Table of contents

PREFACE

We are very pleased to introduce the proceedings of the CMSME2018. A major conference theme was related to the field of Materials Science and Mechanical Engineering. The conference was held in Asian Institute of Technology, Bangkok, Thailand, from February 24 to February 26, 2018.

This conference provides opportunities for the delegates to exchange new ideas face-to-face, to establish business or research relations as well as to find global partners for future collaborations. Their contributions helped to make the Conference as outstanding as it should be. The conference results have lead to significant contributions to the knowledge in these up-to-date scientific fields, encouraged the interaction of researchers and developing academics with the more established academic community in an informal setting to present and to discuss new and current work.

All papers published in this volume of IOP Conference Series: Materials Science and Engineering have been peer reviewed through processes administered by the proceedings Editors. Reviews were conducted by expert referees to the professional and scientific standards expected of a proceedings journal published by IOP Publishing.

Biopolyesters such as synthetic poly(propylene fumarate) (PPF) are widely used in the biomedical field. In order to be used as orthopaedic scaffolds, their stiffness and strength have to be improved. Inorganic boron nitride nanotube (BNNT) 1D nanomaterials have recently attracted a lot of interest as reinforcing fillers of polymers due to their outstanding physical properties. This article deals with the preparation and mechanical characterization of PPF/BNNT composites with nanotube concentrations in the range of 0.1-5 wt%. Results demonstrate that the composites exhibit rigidity enough to be used for tissue engineering applications.

Acidic environment always contributes on casing corrosion phenomenon, the local corrosion and pitting lead to stress concentration, which decreases the strength and is an important factor to cause damage to the casing. The influences of distance of two pitting, corrosion depth, section parameter on collapsing strength of casing are quantitatively analyzed under the condition of double pitting axial distribution and ring distribution. The results showed that the maximum Von Mises stress of casing first increases, and then goes down to a steady state as the distance of double pitting grows under the condition of double pitting axial distribution, while the stress goes down to a steady state as the distance of double pitting grows under the condition of double pitting ring distribution. It can provide the theoretical foundation for the casing design through analyzing and comparing the influence of double pitting on the collapsing strength of casing under different condition.

In the traditional safety assessment of casing string, some influencing factors are ignored for modelling convenience, which makes the casing string safety assessment effect of oil and gas well not very ideal. For complexity and randomness of casing load and its properties parameters in complex well conditions, BP artificial neural network is created in MATLAB based on the analysis of the influencing factors of casing string security. Casing string section whose safety assessment is more mature is taken as a sample to train the BP neural network. The trained network is applied to make case assessment. At the same time, GUI interface is applied to implement the visualization. The results show that safety evaluation of the casing string can be achieved by using BP neural network. The accuracy of the casing string network safety evaluation is high. It will realize the visualization of safety evaluation and provide more accurate and effective reference for the design of casing string.

This paper reports synthesis of rare earth doped BZO perovskite ceramic by facile solid state reaction synthesis route. The phosphor confirms its nanocrystalline structure with high order purity and homogeneity. Characterized by XRD, SEM, EDX, FTIR and TL, a complete investigation of its structural, morphological and thermoluminescent properties is done. The kinetic parameters estimated using peak shape method confirms the second order kinetics of synthesized ceramic powder. With the emerging global concern regarding UVR exposure protection, the BZO perovskite ceramic are emerging as dynamic alternatives for TL mapping.

Present study investigates the phase evolution behaviour of AlCoCrCuFeMnSix (x = 0, 0.3, 0.6 and 0.9) high entropy alloys, synthesized by mechanical alloying and arc melting. The phase evolution, microstructure, and mechanical properties were analysed to understand the effect of Si addition in AlCoCrCuFeMn high entropy alloy. The X-ray diffraction, after 15h mechanical alloying, reveals the mixture of body-centered and face-centered cubic structure. The addition of Si favours body-centered cubic structure formation during mechanical alloying. The phase evolution observed after XRD are in accord with the thermodynamically predicted phases.

The p-SnS/n-WO₃:Sb heterojunction diode was successfully obtained by thermal evaporating SnS thin films on WO₃ doped with 2.0 mol% Sb₂O₃ of 1 mm thick ceramic pellet substrate. The electrical properties of p-SnS/n-WO₃:Sb heterojunction were investigated by forward current–voltage–temperature (I–V–T) characteristics in the temperature range of 20-300 K. It was found that at low forward bias voltage (<0.25V), the conduction mechanism of the diode exhibits Ohmic conduction. At intermediate voltage (0.25<V<1.0V), the conduction mechanism is dominated by thermionic emission (TE). At bias voltage above 1.0 V, the current transport is due to space charge limited current (SCLC) controlled by an exponential trap distribution in the band gap of WO₃:Sb. The temperature dependence of the saturation current and ideality factor are well described by tunneling enhanced recombination model occurring at junction interface with E_a and E₀₀ values about 1.565 eV and 99.5 meV, respectively.

Tin monosulfide (SnS) thin films were prepared by close spaced sublimation method at three different source temperatures of 550, 575 and 600°C. Structural, textural and compositional features were investigated by XRD, SEM, EDS and Raman spectroscopy. From absorption spectra, direct band gap increased from 1.18 to 1.23 eV with increasing source temperature. Electrical resistivity, Hall constant, carrier concentration and mobility values of the films prepared at source temperature of 600°C were 0.54 Ω.cm, 40.76 cm³/C, 1.537#x00D7;10¹⁷ and 75.48 cm²/(V.s), respectively. The temperature-dependent conductivity was performed in the temperature range of 50-300 K. It was shown that three types of conduction mechanisms can be expected: thermionic emission passing through grain boundary at high temperature range (240-300 K), the Mott variable-range hopping (Mott-VRH) at low temperature range (135-235 K) and the Efros-Shklovskii variable-range hopping (ES-VRH) at very low temperature range (80-130 K).

The cathode materials of Li-ion battery are suffering from huge loss in the specific capacity as the C-rate or cycle increases due to the unusually low diffusivity of Li-ion in specific phase. Although the porous cathode has shown the improved performance, it still has not been clearly explained whether the porosity really increases the specific capacity and how much high rate capability we can obtain. Here we report the importance of the design of porous cathode, which may provide an ultrahigh or even lower than that of the simple sphere-shaped cathode. Numerical simulations show the improved specific capacity with the porosity and the effect of porosity becomes significant as the C-rate increases. As the C-rate increases from 2.5 to 40C, the loss of specific capacity becomes only 20% with the 50% porosity, while that is about 60% with the simple sphere-shaped cathode. In addition, that decreases during total cycles from 30% to only about 2% with the 50% porosity under 40C. Interestingly, the porous cathode does not guarantee the improved specific capacity even porosity increases unless the pores are evenly distributed. The presented analysis provides important issues to design the ultrahigh performance of cathode.

