The 50 most-cited articles in Applied Sciences, 2016

This paper presents and discusses various metrics proposed for evaluation of polyphonic sound event detection systems used in realistic situations where there are typically multiple sound sources active simultaneously. The system output in this case contains overlapping events, marked as multiple sounds detected as being active at the same time. The polyphonic system output requires a suitable procedure for evaluation against a reference. Metrics from neighboring fields such as speech recognition and speaker diarization can be used, but they need to be partially redefined to deal with the overlapping events. We present a review of the most common metrics in the field and the way they are adapted and interpreted in the polyphonic case. We discuss segment-based and event-based definitions of each metric and explain the consequences of instance-based and class-based averaging using a case study. In parallel, we provide a toolbox containing implementations of presented metrics.

Dedicated multi-project wafer (MPW) runs for photonic integrated circuits (PICs) from Si foundries mean that researchers and small-to-medium enterprises (SMEs) can now afford to design and fabricate Si photonic chips. While these bare Si-PICs are adequate for testing new device and circuit designs on a probe-station, they cannot be developed into prototype devices, or tested outside of the laboratory, without first packaging them into a durable module. Photonic packaging of PICs is significantly more challenging, and currently orders of magnitude more expensive, than electronic packaging, because it calls for robust micron-level alignment of optical components, precise real-time temperature control, and often a high degree of vertical and horizontal electrical integration. Photonic packaging is perhaps the most significant bottleneck in the development of commercially relevant integrated photonic devices. This article describes how the key optical, electrical, and thermal requirements of Si-PIC packaging can be met, and what further progress is needed before industrial scale-up can…

Endowing machines with sensing capabilities similar to those of humans is a prevalent quest in engineering and computer science. In the pursuit of making computers sense their surroundings, a huge effort has been conducted to allow machines and computers to acquire, process, analyze and understand their environment in a human-like way. Focusing on the sense of hearing, the ability of computers to sense their acoustic environment as humans do goes by the name of machine hearing. To achieve this ambitious aim, the representation of the audio signal is of paramount importance. In this paper, we present an up-to-date review of the most relevant audio feature extraction techniques developed to analyze the most usual audio signals: speech, music and environmental sounds. Besides revisiting classic approaches for completeness, we include the latest advances in the field based on new domains of analysis together with novel bio-inspired proposals. These approaches are described following a taxonomy that organizes them according to their physical or perceptual basis, being subsequently…

Structural health monitoring is an important aspect of maintenance for bridge columns in areas of high seismic activity. In this project, recently developed piezoceramic-based transducers, known as smart aggregates (SA), were utilized to perform structural health monitoring of a reinforced concrete (RC) bridge column subjected to pseudo-dynamic loading. The SA-based approach has been previously verified for static and dynamic loading but never for pseudo-dynamic loading. Based on the developed SAs, an active-sensing approach was developed to perform real-time health status evaluation of the RC column during the loading procedure. The existence of cracks attenuated the stress wave transmission energy during the loading procedure and reduced the amplitudes of the signal received by SA sensors. To detect the crack evolution and evaluate the damage severity, a wavelet packet-based structural damage index was developed. Experimental results verified the effectiveness of the SAs in structural health monitoring of the RC column under pseudo-dynamic loading. In addition to monitoring the…

Today’s world needs highly efficient systems that can fulfill the growing demand for energy. One of the promising solutions is the fuel cell. Solid oxide fuel cell (SOFC) is considered by many developed countries as an alternative solution of energy in near future. A lot of efforts have been made during last decade to make it commercial by reducing its cost and increasing its durability. Different materials, designs and fabrication technologies have been developed and tested to make it more cost effective and stable. This article is focused on the advancements made in the field of high temperature SOFC. High temperature SOFC does not need any precious catalyst for its operation, unlike in other types of fuel cell. Different conventional and innovative materials have been discussed along with properties and effects on the performance of SOFC’s components (electrolyte anode, cathode, interconnect and sealing materials). Advancements made in the field of cell and stack design are also explored along with hurdles coming in their fabrication and performance. This article also gives an…

Lithium-ion batteries are the primary power source in electric vehicles, and the prognosis of their remaining useful life is vital for ensuring the safety, stability, and long lifetime of electric vehicles. Accurately establishing a mechanism model of a vehicle lithium-ion battery involves a complex electrochemical process. Remaining useful life (RUL) prognostics based on data-driven methods has become a focus of research. Current research on data-driven methodologies is summarized in this paper. By analyzing the problems of vehicle lithium-ion batteries in practical applications, the problems that need to be solved in the future are identified.

