bluuebunny/crossref_metadata_2025 huggingface dataset:
Natural Frequencies of Rectangular Laminated Plates—Introduction to Optimal Design in Aeroelastic Problems
Authors: Muc Aleksander
Published: September 2018

Free vibration (or eigenvalue analysis) is a prerequisite for aeroelastic analysis. For divergence analysis, slope influence coefficients (rotation at point i due to unit load at point j) are calculated using free vibration mode shapes and corresponding frequencies. The lowest eigenvalue is of interest and gives the divergence speed. The present paper considers the maximization problem of eigenfrequencies for composite panels. The influence of boundary conditions and constant or variable stiffnesses on optimization results are investigated herein. A new convenient set of design variables is employed in the analysis. The computations are carried out with the use of the Rayleigh–Ritz method and Finite Element analysis (2D quadrilateral and 3D solid elements).
Durum Wheat Quality, Yield and Sanitary Status under Conservation Agriculture
Authors: Calzarano Francesco , Stagnari Fabio , D’Egidio Sara , Pagnani Giancarlo , Galieni Angelica , Di Marco Stefano , Metruccio Elisa Giorgia , Pisante Michele
Published: September 2018

In Mediterranean environments the adoption of Conservation Agriculture (CA) would allow growers to achieve environmental, agronomic and economic sustainability. We investigated the effect of different combination of crop establishment treatments and crop sequence (conventional tillage (CT) and durum wheat monocropping (WW); conventional tillage (CT) and durum wheat following faba beans (WF); zero tillage (ZT) and durum wheat monocropping (WW); zero tillage (ZF) and durum wheat following faba beans (WF) on yield, grain quality traits as well as on disease incidence and severity in durum wheat (var. Saragolla). The results of two years of data of a long-term experiment (seven-year experiment; split-plot design) are discussed. The CA approach (ZT + WF), which always induced the highest grain yields (6.1 t ha−1 and 3.3 t ha−1 in 2016 and 2017) thanks to an increased number of spikes m−2 (296 vs. 269 and 303 vs. 287 spikes m−2 in 2016 and 2017, respectively) as well as a more pronounced ear length, demonstrated significantly positive influences in terms of grain quality. It promoted grain protein accumulation (12.1% for ZT + WF vs. 11.4% for ZT + WW and 12.4% for ZT + WF vs. 10.6% for ZT + WW in 2016 and 2017) and improved the gluten quality (in terms of sodium dodecyl sulphate (SDS) sedimentation test) and colour of the grain. The abundance of crop residues determined a higher incidence and severity of Zymoseptoria tritici leaf symptoms under the CA system; nevertheless, the late appearance of infection was the main reason for not affecting yield and quality traits. The presence of faba beans (WF) in the rotation significantly reduced leaf symptoms in Z. tritici.
GainTKW: A Measurement System of Thousand Kernel Weight Based on the Android Platform
Authors: Wu Wenhua , Zhou Lei , Chen Jian , Qiu Zhengjun , He Yong
Published: September 2018

Thousand kernel weight (TKW) is an important parameter for the evaluation of grain yield. The traditional measurement method relies on manual steps: weighing and counting. In this paper, we developed a system for the automated evaluation of thousand kernel weight that combines a weighing module and Android devices, called “gainTKW”. The system is able to collect the weight information from the weighing module through a serial port using the RS232-micro USB cable. In the imaging process, we adopt a k-means clustering segmentation algorithm to solve the problem of uneven lighting. We used the marker-controlled watershed algorithm and area threshold method to count the number of kernels that are touching one another. These algorithms were implemented based on the OpenCV (Open Source Computer Vision) libraries. The system tested kernel images of six species taken with the Android device under different lighting conditions. The algorithms in this study can solve the segmentation problems caused by shadows, as well. The appropriate numbers of kernels, of different species, are counted with an error ratio upper limit of 3%. The application is convenient and easy to operate. For the experiments, we can prove the efficiency and accuracy of the developed system by comparing the results between the manual method and the proposed application.
A Spatial Pyramid Pooling-Based Deep Convolutional Neural Network for the Classification of Electrocardiogram Beats
Authors: Li Jia , Si Yujuan , Lang Liuqi , Liu Lixun , Xu Tao
Published: September 2018

An accurate electrocardiogram (ECG) beat classification can benefit the diagnosis of the cardiovascular disease. Deep convolutional neural networks (CNN) can automatically extract valid features from data, which is an effective way for the classification of the ECG beats. However, the fully-connected layer in CNNs requires a fixed input dimension, which limits the CNNs to receive fixed-scale inputs. Signals of different scales are generally processed into the same size by segmentation and downsampling. If information loss occurs during a uniformly-sized process, the classification accuracy will ultimately be affected. To solve this problem, this paper constructs a new CNN framework spatial pyramid pooling (SPP) method, which solves the deficiency caused by the size of input data. The Massachusetts Institute of Technology-Biotechnology (MIT-BIH) arrhythmia database is employed as the training and testing data for the classification of heartbeat signals into six categories. Compared with the traditional method, which may lose a large amount of important information and easy to be over-fitted, the robustness of the proposed method can be guaranteed by extracting data features from different sizes. Experimental results show that the proposed architecture network can extract more high-quality features and exhibits higher classification accuracy (94%) than the traditional deep CNNs (90.4%).
Study on the Thermal Distribution Characteristics of High-Speed and Light-Load Rolling Bearing Considering Skidding
Authors: Li Junning , Xue Jiafan , Ma Zhitao
Published: September 2018