In this paper, the multi-step forming process was studied with the fine blanking (FB) tool and the FB experiments for the precise clutch cam of automobile seat lifer pumping device (PCC). In order to form the PCC, the multi-step compound FB tooling system was taken; the three forces were directly gained from the rams of the FB press and the other force was gained from the auxiliary hydraulic device in the FB press. The FB tool was optimally designed through the FB simulation and fabricated. From the FB experiments with the FB press (Mori Iron Co., Ltd, FB400), the 5 samples of the PCC were taken and measured. All samples fulfilled the tolerance conditions.

Fused deposition modelling (FDM) is one of the widely used rapid prototyping techniques for fabricating complex shaped objects from CAD data. Minimum wastage of material, simple manufacturing process and economical desktop like machine have made the technique a major contender in the field of manufacturing. However, due to layered manufacturing process, the surface of FDM parts lacks quality. In the present research work, the FDM built parts were surface treated with organically modified montmorillonite (OMMT) nanoparticles. The post-treated specimens were characterised by XRD, FTIR, SEM and UV-vis analysis which revealed the successful deposition of nanoparticles on the surface of the FDM built specimens. Effect of post-treatment parameters on surface hardness, dimensional accuracy and average surface roughness was investigated using Taguchi technique. It was found that the embedment of OMMT nanoparticles increased the hardness of FDM parts due to its ceramic attributes and the combined effect of nanoparticles/chemicals reduced the surface roughness providing a smooth surface. Moreover, the process does not marred the dimensional accuracy of the fabricated parts. Further, multi objective optimisation technique was used to find the optimum post-treatment parameters. The present approach can be utilised for improving the surface integrity of FDM parts.

Design and synthesis of metal-organic frameworks (MOFs) with multi-functionality have attracted a lot of attention since the different functional groups can enhance the cooperative effect providing properties superior to those found in mono-functional MOFs. The efficiency and selectivity of the reactions can be improved by the simultaneous activation of multi-functional catalysts. Herein, a series of BrØnsted acid-base bifunctional UiO-66 bearing acidic sulfo- and basic amino- functional groups were successfully prepared via a simple one-pot solvothermal method. PXRD patterns of the bifunctional frameworks were similar to that of simulated UiO-66. The existence of sulfo-and amino- functional groups was investigated by IR and H¹-NMR. The bifunctional frameworks showed high thermal stability up to 300°C examined by TGA. By varying the molar ratios of ligands, the proportions of acidic and basic moieties in the framework were successfully tuned. The amount of functional groups anchoring in resulting frameworks was determined by ¹H-NMR. This bifunctional UiO-66 was tested for CO₂ capture.

Laser Induced Breakdown Spectroscopy (LIBS) technique has been applied to study the annealing effect of Al-Ge alloy at 150, 175, 240, 280, 325 °C. LIBS spectra of all samples prepared at these annealing temperatures were recorded. The signal intensity of the Al and Ge spectral lines increases with increase in annealing temperature. This increase in the signal intensity is due to structural modification of Al-Ge sheets surface with annealing temperatures. This variation in intensity verifies the assessment of annealed materials which can be performed with LIBS technique.

Sensor data abstraction is necessary to provide users with context-aware services. Sensor data abstraction mechanism in context-aware system usually consists of collecting data, converting, and context reasoning. For this mechanism in IoT environments, sensor data is used that is described in the pairs of key-value set or digit value. However, environmental data cannot be sufficiently formed since these sensors data are provided with these values. For example, it may need metadata of contexts and things description. In this paper, we propose a new conceptual metadata model for sensor data abstraction in IoT environments. The proposed model provides sensor data and their metadata as low-level context, which is a part of basic context for presenting given environment, to context-aware system. In the experiments, we describe a procedure to generate low-level context for sensor data abstraction based on the proposed model and to provide this information to the context-aware system.

Nowadays, energy saving is one of the most talked about issues in our life, it is also increasingly important in the manufacturing industry. This research considers the dynamic flexible flow shop scheduling (DFFS) problem, which is an extended version of the classical flow-shop scheduling problem. A flexible flow shop has multiple stages with multiple machines at each stage for processing multiple products. Previous research on DFFS aimed to achieve just-in-time production, or reducing difference between the actual completion time and the due date of each job. However, little research has been made on energy saving of machines in production. To address such a need, this paper proposes a method that dynamically turns on and off machines so as to reduce energy consumption while achieving JIT production. The proposed method has been tested on different environments, and the results show that it is high performing for both JIT production and energy saving.

This paper describes a new approach for tracking the trajectory of uncertain robotic manipulators using ANFIS (Artificial Neuro-Fuzzy Inference System) and uncalibrated vision system. The main emphasis of this work is on the ability to estimate the positioning accuracy and repeatability of a low-cost robotic arm with unknown parameters under uncalibrated vision system. In this study, captured image data are collected from two fixed-cameras vision system; installed on the top and lateral sides of the robot, respectively. For training and validating purposes, the robot is manoeuvring within its workspace using forward kinematics. The tracking system is trained using ANFIS with subtractive clustering method in MATLAB. Extensive simulations were carried out to illustrate the effectiveness of the proposed visual tracking method for LabVolt R5150 manipulator in our laboratory. Observing the simulation results, the performance of the proposed approach is efficient for using the vision-based learning system as visual feedback in uncertain robotic manipulator.

We propose a slim optical fingerprint sensor for fake fingerprint detection on mobile environment. The sensor proposed in this paper is compact size and slim thickness. Also, it can be used by only the power of smart phone without battery or external power. This sensor has a new lens design and optical path to minimize distortion. This sensor shows detailed images of ridges and valleys characteristic of fingerprints and has a characteristic of being resistant to moisture. The proposed sensor can detect various kinds of fake fingerprint (Paper, rubber, silicone, etc.). Simulations show that the slim optical fingerprint sensor has an effective performance on the results of the fake fingerprint detection rate.

Indoor positioning systems have received increasing attention for supporting location-based services. In recent Wi-Fi networks, the rich information in the physical layer, known as channel state information (CSI), has been recognized an effective positioning characteristic rather than traditional received signal strength. However, the positioning performance depends on a very high-dimensional CSI due to all pairs of transceiver antenna, which may incur over-fitting problems. This paper proposes a subcarrier-selection approach based on information theoretic learning to compensate for over-fitting problems in CSI-based localization systems. After equalizing the histogram of CSIs, the proposed algorithm computes the information gain of each subcarrier and forms a new low-dimensional subset of CSIs to reduce the complexity and to decrease possible over-fitting caused by redundant CSIs. We demonstrate the effectiveness of the proposed algorithm through experiments. On-site experimental results demonstrate that the proposed approach outperforms traditional feature selection schemes.