Climate change, awareness of energy efficiency, new trends in electricity markets, the obsolescence of the actual electricity model, and the gradual conversion of consumers to prosumer profiles are the main agents of progressive change in electricity systems towards the Smart Grid paradigm. The introduction of multiple distributed generation and storage resources, with a strong involvement of renewable energies, exposes the necessity of advanced metering or Smart Metering systems, able to manage and control those distributed resources. Due to the heterogeneity of the Smart Metering systems and the specific features of each grid, it is easy to find in the related literature a wide range of solutions with different features. This work describes the key elements in a Smart Metering system and compiles the most employed technologies and standards as well as their main features. Since Smart Metering systems can perform jointly with other activities, these growing initiatives are also addressed. Finally, a revision of the main trends in Smart Metering uses and deployments worldwide is…

We review the application of atomically thin transition metal dichalcogenides in optoelectronic devices. First, a brief overview of the optical properties of two-dimensional layered semiconductors is given and the role of excitons and valley dichroism in these materials are discussed. The following sections review and compare different concepts of photodetecting and light emitting devices, nanoscale lasers, single photon emitters, valleytronics devices, as well as photovoltaic cells. Lateral and vertical device layouts and different operation mechanisms are compared. An insight into the emerging field of valley-based optoelectronics is given. We conclude with a critical evaluation of the research area, where we discuss potential future applications and remaining challenges.

Spinel copper ferrite (CuFe2O4) and zinc ferrite (ZnFe2O4) nanoparticles were synthesized using a sol-gel self-combustion technique. The structural, functional, morphological and magnetic properties of the samples were investigated by Fourier transform infrared spectroscopy (FTIR), X-ray diffraction (XRD), Transmission electron microscopy (TEM) and vibrating sample magnetometry (VSM). XRD patterns conform to the copper ferrite and zinc ferrite formation, and the average particle sizes were calculated by using a transmission electron microscope, the measured particle sizes being 56 nm for CuFe2O4 and 68 nm for ZnFe2O4. Both spinel ferrite nanoparticles exhibit ferromagnetic behavior with saturation magnetization of 31 emug−1 for copper ferrite (50.63 Am2/Kg) and 28.8 Am2/Kg for zinc ferrite. Both synthesized ferrite nanoparticles were equally effective in scavenging 2,2-diphenyl-1-picrylhydrazyl hydrate (DPPH) free radicals. ZnFe2O4 and CuFe2O4 nanoparticles showed 30.57% ± 1.0% and 28.69% ± 1.14% scavenging activity at 125 µg/mL concentrations. In vitro cytotoxicity study revealed…

(Aim) Classification of brain images as pathological or healthy case is a key pre-clinical step for potential patients. Manual classification is irreproducible and unreliable. In this study, we aim to develop an automatic classification system of brain images in magnetic resonance imaging (MRI). (Method) Three datasets were downloaded from the Internet. Those images are of T2-weighted along axial plane with size of 256 × 256. We utilized an s-level decomposition on the basis of dual-tree complex wavelet transform (DTCWT), in order to obtain 12s “variance and entropy (VE)” features from each subband. Afterwards, we used support vector machine (SVM) and its two variants: the generalized eigenvalue proximal SVM (GEPSVM) and the twin SVM (TSVM), as the classifiers. In all, we proposed three novel approaches: DTCWT + VE + SVM, DTCWT + VE + GEPSVM, and DTCWT + VE + TSVM. (Results) The results showed that our “DTCWT + VE + TSVM” obtained an average accuracy of 99.57%, which was not only better than the two other proposed methods, but also superior to 12 state-of-the-art approaches. In…

