Aiming at the problems of substantial pressure loss, small range ratio and contact measurement in traditional gas flowmeters, this paper designs a new type of data-filtering ultrasonic gas flowmeter. The flowmeter is composed of hardware circuits such as STM32F407 (ARM Cortex 32-bit microcontroller) main control chip and high-precision timing chip TDC-GP22 (time to digital converter). The software uses a new data-filtering algorithm combining Kalman filtering algorithm and arithmetic average algorithm to improve the measurement accuracy of ultrasonic gas flowmeter. Through experimental comparison, we find that the filtering algorithm effectively reduces the measurement error of the system. Within the flow range of 0.025–4 m³/h, the maximum relative error of the system measurement is 2.7404%, which meets the national standard for the measurement error of the 1.5-level instruments. Moreover, it reduces the zero-drift to about one half of the original, which significantly improves the stability of the system. The gas flowmeter has the characteristics of high accuracy, good stability, low power consumption, and the overall performance is significantly improved.

Ultrasonic water meters have current widespread problems of poor site adaptability, low measurement accuracy, and poor stability. A high-precision intelligent ultrasonic water meter with self-diagnosis function and adaptive technology was proposed in this paper, which is focus on improving the measurement accuracy and repeatability of the small pipe diameters. The hardware circuit design of the ultrasonic water meter studied in this paper adopts the low-power STM32L053 microcontroller with Cortex-M0 core architecture and the high-precision 11 ps time resolution timing chip TDC-GP30 to complete the metering function. The software combines pulse width ratio and amplitude voltage measurement technology to make the water meter have self-diagnosis function, avoid measurement errors caused by accidental factors, improve adaptability and measurement accuracy, also the application of adaptive measurement period method is used to improve measurement repeatability. The software adopts the moving average filtering algorithm, which effectively reduces the fluctuation of the time-of-flight(ToF) difference and improve the measurement accuracy of the flow point in the low zone (between the minimum flow and the boundary flow). The experimental verification results show that the accuracy of the small-caliber ultrasonic water meter can reach within ± 1.5 %, and the repeatability is less than 0.5 %. In the face of fluid disturbances, adaptive technology is used in this water meter to adjust the measurement period and carry out self-diagnostic function research, and automatically respond to deal with abnormal faults, thereby realizing the demand for intelligence.

In order to study the temperature distribution in a multi-functional oven and optimize the structural parameters of the oven, the internal temperature uniformity was improved. The test was conducted and the numerical simulation was conducted in two ways. The distribution of temperature field in each layer of ovens was measured in real time using a 13-point distributed thermocouple, and the oven temperature uniformity index was measured and analyzed. The temperature field inside the oven was numerically simulated using computational fluid dynamics. Investigated the heat conduction, convection and radiation effects respectively, and found out the main heat transfer mode of the oven. Further through the test of temperature measurement, verify the accuracy of the numerical simulation method. According to the results of the experiment and simulation, the reason of the uneven temperature field in the original structure of the oven was revealed and analyzed. By changing the structure of the oven tailgate, adjusting the air volume distribution, changing the distribution of the air outlet and other measures, greatly improving the uniformity of the temperature field inside the oven.

Increased speed is not only the goal of human sports but also the aim we seek to achieve for artificial microswimmers. Microswimmers driven by various power mechanisms have shown unrivaled advantages in drug delivery and cancer therapy. Attaining high mobility with limited power has been a never-ending motive for researchers. We show the speed of squirmer-type microswimmers can be noticeably enhanced as they are released to move along the surface of a pillar array, which is constructed of multiple pillars of equal sizes and spacing. An additional pressure force arising from the significant low pressure between the swimmers and the surface is likely behind this enhancement. According to their polarity strengths, the speed of the microswimmers can be double or triple (or even more) compared with that in an unbounded environment. In particular, for systems requiring microswimmers moving along a complex path, the transport rate, instead of being slowed down, may be increased owing to the curvatures of the path constructed by the pillar arrays. We reveal two types of motion for microswimmers after increasing the pillar gap: free and forced oscillating. Our study sheds light on the hydrodynamic interactions between squirmer-type microswimmers and a rough wall.

This study proposes a dual-parameter photonic crystal fiber-based surface plasmon resonance (SPR) sensor for simultaneous refractive index and temperature detection. The sensor architecture incorporates an asymmetric air hole lattice, featuring elliptical inner holes (aspect ratio: 1.5) to enhance birefringence and axially aligned outer circular holes to optimize surface plasmon coupling. Horizontally, symmetrically deposited silver films and silicon nitride layers constitute the RI-sensing channel, while a vertically machined PDMS-coated silver–nitride structure enables temperature responsivity. The temperature-sensing channel delivers a sensitivity of 20 nm/°C within 0–100 °C, while the RI channel achieves a peak sensitivity of 18,600 nm/RIU across n_a = 1.33–1.41 with a resolution of 5.38 × 10⁻⁶ RIU. Notably, cross-sensitivity between the two channels remains below 5%, underscoring the sensor’s capability for independent dual-parameter analysis. This low-interference, high-sensitivity platform holds significant promise for advanced biosensing applications requiring real-time multiparametric monitoring.

Induced charge electroosmotic flow is a new electric driving mode. Based on the Navier–Stokes equations and the Poisson–Nernst–Planck (PNP) ion transport equations, the finite volume method is adopted to calculate the equations and boundary conditions of the induced charge electroosmotic flow. In this paper, the formula of the induced zeta potential of the polarized solid surface is proposed, and a UDF program suitable for the simulation of the induced charge electroosmotic is prepared according to this theory. At the same time, on the basis of this theory, a cross micropump driven by induced charge electroosmotic flow is designed, and the voltage, electric potential, charge density, and streamline of the induced electroosmotic micropump are obtained. Studies have shown that when the cross-shaped micropump is energized, in the center of the induction electrode near the formation of a dense electric double layer, there exist four symmetrical vortices at the four corners, and they push the solution towards both outlets; it can be found that the average velocity of the solution in the cross-flow microfluidic pump is nonlinear with the applied electric field, which maybe helpful for the practical application of induced electroosmotic flow in the field of micropump.