This study proposes an online to offline (O2O) learning framework, ArgiZero, based on three components: a generative adversarial network, an online auction market, and offline simulated agents (digital twins: buyers, farmers, natures, and markets). The generative time series and digital twins are massively generated in a manner of Monte Carlo but with extremely efficient algorithms. The goal of the generator is to produce time series that are statistically indistinguishable with the records from auction market. The goal of the discriminator is to develop a triangulation method based on semi-modeless assimilation to separate generated from actual time series. Most farmers believe agriculture is impossible to be planned because uncertainty, crowding, crisis, and risk cannot be foreseen and accommodated. This AgriZero framework alleviates the challenges through the techniques of Bayesian deep learning and data assimilation as well as the mega power of GPU computation. Thanks to Bayesian hierarchical estimation, which is akin to deep learning but more sophisticate and longer history. We are able to estimate human behaviour in the agents of buyers and farmers, natural disaster in the agents of natures, and price fluctuations in the agents of markets. The framework has been validated by a large amount of records in vegetable auctions of Taiwan and USA. The hierarchical Bayesian estimation and Monte Carlo Markov Chain particle filters used in hidden Markov model are appreciated during the massive construction of the most probable digital twins. The feature space mapping in wavelet time series, Bayesian deep learning in recurrent neural network, kernel induced Hamiltonian dynamics ABC, and hybrid SDE-kernel based forecasting for time series analysis embodies the particle generator in the GAN structure. We also apply time series clustering, RNN, bagging and boosting, and semi-modeless assimilation to assist the performance of the triangulated discriminator.

This paper proposes an improved wavelet cerebellar model articulation control system (IWCMACS) to control precision positioning of the linear piezoelectric motor (LPM). The proposed system combines the improved wavelet cerebellar articulation model controller (IWCMAC) with the estimated bound compensator controller to obtain high-precision positioning for applications requring accuracy within micrometer or nanometer range. In this research, the momentum and propotional factors are added into learning algorithm to escape from local minima points and speed up convergence of the system. The Lyapunov-Like Lema theory is used to estimate error bound to guarantee the stable of the system. The experimental results for the piezo-priven stage conclude the effectiveness and applicability of the proposed control system for model-free nonlinear.

The problem of exponential stability for linear system with mixed time-varying delay is investigated. The stability of linear system are proposed with feedback control. Based on the constructing of improved Lyapunov-Krasovskii functionals combined with Leibniz-Newton's formula and by utilizing the integral inequality, new sufficient condition for the stabilization of the systems is first established in terms of LMIs. A numerical example is given to illustrate that the effectiveness of the proposed feedback control.

Beyond the conventional hot-wire sensor, a new thermoelectric sensor with ultra-low power consumption without heating is proposed. Using the TSMC 0.35 um CMOS-MEMS process, the thermoelectric sensor is fabricated with 32 pair of central-symmetrical thermocouples positioned. When the fluid passes through the thermopile, the fluid will take away the heat, so that a temperature difference is generated between the cold end and hot end of the thermocouples. The temperature sensor is calibrated and senses the drop of temperature at the center of membrane during the measurement. For different flow velocities, it is interesting to find that the drop of temperature is verified by the output voltage of sensing circuit from thermopile and the same for temperature sensor which behaves as a function of flow velocity. The new approach for the anemometer of sensing flow velocity is realized by our proposed thermopile which is proved to be a practical technique with ultra-low power consumption.

Gyroscope is an instrument widely used in the navigation systems for sensing inertial angular motion. One of the principle of Gyroscope is Coriolis Vibrating Gyroscope (CVG), which is simple and easy to operate. It is realized during the development of the CVG that it is most suitable inertial sensor for aerospace applications. In this paper, a novel method for high reliable gyroscope application is demonstrated to verify the 'Mode 2' vibration pattern of vibrating hemispherical metallic shell. A parallel plate capacitor arrangement is made by placing discrete metallic plates around the metallic shell to study the vibration mode pattern. The shell vibrating at this particular mode, flexes along the axial direction of capacitor. The air gap of the parallel plate capacitor changes as the shell vibrates. The 'Mode 2' vibration pattern from the shell is confirmed by studying the phase relation at different capacitor locations.

Beyond the conventional non-contact temperature measurement with ambient temperature compensation and our previous work of multi-sensors compensation, two compensation schemes are proposed and compared. An infrared radiation measurement module with several temperature sensors are built and calibrated with ambient compensation to investigate the dynamic temperature distribution under moving of module from one place to another. The new approach we proposed including the infrared radiation exchanges model between the target, sensor and the optical path thorough temperature monitoring and two fast temperature measurement schemes with dynamic compensation. After careful calibrations and verification of several experiment conditions, our models of two dynamic compensation schemes both show an excellent agreement with the measuring data. The experimental data of compensation scheme reach a stable reading value of target temperature down from 40 min to 2 min for the differential scheme compensation and 6 min for multi-sensors scheme compensation with temperature error around 0.2 °C.

Diabetes can cause many complications in the human body. The disease is commonly diagnoses invasively using blood glucose test. A good correlation between blood glucose and exhale breathe acetone has opened a way for non-invasive diagnosis through the detection of the breath acetone from the exhale breathe. However, the conventional means of detecting exhale breathe acetone (e.g. GC-MS) are bulky, require technical knowhow, do not offer real time measurement and found only at advanced institutions that can afford the equipment. This work is aimed at developing a real time, sensitive and selective optical based Surface Plasmon Resonance (SPR) breath acetone biosensor for non-invasive monitoring and screening of diabetes. The motivation of this work arises from the promising advantages of optical based biosensors over other biosensors. Additionally, a novel doped polyaniline (PANI) conducting polymer would be the SPR metallic layer while Chitosan would be the selective sensing layer. Mathematical modeling and SPR simulation has been conducted. The result has shown that the replacement of conventional gold or silver SPR layer with doped Polyaniline (PANI) SPR layer provides better promising sensitivity at mid infrared wavelength range. Therefore, additional inclusion of chitosan layer on the proposed SPR based biosensor would give rise to a sensitive and selective breathe acetone biosensor for easy monitoring and screening of diabetes.