In this paper, a piezoelectric impedance frequency shift method is developed to estimate the bolt preload for the detection of bolt looseness in engineering structures. An experimental device that allows the precision control of the axial preload force on a bolt is designed and fabricated. A universal testing machine is used to preload accurately on the bolt in the experiments. Under different bolt preload conditions, the impedance analyzer measures the admittance (inverse of the impedance) signal of the PZT (Lead ZirconateTitanate) patches which are bonded on the bolt head. Firstly, a wide frequency band is swept to find a sensitive frequency band of the piezoelectric admittance with the imaginary part. Then in the sensitive frequency band, a specified peak frequency of the admittance signature is chosen to investigate the frequency shift with different bolt preloads. The relationship between the specified frequency shift and the bolt preload is established. The experimental results show that the specified peak frequency decreases as the bolt preload increases for both M16 and M12…

The implementation of effective strategies to manage leaks represents an essential goal for all utilities involved with drinking water supply in order to reduce water losses affecting urban distribution networks. This study concerns the early detection of leaks occurring in small-diameter customers’ connections to water supply networks. An experimental campaign was carried out in a test bed to investigate the sensitivity of Acoustic Emission (AE) monitoring to water leaks. Damages were artificially induced on a polyethylene pipe (length 28 m, outer diameter 32 mm) at different distances from an AE transducer. Measurements were performed in both unburied and buried pipe conditions. The analysis permitted the identification of a clear correlation between three monitored parameters (namely total Hits, Cumulative Counts and Cumulative Amplitude) and the characteristics of the examined leaks.

In this paper, the influence of induced magnetic field on free convection of Al2O3-water nanofluid on permeable plate by means of Koo-Kleinstreuer-Li (KKL) model is reported. Impact of Brownian motion, along with the properties of nanofluid, are also taken into account. The resulting equations are solved utilizing Runge-Kutta integration method. Obtained results are examined for innumerable energetic parameters, namely Al2O3 volume fraction, suction parameter, and Hartmann and magnetic Prandtl numbers. Results indicate that the velocity profile reduces with rise of the suction parameter and magnetic Prandtl and Hartmann numbers but it increases with addition of nanoparticles. Shear stress enhances with rise of suction parameter, magnetic Prandtl and Hartmann numbers. Temperature gradient improves with augment of suction parameter.

In the race towards two-dimensional electronic and optoelectronic devices, semiconducting transition metal dichalcogenides (TMDCs) from group VIB have been intensively studied in recent years due to the indirect to direct band-gap transition from bulk to the monolayer. However, new materials still need to be explored. For example, semiconducting TMDCs from group IVB have been predicted to have larger mobilities than their counterparts from group VIB in the monolayer limit. In this work we report the mechanical exfoliation of ZrX2 (X = S, Se) from bulk down to the monolayer and we study the dimensionality dependence of the Raman spectra in ambient conditions. We observe Raman signal from bulk to few layers and no shift in the peak positions is found when decreasing the dimensionality. While a Raman signal can be observed from bulk to a bilayer for ZrS2, we could only detect signal down to five layers for flakes of ZrSe2. These results show the possibility of obtaining atomically thin layers of ZrX2 by mechanical exfoliation and represent one of the first steps towards the…

Audio equalization is a vast and active research area. The extent of research means that one often cannot identify the preferred technique for a particular problem. This review paper bridges those gaps, systemically providing a deep understanding of the problems and approaches in audio equalization, their relative merits and applications. Digital signal processing techniques for modifying the spectral balance in audio signals and applications of these techniques are reviewed, ranging from classic equalizers to emerging designs based on new advances in signal processing and machine learning. Emphasis is placed on putting the range of approaches within a common mathematical and conceptual framework. The application areas discussed herein are diverse, and include well-defined, solvable problems of filter design subject to constraints, as well as newly emerging challenges that touch on problems in semantics, perception and human computer interaction. Case studies are given in order to illustrate key concepts and how they are applied in practice. We also recommend preferred signal…