Skidding, which frequently occurs in high-speed rolling bearings, has a significant effect on the thermal distribution and service reliability of the bearings. An improved theoretical model of friction power loss distribution in high-speed and light-load rolling bearings (HSLLRBs) considering skidding is established, and the effects of various operating parameters on the friction power loss are investigated. The results show that the friction power loss of the inner ring and outer ring as well as the total friction power loss of the bearing increase as the slip ratio increases, but that the friction power loss of the cage guide surface and roller oil churning show a reverse trend. In addition, the increase in inner ring speed and kinematic viscosity leads to an increase in bearing friction power loss. The steady and transient temperature field distribution of HSLLRBs is obtained by the finite element method (FEM), and the results show that the inner ring raceway has the highest temperature, whereas the cage has the lowest. The temperature distribution test rig of a full-size roller bearing is constructed, and the influence mechanism of the slip ratio, rotation speed, load, lubrication, and surface topography on the bearing temperature distribution are obtained. The experimental results are consistent with the theoretical results, which also validates the theoretical method.
A Design of a Lightweight In-Vehicle Edge Gateway for the Self-Diagnosis of an Autonomous Vehicle
Authors: Jeong YiNa , Son SuRak , Jeong EunHee , Lee ByungKwan
Published: September 2018

This paper proposes a Lightweight In-Vehicle Edge Gateway (LI-VEG) for the self-diagnosis of an autonomous vehicle, which supports a rapid and accurate communication between in-vehicle sensors and a self-diagnosis module and between in-vehicle protocols. A paper on the self-diagnosis module has been published previously, thus this paper only covers the LI-VEG, not the self-diagnosis. The LI-VEG consists of an In-Vehicle Sending and Receiving Layer (InV-SRL), an InV-Management Layer (InV-ML) and an InV-Data Translator Layer (InV-DTL). First, the InV-SRL receives the messages from FlexRay, Control Area Network (CAN), Media Oriented Systems Transport (MOST), and Ethernet and transfers the received messages to the InV-ML. Second, the InV-ML manages the message transmission and reception of FlexRay, CAN, MOST, and Ethernet and an Address Mapping Table. Third, the InV-DTL decomposes the message of FlexRay, CAN, MOST, and Ethernet and recomposes the decomposed messages to the frame suitable for a destination protocol. The performance analysis of the LI-VEG shows that the transmission delay time about message translation and transmission is reduced by an average of 10.83% and the transmission delay time caused by traffic overhead is improved by an average of 0.95%. Therefore, the LI-VEG has higher compatibility and is more cost effective because it applies a software gateway to the OBD, compared to a hardware gateway. In addition, it can reduce the transmission error and overhead caused by message decomposition because of a lightweight message header.
Review on In Situ Acoustic Emission Monitoring in the Context of Structural Health Monitoring in Mines
Authors: Manthei Gerd , Plenkers Katrin
Published: September 2018

A major task in mines and even more in underground repositories for nuclear waste is to investigate crack formation for evaluation of rock mass integrity of the host rock. Therefore, in situ acoustic emission (AE) monitoring are carried out in mines as part of geomechanical investigations regarding the stability of underground cavities and the integrity of the rock mass. In this work, the capability of in situ AE monitoring in the context of structural health monitoring (SHM) in mines and in various geological settings will be reported. SHM pointed out, that the AE network is able to monitoring AE activity in rock with a volume up to 10 6 cubicmeter and distances up to 200 m (e.g., 100 m × 100 m × 100 m) in the frequency range of 1 kHz to 150 kHz. Very small AE events with source size in approximately centimeter to millimeter scale are detected. The results show that AE activity monitors rock deformation in geological boundaries due to convergence of the rock. In addition, high AE activity occurs in zones of dilatancy stress in homogenous rock. In conclusion in situ AE monitoring is a useful tool to observe instabilities in rock long before any damage becomes visible.
Passively Conducted Vibration Sensing with Fiber Bragg Gratings
Authors: Mohanty Lipi , Yang Yaowen , Tjin Swee Chuan
Published: September 2018

Measuring vibrations is a common method of monitoring the integrity of structures and heavy machinery, that are subject to dynamic loads. Strong vibrations for prolonged periods of time can be caused by various sources, such as trains, motors and heavy machinery. These strong vibrations should be identified and managed to ensure operational safety. This study proposes a flexible metal beam sensor with a fiber Bragg grating (FBG) mounted on the surface to measure the vibrational frequency. We present a sensor for measuring the vibrational frequencies on-site by placing the beam so that it makes physical contact with the vibrating body. The sensor has been tested in the range of 50–200 Hz. The sensing beam can detect the vibrations that are induced in other metallic bodies where there are metallic structures of low stiffness to conduct the vibration. The results show that the sensing beam is capable of detecting the frequency of forced vibrations from its periphery when placed in different orientations.
Research on Compression Behavior of Square Thin-Walled CFST Columns with Steel-Bar Stiffeners
Authors: Yang Zhao , Xu Chengxiang
Published: September 2018