Assessment of reinforced concrete building capacity under seismic excitation has been recognized to be highly important for the past decades especially in Indonesia. Previous studies showed failures of RC building occurred in columns with bad confinement. The confinement in RC column has significant role in providing ductility and shear capacity for seismic loads. For this aim, a five-story RC building having different confinement on column members are investigated under seismic excitation. Three set of ground motions are selected and matched with target response spectrum of Indonesian code. Nonlinear analysis is performed by utilizing OpenSEES finite element software. To account the inelastic behaviour of beam and column elements, two types of plastic hinge are applied for both elements, namely finite length plastic hinges (plastic zone) and distributed hinges along the length of elements. The results show that there is a noticeable difference in seismic responses in correlation with the building model.

Fuel consumed in collecting municipal solid waste (MSW) accounts for a major portion of the cost of waste management. In this study, several cases were developed using the ArcGIS Network Analyst to establish optimum conditions for MSW collection in Um Gafa district in Al Ain city, UAE. A GIS model was created based on data collection and GPS tracking of collection route and bins position in the area. Results show that current waste collection at Um Gafa does not strictly follow U-turn and curb approach policies. When route optimization is applied for similar conditions, a saving of 14.3% in fuel consumption is gained. Two models were tested for optimal number and location of bins. One model was based on a 40-m service zone while the other was based on population density and land use. By adopting model 1, the number of bins was reduced by 12%, while in model 2 the number of bins was reduced by 20%. Model 2 showed higher superiority, compared to model 1, in terms of fuel consumption.

We investigated the effect of different window designs employed in Abu Dhabi Emirate- UAE on the level of noise transmission. For that, 21 window cases were tested in the laboratory. Several factors were considered, including window glass thickness, glazing, lamination, opening style, area, frame type, frame style, and use of shutters. Results showed that sound transmission loss is improved significantly with the use of shutters and the use of hinged, not sliding, windows. The instalment of glass thicker than 6 mm did not cause any improvement. As for the double glazed windows, no noticeable improvement was detected with an air gap of 12 mm or less, but increasing the air gap to 20 mm causes a moderate improvement. Slight improvement was found when a lamination layer or uPVC frame (instead of aluminum) was used. It was further found that box umbrella and curtain wall frames did not seal as well as half umbrella frames, and thus resulted in a lower acoustic performance of the windows.

In order to analyze the simulation results of UOE molding and solve the buckling problem of high strength pipeline steel in the process of ocean laying, taking X80 pipeline steel sample as the object of study, a better mechanical model of kinematic hardening was adopted. With the aid of ABAQUS finite element analysis software, the finite element analysis of UOE simulation results, the loading of UOE simulation results and buckling in ocean laying are carried out. The results show that: Through the extraction of the load at the end of the welded tube and the strain at the buckling position, draw it into curves and observe the position of the strain corresponding to the inflection point of the curve. The critical strain of welded pipe subjected to buckling under different working conditions is analyzed, so it is found that the critical strain increases with the increase of internal pressure and the critical strain becomes smaller with the increase of the external pressure. The analysis method and results can also provide reference for the actual production, laying and installation of oil and gas pipelines.

The use of timber in building industry has expanded in many countries over last 20 years due mainly to its lightweight, little adverse impact to the environment, and strong anti-seismic properties. Despite the fast development of the construction industry in China in recent years, timber products utilization is still very limited. Therefore, the purpose of this study was to investigate the feasibility to further utilize timber based products in the building industry in China. A review of engineered wood products utilization in China, and oversees was conducted first. The general properties of timber products were followed. Based on this, a survey focusing on the current situation and suitability of localised grown timber products was carried out to study the feasibility. This paper concludes that timber based products have a great future in China. It recommends that it is imperative to further research how to promote timber's utilization in China to be in line with the sustainable development.

The assessment and strengthening method of existing reinforced concrete buildings in terms of seismic responses have been highly important for the past decades especially buildings with soft-story mechanism which are found to be more vulnerable. Several strengthening techniques have been proposed including Fibre Reinforced Polymer and steel jacket of RC column elements. This paper aims to evaluate the effectiveness of two strengthening techniques with variability of soft-story under severe earthquake excitations. Five-story RC building is investigated and non-linear dynamic analysis is performed to capture the inelastic responses of the structure. Four sets of ground motion are selected and matched with target response spectrum for Aceh earthquake. Seismic responses of the considered models and strengthening techniques are compared.

This study is intended to evaluate and analyze R&D projects for natural disaster prediction and reduction that have been conducted from 2003 up to 2016 in Korea and use it as foundational material for future R&D projects for disaster prevention technology in Korea. In consideration of essentiality about the characteristics of Korea's natural disaster prediction and reduction R&D projects and achievement of project goals, scientific, technological, and social performances are arising. Concerning "technical performance", in 2016, there were 4 patents registered receiving over 80 points (out of 100) (50%), so in the future, technology level is expected to rise greatly. Moreover, a lot of research results are being applied practically to the affair of Ministry of Public Safety and Security.

Program spatial movement of a high-speed vehicle has been synthesized with the help of hodograph in terms of spiral paths. A mathematical model of a primary road in the form of a line over ruled bearing surface in the neighbourhood of the program trajectory has been developed. Vector equations of the elements of ruled surface and bearing surfaces oriented orthogonally to inertia forces have been set up. The inertia forces effecting a mass of a highspeed vehicle in the context of non-uniform motion along spiral program path has been demonstrated in a vector form.

Main goal of the paper is to present an algorithm for stochastic optimization of design of steel-reinforced concrete element's cross section. Firstly, the deterministic problem is introduced and described, followed by the description of uncertainties involved in the process and stochastic reformulation of the problem. Afterwards, the algorithm itself is introduced. This algorithm is based on internal cycle of deterministic optimization using reduced gradient method and external cycle of stochastic optimization using regression analysis. The probability is assessed on orthogonal grid via modified bisection method. The paper concludes with presentation of the performed calculations and their results.

In Ground Source Heat Pumps (GSHP), Energy Piles pose as heat exchangers that transfer the heat from the buildings to the shallow ground lower temperature in order to decrease the energy consumption whilst cooling the buildings. These piles are mainly designed for highest possible thermal conductance. In this paper, nine factors influencing the thermal conductance of the energy pile are defined and statistically evaluated. These nine factors are; number of tubes, pile diameter, tube diameter, tube thickness, tube location, pile conductivity, tube conductivity, soil conductivity, and water flow rate. The thermal conductance of the energy pile is calculated using finite element model. The significance of these factors is evaluated using fractional factorial uniform design of experiment. The results show significance increase in the pile thermal conductance with the increase of the tube diameter, number of tubes, water flow rate, and tube and pile thermal conductivities. Furthermore, the tubes location near the pile outer surface show significant increase in the pile thermal conductance. On the other hand, decreasing pile diameter slightly increases the pile thermal conductance. Nevertheless, the soil thermal conductivity has shown insignificant effects on the pile thermal conductance.

