Search results

This study aims to establish a multi-physics-coupled model for an electrostatic particulate matter (PM) sensor. The focus lies on investigating the deposition patterns of particles within the sensor and the variation in the regeneration temperature field.

Computational simulations were initially conducted to analyse the distribution of particles under different temperature and airflow conditions. The study investigates how particles deposit within the sensor and explores methods to expedite the combustion of deposited particles for subsequent measurements.

The results indicate that a significant portion of the particles, approximately 61.8% of the total deposited particles, accumulates on the inside of the protective cover. To facilitate rapid combustion of these deposited particles, a ceramic heater was embedded within the metal shielding layer and tightly integrated with the high-voltage electrode. Silicon nitride ceramic, selected for its high strength, elevated temperature stability and excellent thermal conductivity, enables a relatively fast heating rate, ensuring a uniform temperature field distribution. Applying 27 W power to the silicon nitride heater rapidly raises the gas flow region's temperature within the sensor head to achieve a high-temperature regeneration state. Computational results demonstrate that within 200 s of heater operation, the sensor's internal temperature can exceed 600 °C, effectively ensuring thorough combustion of the deposited particles.

This study presents a novel approach to address the challenges associated with particle deposition in electrostatic PM sensors. By integrating a ceramic heater with specific material properties, the study proposes an effective method to expedite particle combustion for enhanced sensor performance.

The purpose of this study is to synthesize a new kind of a cationic-type UV-curing prepolymer diepoxycyclohexylethyl tetramethyldisiloxane, which is used to replace the current prepolymers’ common cycloaliphatic epoxy resins to prepare a novel 3D printing stereolithography material.

Diepoxycyclohexylethyl tetramethyldisiloxane was characterized and analyzed by FT-IR and 1HMR. Diepoxycyclohexylethyl tetramethyldisiloxane was compounded with a polycaprolactone polyol, some acrylates and photoinitiators to prepare a novel 3D printing stereolithography resin (3DPSLR11). Optical properties of 3DPSLR11 were investigated by HRPL-150A stereolithography apparatus and INITELLI-RAY400 UV-curing system. Tensile mechanical properties of printed 3DPSLR11 specimens were tested by WDW-50-type universal testing machine, and the glass transition temperature (Tg) was determined by DMA. Rectangle plates and double-cantilever parts were fabricated by using the stereolithography apparatus with 3DPSLR11 as the printing material, and the dimension shrinkage factors and the curl factors of the parts were investigated.

The experimental results showed that the critical exposure (Ec) of the 3D printing 3DPSLR11 was 11.6 mJ/cm², its penetration depth (Dp) was 0.18 mm, the tensile strength of the cured 3DPSLR11 was 40.1 MPa, the tensile modulus was 1,741.4 MPa, the elongation at break was 15.3%, Tg was 113°C, the dimension shrinkage factor was less than 0.85% and the curl factor was less than 8.00%.

In this work, a novel 3D printing 3DPSLR11 was prepared with diepoxycyclohexylethyl tetramethyldisiloxane as a main prepolymer. The novel 3DPSLR11 possessed excellent photosensitivity, and its cured products had good mechanical and thermal properties. The accuracy and resolution of the fabricated parts were high with 3DPSLR11 for stereolithography in 3D printing, which showed that 3DPSLR11 has potential application value as 3D printing material.

The purpose of this study was to investigate the thermal deformation effect of a machine tool frame on hole registration accuracy. Hole registration accuracy represents the drilling performance of a machine tool, and it greatly depends on the thermal deformation of the machine frame structures in practical engineering. Reducing thermally induced errors is crucial to improve the hole quality.

First, the thermal design of the machine frame was performed via an optimization procedure to reduce the thermal deformation at an early stage. Then, a thermal–mechanical coupling finite element method model was established to quantify the thermal deformation of the machine tool under environmental temperature fluctuations, and the validity of the presented model was confirmed experimentally using laser interferometry. Finally, a series of drilling tests, including micro-holes and medium holes, was carried out to practically investigate the hole drilling registration accuracy of the machine with a mineral casting frame under different thermal conditions.