Local buckling in steel tubes was observed to be capable of reducing the ultimate loads of thin-walled concrete-filled steel-tube (CFST) columns under axial compression. To strengthen the steel tubes, steel bars were proposed in this paper to be used as stiffeners fixed onto the tubes. Static-loading tests were conducted to study the compression behavior of square thin-walled CFST columns with steel bar stiffeners placed inside or outside the tube. The effect and feasibility of steel bar stiffeners were studied through the analysis of failure mode, load–displacement relationship, ultimate load, ductility, and local buckling. Different setting methods of steel bars were compared as well. The results showed that steel-bar stiffeners proposed in this paper can be effective in delaying local buckling as well as increasing the bearing capacity of the columns, but will decrease the ductility of the columns. In order to obtain a higher bearing capacity of columns, steel bars with low stiffness should be placed inside and steel bars with high stiffness should be placed outside of the steel tubes. The study is helpful in providing reference to the popularization and application of this new structural measure to avoid or delay the local buckling of thin-walled CFST columns.
Short-Term Load Forecasting Based on Elastic Net Improved GMDH and Difference Degree Weighting Optimization
Authors: Liu Wei , Dou Zhenhai , Wang Weiguo , Liu Yueyu , Zou Hao , Zhang Bo , Hou Shoujun
Published: September 2018

As objects of load prediction are becoming increasingly diversified and complicated, it is extremely important to improve the accuracy of load forecasting under complex systems. When using the group method of data handling (GMDH), it is easy for the load forecasting to suffer from overfitting and be unable to deal with multicollinearity under complex systems. To solve this problem, this paper proposes a GMDH algorithm based on elastic net regression, that is, group method of data handling based on elastic net (EN-GMDH), as a short-term load forecasting model. The algorithm uses an elastic net to compress and punish the coefficients of the Kolmogorov–Gabor (K–G) polynomial and select variables. Meanwhile, based on the difference degree of historical data, this paper carries out variable weight processing on the input data of load forecasting, so as to solve the impact brought by the abrupt change of load law. Ten characteristic variables, including meteorological factors, meteorological accumulation factors, and holiday factors, are taken as input variables. Then, EN-GMDH is used to establish the relationship between the characteristic variables and the load, and a short-term load forecasting model is established. The results demonstrate that, compared with other algorithms, the evaluation index of EN-GMDH is significantly better than that of the rest algorithm models in short-term load forecasting, and the accuracy of prediction is obviously improved.
From ‘Scottish’ Play to Japanese Film: Kurosawa’s Throne of Blood
Authors: Martinez Dolores P.
Published: September 2018

Shakespeare’s plays have become the subject of filmic remakes, as well as the source for others’ plot lines. This transfer of Shakespeare’s plays to film presents a challenge to filmmakers’ auterial ingenuity: Is a film director more challenged when producing a Shakespearean play than the stage director? Does having auterial ingenuity imply that the film-maker is somehow freer than the director of a play to change a Shakespearean text? Does this allow for the language of the plays to be changed—not just translated from English to Japanese, for example, but to be updated, edited, abridged, ignored for a large part? For some scholars, this last is more expropriation than pure Shakespeare on screen and under this category we might find Kurosawa’s Throne of Blood (Kumonosu-jō 1957), the subject of this essay. Here, I explore how this difficult tale was translated into a Japanese context, a society mistakenly assumed to be free of Christian notions of guilt, through the transcultural move of referring to Noh theatre, aligning the story with these Buddhist morality plays. In this manner Kurosawa found a point of commonality between Japan and the West when it came to stories of violence, guilt, and the problem of redemption.
Abrupt Climate Shift in the Mature Rainy Season of the Philippines in the Mid-1990s
Authors: Olaguera Lyndon Mark , Matsumoto Jun , Kubota Hisayuki , Inoue Tomoshige , Cayanan Esperanza O. , Hilario Flaviana D.
Published: September 2018

A robust climate shift around 1993/1994 from early August to early September, which corresponds to the mature rainy season of the Philippines, was identified in stations located over the western coast of the country. The convection in the mature rainy season during 1994–2008 (E2) was suppressed compared with 1979–1993 (E1). The possible role of the changes in the large-scale conditions and tropical cyclone (TC) activity were analyzed. The results show that the western North Pacific Subtropical High has extended further westward in E2 leading to an enhanced lower-level divergence and less moisture transport over the Philippines. The changes in the large-scale conditions, which featured a mid-tropospheric descent, a decrease in low-level relative humidity, an enhanced vertical zonal wind shear, and a decrease in the perturbation kinetic energy, also inhibited the synoptic-scale disturbances in the vicinity of the Philippines. In particular, fewer TCs developed and made landfall over the Philippines in E2. We also found inconsistent climate shifts in May, June, July, and September between the rainfall data from the stations and the Climate Prediction Center Merged Analysis of Precipitation, which highlights the importance of sub-seasonal analysis in decadal-to-interdecadal climate change studies.
Chemical Sensing Employing Plant Electrical Signal Response-Classification of Stimuli Using Curve Fitting Coefficients as Features
Authors: Chatterjee Shre Kumar , Malik Obaid , Gupta Siddharth
Published: September 2018