In view of the poor continuity of the pre-mixed abrasive jet equipment and the non-uniform mixing of the abrasive particles in the post-mixed abrasive jet system, this thesis is based on electromagnetic abrasive slurry jet technology. The affecting factors of jet compression characteristics of electromagnetic abrasive slurry are studied through the combination of numerical simulation analysis and experimental research. According to previous research results, the influence of two parameters of magnetic flux density and voltage on the outlet velocity and kinetic energy of conductive medium are predicted through numerical simulation. Combined with orthogonal test characteristics, we set up a test platform and carry out some experiments. The experimental results show that the biggest influence on jet supercharging characteristics is magnetic flux density and the next one is the voltage. The results of numerical simulation are verified. When the flux density is 0.7T, the voltage is 72V, the concentration of conductive medium is 18% and the characteristics of jet pressurize are best.

In order to study the effect of external field treatment on mechanical properties, cutting performance, microstructure of cemented carbide, the cemented carbide samples were treated by different magnetic field frequency (f=0.3 Hz, 0.4 Hz, 0.5 Hz) processing methods using self-made electromagnetic compound treatment device. On the basis of the study of this method, the electromagnetic compound treatment method was proposed to couple pulsed magnetic field and pulsed current. The results show that after the treatment of magnetic field frequency, the hardness of the sample slightly higher than that untreated sample, the increase value of percent between 0.5% and 1.3%, the value of hardness was 1594.72 HV, 1587.76 HV, 1582.45 HV, the longer the magnetization time, the higher the hardness; the cutting performance was increased, which means the tool life was increased, the increase value of percent from 4.5% to 7.0%. After electromagnetic compound treatment, the increase value of percent was 1.7% and 2.3%, the value of hardness was 1601.6 HV, 1609.82 HV; the tool life was increased 7.5% and 8.4%. After external field treatment, the angular state of wolfram carbide (WC) particle was transformed into smooth state and was more evenly distributed.

This paper presents a 5-zone-car-cabin model which is able to simulate the car cabin's thermal condition depending on several influencing parameters. This includes the solar radiation, to which special attention is paid in this paper. In addition, a generic methodology for parameter optimization considering measurements on a reference vehicle is presented. Thus, a very high degree of determination of the model was achieved. This paper is motivated by the impact of auxiliary loads on overall energy consumption in battery electric vehicles. The further use of the model is intended to calculate the energy saving potentials of the heating, ventilation, and air conditioning system by reducing or increasing the target interior temperature. This is necessary for a predictive control of secondary consumers.

Permanent Magnet Synchronous Motor (PMSM) is often used in Electrified Vehicle (EV), while its I_d (direct-axis current) and I_q (quadrature-axis current) are coupled. Traditional FOC (Field Oriented Control) method can't get an accurate decoupling control of them when the motor speed changed with the vehicle's driving condition, especially at high speed. This coupling issue leads an unstable torque output. And further, it deteriorates the NVH (noise vibration and harshness) performance of EV. This paper focuses on the decoupling solution and puts forward a new control strategy which combines the neural network control idea with FOC method. The novel method gives a neural network controller based on four single neuron PID controllers, which its function is to realize the d-q axis interacted adjustment and decoupling. Four single neurons PID controllers achieve the negative feedback control of I_d to U_d (direct-axis voltage), I_q to U_d, I_q to U_q (quadrature-axis voltage), and I_d to U_q respectively. Creatively, it takes PMSM speed as one of the neuron inputs to adjust the feedback weight of I_d and I_q dynamically. A comparing simulation which is set up in the Simulink platform is given in this paper. Simulation results show that this method gives a good self-adaptiveness and decouples the influence of I_d and Iq, as well as improve the motor control quality at high speed.

To decrease the influence of train passage on the efficiency of the intersection near a highway-railway at-grade crossing, this paper proposes a signal control strategy that dynamically applies two fixed signal timings and a priority phase based on the different scenarios, including two rules for judging different scenarios and two signal timings. The rule for judging whether a train is crossing a highway-railway at-grade crossing or not is established by using detected information. The rule for judging whether the influence of train passage is eliminated is designed according to train passage time and signal cycle length with the influence of train passage. Signal timing parameters for traffic flow, with and without the influence of train passage are respectively optimized by the ARRB method. The simulation results indicated that the performance of the dynamic strategy is superior to the performance of the two fixed signal schemes.

Echoing the pressing need to improve optimization efficiency and change the method of vehicle dynamic performance optimization by varying single parameter, a new method based on the Kriging approximate model and NSGA-II genetic algorithm is proposed to obtain more accurate results and shorten the design cycle. Accordingly, taking the suspension parameters as the variables, the dynamic performance indexes as the responses to fit the Kriging approximate model, the dynamic model of the 70% low-floor vehicle has been established. Subsequently, multi-parameter, multi-objective optimization of vehicle dynamic performance is achieved by virtue of the approximate model. The results show that, compared with the original method, all indexes are improved except the vertical comfort and stability. In particular, the optimization efficiency is significantly enhanced, and the effectiveness and feasibility of applying the optimization method to vehicle dynamic performance by virtue of the Kriging model have been proved.

The matching of wheel profile with rail profile is the key issue in design of high-speed railway, it directly affects the vehicle dynamics performance during travelling and the wear behavior of wheel/rail. The matching performance of wheel profiles LMA, S1002CN and XP55 widely used in Chinese high-speed railway with CHN60N rail was analyzed in the study in terms of wheel/rail contact geometry, wheel/rail rolling contact and vehicle-track coupling dynamics. The results indicate that: By comparing the matching performance of the three wheel profiles with CHN60 rail, S1002CN profile matches best with the CHN60N rail. XP55 profile is not applicable to CHN60N rail.

In this paper, we propose a novel intelligent classification model to classify the railway signal equipment fault based on SMOTE and ensemble learning. To tackle the imbalanced fault text data, the model uses SMOTE algorithm to generate the minority railway signal equipment fault class data randomly, making the data balanced. Then the model adopts the base classifier, such as Logistic Regression, Multinomial Naive Bayes, SVM and the ensemble classifier, such as GBDT, Random Forests to classify the data processed by SMOTE. To combine the advantages of various classifiers, the model integrates multiple classifiers by way of voting. Based on the experiment analysis of railway signal equipment fault text data from 2012 to 2016, the result shows that the model has a significant improvement in fault classification accuracy, recall rate and f-score.

