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Machining dynamics plays an essential role in machine tools (MTs) and machining operations, directly impacting the material removal rate, surface quality, and dimensional accuracy. With the increasing use of numerical control (NC) MTs and increasing automation of production, machining inaccuracy due to thermal deformation has become a significant issue. Furthermore, since the rotation speed and feed rate have risen, more heat is produced in MTs. In addition, since high machining precision is now required, techniques to avoid or regulate thermal deformation are also needed. Traditionally, researchers used the finite element method, support vector method (SVM), regression analysis method, neural network, and other methods to predict and compensate for the thermal deformation of MT spindles. However, these methods do not directly reduce the thermal errors caused by the heat source to improve the accuracy of MTs. Therefore, in this study, a cooling control method is proposed to reduce the impact of heat on the spindle by using a thermal suppression technique accompanied by the adaptive neuro- fuzzy inference system (ANFIS) control method to predict the static thermal behavior of a spindle. The root mean square error (RMSE) is used as the ANFIS evaluation index to reflect the quality of the prediction model. This method is implemented in Simulink to simulate the dynamics of the coolant during the real-time monitoring of the cutting and resting positions of the MT. Finally, a thermal deformation prediction model is generated to demonstrate that the cooling control method developed in this study can be applied to the intelligent cooling of an MT. It is shown that the developed ANFIS prediction model is efficient for controlling cooling. A simulation also shows that this method can reduce the running cost, energy consumption and accurately predict the thermal deformation of MT spindles. It is predicted that the most suitable coolant pump operating frequencies for the spindle at rotation speeds of 2000, 8000, 10000, and 12000 rpm are 20, 40, 40, and 60 Hz and the reductions of the spindle heat are 92.4, 99.9, 80.1, and 60.2%, respectively, with a prediction accuracy within 4.745 µm. [ABSTRACT FROM AUTHOR]

We proposed a vapor injection dynamic control method for a two-stage compression heat pump system with a circulating water heating method in order to attain high operational performance with increasing condensation temperature of the heat pump. During the water heating process, the circulating water is heated from a normal temperature of 35 °C to a high temperature of 80 °C and the corresponding condensation temperature of the refrigeration cycle is also increased from 40 to 85 °C. Owing to the dynamical increases in the circulating water temperature and condensation temperature of the refrigeration cycle, the automatic and optimal control of the heat pump system in operation cannot be implemented through the traditional feedback control method by directly sensing the vapor injection pressure of the refrigeration cycle. It is found that, for optimal performance of the developed system in dynamical operation, the vapor injection pressure of the heat pump under each condensation temperature is related to the corresponding subcooling degree. The subcooling degree of the refrigeration cycle was obtained from the temperature sensors in the condenser and at the refrigerant inlet of the expansion valve. In this study, regarding the optimal performance operation of the heat pump system, a regression model of the subcooling degree in terms of different condensation temperatures of the refrigeration cycle was built in order to control the vapor injection pressure with the dynamic variations of the condensation temperature of the refrigeration cycle. By sensing the condensation temperature of the refrigeration cycle, the corresponding subcooling degree of the refrigeration cycle for the optimal vapor injection pressure can be determined from the regression model. Finally, the openness of the control valve on the vapor injection piping route was automatically adjusted to approach the corresponding optimal subcooling degrees of different condensation temperatures to attain high operational performance. The experimental results are in agreement with the theoretical results within the range of 10-20%. In comparison with the system with constant vapor injection pressure, the coefficent of heating perfromance (COPh) of the system can be increased by 20% with the vapor injection pressure control. From the experimental results, it is found that COPh and the required power of the heat pump system using the proposed automatic control method are in reasonable agreement with those obtained by the optimal adjustment at different condensation temperatures. This indicates that the proposed model of automatic vapor injection can be applied to dynamically control the intermediate pressure of the refrigeration cycle to maintain high operational performance of a two-stage compression heat pump. [ABSTRACT FROM AUTHOR]

In this paper, we expand our previous paper [Mod. Phys. Lett. B 32 (2018) 1750355] from the calculation of planar graphene with one band (pz) to the calculation of two-dimensional buckled group-IVA materials with multiple bands (S, px, py, and pz); thus, the proposed method is a fullband model. Furthermore, the proposed method is established using a nonequilibrium Green's function (NEGF) method in association with the complex energy-band technique, so it is in the full-quantum framework. Unlike other methods, the proposed method is noniterative and thus computationally cost-efficient. [ABSTRACT FROM AUTHOR]