In order to exploit plants as environmental biosensors, previous researches have been focused on the electrical signal response of the plants to different environmental stimuli. One of the important outcomes of those researches has been the extraction of meaningful features from the electrical signals and the use of such features for the classification of the stimuli which affected the plants. The classification results are dependent on the classifier algorithm used, features extracted and the quality of data. This paper presents an innovative way of extracting features from raw plant electrical signal response to classify the external stimuli which caused the plant to produce such a signal. A curve fitting approach in extracting features from the raw signal for classification of the applied stimuli has been adopted in this work, thereby evaluating whether the shape of the raw signal is dependent on the stimuli applied. Four types of curve fitting models—Polynomial, Gaussian, Fourier and Exponential, have been explored. The fitting accuracy (i.e., fitting of curve to the actual raw signal) depicted through R-squared values has allowed exploration of which curve fitting model performs best. The coefficients of the curve fit models were then used as features. Thereafter, using simple classification algorithms such as Linear Discriminant Analysis (LDA), Quadratic Discriminant Analysis (QDA) etc. within the curve fit coefficient space, we have verified that within the available data, above 90% classification accuracy can be achieved. The successful hypothesis taken in this work will allow further research in implementing plants as environmental biosensors.
Safety of Transcranial Direct Current Stimulation of Frontal, Parietal, and Cerebellar Regions in Fasting Healthy Adults
Authors: Almousa Abdullah , Alajaji Reema , Alaboudi Malak , Al-sultan Fahad , Bashir Shahid
Published: September 2018

(1) Background: Transcranial direct current stimulation (tDCS) is a non-invasive brain stimulation modality that has been investigated in a large number of studies in terms of it is effects on brain function, safety of use, and future implications. The principal aim of this study was to investigate the safety of 1.5-mA tDCS of three brain areas, that is, frontal, partial, and cerebellar cortices, in fasting healthy individuals during the month of Ramadan. (2) Methods: In a single-blinded, sham-controlled study, we assessed the safety of a 20-min tDCS current (1.5 mA, 35 cm2) over the right frontal, parietal, and cerebellar cortex areas after 8 h of fasting in healthy right-handed adult subjects using a standard safety questionnaire. (3) Results: A total of 49 subjects completed the tDCS sessions and safety questionnaire. None of the sessions were stopped due to pain or discomfort during stimulation. Moreover, no subject experienced serious adverse events such as seizures or loss of consciousness. (4) Conclusions: There was no significant difference in the frequency or type of side effects between active and sham stimulation sessions. The tDCS protocol applied in this study was found to be safe in fasting healthy adults.
Evaluation of Thermal Comfort in Traditional Houses in a Tropical Climate
Authors: Shaeri Jalil , Yaghoubi Mahmood , Aflaki Ardalan , Habibi Amin
Published: September 2018

A considerable amount of energy is being consumed for heating and cooling indoor environments in order to provide thermal comfort. For older buildings located in the southern parts of Iran, particularly in Bushehr, many climatic and passive design strategies are being used to provide indoor thermal comfort. This architecture and these elements have been developed in response to unfavorable weather conditions. The current study aimed to identify those passive elements and evaluate indoor thermal comfort in older houses. To achieve these objectives, passive elements in main houses located in the ancient urban structure were first identified. Then, a house in the coastal belt, Tabib’s house, and another house inside the ancient urban structure, Nozari’s house, were selected for the purpose of field measurement. The results revealed that the passive techniques used in these older houses significantly provide sufficient indoor thermal conditions. The mean measured predicted mean vote (PMV) of Tabib’s rooms was 0.88 and the mean measured PMV of Nozari’s rooms was 0.91, which were in an acceptable range. The measured predicted percentage of dissatisfied of rooms in both houses were lower than 10%. The main factor in creating indoor thermal comfort in these houses was the natural ventilation and its availability in the selected houses.
Two Possible Side Reaction Pathways during Furanic Etherification
Authors: Fang Wenting , Hu Hualei , Ma Zhongsen , Wang Lei , Zhang Yajie
Published: September 2018

The revealing mechanism of side reactions is crucial for obtaining theoretical yield in industrialization when 2,5-bis(methoxymethyl)furan (BMMF) yield is above 95%. By-products catalyzed by the conventional ZSM-5 (C-ZSM-5) and hierarchical porous ZSM-5 (HP-ZSM-5) catalytic systems were different, and some key by-products were identified. Thus, possible pathways were proposed, which helps to further improve BMMF selectivity. Additionally, HP-ZSM-5 exhibited quicker reaction rate, higher BMMF yield and selectivity, and slower deactivation process. The relatively weak acidity of HP-ZSM-5 suppresses the ring-opening reaction and subsequent side reactions, and introduction of mesopores improves mass transport and slightly increases hydration of 2,5-bis(hydroxymethyl)furan (BHMF).
A Hybrid Reactor System Comprised of Non-Thermal Plasma and Mn/Natural Zeolite for the Removal of Acetaldehyde from Food Waste
Authors: Song Min Young , Ryu Hae Won , Jung Sang-Chul , Song JiHyeon , Kim Byung-Joo , Park Young-Kwon
Published: September 2018

