Study on preparation process parameters and tribological properties of porous PI materials

Purpose Previously, the effect of pore-forming agents on the properties of pore size and morphology was studied. In this paper, we determine the optimal combination of parameters by tensile strength and perform tribological tests with optimal combination of parameters. Design/methodology/approach In this paper, porous polyimide (PI) materials were fabricated using vacuum hot molding technology. The orthogonal experiment was designed to test the mechanical properties of porous PI materials with the process parameters and the content of pore-forming agent as the changing factors. The porous PI oil-bearing materials were obtained by vacuum immersion, and tribological test were carried out. Findings The results showed that porous PI oil-bearing materials are suitable for low-speed and low-load conditions. The actual value of the friction coefficient basically match with the theoretical value of the regression analysis, and the errors of the friction coefficient are within 10% and 3%, respectively, which proves that the method used in the study is feasible for the friction coefficient prediction. Originality/value In this paper, we have produced a new porous oil-bearing material with good tribological properties. This study can effectively predict the friction coefficient of PI porous material.

Variable Speed Diesel Generators: Performance and Characteristic Comparison

Diesel generators (DGs) are set to work as a backup during power outages or support the load in remote areas not connected to the national grid. These DGs are working at a constant speed to produce reliable AC power, while electrical energy demand fluctuates according to instantaneous needs. High electric loads occur only for a few hours a day in remote areas, resulting in oversizing DGs. During a low load operation, DGs face poor fuel efficiency and condensation of fuel residues on the walls of engine cylinders that increase friction and premature wear. One solution to increase combustion efficiency at low electric loads is to reduce diesel engine (DE) speed to its ideal regime according to the mechanical torque required by the electrical generator. Therefore, Variable Speed Diesel Generators (VSDGs) allow the operation of the diesel engine at an optimal speed according to the electrical load but require additional electrical equipment and control to maintain the power output to electrical standards. Variable speed technology has shown a significant reduction of up to 40% fuel consumption, resulting in low GHG emissions and operating costs compared to a conventional diesel generator. This technology also eliminates engine idle time during a low load regime to have a longer engine lifetime. The main objective of this survey paper is to present the state of the art of the VSDG technologies and compare their performance in terms of fuel savings, increased engine lifetime, and reduced greenhouse gases (GHG) emissions. Various concepts and the latest VSDG technologies have been evaluated in this paper based on their performance appraisal and degree of innovation.

Effect of low-load resistance training with different degrees of blood flow restriction in patients with knee osteoarthritis: study protocol for a randomized trial

Background Knee osteoarthritis (KOA) is a common degenerative disease that causes pain, functional impairment, and reduced quality of life. Resistance training is considered as an effective approach to reduce the risk of muscle weakness in patients with KOA. Blood flow restriction (BFR) with low-load resistance training has better clinical outcomes than low-load resistance training alone. However, the degree of BFR which works more effectively with low-load resistance training has not been determined. The purpose of this study is to evaluate the effectiveness of different degrees of BFR with low-load resistance training in patients with KOA on pain, self-reported function, physical function performance, muscle strength, muscle thickness, and quality of life. Methods This is a study protocol for a randomized, controlled trial with blinded participants. One hundred individuals will be indiscriminately assigned into the following groups: two training groups with a BFR at 40% and 80% limb occlusion pressure (LOP), a training group without BFR, and a health education group. The three intervention groups will perform strength training for the quadriceps muscles twice a week for 12 weeks, while the health education group will attend sessions once a week for 12 weeks. The primary outcome is pain. The secondary outcomes include self-reported function, physical function performance, muscle strength of the knee extensors, muscle mass of the quadriceps, quality of life, and adverse events. Intention-to-treat analysis will be conducted for individuals who withdraw during the trial. Discussion Previous studies have shown that BFR with low-load resistance training is more effective than low-load resistance training alone; however, a high degree of BFR may cause discomfort during training. If a 40% LOP for BFR could produce similar clinical outcomes as an 80% LOP for BFR, resistance training with a low degree of BFR can be chosen for patients with KOA who are unbearable for a high degree of BFR. Trial registration Chinese Clinical Trial Registry ChiCTR2000037859 (http://www.chictr.org.cn/edit.aspx?pid=59956&htm=4). Registered on 2 September 2020