Traffic congestion in metropolitan areas such as shenzhen, has become more and more serious. Over the past decades, many academic and industrial efforts have been made to alleviate this issue. In this paper, we propose a novel approach to predicting short-term traffic congestion. At first, we pre-process the data to get the speed, traffic, lane number of these parameters. Second, we carry out statistical data and create training samples. Third, We establish a hybrid neural network prediction model based on LSTM and substitute the generated samples into training. Finally, we use the model to predict the future congestion situation. The experimental results show that our model achieves good predictive results.

With the increase of air transport business year by year, the airport comprehensive service capabilities are increasingly facing severe challenges. As a key part of airport service, ground scheduling is crucial to the departure of flights on time. by analyzing the traditional rules of airport trailer and combining with the service processes and the characteristics of trailers, the paper develops a multi-target trailer emergency scheduling model with rolling windows. When the model is solved, the simulation annealing algorithm is introduced into the genetic algorithm to prevent the optimal result falling into the local optimal solution. The simulation results show that the model can more effectively solves the problem of airport trailer emergency scheduling in the case of flight delays than the traditional scheme,and to relieve the pressure of flight delay for busy airports.

Operating the express/local train plan can meet the characteristics of imbalance of passenger volume temporal and spatial distribution, and satisfy the demands of long-distance commuters who want to travel fast. Although the program can improve the organizational operating efficiency and passenger service level, it will reduce the carrying capacity of system to some extent. Above all, based on analysing the factors of the express/local train plan and the composition of passenger travel time in detail, the 0-1 integer programming model of stopschedule plan problem was established by minimizing the passenger travel time. And combined with a simulation case, the immune genetic algorithm was designed to study the effect of line capacity.

Under the background of the network operation of urban rail transit, the rapid expansion of rail network structure in various cities, on the one hand, has promoted the rapid development of rail transit industry. On the other hand, it put tremendous pressure on the daily operation and management of rail transit operators. The traditional centralized disposal mode is not in a position to meet the increasingly complex network and passenger demand any more. In this paper, based on the distributed workflow theory, a distributed multi-aircraft collaborative system framework is established for emergency management of urban rail transit and an emergency response model, using Oracle database management system as the main technical to realize the digital management of contingency plans, the theory is finally applied in practice, and the design of the urban rail transit emergency response system for OCC layer is realized.

Catamaran vessels have been used for various purposes such as leisure craft and research vessel. Especially, asymmetric catamaran has a half of the symmetrical hull and flat side of facing inward demi-hull, and has feature of planing hulls such as hard chine, spray rail. Therefore, these vessels can travel at high speed with better stability and resistance performance. However, these features cause asymmetric catamaran to have large trim angle at high-speed condition, which cause problem on vessel's operation performances such as visibility and dynamic instability motion. To overcome these negative effects, tunnel shape in stern has been introduced. By applying this shape, trim angles are also suppressed because large dynamic lift developed on the exit region of tunnel stern. In this research, tunnel stern was applied on the asymmetric high-speed catamaran to evaluate vessel's hydrodynamic performance by numerical method, and the tunnel stern types are distinguished by slope of tunnel exit region: flat or narrow types. Consequently, it is confirmed that the total resistance of tunnel types is lower about 1.6∼5.0% than the bare hull in the wide speed range while showing almost same phase with the bare hull after FnV=2.3. Also, narrow type improves resistance performance further than flat type. On the other hand, trim angles show different trend with each tunnel type. In case of narrow type, the trim angle is stabilized after FnV=1.8 while that of flat type show an increasing trend as ship speed increase. These indicated that the narrow type has better resistance and operation performance than others.

To prevent the recurrence of containers overboard accident during loading and unloading, taking the accident at Yueyang Chenglingji Teminal as the study object, the mechanical deduction is carried out. A kind of method to determine whether a container will overturn is put forward, including the criterion and the quantitative algorithm of the corresponding indicators, i.e. the allowable heel angles. By verifying, the estimated results according to the algorithm described in this article, are basically consistent with the Yueyang accident. Thereout a set of measures to prevent such accidents are provided, including adding allowable heel angles during loading and unloading in the loading manual, carrying out stowage plan and evaluating and controlling the ship floating state before operating, monitoring and adjusting of the ship floating state during operating.

The opening of the Ice Silk Road is a great significant for the realization of the close connection with the European, and it is a promotion for China's economic development. The icebreaker will play an important role in the Arctic strategy. More accurate ice load calculation and prediction of ice breaking capacity methods will provide important technical support for the design and construction of icebreaker. This paper aims to solve the above problems and carry out the following research work. The ice load in continuous icebreaking type is calculated in 3D numerical method. Then, the motion differential equation in time history is established to calculate the motion response. In addition, the structure strength under ice breaking condition is evaluated based on FEM. At last, the evaluation method of continuous ice breaking capacity is proposed in this paper. Compared with the results of literature, the accuracy of the ice load calculated by this method meets the requirements and could further guide the design and development of ice breaking vessels.

Unsteady flow past a cylinder (Re=3900) was computed using large eddy simulation (LES) by OpenFOAM. The study includes the prediction of drag and lift coefficient, and pressure distribution around the cylinder. During the simulation, the one-equation sub-grid scale (SGS) model was applied. LES numerical results were compared with published RANS k-ε model, k-ω model and experimental data. Results indicate that LES one-equation SGS model provides better agreement in force coefficients and pressure distribution than above mentioned RANS turbulence models. Besides, effect of spanwise discretization to numerical results is also investigated, showing that medium gird is fine enough to yield accurate results compared to the fine grid, which is very computationally expensive.

Large container ship's structural strengths are the major concerns of owners and designers, and local stiffened panels within the mid-ship scope are similar due to the typical arrangements adopted in these ships. In this paper, investigations on longitudinal ultimate strength are made for these typical stiffened panels where considerations of modelling extent, boundary conditions and initial deflections are included. Additionally, the resulting force-load curves and collapse modes are compared with hull girder bending analysis (both hogging and sagging), thus validation are made in the more practical background. The study in this paper can be of reference values to similar container ships.

The analysis of yacht resistance performance using empirical methods has become an accepted approach over the last decade. Which are based on existing statistical material of yachts to obtain the empirical equations or map methods. There are not many simple methods to obtain the resistance of yachts, and the accuracy of the results is not always uncertain for different types of yachts. The study is focused on determining the appropriate empirical equation to estimate resistance for different kinds of yachts. And based on computational fluid dynamics (CFD), XFlow software to calculate resistance of yachts under turbulent state is selected. This paper provides a review of these methods and two real yachts are chose as examples according to the classification of yachts. It discusses the resultant implications for practical applications. Simulations on an identical yacht using empirical methods and softwares are compared. Good agreements are achieved for both Daisumi Mihiro's empirical methods and numerical simulation methods, which shows that Daisumi Mihiro's empirical equation to estimate resistance of the planning yacht is relatively feasible and Daisumi Mihiro's map method is reliable for the transition and drainage boats.