The degradation of low concentrations of acetaldehyde while using a non-thermal plasma (NTP)/catalyst hybrid reactor system was investigated while using humidified air at ambient temperature. A series of highly active manganese-impregnated natural zeolite (Mn/NZ) catalysts were synthesized by the incipient wetness method using sonication. The Mn/NZ catalysts were analyzed by Brunauer-Emmett-Teller surface area measurements and X-ray photoelectron spectroscopy. The Mn/NZ catalyst located at the downstream of a dc corona was used for the decomposition of ozone and acetaldehyde. The decomposition efficiency of ozone and acetaldehyde was increased significantly using the Mn/NZ catalyst with NTP. Among the various types of Mn/NZ catalysts with different Mn contents, the 10 wt.% Mn/NZ catalyst under the NTP resulted the highest ozone and acetaldehyde removal efficiency, almost 100% within 5 min. Moreover, this high efficiency was maintained for 15 h. The main reason for the high catalytic activity and stability was attributed to the high dispersion of Mn on the NZ made by the appropriate impregnation method using sonication. This system is expected to be efficient to decompose a wide range of volatile organic compounds with low concentrations.
Classical and Quantum Causal Interventions
Authors: Milburn Gerard , Shrapnel Sally
Published: September 2018

Characterising causal structure is an activity that is ubiquitous across the sciences. Causal models are representational devices that can be used as oracles for future interventions, to predict how values of some variables will change in response to interventions on others. Recent work has generalised concepts from this field to situations involving quantum systems, resulting in a new notion of quantum causal structure. A key concept in both the classical and quantum context is that of an intervention. Interventions are the controlled operations required to identify causal structure and ultimately the feature that endows causal models with empirical meaning. Although interventions are a crucial feature of both the classical and quantum causal modelling frameworks, to date there has been no discussion of their physical basis. In this paper, we consider interventions from a physical perspective and show that, in both the classical and quantum case, they are constrained by the thermodynamics of measurement and feedback in open systems. We demonstrate that the perfect “atomic” or “surgical” interventions characterised by Pearl’s famous do-calculus are physically impossible, and this is the case for both classical and quantum systems.
Information Geometric Approach on Most Informative Boolean Function Conjecture
Authors: No Albert
Published: September 2018

Let X n be a memoryless uniform Bernoulli source and Y n be the output of it through a binary symmetric channel. Courtade and Kumar conjectured that the Boolean function f : { 0 , 1 } n → { 0 , 1 } that maximizes the mutual information I ( f ( X n ) ; Y n ) is a dictator function, i.e., f ( x n ) = x i for some i. We propose a clustering problem, which is equivalent to the above problem where we emphasize an information geometry aspect of the equivalent problem. Moreover, we define a normalized geometric mean of measures and interesting properties of it. We also show that the conjecture is true when the arithmetic and geometric mean coincide in a specific set of measures.
Hardware Acceleration for RLNC: A Case Study Based on the Xtensa Processor with the Tensilica Instruction-Set Extension
Authors: Acevedo Javier , Scheffel Robert , Wunderlich Simon , Hasler Mattis , Pandi Sreekrishna , Cabrera Juan , Fitzek Frank H. P. , Fettweis Gerhard , Reisslein Martin
Published: September 2018

Random linear network coding (RLNC) can greatly aid data transmission in lossy wireless networks. However, RLNC requires computationally complex matrix multiplications and inversions in finite fields (Galois fields). These computations are highly demanding for energy-constrained mobile devices. The presented case study evaluates hardware acceleration strategies for RLNC in the context of the Tensilica Xtensa LX5 processor with the tensilica instruction set extension (TIE). More specifically, we develop TIEs for multiply-accumulate (MAC) operations for accelerating matrix multiplications in Galois fields, single instruction multiple data (SIMD) instructions operating on consecutive memory locations, as well as the flexible-length instruction extension (FLIX). We evaluate the number of clock cycles required for RLNC encoding and decoding without and with the MAC, SIMD, and FLIX acceleration strategies. We also evaluate the RLNC encoding and decoding throughput and energy consumption for a range of RLNC generation and code word sizes. We find that for GF ( 2 8 ) and GF ( 2 16 ) RLNC encoding, the SIMD and FLIX acceleration strategies achieve speedups of approximately four hundred fold compared to a benchmark C code implementation without TIE. We also find that the unicore Xtensa LX5 with SIMD has seven to thirty times higher RLNC encoding and decoding throughput than the state-of-the-art ODROID XU3 system-on-a-chip (SoC) operating with a single core; the Xtensa LX5 with FLIX, in turn, increases the throughput by roughly 25% compared to utilizing only SIMD. Furthermore, the Xtensa LX5 with FLIX consumes roughly three orders of magnitude less energy than the ODROID XU3 SoC.
Chitosan-Based Quartz Crystal Microbalance for Alcohol Sensing
Authors: Triyana Kuwat , Sembiring Agustinus , Rianjanu Aditya , Hidayat Shidiq Nur , Riowirawan Riowirawan , Julian Trisna , Kusumaatmaja Ahmad , Santoso Iman , Roto Roto
Published: September 2018