Piezoceramic based active sensing methods have been researched to monitor preload on bolt connections. However, there is a saturation problem involved with this type of method. The transmitted energy is sometimes saturated before the maximum preload which is due to it coming into contact with flat surfaces. When it comes to flat contact surfaces, the true contact area will easily saturate with the preload. The design of a new type of bolt looseness monitoring sensor, a smart washer, is to mitigate the saturation problem. The smart washer is composed of two annular disks with contact surfaces that are machined into convex and concave respectively, to eliminate the complete flat contact surfaces and to reduce the saturation effect. One piezoelectric patch is bonded on the non-contact surface of each annular disk. These two mating annular disks form a smart washer. One of the two piezoelectric patches serves as an actuator to generate an ultrasonic wave that propagates through the contact surface; the other one serves as a sensor to detect the propagated waves. The wave energy…

This study investigated the effects of different fiber contents by volume (0%, 1%, 2%, and 3%) on flowability, entrapped air content, and compressive and flexural strength of ultra high performance concrete (UHPC). Four water-to-binder ratios (0.18, 0.20, 0.22, 0.24) were used and four different dosages of superplasticizer were introduced for preparing each water-to-binder ratio mixture. The experimental results reveal that the increased content of fiber decreases the flowability and entrapped air content of fresh UHPC mixtures. The compressive strength of UHPC increased with a greater addition of steel fiber, from 1% to 3%. The flexural strength was increased slightly by the addition of 1% steel fiber and increased remarkably with the addition of 2% and 3% steel fiber. For every water-to-binder ratio mixture, with and without steel fiber, a good linear relationship can be found between compressive strength and entrapped air content. Therefore, it is suggested that lowering the entrapped air provides a significant contribution to increasing compressive strength of UHPC containing…

Personalized medicine is a hot topic to develop a medical procedure for healthcare. Motivated by molecular dynamics simulation-based personalized medicine, we propose a novel numerical simulation-based personalized diagnosis methodology and explain the fundamental procedures. As an example, a personalized fault diagnosis method is developed using the finite element method (FEM), wavelet packet transform (WPT) and support vector machine (SVM) to detect faults in a shaft. The shaft unbalance, misalignment, rub-impact and the combination of rub-impact and unbalance are investigated using the present method. The method includes three steps. In the first step, Theil’s inequality coefficient (TIC)-based FE model updating technique is employed to determine the boundary conditions, and the fault-induced FE model of the faulty shaft is constructed. Further, the vibration signals of the faulty shaft are obtained using numerical simulation. In the second step, WPT is employed to decompose the vibration signal into several signal components. Specific time-domain feature parameters of all of the…

The use of plastic film in agriculture has the serious drawback of producing vast quantities of waste. In this work, films were prepared from natural fibers and biodegradable polymers as potential substitutes for the conventional non-biodegradable plastic film used as mulching material in agricultural production. The physical properties (e.g., mechanical properties, heat preservation, water permeability, and photopermeability) and degradation characteristics (evaluated by micro-organic culture testing and soil burial testing) of the films were studied in both laboratory and field tests. The experimental results indicated that these fiber/polymer films exhibited favorable physical properties that were sufficient for use in mulching film applications. Moreover, the degradation degree of the three tested films decreased in the following order: fiber/starch (ST) film > fiber/poly(vinyl alcohol) (PVA) film > fiber/polyacrylate (PA) film. The fiber/starch and fiber/PVA films were made from completely biodegradable materials and demonstrated the potential to substitute non-biodegradable…

Recent years have witnessed an ever-mounting interest in the research of sparse representation. The framework, Sparse Representation-based Classification (SRC), has been widely applied as a classifier in numerous domains, among which Synthetic Aperture Radar (SAR) target recognition is really challenging because it still is an open problem to interpreting the SAR image. In this paper, SRC is utilized to classify a 10-class moving and stationary target acquisition and recognition (MSTAR) target, which is a standard SAR data set. Before the classification, the sizes of the images need to be normalized to maintain the useful information, target and shadow, and to suppress the speckle noise. Specifically, a preprocessing method is recommended to extract the feature vectors of the image, and the feature vectors of the test samples can be represented by the sparse linear combination of basis vectors generated by the feature vectors of the training samples. Then the sparse representation is solved by l 1 -norm minimization. Finally, the identities of the test samples are inferred by the…