The increase of demand and the depletion of energy resources have led to a rising demand of renewable energy. Among them, wind turbine has been researched because of wide generality with high resource potential. Despite these advantages, onshore wind turbine has a spatial constraint. To solve these problems, offshore wind turbine has been researched and the installation area of onshore structures has been expanded to offshore field. The design of the substructure is one of the most important issues in case of motion characteristics in the ocean rather than on the coast. Tri-pod type is attracting attention because it is easy to manufacture and efficient to reduce environmental load. However, the motion characteristics of these types of structures have not been clarified yet and are currently studied. In order to improve the float performance, it is necessary to apply the optimal float design such as size, weight, water plane area, and mooring to each design. In this study, we have described tri-pod type model and evaluated the model test to find the effects of the ratio of the diameter to draft in dynamic motions of the structures on the basis of the floating column design. Since each design variables are determined, experimental RAO results have analysed through motion analysis of 6 degrees of freedom.

The lying identity of an access point (AP) is one of the most serious threat in Wi-Fi positioning because an adversary can easily acquire a valid address by monitoring the transmission and masquerade as another AP in the networks. This study proposes a robust Wi-Fi localization algorithm that can tolerate the liars instead of explicitly detecting them. The proposed algorithm considers all possible combinations of APs in an unionbased approach such that the adversaries cannot easily affect the positioning results by masquerading APs. Onsite experimental results demonstrate that this approach apparently achieves more robust location estimation than the Bayesian approach and the cluster-based method in the presence of lying identities.

In fast time-varying environment, orthogonal frequency division multiplexing (OFDM) systems lose the orthogonality between subcarriers due to the Doppler effect, resulting in inter-carrier interference (ICI), which greatly affects the performance of the communication system. Based on the analysis of the principle of ICI generation in time-varying environment, an ICI triple cancellation scheme is proposed to reduce the ICI of the OFDM systems in fast time-varying environment. In the scheme, the ICI self-cancellation modulation is performed at the transmitter of the OFDM system. Then, the time-varying channel is modeled as a linearly time-varying (LTV) model for ICI dual cancellation. Finally, the ICI self-cancellation demodulation is executed at the receiver of the system. Simulation experiment results show that the proposed ICI triple cancellation scheme can achieve a better effect of ICI cancellation than ICI self-cancellation scheme and ICI dual cancellation scheme, improving the performance of the communication system.

The dust deposited on the surface makes a significant impact on the performance of photovoltaic modules. This paper mainly studies the sucker's reliability analysis of the photovoltaic panel cleaning robot. The research is carried from two aspects, the mechanical analysis and the finite element analysis. The reliability including anti-slipping, anti-overturning, and anti-twisting is researched based on the mechanical model, while the influence of the mechanical load is studied by the finite element model of the PV module. According to the constrain conditions, the sucker of the photovoltaic panel cleaning robot has been selected. Based on the prototype of PV cleaning robot, the reliability experiment is conducted to verify the sucker's reliability analysis.

This project consist in evaluating a series of specific and general situations and thus to be able to collect data using some device that facilitate the reception, processing and sending of information that, when combined, can ignite the vehicle whose purpose is to reduce the rate of citizen insecurity in a significant in Peru and Latin American countries where the index of traffic accidents and thefts is critical. The project will avoid that people in an ethyl state of with cardiac diseases and thieves can drive since these situations have already been foressen and thus we have discovered a great security system making only the owner can access the vehicle.

This paper analyzes the reactive power characteristics of the doubly-fed induction generator (DFIG) during the emergency off-grid process caused by the crowbar protection action. Since the action of the crowbar is much faster than the stator switching, the DFIG would be running with a short-term squirrel cage asynchronous operation. The mathematical model of the DFIG under above situation was proposed in this paper, based on which detailed analysis was given on reactive power demands during squirrel-cage asynchronous state of the DFIG. It is achieved that the amount of reactive power absorption was associated with the initial operating conditions such as the terminal voltage and speed before disconnection, which can be prescribed as the s-Q characteristic of DFIG. Finally, analysis on the measured data of the wind farm disconnected event verified the validity of the model.

In order to reduce the fuel consumption of air-conditioning in vehicle, an air conditioning system was designed based on the principle of direct evaporative cooling and liquid dehumidification. In this paper, main devices were conducted in the way of numerical simulation and experiment, the overall layout of the device was designed under the guidance of Solidworks. The results showed that the high temperature and humidity air could be changed into the livable air. In particular, the regenerator could be operated with waste heat from the engine for higher energy efficiency. It can achieve the effect of the temperature dropped by 5-7°C. which need less energy than the traditional car air-conditioning while satisfy the comfort of the human body.

Al-Uswah Elementary School holds an Eco-Garden program, but in the process, Al-Uswah has an issue with the lack of water to fulfil the daily watering needs. So we assumed the solution to this problem is filtering the wastewater in Al-Uswah into clean water, which is mainly available in Al-Uswah. Filtering of wastewater to supply clean water for the eco-garden and hydroponic system using electro-chlorination water filter integrated with Solar PV is one of the best ways to provide daily hydroponic water needs. This paper presents a method for modelling and sizing electro-chlorination water filter integrated with Solar PV for an eco-garden and hydroponic system. The model of electro-chlorination described how to convert wastewater into clean water, predict flow rate to meet the daily need, and provide an experimental result to calculate the accuracy of the model.

Water is a primary human need. Of the total fresh water in the world, less than 1% are ready to drink and 11% of the total human population cannot achieve it. WHO/UNICEF by 2015 reports there are nearly 750 million people in the world who still have inadequate drinking water. The current condition is also occurs in the Ay Island which located in Banda Naira Islands, Central Maluku, Indonesia. Ay Island residents have to travel for 4 hours to the main island of Banda Naira to buy clean water. To overcome the current situation, the government have tried to provide clean water by building a $4 billion dam project in 2016. However, the dam project is not able to meet the needs of the resident because of the polluted water. In this research is proposed an Eco Water Treatment by using Parabolic Solar Concentrator and Photovoltaic Pump. This method consists of two main parts, PV Sea Water Pump and Solar PV-Distillator. The PV Pump is used to deliver water from the sea to the boiler, while the solar-powered distillator converts sea water into fresh water. Fresh water generated from the distillator have the same content as the Indonesian Minister of Health's standard. The system can provide clean water for 50 liter continuously based on capacity of the boiler each day depend on the weather and the temperature. From the experiment, proven that solar concentrator could increase the boiler temperature up to 300oC to boil the seawater and produce clean water.