Short-chain alcohols are a group of volatile organic compounds (VOCs) that are often found in workplaces and laboratories, as well as medical, pharmaceutical, and food industries. Real-time monitoring of alcohol vapors is essential because exposure to alcohol vapors with concentrations of 0.15–0.30 mg·L−1 may be harmful to human health. This study aims to improve the detection capabilities of quartz crystal microbalance (QCM)-based sensors for the analysis of alcohol vapors. The active layer of chitosan was immobilized onto the QCM substrate through a self-assembled monolayer of L-cysteine using glutaraldehyde as a cross-linking agent. Before alcohol analysis, the QCM sensing chip was exposed to humidity because water vapor significantly interferes with QCM gas sensing. The prepared QCM sensor chip was tested for the detection of four different alcohols: n-propanol, ethanol, isoamyl alcohol, and n-amyl alcohol. For comparison, a non-alcohol of acetone was also tested. The prepared QCM sensing chip is selective to alcohols because of hydrogen bond formation between the hydroxyl groups of chitosan and the analyte. The highest response was achieved when the QCM sensing chip was exposed to n-amyl alcohol vapor, with a sensitivity of about 4.4 Hz·mg−1·L. Generally, the sensitivity of the QCM sensing chip is dependent on the molecular weight of alcohol. Moreover, the developed QCM sensing chips are stable after 10 days of repeated measurements, with a rapid response time of only 26 s. The QCM sensing chip provides an alternative method to established analytical methods such as gas chromatography for the detection of short-chain alcohol vapors.
Improved Step Load Response of a Dual-Active-Bridge DC–DC Converter
Authors: Zhang Yifan , Li Xiaodong , Sun Chuan , He Zhanhong
Published: September 2018

This paper proposes a fast load transient control for a bidirectional dual-active-bridge (DAB) DC/DC converter. It is capable of maintaining voltage–time balance during a step load change process so that no overshoot current and DC offset current exist. The transient control has been applied for all possible transition cases and the calculation of intermediate switching angles referring to the fixed reference points is independent from the converter parameters and the instantaneous current. The results have been validated by extended experimental tests.
Correlation Analysis between Wind Speed/Voltage Clusters and Oscillation Modes of Doubly-Fed Induction Generators
Authors: Miao Jierong , Xie Da , Gu Chenghong , Wang Xitian
Published: September 2018

Potential machine-grid interactions caused by large-scale wind farms have drawn much attention in recent years. Previous work has been done by analyzing the small–signal modeling of doubly-fed induction generators (DFIGs) to obtain the oscillation modes. This paper, by making use of the metered power data of wind generating sets, studies the correlation between oscillation modes of the DFIG system and influence factors which includes wind speed and grid voltage. After the metered data is segmented, the Prony algorithm is used to analyze the oscillation modes contained in the active power. Then, the relevant oscillation modes are extracted in accordance with the small-signal analysis results. Meanwhile, data segments are clustered according to wind speed and grid voltage. The Apriori algorithm is finally used to discuss the association rules. By training the mass of data of wind generating sets, the inevitable association rules between oscillation modes and influence factors can be mined. Therefore, the prediction of oscillation modes can be achieved based on the rules. The results show that the clustering number quite affects the association rules. When the optimal cluster number is adopted, part of the wind speed/voltage clusters can analyze the certain oscillation modes. The predicted results are quite consistent with the practical data.
On Small Signal Frequency Stability under Virtual Inertia and the Role of PLLs
Authors: Khan Sohail , Bletterie Benoit , Anta Adolfo , Gawlik Wolfgang
Published: September 2018

This paper presents a methodology that aims at identifying virtual inertia (VI) gain limitations from virtual synchronous generators (VSGs) while maintaining the frequency stability considering the delay associated with the frequency measurement process. The phase-locked loop (PLL) is typically used for frequency estimation that is used to calculate the rate of change of frequency (RoCoF) and it drives the VI loop. The PLL is generally accompanied by a low-pass filter that aims to suppress the impact of harmonics. This filter introduces a delay that when used with the VI control loop causes stability issues for high values of VI gain. A comparison of various PLL approaches suggests that certain variants tend to permit higher value of cut-off frequencies which can be utilized to increase the VI gain limit from VSG. This study presents a method by which the upper limit on VI gain can be quantified and related to the cut-off frequency of the PLL low pass filter that is indirectly representing the delay. It is performed using small signal frequency stability analysis on the frequency domain model of the grid with virtual inertia emulating VSG. The effective maximum VI gain from VSG is explored while satisfying the frequency measurement accuracy specification considering harmonics. The results show that the requirements of reaching a stable operation with sufficient stability margins can still be met with a faster PLL-based system and the potential increases in VI support from VSG can be quantified using the proposed method. The study has been first performed on a single machine single inverter bus (SMSIB) system and is generalized to the multi-machine and multi-inverter system.
Multi-Objective Control of Air Conditioning Improves Cost, Comfort and System Energy Balance
Authors: Izawa Andrew , Fripp Matthias
Published: September 2018

