation of novel P–O–Y bonds, and the deconvoluted Raman spectra also exhibited the occurrence of the disproportionation reaction in the glass melting process. The content of non-bridging oxygen (NBOs) from the UV–vis spectra first increased and then decreased with increasing Y2O3. The thermal behaviors show that the Y2O3 reduced the crystallization peak temperature and the thermal stability of the glasses. The crystalline behaviors of the phosphate glass matrix were investigated at different crystallization times of 2–10 h, and a transformation of the crystallization mechanism from surface to volume crystallization was found. The yttrium phosphate glass-ceramics crystallized for 10 h exhibited transformation of the main crystalline phases with increasing Y2O3, and the grain-oriented crystalline surface became irregular.

ABSTRACT The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) outbreak urgently necessitates sensitive and convenient COVID-19 diagnostics for the containment and timely treatment of patients. We aimed to develop and validate a novel reverse transcription–loop-mediated isothermal amplification (RT-LAMP) assay to detect SARS-CoV-2. Patients with suspected COVID-19 and close contacts were recruited from two hospitals between 26 January and 8 April 2020. Respiratory samples were collected and tested using RT-LAMP, and the results were compared with those obtained by reverse transcription-quantitative PCR (RT-qPCR). Samples yielding inconsistent results between these two methods were subjected to next-generation sequencing for confirmation. RT-LAMP was also applied to an asymptomatic COVID-19 carrier and patients with other respiratory viral infections. Samples were collected from a cohort of 129 cases (329 nasopharyngeal swabs) and an independent cohort of 76 patients (152 nasopharyngeal swabs and sputum samples). The RT-LAMP assay was validated to be accurate (overall sensitivity and specificity of 88.89% and 99.00%, respectively) and diagnostically useful (positive and negative likelihood ratios of 88.89 and 0.11, respectively). RT-LAMP showed increased sensitivity (88.89% versus 81.48%) and high consistency (kappa, 0.92) compared to those of RT-qPCR for SARS-CoV-2 screening while requiring only constant-temperature heating and visual inspection. The time required for RT-LAMP was less than 1 h from sample preparation to the result. In addition, RT-LAMP was feasible for use with asymptomatic patients and did not cross-react with other respiratory pathogens. The developed RT-LAMP assay offers rapid, sensitive, and straightforward detection of SARS-CoV-2 infection and may aid the expansion of COVID-19 testing in the public domain and hospitals. IMPORTANCE We developed a visual and rapid reverse transcription–loop-mediated isothermal amplification (RT-LAMP) assay targeting the S gene for SARS-CoV-2 infection. The strength of our study was that we validated the RT-LAMP assay using 481 clinical respiratory samples from two prospective cohorts of suspected COVID-19 patients and on the serial samples from an asymptomatic carrier. The developed RT-LAMP approach showed an increased sensitivity (88.89%) and high consistency (kappa, 0.92) compared with those of reverse transcription-quantitative PCR (RT-qPCR) for SARS-CoV-2 screening while requiring only constant-temperature heating and visual inspection, facilitating SARS-CoV-2 screening in well-equipped labs as well as in the field. The time required for RT-LAMP was less than 1 h from sample preparation to the result (more than 2 h for RT-qPCR). This study showed that the RT-LAMP assay was a simple, rapid, and sensitive approach for SARS-CoV-2 infection and can facilitate COVID-19 diagnosis, especially in resource-poor settings.

The traffic congestion in ramp areas is becoming increasingly prominent. In the upstream segments of ramp areas, effective management and control of lane-changing behaviors can improve the road capacity and make full use of the existing road resource. With the continuous development and application of connected vehicle technologies, lane-changing behaviors can be performed by vehicle groups. Under a connected vehicle environment, the lane-changing behaviors by vehicle groups are controlled in the upstream segment in a ramp area, and the lane-changing behaviors can be completed prior to entering the ramp area. Finally, lane-changing strategies are optimized and identified. VISSIM simulates these proposed strategies. This paper considers the delay as the output index for analyzing and comparing various strategies. The results demonstrate that the delays of different lane-changing strategies are also different. If the delays of ramp areas are to be substantially reduced, it is necessary to continuously optimize the lane-changing strategies by vehicle groups in the upstream segments. This optimization of lane-changing strategies will effectively regulate drivers’ lane-changing behaviors, improve road safety, and increase traffic capacity.

With the increase of vehicle ownership and the rapid growth of urban traffic, the problem of congestion in the off-ramp area of the main expressway has become the main factor restricting overall section efficiency and inducing traffic accidents. This paper focuses on the problem of group collaborative lane-changing behaviors of off-ramp vehicles and through vehicles in off-ramp areas and proposes four kinds of vehicle group collaborative strategies based on different road space balance conditions. According to a three-lane expressway scene, a VISSIM-based simulation model is built and the optimization scheme is simulated and evaluated. The simulation results show that with the increase of traffic flow in off-ramp areas, a flow-balance strategy for downstream lanes where off-ramp vehicles merge with the outside lane in advance is more advantageous. When vehicles are leaving the main road, if traffic flow is heavy, the flow-balance strategy for lanes where off-ramp vehicles merge with the outside lane in advance (for example, the proportion of off-ramp vehicles in three lanes is 0 : 0 : 1) is better; otherwise, when the traffic flow on the main road is relatively small, the flow-balance strategy for lanes where off-ramp vehicles are distributed in lanes with different ratios (e.g., 1 : 3 : 6) is better. What is more, for future traffic management in connected vehicle environments, it can be concluded that collaborative vehicle lane-changing strategies with different traffic flow states can help to enhance traffic efficiency.