This paper presents a novel tunable multi-frequency hybrid energy harvester (HEH). It consists of a piezoelectric energy harvester (PEH) and an electromagnetic energy harvester (EMEH), which are coupled with magnetic interaction. An electromechanical coupling model was developed and numerically simulated. The effects of magnetic force, mass ratio, stiffness ratio, and mechanical damping ratios on the output power were investigated. A prototype was fabricated and characterized by experiments. The measured first peak power increases by 16.7% and 833.3% compared with that of the multi-frequency EMEH and the multi-frequency PEH, respectively. It is 2.36 times more than the combined output power of the linear PEH and linear EMEH at 22.6 Hz. The half-power bandwidth for the first peak power is also broadened. Numerical results agree well with the experimental data. It is indicated that magnetic interaction can tune the resonant frequencies. Both magnetic coupling configuration and hybrid conversion mechanism contribute to enhancing the output power and widening the operation bandwidth.…

Medical ultrasound is an imaging technique that utilizes ultrasonic signals as information carriers, and has wide applications such as seeing internal body structures, finding a source of a disease, and examining pregnant women. The most commonly used ultrasonic transducer today is based on piezoelectricity. The piezoelectric transducer, however, may have a limited bandwidth and insufficient sensitivity for reduced element size. Laser-generated ultrasound (LGUS) technique is an effective way to resolve these issues. The LGUS approach based on photoacoustic effect is able to greatly enhance the bandwidth of ultrasound signals and has the potential for high-resolution imaging. High-amplitude LGUS could also be used for therapy to accomplish high precision surgery without an incision. Furthermore, LGUS in conjunction with optical detection of ultrasound allows all-optical ultrasound imaging (i.e., ultrasound is generated and received optically). The all-optical platform offers unique advantages in providing high-resolution information and in facilitating the construction of miniature…

Several studies have investigated how environmental sounds and music can modulate people’s behaviours, particularly in marketing research. However, there are relatively few examples of research about such relationships with a focus on the management of urban public spaces. The current study investigated an open public space used mainly as a pedestrian crossing to analyse the relationship between the audio stimuli and peoples’ behaviours. An experiment relying on covert behavioural observation was performed. During the experiment, three different music stimuli and a control condition (i.e., no music) were reproduced in order to find out firstly whether music compared to no music could elicit an increase in the number of people stopping in the investigated area, and secondly whether music is associated with a longer duration of stay for those who stop. Results showed that the presence of music had no effect on the number of people stopping in the area, but it had a statistically significant effect on the duration of stay for those who stopped. The above findings support the idea that…

Fault diagnosis in rotating machinery is significant to avoid serious accidents; thus, an accurate and timely diagnosis method is necessary. With the breakthrough in deep learning algorithm, some intelligent methods, such as deep belief network (DBN) and deep convolution neural network (DCNN), have been developed with satisfactory performances to conduct machinery fault diagnosis. However, only a few of these methods consider properly dealing with noises that exist in practical situations and the denoising methods are in need of extensive professional experiences. Accordingly, rethinking the fault diagnosis method based on deep architectures is essential. Hence, this study proposes an automatic denoising and feature extraction method that inherently considers spatial and temporal correlations. In this study, an integrated deep fault recognizer model based on the stacked denoising autoencoder (SDAE) is applied to both denoise random noises in the raw signals and represent fault features in fault pattern diagnosis for both bearing rolling fault and gearbox fault, and trained in a…

The main purpose of the paper is to present an innovative higher-order structural theory to accurately evaluate the natural frequencies of laminated composite shells. A new kinematic model is developed starting from the theoretical framework given by a unified formulation. The kinematic expansion is taken as a free parameter, and the three-dimensional displacement field is described by using alternatively the Legendre or Lagrange polynomials, following the key points of the most typical Layer-wise (LW) approaches. The structure is considered as a unique body and all the geometric and mechanical properties are evaluated on the shell middle surface, following the idea of the well-known Equivalent Single Layer (ESL) models. For this purpose, the name Equivalent Layer-Wise (ELW) is introduced to define the present approach. The governing equations are solved numerically by means of the Generalized Differential Quadrature (GDQ) method and the solutions are compared with the results available in the literature or obtained through a commercial finite element program. Due to the generality…

Semiconducting transition metal dichalcogenides present a complex electronic band structure with a rich orbital contribution to their valence and conduction bands. The possibility to consider the electronic states from a tight-binding model is highly useful for the calculation of many physical properties, for which first principle calculations are more demanding in computational terms when having a large number of atoms. Here, we present a set of Slater–Koster parameters for a tight-binding model that accurately reproduce the structure and the orbital character of the valence and conduction bands of single layer MX 2 , where M = Mo, W and X = S, Se. The fit of the analytical tight-binding Hamiltonian is done based on band structure from ab initio calculations. The model is used to calculate the optical conductivity of the different compounds from the Kubo formula.

