Springer Science and Business Media LLC

‘Storage oxidation stability’ is one of the most significant criteria for appraising the biodiesel quality. Poor oxidation stability is the chief technical blockage related with the commercialization of biodiesel. The present paper investigates the effects of Tert- butyl hydroquinone (TBHQ) antioxidant additive concentrations on the long-term storage stability, thermal stability and accelerated oxidation stability of Calophyllum inophyllum biodiesel. Fourier transform infra-red (FTIR) spectroscopy was used to characterize the biodiesel oxidation variability, following the regions of C-H and O-H bonds in FTIR spectrum for different concentrations of TBHQ. Addition of TBHQ at 1000 ppm concentration (B100A3) with pure biodiesel enhances the oxidation stability by 94.67 %, storage stability by 14.47 % and thermal stability by 69.55 %; whereas further concentration of antioxidant deteriorates the formation of hydrophobic and hydrophilic clusters between biodiesel/antioxidant compounds, which is characterized by FTIR spectrum data. It is concluded that the Calophyllum inophyllum biodiesel could be accumulated for an extensive period by dosing 1000 ppm of TBHQ antioxidant.

An array of air chambers embedded on the tunnel track is numerically investigated for different configurations. The air chambers act as an in-tunnel countermeasure to alleviate non-linear steepening of compression waves during propagation process thereby mitigating emission of high amplitude micro-pressure waves (MPWs) from the exit portal. The air chambers are designed to entrap the incoming flow and induce damping behavior so as to reduce wave steepening in tunnels. Initially, qualititative comparisons are made between Helmholtz resonator and damping type air chambers. Thereafter, the quantitative assessment of the compression wave properties are checked in detail. From results, over damped air chamber shows 60 % reduction in peak over pressure for weak compression wave whereas the Helmholtz resonator and critically damped shows 35 % and 22 %, respectively. Similarly, due to the presence of over damped air chamber, 17 % reduction in maximum pressure gradient is noticed while critically damped shows close to 10 % reduction.

In micro-turbojet engines with less than 350 kW power, it is not easy to find a suitable fuel injector with good spray quality. However, the rotating fuel injection system can potentially provide high atomization quality without the high-pressure fuel pump through the centrifugal forces of the engine shaft. With this motivation, a very small rotating fuel injector with 40 mm diameter is designed for the micro-turbo jet engine. It is directly linked to a high-speed rotational spindle capable of a speed up to 100,000 rpm. The droplet size, velocity, and spray distribution from the PDPA (Phase Doppler Particle Analyzer) system are measured. The spray is also visualized by a high-speed camera. The test results show that the length of liquid column from injection orifice is controlled by the rotational speeds and that SMD (Sauter Mean Diameter) is decreased with increasing rotational speeds. At a rotational speed of 73.3 m/s (35,000 rpm), SMD is lower than 60 μm at the entirety of the measuring space in the case of Type 2 (injection orifice diameter of 1.5 mm) and Type 3 (injection orifice diameter of 2.2 mm). Therefore, conceptually, it is possible to apply this small rotating fuel injection system to the micro-turbojet engine combustor.

This paper presents classic and knowledge-based intelligent controllers for regulation of a vibratory MEMS accelerometer. The proposed methods comprise Fuzzy type I (FTI), Fuzzy type II (FTII) and Full-state-feedback (FSF) control systems. An ideal model of sensor under FSF controller is used to generate the required reference data to train if-then rule-base and Membership functions (MFs) of both fuzzy controllers. Through feeding the reference data as well as the FTI/FTII output into an Adaptive neural fuzzy inference system (ANFIS), the rules and MFs of the FTI/FTII system are updated. The control systems are realized by adding a Kalman filter (KF) loop to the force-balancing method for estimation of state variables and input acceleration. Stochastic noises are filtered out while keeping good tracking performance of MEMS accelerometer and reducing the displacement of the mass under the closed-loop ANFIS-KF structure.

Previous correlations that have been used to predict the heat transfer performance of pulsating heat pipes (PHPs) offer limited thermal predictions within a narrow range of fluid-filling ratios and PHP inclinations. In this paper, a novel semi-empirical correlation with improved scope is proposed, with an increased range of fluid-filling ratios and PHP inclinations. The proposed correlation employs the dimensionless numbers governing the thermo-hydrodynamic operation of PHPs, and achieved ±30 % accuracy when predicting selected experimental data, showing reasonably good agreement. Unlike previous correlations, the new correlation can be used for different working fluids, geometrical aspect ratios, and heat loads. A comprehensive assessment of the relative significance of the correlation parameters on the total heat transfer performance is discussed. The new correlation with its flexible application range is expected to assist in faster and more enhanced thermal predictions as interest in PHPs grows.