Hole registration accuracy showed positional dependency and distinctly non-linear behaviour at different drilling axes which was closely related with the thermal conditions. The positional deviations of medium holes and micro-holes all showed an increasing trend in different degrees under the same temperature fluctuations, and the former were more sensitive to the latter. Therefore, keeping the drilling workshop under thermally stable conditions is crucial for improving the drilling performance of the machine.

The goal of this paper is to reveal the mechanism of hole registration accuracy variations with thermal fluctuations and to provide a strategy for the machine tool industry to further improve the drilling performance during the machining process.

Agricultural insurance has become increasingly important to farmers' livelihood and production in rural China. Yet despite the enormous governmental subsidizing efforts, the insurance participation rate remains below expectations. This study revisits the linkage between farmers' risk attitudes and crop insurance utilization by providing a cross-cutting perspective such that the role of risk aversion is re-scrutinized in Chinese “kindred” village economies.

The authors administrated a lottery-based multiple price list (MPL) experiment by recruiting rice farmers from 12 villages in Sichuan province in southwestern China. Using the experimental data, farmers' risk attitudes are assessed and coefficients of risk aversion are estimated within the rank-dependent expected utility (RDEU) framework by maximizing a structured likelihood function.

This study provides substantiating evidence that rice farmers in southwestern China exhibit relatively high risk aversion. The authors also provide suggestive evidence of the positive relationship between farmers' risk aversion and crop insurance utilization. In addition, findings reveal that kinship network has a negative effect on crop insurance utilization, such that farmers who are connected in higher degree of kinship network have lower likelihood of crop insurance utilization, which suggests that kinship network may be substitute for formal crop insurance. Result also demonstrates that the incentive effect of risk aversion on farmers' crop insurance participation manifests differently depending on the degree of kinship network in rural China.

This study provides a cross-cutting perspective by scrutinizing the effects of farmers' risk attitudes and kinship network on crop insurance participation in rural China, which has received relatively little attention in the literature. Conclusions on the effects of risk aversion on crop insurance participation have been mixed in previous studies. In addition, to the best of our knowledge, little has been done to explicitly examine the influence of social proximity and networks on farmers' insurance uptake. This study attempts to fill both gaps. This study provides new insights which might shed lights on the understanding of farmers' crop insurance participation in rural China.

The former residences of historical figures are typical landscape elements of historic districts, which are characterised by the styles of these residences and spiritual historical figures cultures. The purpose of this paper is to determine how the former residences respond once the historical figures living there have passed.

The history of human culture and progression of urban construction – which are submerged in societal transformation – is recorded for old Beijing city. Narrative space theory is used and methods such as a content analysis, map overlay and the Geographic Information System are employed to analyse the selected 300 former residences of historical figures in old Beijing city.

The results are as follows: the political setting played a key role in the evolution process, three political narrative areas in the inner city and one cultural narrative area in the outer city form the narrative spatial structure of the former residences of historical figures, “government construction” and “resident construction” are the main reasons for the loss and destruction of narrative spaces and ordinary life is an important channel for showcasing the history of former residences. The narrative spaces of these residences carry double histories, namely, the development of human history and of city construction.

Different from former studies that focus on the preservation of the single historical building, this study explores the integral logic of historic buildings in the whole city through narrative space theory to get a combination of culture and space.

This study aims to propose a force control algorithm based on neural networks, which enables a robot to follow a changing reference force trajectory when in contact with human skin while maintaining a stable tracking force.

Aiming at the challenge of robots having difficulty tracking changing force trajectories in skin contact scenarios, a single neuron algorithm adaptive proportional – integral – derivative online compensation is used based on traditional impedance control. At the same time, to better adapt to changes in the skin contact environment, a gated recurrent unit (GRU) network is used to model and predict skin elasticity coefficients, thus adjusting to the uncertainty of skin environments.

In two robot–skin interaction experiments, compared with the traditional impedance control and robot force control algorithm based on the radial basis function model and iterative algorithm, the maximum absolute force error, the average absolute force error and the standard deviation of the force error are all decreased.

As the training process of the GRU network is currently conducted offline, the focus in the subsequent phase is to refine the network to facilitate real-time computation of the algorithm.

This algorithm can be applied to robot massage, robot B-ultrasound and other robot-assisted treatment scenarios.

As the proposed approach obtains effective force tracking during robot–skin contact and is verified by the experiment, this approach can be used in robot–skin contact scenarios to enhance the accuracy of force application by a robot.