Sago biomass is an agro-industrial waste produced in large quantities, mainly in the Asia-Pacific region and in particular South-East Asia. This work focuses on using sago biomass to obtain cellulose as the raw material, through chemical processing using acid hydrolysis, alkaline extraction, chlorination and bleaching, finally converting the material to pharmaceutical grade carboxymethyl sago cellulose (CMSC) by carboxymethylation. The cellulose was evaluated using Thermogravimetric Analysis (TGA), Infrared Spectroscopy (FTIR), X-Ray Diffraction (XRD), Differential Scanning Calorimetry (DSC) and Field Emission Scanning Electronic Microscopy (FESEM). The extracted cellulose was analyzed for cellulose composition, and subsequently modified to CMSC with a degree of substitution (DS) 0.6 by typical carboxymethylation reactions. X-ray diffraction analysis indicated that the crystallinity of the sago cellulose was reduced after carboxymethylation. FTIR and NMR studies indicate that the hydroxyl groups of the cellulose fibers were etherified through carboxymethylation to produce CMSC.…

This paper proposes a new demand response scheduling framework for an array of households, which are grouped into different categories based on socio-economic factors, such as the number of occupants, family decomposition and employment status. Each of the households is equipped with a variety of appliances. The model takes the preferences of participating households into account and aims to minimize the overall production cost and, in parallel, to lower the individual electricity bills. In the existing literature, customers submit binary values for each time period to indicate their operational preferences. However, turning the appliances “on” or “off” does not capture the associated discomfort levels, as each appliance provides a different service and leads to a different level of satisfaction. The proposed model employs integer values to indicate household preferences and models the scheduling problem as a multi-objective mixed integer programming. The main thrust of the framework is that the multi-level preference modeling of appliances increases their “flexibility”; hence, the…

For large-scale selective laser melting (SLM) additive manufacturing technology, three main problems severely restrict its development and application, namely the residual stress, defects, and columnar grains with anisotropy. To overcome these problems, a new method is proposed by combining SLM with ultrasonic impact treatment (UIT) technique. This study explores the feasibility of UIT assisted SLM, as well as the effect of UIT on the residual stress, defects and β grains of Ti-6Al-4V alloy sample. The results indicate that after the application of UIT during SLM, residual stress can be largely reduced and defects can be hammered flat and even eliminated. Meanwhile, the epitaxial growth of columnar grains is prevented, and fine equiaxed grains are formed due to plastic deformation and recrystallization.

Selective laser melting (SLM), used to fabricate metallic objects with high geometrical complexity, is currently of increasing interest to the fields of medicine and dentistry. SLM-fabricated products should have highly smooth surfaces to minimize the use of post-processing procedures such as finishing and polishing. This study investigated the effect of various laser process parameters (laser power, scan rate, and scan-line spacing) on the surface roughness of a Co–Cr dental alloy that was three-dimensionally (3D) constructed via SLM. Initially, a single-line formation test was used to determine the optimal laser power (200 W) and scan rate (128.6 mm/s) that resulted in beads with an optimal profile. During subsequent multi-layer formation tests, the 3D Co–Cr body with the smoothest surface was produced using a scan-line spacing of 100 μm. The findings of this study show that laser process parameters have crucial effects on the surface quality of SLM-fabricated Co–Cr dental alloys.