Deep neural networks (DNNs) for intelligent machinery fault diagnosis require a large amount of training data, powerful computational facilities and have many hyper-parameters that have to be carefully tuned to ensure maximum performance. Deep forest, as a novel alternative to the deep learning framework, has the potential to overcome these shortcomings. In this study, a deep forest-based end-to-end intelligent fault diagnosis method is proposed for hydraulic turbine, in which multi-grained scanning is first used to transform fault feature representations from raw data and enhance fault feature learning ability, and then cascade structure is constructed with different types of random forests to learn fault features level by level and classify faults. The effectiveness of the proposed method is validated using the experimental dataset under twelve conditions, and its practicability is validated using a simulated dataset generated by adding white Gaussian noise to raw experimental signals. The results show that the proposed method is able to adaptively mine available fault features from measured signals, and its diagnosis accuracy is better than that obtained by existing methods. More importantly, the proposed method has better robustness to noise and is less limited to the number of training data.

This paper presents the development of predictive models for bend force and final bend angle (after springback) in air bending of electrogalvanized steel sheet employing response surface methodology. The models are developed based on five-level half factorial central composite design of experiments with strain hardening exponent, coating thickness, die opening, die radius, punch radius, punch travel, punch velocity as input parameters and bend force and final bend angle as responses. The results obtained from the models are in good accord with the experimental results. The effects of individual parameters and their interactions on the responses have also been analyzed in this study.

Structure vibration is known to influence the firing accuracy of a machine gun system. Studying the dynamic characteristics of the machine gun system and reducing its vibration response are crucial. Eigenfrequency optimization based on topology is an emerging vibration suppression technique that reduces structural vibration and stabilizes a machine gun system. This paper presents an effective and efficient method that accomplishes these tasks. The objective function is the frequency of the main vibration mode confirmed by modal and transient dynamic analyses. The frequency is maximized by subjecting topology optimization to mass constraints. Based on topology optimization results, the revised model addresses all structural and manufacturability concerns. Dynamic analysis, exterior ballistics calculation, and experimental test are conducted to verify the effectiveness of the proposed method. Results show that muzzle vibration and structure deformation are reduced and firing accuracy is remarkably improved.

Wood pellets are a kind of solid biomass energy and a renewable energy source. Made by compressing sawdust, wood pellets have a higher energy density than split firewood and wood chips. In 2007, the new and renewable energy (NRE) portion was 2.4% with respect to total primary energy in Korea. The Korean government wants to increase the new and renewable energy (NRE) portion up to 6.1% by 2020 [1]. To achieve this target, the government has been establishing some policies, such as incentive policy, NRE mandatory use for public building and renewable portfolio standard (RPS) and so on. To supply wood pellets as fuel for the combustion chamber of a wood pellet boiler, most domestic wood pellet boilers put a constant volume by using an auger type fuel feed system. In an auger system as fuel feeding, there is the possibility of changing energy input due to the different density of wood pellets even in a constant volume flow rate of wood pellets. If fuel input rate is changed without any correction of air flow rate for combustion, the condition of combustion in a wood pellet boiler can be deteriorated. We have developed an air-fuel control system for a domestic wood pellet boiler by using flue gas oxygen concentration measurement and a PID controller. To measure O2 concentration of flue gas, a wide band O2 sensor was adopted. We changed fuel input from 100% to 50% by artificial manipulation to confirm the control system. The O2 concentration in flue gas can be controlled to be 8.5% ± 1% without significant change of CO and NOx concentration.

This paper proposes a non-iterative implicit integration method for real-time analysis of multibody systems. Although the implicit Euler integrator is widely used for real-time simulations, we use a HHT-α integrator to improve the accuracy of the solution. For a noniterative procedure, the HHT-α integral formula was reformed and applied to the linearized equations of motion for multibody systems. A stability analysis of the HHT-α integrator was carried out to determine whether the proposed integrator has absolute stability. Numerical simulations with stiff linear systems that represent a highly damped system and a highly oscillatory system were also carried out to evaluate the performance of the proposed integrator. For non-linear multibody systems, the performance of the proposed integrator was also evaluated with a double pendulum example. Through the double pendulum multibody simulations, we confirmed the accuracy and stability characteristics of the proposed integration method by comparison of the conventional HHT-α integrator with the iterative method and the implicit Euler integrator, which is widely used in real-time applications.