No abstract

Three-point bending tests on notched beams of three types of steel fiber-reinforced self-compacting concrete (SFRSCC) have been performed by using both a servo-hydraulic machine and a drop-weight impact instrument. The lo ading rates had a range of six orders of magnitude from 2.20 × 10−3 mm/s (quasi-static) to 2.66 × 103 mm/s. These SFRSCCs had the same matrix, but various types of steel fiber (straight and hooked-end) and contents (volume ratios), 0.51%, 0.77% and 1.23%, respectively. The results demonstrate that the fracture energy and the flexural strength increase as the loading rate increases. Moreover, such tendency is relatively moderate at low rates. However, at high rates it is accentuated. For the 0.51% fiber content, the dynamic increase factors of the flexural strength and the fracture energy are approximately 6 and 3, while for the 1.23% fiber content, they are around 4 and 2, respectively. Thus, the higher the fiber content the less rate sensitivity there is.

In the present work, the nano-Aluminum oxide (Al 2 O 3 ), nano-Silicon Carbide (SiC), or a hybrid of them were infused into epoxy resin with an ultrasonic system with various weight percentage ratios of the nanoparticles. Small punch testing (SPT) and indirect tension testing were adopted to measure the tensile properties of the present nanocomposites. Pin-on-ring wear testing was also performed to examine wear performance of epoxy Al 2 O 3 and SiC nanocomposites. The Finite Element Analysis method is introduced to simulate the indirect tension test and SPT to give a complete vision of the stress distribution in the nanocomposite specimen during the loading, and to examine its mode of failure. Good agreement between the numerical and experimental results was observed. The addition of nanoparticles from Al 2 O 3 or SiC improves the wear resistance of epoxy. Furthermore, epoxy with nano-Al 2 O 3 has a higher wear resistance than that with nano-SiC. The tensile strength and modulus of elasticity of epoxy are reduced by adding the Al 2 O 3 nanoparticle. The synergistic effect is not observed in the present study.

The main aim of this work is to establish a sensor MESH network using an ESP-MESH networking protocol with the ESP32 MCU (a Wi-Fi-enabled microcontroller) for indoor and outdoor air quality monitoring in real time. Each sensor node is deployed at a different location on the college campus and includes sensor arrays (CO2, CO, and air quality) interfaced with the ESP32. The ESP-MESH networking protocol is a low-cost, easy-to-implement, medium-range, and low-power option. ESP32 microcontrollers are inexpensive and are used to establish the ESP-MESH network that allows numerous sensor nodes spread over a large physical area to be interconnected under the same wireless network to monitor air quality parameters accurately. The data of different air quality parameters (temperature, humidity, PM2.5, gas concentrations, etc.) is taken (every 2 min) from the indoor and outdoor nodes and continuously monitored for 72 min. A custom time-division multiple-access (TDMA) scheduling scheme for energy efficiency is applied to construct an appropriate transmission schedule that reduces the end-to-end transmission time from the sensor nodes to the router. The performance of the MESH network is estimated in terms of the package loss rate (PLR), package fault rate (PFR), and rate of packet delivery (RPD). The value of the RPD is more than 97%, and the value of the PMR and PER for each active node is less than 1.8%, which is under the limit. The results show that the ESP-MESH network protocol offers a considerably good quality of service, mainly for medium-area networks.

In this paper, a solar photovoltaic model integrated with brushless DC motor via DC to DC zeta converter is controlled in two stage. In first stage, a fuzzy rule based maximum power point tracking (PPT) is proposed to generate the pulse for DC to DC zeta converter. It is efficient intelligent control approach to extract maximum power from the solar PV system and enhance the speed to track the maximum power. The basic three process of fuzzy logic controller (FLC) are fuzzifier, inference and defuzzifier where the defuzzification process is used center of gravity (COG) method to convert its original value. The FLC to extract maximum PPT for solar PV based brushless DC motor can be examined the performance under transient and dynamic condition with different solar insolation. Moreover, in second stage a trapezoidal control approach based electronic commutation is chosen to generate the pulses of voltage source inverter (VSI) and it offers the smooth control of the brushless DC motor which can easily applicable for water pumping or irrigation purpose. A second stage, trapezoidal control approach is close loop control algorithm using sensorless drive. The performance of proposed fuzzy rule based control algorithm is shown using simulation results on MATLAB platform.