This research proposed a Smart Meter design that have a feature to calculate the total wasted energy from electricity usage. This feature obtained by monitoring and scheduling any installed electricity equipment. With this feature, every Smart Meter user expected to be able to manage the use of electronic equipment that installed in each home optimally. In this research artificial neural network with a radial basis network learning algorithm (RBFNN) used to identify any connected device. This method is one of the controlled learning methods and have fast learning speed. To identify the electronic equipment, it used the RMS current rating and the peak value of the wavelet transformation of the RMS current. From the transformation will become input for the RBFNN. Experiment and simulation results show that the Smart Meter with radial basis network method able to identify each load well, where the average training accuracy is 96.76% and the average testing accuracy is 85.08%.

The economic growth in Asia is now remarkable. Because of this, the energy consumption has also increased drastically. Under such condition, it is necessary for efficient use of energy to introduce smart grid. At that time, electromagnetic interference (EMI) generated by the voltage harmonics from power converters which are connected to the power system becomes one of the biggest issues. Therefore, to suppress voltage harmonics in the power converters is required. Although it can be realized by connecting passive filters, it leads to circuit enlargement. On the other hand, recently there are some suggestions that the multilevel converters will be miniaturized and integrated in the future. If such a converter is introduced, it is considered that the smart grid system with renewable energy sources can provide high-quality electricity without EMI. Therefore, in this paper, the voltage harmonics to the grid system by assigning multi-level converters is investigated.

Solar assisted heat pump system is the system using solar thermal energy that can lead to the improvement of performance of heat pump by transferring solar thermal energy obtained from solar collector to evaporator of the heat pump for evaporation of refrigerant. In traditional system, solar collector can get a thermal energy only from solar radiation. So, the collector is hard to be used when the solar radiation is not enough such as cloudy day or night even though these collector take up much space. Thus the hybrid solar collector that has fin- and-tube heat exchanger have been developed for getting a thermal energy from not only solar radiation but also ambient air. Due to the fin-and-tube heat exchanger, this collector can get a thermal energy from ambient air for heating chilled water by evaporation of refrigerant in heat pump system. At this time, heat gain of water from ambient air by the collector needs to be confirmed before combining with real heat pump system. Thus, in this study, heat gain of water in the hybrid solar collector was investigated experimentally with respect to air and water flow rate on the various temperature difference between inlet air and water. As a results, heat gain of water was shown maximum value of 900W and it was increased with increment of air and water flow rate. Also, heat gain of water was changed linearly with increment or decrement of temperature difference between inlet air and water on the specific air and water flow rate. Furthermore, relationship between heat gain of water and operating conditions was also confirmed that can be used for decision of collector area and heat pump capacity for designing solar assisted heat pump integrated with this collector.

The rice-cracker is one of the popular snacks in Thailand. To produce it, drying is a necessary preparative step. This research aims to investigate the performance of a solar dryer with fins and baffles installed in the air flow channels of the dryer for rice crackers. The cover made of a 4 mm thickness poly methyl methacrylate (PMMA). A mathematical model was developed and used to design a solar dryer. The simulations revealed that a minimum of 2.25 m² solar collector area is required for solar radiation of 628.93 W/m² and the mass flow rate of 34 kg/hr and outlet temperature of 64.9°C are obtained. In addition, the collector efficiency is 52.01%.

The performance of photovoltaic (PV) cannot be described by the user, so it is difficult to anticipate when it's undesirable or fault condition occurs. Therefore, the monitoring of PV output parameters is needed. In this case, the parameters that can be displayed are current and voltage value. The parameter data are obtained from PV tracking of the sun position by MPPT Perturb and Observe (P&O) method used in a mechanical system of the dual axis solar tracker. In this experiment, there are two monitoring methods used, which are Real-time Online Monitoring Based on Android system and Human Machine Interface (HMI) display monitoring which is controlled by Arduino Mega 2560. Both methods are expected to show the performance of PV in real-time, remotely or not. The results of this experiment are Android apps and HMI that can monitor the PV output condition. To maintain the PV system in real-time, they keep the device under the supervision and extend its lifetime for more prolonged use.

The facts show that most large-scale power projects in Indonesia cannot be completed on schedule. The reason is related to the dynamic constraints such as legal, political, economic, social and cultural issues. In general, there is a potential of community empowerment approach using a small size plant has not been done. Such approach may give a lot of advantages including shorter construction time and easier to use clean energy like solar, wind, and waste or biomass which is available around us. Constructing 1000 units of 1 MW power plant simultaneously will have similar capacity with the construction of one 1000 MW power plant unit that had so many obstacles. Another important advantage is that this kind of plant can be self-managed under the ownership of local communities that can empower local businesses to become small- scale IPP developers with simple technology and small capital costs. This paper will examine the economical impact of local people's electrical self-management known as IPP UMKM by simulating several scenarios.

Boundary Layer Ingestion (BLI) has been studied extensively for implementation in Blended Wing Body (BWB) transport aircrafts, and it has been reported that BLI offers potential benefits mainly in terms of energy, improving the propulsive efficiency of a propulsion system and reducing the fuel consumption. This paper examines potential benefits of BLI related with a reduction on the Take-Off Gross Weight (TOGW) for a BWB-Unmanned Aerial Vehicle (UAV). It is discussed the methodology for weight estimation of a BWB-UAV through parametric models. To evaluate the benefits of BLI in terms of weight reduction, it has been taken into account the removal of pylons and the nacelle weight reduction when embedding nacelles into the airframe. The validation of the parametric models, and the case of study have been carried out for the aircraft NASA X-48B. The results show a reduction in TOGW between 8% and 19% when removing pylons and embedding nacelles into the airframe.

In this article, the effect of two variables namely nickel content and austempering heat treatment temperature on mechanical and microstructural properties of ADI were investigated. Four Nickel content levels of 0.0, 0.6, 0.8 and 1% and three austempering temperatures of 320, 340 and 360°C were selected. Prior to austempering, all the samples were austenitized for 30 min at 840°C. The microstructure of austempered alloys mainly consisted of a mixture of needle like acicular ferrite and carbon stabilized austenitic matrix. The increase in Ni content improved the strength and hardness and it reached its peak at 0.8%. The microstructures also became finer with increase in Ni content as confirmed by Impact energy and elongation. Nodularity was found to be above 90% for all alloys at all austempering temperatures. However, the nodule counts increased with increase in Ni content up to 0.8% and then dropped. XRD analysis was done to estimate the retained austenite content present in the ausferrite matrix and it was concluded that for any given Nickel content level, the retained austenite content increases with austempering temperature. Nickel of 0.8% was found to be optimum for all austempering temperatures.