A new model predictive control (MPC) algorithm is used to select optimal air conditioning setpoints for a commercial office building, considering variable electricity prices, weather and occupancy. This algorithm, Cost-Comfort Particle Swarm Optimization (CCPSO), is the first to combine a realistic, smooth representation of occupants’ willingness to pay for thermal comfort with a bottom-up, nonlinear model of the building and air conditioning system under control. We find that using a quadratic preference function for temperature can yield solutions that are both more comfortable and lower-cost than previous work that used a “brick wall” preference function with no preference for further cooling within an allowed temperature band and infinite aversion to going outside the allowed band. Using historical pricing data for a summer month in Chicago, CCPSO provided a 1% reduction in costs vs. a similar “brick-wall” MPC approach with the same comfort and 6–11% reduction in costs vs. other control strategies in the literature. CCPSO can also be used to operate the building with much greater comfort and costs or much lower costs and comfort than the “brick-wall” approach, depending on user preferences. CCPSO also reduced peak-hours demand by 3% vs. the “brick-wall” strategy and 4–14% vs. other strategies. At the same time, the CCPSO strategy increased off-peak energy consumption by 15% or more vs. other control methods. This may be valuable for power systems integrating large amounts of renewable power, which can otherwise become uneconomic due to saturation of demand during off-peak hours.
Dimensional Analysis of Power Prediction of a Real-Scale Wind Turbine Based on Wind-Tunnel Torque Measurement of Small-Scaled Models
Authors: Sutrisno  , Iswahyudi Sigit , Wibowo Setyawan
Published: September 2018

A preliminary study of a horizontal-axis wind turbine (HAWT) design is carried out using a wind tunnel to obtain its aerodynamic characteristics. Utilization of data from the study to develop large-scale wind turbines requires further study. This paper aims to discuss the use of wind turbine data obtained the wind-tunnel measurements to estimate the characteristics of wind turbines that have field size. One should measure the torque of two small-scale turbines inside the wind tunnel. The first small-scale turbine has a radius of 0.14 m, and the radius of the second small turbine is 0.19 m. Torque measurement results from both turbines were analyzed using the Buckingham π theorem to obtain a correlation between torsion and diameter variations. The obtained correlation equation was used to estimate the field measurement of turbine power with a radius of 1.2 m. The resulting correlation equation can be applied to approximate the energy generated by the turbine using the size of the field well in the operating area and the tip-speed ratio (λ) of the turbine design.
Analytical Calculation of Armature Reaction Field of the Interior Permanent Magnet Motor
Authors: Ma Fangwu , Yin Hongbin , Wei Lulu , Wu Liang , Gu Cansong
Published: September 2018

The energy crisis and environmental concerns worldwide have helped usher in the age of electric vehicles (EVs) and hybrid EVs (HEVs). The interior permanent magnet motors (IPMMs) are widely used in these vehicles. The analysis of the armature reaction field is the most critical issue in the study of IPMMs since it determines the characters of torque, efficiency, vibration, and the radiated acoustic noise. This paper provides a calculation method of the armature reaction magnetic field (ARMF) of an IPMM. First, the formulas of ARMF without magnetic barrier are derived. Second, the relative permeance function of an IPMM is calculated. Third, the analytical solution of the ARMF of an IPMM is derived by applying the armature reaction magnetic field with unsaturated rotor multiplied by relative permeance function. Finally, several results of comparisons between the calculation method proposed in this paper and the finite element method are presented. Based on the calculation method proposed in this paper, the magnetic barrier’s influence on the ARMF is studied. The spatial harmonic orders and time harmonic orders of the ARMF of IPMM are revealed respectively.
Cross-Border Electricity Transmission Network Investment: Perspective and Risk Framework of Third Party Investors
Authors: Huang Diyun , Van Hertem Dirk
Published: September 2018

In Europe, significant amount of interconnection capacity investments are expected in the next decades. However, the risks associated with transmission network investment in the cross-border context are rarely discussed. In this paper, we develop a conceptual framework to assess the cross-border transmission network investment risks from the third party investor perspective. Risks are examined in relation to cost benefit perceptions in different phases of projects to shed lights of the dynamics in the life cycle of the project. The risk framework also takes into account the energy governance at different institutional level to characterize the uncertainties from cross-border coordination. The proposed risk framework is applied to the European case study.
Novel Analytical Microbial Fuel Cell Design for Rapid in Situ Optimisation of Dilution Rate and Substrate Supply Rate, by Flow, Volume Control and Anode Placement
Authors: You Jiseon , Greenman John , Ieropoulos Ioannis
Published: September 2018

