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Incineration has become increasingly important in many large cities around the world because of fast urbanization and population growth. The benefits of energy production and large reduction in the waste volume to landfills also contribute to its growing adaptation for solid waste management for these cities. At the same time, the environmental impact of the pollutant gases emitted from the incineration process is a common concern for various stakeholders which must be properly addressed. To minimize the pollutant gas emission levels, as well as maximize the energy efficiency, it is critically important to optimize the combustion performance of an incinerator freeboard which would require the development of reliable approaches based on computational fluid dynamics (CFD) modeling. A critical task in the CFD modeling of an incinerator furnace requires the specification of waste characteristics along the moving grate as boundary conditions, which is not available in standard CFD packages at present. This study aims to address this gap by developing a numerical incinerator waste bed model.

A one-dimensional Lagrangian model for the incineration waste bed has been developed, which can be coupled to the furnace CFD model. The changes in bed mass due to drying, pyrolysis, devolatilization and char oxidation are all included in the model. The mass and concentration of gases produced in these processes through reactions are also predicted. The one-dimensional unsteady energy equations of solid and gas phases, which account for the furnace radiation, conduction, convection and heat of reactions, are solved by the control volume method.

The Lagrangian model is validated by comparing its prediction with the experimental data in the literature. The predicted waste bed height reduction, temperature profile and gas concentration are in reasonable agreement with the observations.

The simplicity and efficiency of the model makes it ideally suitable to be used for coupling with the computational furnace model to be developed in future (so as to optimize incinerator designs).

This study aims to analyze the differences of electrocardiograph (ECG) characteristics for female drivers in calm and anxious states during driving.

The authors used various materials (e.g. visual materials, auditory materials and olfactory materials) to induce drivers’ mood states (calm and anxious), and then conducted the real driving experiments and driving simulations to collect driver’s ECG signal dynamic data. Physiological changes in ECG during the stimulus process were recorded using PSYLAB software. The paired T-test analysis was conducted to determine if there is a significant difference in driver’s ECG characteristics between calm and anxious states during driving.

The results show significant differences in the characteristic parameters of female driver’s ECG signals, including (average heart rate), (atrioventricular interval), (percentage of NN intervals > 50ms), (R wave average peak), (Root mean square of successive), (Q wave average peak) and ( S wave average peak), in time domain, frequency domain and waveform in emotional states of calmness and anxiety.

Findings of this work show that ECG can be used to identify driver’s anxious and calm states during driving. It can be used for the development of personalized driver assistance system and driver warning system.

Only a few attempts have been made on the influence of human emotions on physiological signals in the transportation field. Hence, there is a need for transport scholars to begin to identify driver’s ECG characteristics under different emotional states. This study will analyze the differences of ECG characteristics for female drivers in calm and anxious states during driving to provide a theoretical basis for developing the intelligent and connected vehicles.

This study aims to explore the formation mechanism of aerodynamic noise of a high-speed maglev train and understand the characteristics of dipole and quadrupole sound sources of the maglev train at different speed levels.

Based on large eddy simulation (LES) method and Kirchhoff–Ffowcs Williams and Hawkings (K-FWH) equations, the characteristics of dipole and quadrupole sound sources of maglev trains at different speed levels were simulated and analyzed by constructing reasonable penetrable integral surface.

The spatial disturbance resulting from the separation of the boundary layer in the streamlined area of the tail car is the source of aerodynamic sound of the maglev train. The dipole sources of the train are mainly distributed around the radio terminals of the head and tail cars of the maglev train, the bottom of the arms of the streamlined parts of the head and tail cars and the nose tip area of the streamlined part of the tail car, and the quadrupole sources are mainly distributed in the wake area. When the train runs at three speed levels of 400, 500 and 600 km·h⁻¹, respectively, the radiated energy of quadrupole source is 62.4%, 63.3% and 71.7%, respectively, which exceeds that of dipole sources.

This study can help understand the aerodynamic noise characteristics generated by the high-speed maglev train and provide a reference for the optimization design of its aerodynamic shape.

Biodegradable polymers are widely used in personalized medical devices or scaffolds for tissue engineering. The manufacturing process should be finished with sterilization procedure. However, it is not clear how the different sterilization methods have an impact on the mechanical strength of the three-dimensional (3D)-printed parts, such as bone models or personalized mechanical devices. This paper aims to present the results of mechanical testing of polylactide-based bone models before and after sterilization.

Polylactide specimens prepared in fused filament fabrication technology were sterilized with different sterilization methods: ultraviolet (UV) and ethylene oxide. Mechanical properties were determined by testing tensile strength, Young’s modulus and toughness.