Misfire Detection Using Crank Speed and Long Short-Term Memory Recurrent Neural Network

In this work, a new approach was developed for the detection of engine misfire based on the long short-term memory recurrent neural network (LSTM RNN) using crank speed signal. The datasets are acquired from a six-cylinder-inline, turbo-charged diesel engine. Previous works investigated misfire detection in a limited range of engine running speed, running load or misfire types. In this work, the misfire patterns consist of normal condition, six types of one-cylinder misfire faults and fifteen types of two-cylinder misfire faults. All the misfire patterns are tested under wide range of running conditions of the tested engine. The traditional misfire detection method is tested on the datasets first, and the result show its limitation on high-speed low-load conditions. The LSTM RNN is a type of artificial neural network which has the ability of considering both the current input in-formation and the previous input information; hence it is helpful in extracting features of crank speed in which the misfire-induced speed fluctuation will last one or a few cycles. In order to select the engine operating conditions for network training properly, five data division strategies are attempted. For the sake of acquiring high performance of designed network, four types of network structure are tested. The results show that, utilizing the datasets in this work, the LSTM RNN based algorithm can overcome the limitation at high-speed low-load conditions of traditional misfire detection method. Moreover, the network which takes fixed segment of raw speed signal as input and takes misfire or fault-free labels as output achieves the best performance with the misfire diagnosis accuracy not less than 99.90%.

Research on Water Droplet Movement Characteristics in the Last Two Stages of Low-Pressure Cylinder of Steam Turbine Under Low Load Conditions

In the operating process of the coal-fired generation during flexible peaking regulation, the primary and secondary water droplets in the steam flowing through the last two stages of the low-pressure cylinder could influence the efficiency and safety of the steam turbine definitely. However, systematic analysis of the movement characteristics of water droplets under low-load conditions is scarcely in the existing research, especially the ultra-low load conditions below 30%. Toward this end, the more novel algebraic slip model and particle transport model mentioned in this paper are used to simulate the primary and secondary water droplets. Taking a 600 MW unit as a research object, the droplets motion characteristics of the last two stages were simulated within four load conditions, including 100, 50, 40, and 30% THA. The results show that the diameter of the primary water droplets is smaller, ranging from 0 to 1 µm, during the flexible peak regulation process of the steam turbine. The deposition is mainly located at the entire moving blades and the trailing edge of the last two stator blades. With the load decreasing, the deposition effect decreases sustainably. And the larger diameters of secondary water droplets range from 10 to 300 µm. The erosion of secondary water droplets in the last stage is more serious than that of the second last stage for different load conditions, and the erosion of the second last stage could be negligible. The pressure face and suction face at 30% blade height of the last stage blade have been eroded most seriously. The lower the load, the worse erosion from the secondary water droplets, which poses a potential threat to the fracture of the last stage blades of the steam turbine. This study provides a certain reference value for the optimal design of steam turbine blades under flexible peak regulation.

Thermal System Simulation Study of Wide-Load Out-Of-Stock Technical Transformation to Reduce SCR Inlet Flue Gas Temperature of 300MW Subcritical Boiler

During the operation of a 300MW subcritical boiler of a power plant, there is a low temperature of the SCR inlet flue gas under medium and low load conditions. In order to effectively solve the problem of low SCR inlet temperature under low load conditions, and improve the adaptability of the coal type. Three kinds of wide load denitration technology reform schemes are proposed. With the boiler thermal system simulation software BESS, the thermal calculations of the three transformation schemes were carried out. The results show that: the Scheme C is the optimal solution. After the transformation, the temperature of the SCR inlet flue gas increased by 21°C under the ultra-low load condition, and the exhaust gas temperature increased by about 7°C. At the same time, the possible impacts of the reform of the Scheme C and the key issues that need to be paid attention to during the transformation process are evaluated and discussed.