A new analytical design of continuously-fed microbial fuel cell was built in triplicate in order to investigate relations and effects of various operating parameters such as flow rate and substrate supply rate, in terms of power output and chemical oxygen demand (COD) removal efficiency. This novel design enables the microbial fuel cell (MFC) systems to be easily adjusted in situ by changing anode distance to the membrane or anodic volume without the necessity of building many trial-and-error prototypes for each condition. A maximum power output of 20.7 ± 1.9 µW was obtained with an optimal reactor configuration; 2 mM acetate concentration in the feedstock coupled with a flow rate of 77 mL h−1, an anodic volume of 10 mL and an anode electrode surface area of 70 cm2 (2.9 cm2 projected area), using a 1 cm anode distance from the membrane. COD removal almost showed the reverse pattern with power generation, which suggests trade-off correlation between these two parameters, in this particular example. This novel design may be most conveniently employed for generating empirical data for testing and creating new MFC designs with appropriate practical and theoretical modelling.
Wireless Power Charger Based on Class E Amplifier with the Maximum Power Point Load Consideration
Authors: Dai Weili , Tang Wei , Cai Changchun , Deng Lihua , Zhang Xiaofeng
Published: September 2018

The construction of an electromagnetic coupling power transfer system is introduced in this paper. Considering the characteristics of the battery charger, a novel parameter design method based on the load of the maximum power transfer point is proposed. Then, the compensator, resonant circuits, and some key parameters of the electromagnetic coupler are discussed in detail by constructing a mutual inductance model to carry out impedance calculation and analysis. Coupling coefficient influenced by different magnetic circuits and coil distribution were analyzed by building a finite element model and an equivalent magnetic circuit. Moreover, impedance matching and compensation network parameters were theoretically calculated and simulated. Finally, a wireless power charger based on an open-loop class E amplifier with the maximum power point load consideration was manufactured. Simulation and experiments were done to verify the analyses, and the capability of 4.2 W power delivery at a distance of 10 mm and a peak system efficiency exceeding 72% were demonstrated.
Locating Fault on Transmission Line with Static Var Compensator Based on Phasor Measurement Unit
Authors: Khoa Ngo Minh , Tung Doan Duc
Published: September 2018

The flexible alternating current transmission systems (FACTS) have been widely used in modern power systems. Because of the presence of the FACTS devices, distance relays in transmission lines may inaccurately locate fault locations. Therefore, it is significant to find a mechanism for locating fault in transmission lines connected to FACTS in which a static var compensator (SVC) is investigated in this work. Based on the development of a phasor measurement unit (PMU) with global positioning system (GPS), this paper proposes a new method for calculating apparent impedance seen by the distance relay location while a short-circuit fault occurs in a transmission line connected the SVC to the midpoint of the line. According to the method, sampled voltage and current measurement at the relay and SVC locations are synchronized using PMUs and the synchronized measurements are then used to calculate a new apparent impedance and to locate the fault location in the line. The method in this paper has the capability for fast calculation and it also has the robustness for identifying different fault types in power systems. Matlab/Simulink software is applied to simulate the study results and to evaluate the correctness of the modeling and effectiveness of the proposed method for locating fault in this paper.
Simulation of a Fluidized Bed Dryer for the Drying of Sago Waste
Authors: Rosli Masli Irwan , Abdul Nasir Abdul Mu’im , Takriff Mohd Sobri , Chern Lee Pei
Published: September 2018

The large amount of sago waste produced by sago processing industries can cause serious environmental problems. When dried, these residues usually have a high starch content (around 58%) and have many potential applications. In this study, the drying of sago waste using a fluidized bed dryer (FBD), which offers more advantages than other drying methods, is analyzed via computational fluid dynamics (CFD) modeling. A two-dimensional (2D) FBD model is also developed and a mesh independency test is conducted immediately afterwards. A fine mesh is selected for the CFD model and a simulation is conducted using ANSYS Fluent 17.1 software (Ansys Inc., version 17.1, Canonsburg, PA, USA). The governing and discretized algebraic equations are solved by applying the phase-coupled semi-implicit method for pressure-linked equations. Both the Eulerian–Eulerian multiphase model approach and the turbulence model are applied in the simulation due to the turbulent flow in the dryer. A velocity of 1.30 m/s and temperature of 50 °C are selected as boundary conditions based on the optimum parameter values from previous experiments. The final moisture content that we aim to achieve is 10% or a moisture ratio of 0.25 in sago waste for the purpose of animal feed, so as to prevent bacterial growth and for packaging purposes based on common industrial practice. Both the drying rate and fluidization profile are examined at air velocities of 0.6, 1.0, 1.3, 1.8, and 2.2 m/s. Based on the results, the velocity range of 1.0 m/s to 2.2 m/s is deemed suitable for the fluidization and drying of sago waste with a particle size of 2000 μm for a drying simulation of 1 h. The drying rate is further examined at air temperatures of 50 °C, 60 °C, 70 °C, and 80 °C, whereas the fluidization profile is examined at particle sizes of 200, 500, 1000, and 2000 μm. The results reveal excellent fluidization at a particle size range of 500 μm to 2000 μm and a velocity of 1.3 m/s.