Machine tools are an indispensable part of the modern manufacturing industry, by which many items are produced. In the manufacturing process, machining accuracy is very important for the precision of products. However, the thermal error accounts for 40-70% of the machining error. Most of the machine tool heat created during machining originates from the rotating spindle owing to the internal bearing friction and motor power loss. Cooling systems are designed to remove the heat generated in the spindle in real time by coolant circulation to maintain the spindle temperature and improve the machining accuracy of the machine tool. In this study, the thermal deformation of a spindle was investigated under different rotating spindle speeds. To adapt to cooling demand variations at different rotating speeds, the cooling capacity of the cooling system was controlled by changing the supply volume and supply temperature of the coolant to the spindle. The effects of supply coolant volume, supply coolant temperature, and ambient temperature on the thermal deformation of the spindle were analyzed. A regression model for the driving frequency of the coolant pump in terms of the spindle rotational speed and coolant temperature difference was developed. By changing the supply coolant volume and coolant temperature difference in accordance with the spindle rotating speed, the accuracy of the deformation was reduced by up to 25%, and the required time to attain a steady state was also shortened. The shortest required time of 12 min was attained with a pump driving frequency of 80 Hz and a coolant temperature difference of 4 °C at a spindle rotating speed of 24000 rpm. The developed regression model was verified in three dynamical operational processes with different periods in which the spindle rotating speed was changed. [ABSTRACT FROM AUTHOR]

The fundamental purpose of this study is to produce a catalyst for catalyzing the hydrogen production reaction of sodium borohydride (NaBH4). The catalyst for catalyzing this reaction includes a catalyst carrier and a metal catalyst. We use three catalyst bed temperatures with the same ?-Al2O3 carrier and gas sensor, with different chelate concentration processes to make the catalyst. The metal catalyst selected is Co. The effects of the catalyst produced by different catalyst carrier processes on the hydrogen production efficiency and total hydrogen yield of NaBH4 solution are discussed. The experiment shows that when the catalyst soaked in 30 wt% Co/?-Al2O3 is used at 70 ?, the rate and hydrogen production efficiency are 5300 ml/min g cat and 82.92%, respectively. The catalyst has a vigorous hydrolytic hydrogen production reaction with NaBH4. This catalyst can be combined with a fuel cell system for hydrolytic hydrogen production to generate power in the future, enabling the portability and efficiency of stored hydrogen to be enhanced effectively. [ABSTRACT FROM AUTHOR]

Real-time, reliable, accurate, and comprehensive ambient air condition information over time is required in many fields and applications, including medical, scientific, and industrial applications as well as daily life human activities. Such information can be used to enhance the quality and living conditions of humans. Moreover, reliable, accurate, and comprehensive environment condition information helps in solving environmental problems. In this paper, we present a data logging and monitoring system to record air ambient conditions, air quality, and daily weather conditions using a low-cost, fully automated, wireless, real-time, reliable, continuous-logging, portable, and user-friendly device. The proposed device consists of two main parts: a monitoring device and a monitoring terminal. The monitoring terminal is based on an embedded system and a smart electronic sensor array to sense some environmental parameters such as ambient temperature, ambient relative humidity, ambient air pressure, carbon monoxide level, carbon dioxide level, gas methane level, dust particulate level, wind speed, wind direction, and rainfall. All parameter data are recorded in a data logger and displayed on a liquid crystal display (LCD). Environmental parameter data are sent to the monitoring terminal by a Bluetooth module. The parameter data is visualized on a user-friendly graphical user interface (GUI) application that can work on either a notebook or a smartphone platform. The test and validation show that the developed system successfully accomplished environmental condition logging and monitoring wirelessly. The environmental conditions were recorded and monitored by the developed system over a long period of time and in real time with a data transmission rate delay of 2.8 s from the monitoring device to the monitoring terminal. [ABSTRACT FROM AUTHOR]

This study investigated the ambient environmental temperature effect on the positioning accuracy of a periodically-moving carrier. The moving carrier was operated in an environmental chamber in which the operational temperature could be controlled by an air conditioning system. Different operational temperature modes, including a stable environment, a rise in temperature, a decline in temperature, summer daytime hours, and winter nighttime hours in terms of seasonal climate change in Taiwan, were generated within the environmental chamber by an air conditioning system to investigate the operational temperature's effect on positioning accuracy. From the experimental measurements of a periodically-moving carrier, it is found that the operational temperature conditions can significantly affect the positioning accuracy of the moving carrier, especially in the case of an operational temperature decline. Under stable operational conditions, the positioning accuracy of the moving carrier can be considerably improved. In comparison to the case of an operational temperature decline, the positioning accuracy improvement can reach 29.6%. Moreover, the effect of the temperature distributions within the chamber on the positioning accuracy was further investigated. It was found that, with a parallel flow pattern in the chamber, the positioning accuracy can be further enhanced. [ABSTRACT FROM AUTHOR]