Connected vehicle technology has potentials to increase traffic safety, reduce traffic pollution, and ease traffic congestion. In the connected vehicle environment, the information interaction among people, cars, roads, and the environment is significantly enhanced, and driver behavior will change accordingly due to increased external stimulation. This paper designed a Vehicle-to-Vehicle (V2V) on-board unit (OBU) based on driving demand. In addition, a simulation platform for the interconnection and communication between the OBU and simulator was built. Thirty-one test drivers were investigated to drive an instrumented vehicle in four scenarios, with and without the OBU under two different traffic states. Collected trajectory data of the subject vehicle and the vehicle in front, as well as sociodemographic characteristics of the test drivers were used to evaluate the potential impact of such OBUs on driving behavior and traffic safety. Car-following behavior is an essential component of microsimulation models. This paper also investigated the impacts of the V2V OBU on car-following behaviors. Considering the car-following related indicators, the k-Means algorithm was used to categorize different car-following modes. The results show that the OBU has a positive impact on drivers in terms of speed, front distance, and the time to stable regime. Furthermore, drivers’ opinions show that the system is acceptable and useful in general.

Bamboo leaf-like CuO(b) and flaky-shaped CuO(f) were prepared by the hydrothermal method, and then combined with Al nanoparticles to form Al/CuO(b) and Al/CuO(f) by the ultrasonic dispersion method. The phase, composition, morphology, and structure of the composites were characterized by X-ray powder diffraction (XRD), transmission electron microscopy (TEM), scanning electron microscopy (SEM), and energy scattering spectrometer (EDS). The compatibility of CuO, Al/CuO and nitrocellulose (NC) was evaluated by differential scanning calorimetry (DSC). The effects of CuO and Al/CuO on the thermal decomposition of NC were also studied. The results show that the thermal decomposition reactions of CuO-NC composite, Al/CuO-NC composite, and NC follow the same kinetic mechanism of Avrami-Erofeev equation. In the cases of CuO and Al/CuO, they could promote the O-NO2 bond cleavage and secondary autocatalytic reaction in condensed phase. The effects of these catalysts have some difference in modifying the thermolysis process of NC due to the microstructures of CuO and the addition of Al nanopowders. Furthermore, the presence of Al/CuO(f) can make the Al/CuO(f)-NC composite easier to ignite, whereas the composites have strong resistance to high temperature. Compatibility and thermal safety analysis showed that the Al/CuO had good compatibility with NC and it could be used safely. This contribution suggests that CuO and Al/CuO played key roles in accelerating the thermal decomposition of NC.

The fiber-like bis-(dimethylglyoximato) nickel(II) complex, Ni(DMG)2 was successfully synthesized. The obtained samples were characterized by SEM-EDS, FT-IR, XRD, and XPS. The TG-DSC-FTIR-MS coupling technique was used to characterize the thermal decomposition behavior and evolved gas analysis of Ni(DMG)2. The non-isothermal decomposition reaction kinetic parameters were obtained by both combined kinetic analysis and isoconversional Vyazovkin methods. It was found that Ni(DMG)2 begins to decompose at around 280 °C, and a sharp exothermic peak is observed in the DSC curve at about 308.2 °C at a heating rate of 10 °C·min−1. The main gaseous products are H2O, NH3, N2O, CO, and HCN, and the content of H2O is significantly higher than that of the others. The activation energy obtained by the combined kinetic analysis method is 170.61 ± 0.65 kJ·mol−1. The decomposition process can be described by the random nucleation and growth of the nuclei model. However, it was challenging to attempt to evaluate the reaction mechanism precisely by one ideal kinetic model.

Several studies have researched the effect of dynamic message signs (DMSs) on the driving safety in work zones. However, only a few studies have examined the design of DMS control strategies in work zones. The purpose of this study is to investigate the effects of DMS control strategies on driving decisions and behaviors and to improve the driving safety in work zones by changing the content and placement of DMSs. In this study, five control strategies are proposed by combining five DMSs with different contents (“change lane” versus “go straight”). A total of 32 participants participated in this study. Each participant drove in five scenarios in a high-fidelity driving simulator corresponding to strategies 1-5. The results show that the control strategies have a significant effect on drivers’ decisions and behavior (e.g., the driving speed, acceleration, and lateral placement). All strategies reduce the drivers’ speeds and improve their control stability and compliance. After conducting analytic hierarchy process (AHP) analysis, strategy 2 was removed because the approaching speed exceeded the speed limit. The weight vectors of strategies 1, 3, 4, and 5 under free-flow traffic and traffic jam conditions are Ƴfree-flow traffic=0.25,0.28,0.17,0.23 and Ƴtraffic jam=[0.17,0.28,0.2,0.3], respectively. These results show that strategy 4 is not suitable for free-flow traffic in work zones, while strategies 5 and 3 are suitable for traffic jams in work zones. Strategy 3 is suitable for both free-flow traffic and traffic jams. The first occurrence of a decision sign that contains lane change content is key to the driver’s decision; in addition, the position of signage with such information should gradually be moved closer to work zones with increasing traffic flow.