The tensile strength of material after sterilization was significantly higher after ethylene oxide sterilization compared to the UV sterilization, but in both sterilization methods, the specimens characterized lower tensile strength and Young’s modulus when compared to the control. In comparison of toughness results, there was no statistically significant differences. The findings are particularly significant in the perspective of using individual implants, bone grafts and dental guides.

Although fused filament fabrication (FFF) 3D printing devices equipped with UV light sterilization options are available, experimental results of the effect of selected sterilization methods on the mechanical strength of additively manufactured parts have not been described. This paper completes the present state of the art on the problem of sterilization of FFF parts from biodegradable materials.

High-speed maglev technology can address the issues of adhesion, friction, vibration and high-speed current collection in traditional wheel-rail systems, making it an important direction for the future development of high-speed rail technology.

This paper elaborates on the demand and significance of developing high-speed maglev technology worldwide and examines the current status and technological maturity of several major high-speed maglev systems globally.

This paper summarizes the challenges in the development of high-speed maglev railways in China. Based on this analysis, it puts forward considerations for future research on high-speed maglev railways.

This paper describes the development status and technical maturity of several major high-speed maglev systems in the world for the first time, summarizes the existing problems in the development of China's high-speed maglev railway and on this basis, puts forward the thinking of the next research of China's high-speed maglev railway.

The influence of road surface temperature (RST) on vehicles is becoming more and more obvious. Accurate predication of RST is distinctly meaningful. At present, however, the prediction accuracy of RST is not satisfied with physical methods or statistical learning methods. To find an effective prediction method, this paper selects five representative algorithms to predict the road surface temperature separately.

Multiple linear regressions, least absolute shrinkage and selection operator, random forest and gradient boosting regression tree (GBRT) and neural network are chosen to be representative predictors.

The experimental results show that for temperature data set of this experiment, the prediction effect of GBRT in the ensemble algorithm is the best compared with the other four algorithms.

This paper compares different kinds of machine learning algorithms, observes the road surface temperature data from different angles, and finds the most suitable prediction method.

Buildings use approximately 40% of global energy and are responsible for almost a third of the worldwide greenhouse gas emissions. They also utilise about 60% of the world’s electricity. In the last decade, stringent building regulations have led to significant improvements in the quality of the thermal characteristics of many building envelopes. However, similar considerations have not been paid to the number and activities of occupants in a building, which play an increasingly important role in energy consumption, optimisation processes, and indoor air quality. More than 50% of the energy consumption could be saved in Demand Controlled Ventilation (DCV) if accurate information about the number of occupants is readily available (Mysen et al., 2005). But due to privacy concerns, designing a precise occupancy sensing/counting system is a highly challenging task. While several studies count the number of occupants in rooms/zones for the optimisation of energy consumption, insufficient information is available on the comparison, analysis and pros and cons of these occupancy estimation techniques. This paper provides a review of occupancy measurement techniques and also discusses research trends and challenges. Additionally, a novel privacy preserved occupancy monitoring solution is also proposed in this paper. Security analyses of the proposed scheme reveal that the new occupancy monitoring system is privacy preserved compared to other traditional schemes.

The present shift and change in the human lifestyle across the world are undeniable. Currently, individuals spend a substantial amount of time indoors due to the global COVID-19 pandemic that strikes the entire world. This change in human lifestyle has devastating effects on human health and productivity. As a result, the influence of indoor environmental quality (IEQ) on the health and productivity of building users becomes a critical field of research that requires immediate attention. As a result, the purpose of this study is to review the state-of-the-art literature by establishing a connection between the factors that influence health and productivity in any given indoor environment.

The methodology involves a thorough review of selected published journals from 1983 to 2021, and the result was analysed through content analysis. The search included journal articles, books and conference proceedings on the critical factors influencing IEQ and their impact on building occupants, which was sourced from different databases such as ScienceDirect, Taylor, GoogleScholar and Web of Science.

The findings from the 90 selected articles revealed four critical factors influencing the quality of the indoor environment and are categorised into; indoor air quality, indoor thermal comfort, visual comfort and acoustic comfort. The findings suggested that when developing a system for controlling the quality of the indoor environment, the indoor air quality, indoor thermal comfort, visual comfort and acoustic comfort should be taken into account.

The indoor environment deeply impacts the health of individuals in their living and work environments. Industry must have a moral responsibility to provide health facilities in which people and workers feel satisfies and give conditions for prosperity. Addressing these essential aspects will not only help the decision-making process of construction professionals but also encourages innovative construction techniques that will enhance the satisfaction, wellness and performance of building occupants.