The role of maceral compositions (vitrinite and inertinite) in the adsorption characteristics of coal has not been fully understood in terms of energy. In this study, using a microcalorimeter, the adsorption heat of maceral compositions for methane is directly measured for five groups of Chinese coal samples with different coal ranks. The results show that the adsorption heat of the maceral concentrates varies with increasing coal rank, but for the same coal sample, the vitrinite concentrates have a higher adsorption heat than the inertinite concentrates. Furthermore, the adsorption heat of both vitrinite and inertinite concentrates is highest at the long-flame coal stage. This finding indicates that the coalification and maceral compositions have significant effects on the adsorption heat of coal for methane. It is observed that although the inertinite concentrates have a larger pore volume, they are less microporous than their rank equivalent vitrinite concentrates, resulting in lower adsorption heat. Furthermore, it is revealed that the adsorption heat of both vitrinite and inertinite concentrates is primarily correlated to the content of oxygen-containing functional groups and aliphatic hydrocarbons.

High-speed railways (HSRs) have been widely deployed all over the world in recent years and China has entered an era with both high investments and rapid expansion of HSR transport infrastructure. One of the most challenging issues is how to keep the security and safety of millions of HSR infrastructures. Meanwhile, the emerging sensing and wireless sensor network (WSN) technologies for infrastructure health monitoring (IHM) are being substituted for traditional tethered monitoring systems. This paper presents a two-layer architecture of WSN which will be appropriate for infrastructure health monitoring of HSR. The upper layer is named as tree access network and the lower layer is called star detection network. By adapting to the special characteristics of IHM network, we design a short network address and an optimized communication frame structure, which can satisfy the actual requirements and special characteristics of the IHM network. In order to implement a better transmission performance, we propose a novel transmission power based method which adopts the knowledge update mechanism to detect the optimization result. In the end, the details of address assignment and network construction are discussed, and the effectiveness of the proposed method is validated by a practical instance.

The jam flow condition is one of the main traffic states in traffic flow theory and the most difficult state for sectional traffic information acquisition. Since traffic information acquisition is the basis for the application of an intelligent transportation system, research on traffic vehicle counting methods for the jam flow conditions has been worthwhile. A low-cost and energy-efficient type of multi-function wireless traffic magnetic sensor was designed and developed. Several advantages of the traffic magnetic sensor are that it is suitable for large-scale deployment and time-sustainable detection for traffic information acquisition. Based on the traffic magnetic sensor, a basic vehicle detection algorithm (DWVDA) with less computational complexity was introduced for vehicle counting in low traffic volume conditions. To improve the detection performance in jam flow conditions with a “tailgating effect” between front vehicles and rear vehicles, an improved vehicle detection algorithm (SA-DWVDA) was proposed and applied in field traffic environments. By deploying traffic magnetic sensor nodes in field traffic scenarios, two field experiments were conducted to test and verify the DWVDA and the SA-DWVDA algorithms. The experimental results have shown that both DWVDA and the SA-DWVDA algorithms yield a satisfactory performance in low traffic volume conditions (scenario I) and both of their mean absolute percent errors are less than 1% in this scenario. However, for jam flow conditions with heavy traffic volumes (scenario II), the SA-DWVDA was proven to achieve better results, and the mean absolute percent error of the SA-DWVDA is 2.54% with corresponding results of the DWVDA 7.07%. The results conclude that the proposed SA-DWVDA can implement efficient and accurate vehicle detection in jam flow conditions and can be employed in field traffic environments.

To obtain adequate traffic information, the density of traffic sensors should be sufficiently high to cover the entire transportation network. However, deploying sensors densely over the entire network may not be realistic for practical applications due to the budgetary constraints of traffic management agencies. This paper describes several possible spatial distributions of traffic information credibility and proposes corresponding different sensor information credibility functions to describe these spatial distribution properties. A maximum benefit model and its simplified model are proposed to solve the traffic sensor location problem. The relationships between the benefit and the number of sensors are formulated with different sensor information credibility functions. Next, expanding models and algorithms in analytic results are performed. For each case, the maximum benefit, the optimal number and spacing of sensors are obtained and the analytic formulations of the optimal sensor locations are derived as well. Finally, a numerical example is proposed to verify the validity and availability of the proposed models for solving a network sensor location problem. The results show that the optimal number of sensors of segments with different model parameters in an entire freeway network can be calculated. Besides, it can also be concluded that the optimal sensor spacing is independent of end restrictions but dependent on the values of model parameters that represent the physical conditions of sensors and roads.