Cellulase and xylanase are in high demand for application in several industrial processes, consequently necessitating the bioprospecting and manipulation of microbes for novel and greater enzyme productivity. This study reports on the optimal conditions for cellulase and xylanase production by a marine bacterial isolate from Nahoon beach sediment, via the classical process of one variable per time. Furthermore, the inducing effect of mono- and polysaccharides on enzyme production was investigated. The 16S rDNA gene sequence analysis clearly assigned the isolate to the genus Streptomyces, and was deposited at the GenBank under the accession number KU171373. Cellulase and xylanase production was optimal at the following conditions: pH 6 and 8, incubation temperature of 40 and 35 °C, and agitation speed of 100 and 150 rpm, respectively. Under optimum conditions, 0.26 U/mL and 18.54 U/mL activities were attained at 60 and 48 h with specific productivity of 205 and 7417 U/g for cellulase and xylanase, respectively. Xylanase production was induced by the entire mono- and polysaccharides…

The most remarkable variable cycle characteristic of the variable cycle engine (VCE) is that it keeps airflow almost constant during subsonic cruise throttling by modulating variable geometries, which can efficiently decrease spillage drag and increase installed thrust. One of the most critical challenges for the modulation lies in completely maintaining airflow, as well as avoiding specific fuel consumption (SFC) degradation during throttling. This has resulted in a need to investigate the modulation regulation of the adaptive cycle engine (ACE) which is a new concept for VCE and has greater potential for flexibly modulating airflow and pressure ratio. Thus, the aim of this paper is to study the variable geometries’ modulation schedule of ACE in maintaining airflow during throttling. A configuration of an ACE concept and its modeling study are first put forward. Then, the control schedule is researched via the combination of sensibility analysis and basic working principle instead of optimizing them directly. Results show that when the net thrust decreases from 100% to about 55%…

Oxygen Carrier Aided Combustion (OCAC) is realized by using an active oxygen-carrying bed material in fluidized bed boilers. The active material is reduced in fuel rich parts of the boiler and oxidized in air rich parts. Advantages could be achieved such as new mechanisms for oxygen transport in space and time. Here calcined manganese ore has been used as active bed material in a 12 MWth circulating fluidized bed boiler. The fuel was wood chips and the campaign lasted more than two weeks. From an operational point of view, manganese ore worked excellently. From the temperature profile of the boiler it can be concluded that fuel conversion was facilitated, especially in the dense bottom bed. The effect did not always translate to reduced emissions, which suggests that final combustion in the cyclone outlet was also influenced. Substituting 10% of the sand bed with manganese ore made it possible to reduce the air to fuel ratio without generating large amounts of CO. The use of 100% manganese ore resulted in higher emissions of CO than the sand reference, but, when combined sulphur…

The present communication examines the magnetohydrodynamic (MHD) squeezing flow of Jeffrey nanofluid between two parallel disks. Constitutive relations of Jeffrey fluid are employed in the problem development. Heat and mass transfer aspects are examined in the presence of thermophoresis and Brownian motion. Jeffrey fluid subject to time dependent applied magnetic field is conducted. Suitable variables lead to a strong nonlinear system. The resulting systems are computed via homotopic approach. The behaviors of several pertinent parameters are analyzed through graphs and numerical data. Skin friction coefficient and heat and mass transfer rates are numerically examined.

Hyperspectral imaging (HSI) technology has been extensively studied in the classification of seed variety. A novel procedure for the classification of maize seed varieties based on HSI was proposed in this study. The optimal wavelengths for the classification of maize seed varieties were selected using the successive projections algorithm (SPA) to improve the acquiring and processing speed of HSI. Subsequently, spectral and imaging features were extracted from regions of interest of the hyperspectral images. Principle component analysis and multidimensional scaling were then introduced to transform/reduce the classification features for overcoming the risk of dimension disaster caused by the use of a large number of features. Finally, the integrating features were used to develop a least squares–support vector machines (LS–SVM) model. The LS–SVM model, using the integration of spectral and image features combined with feature transformation methods, achieved more than 90% of test accuracy, which was better than the 83.68% obtained by model using the original spectral and image…

Two-dimensional metasurfaces are widely focused on for their ability for flexible light manipulation (phase, amplitude, polarization) over sub-wavelength propagation distances. Most of the metasurfaces can be divided into two categories by the material type of unit structure, i.e., plasmonic metasurfaces and dielectric metasurfaces. For plasmonic metasurfaces, they are made on the basis of metallic meta-atoms whose optical responses are driven by the plasmon resonances supported by metallic particles. For dielectric metasurfaces, the unit structure is constructed with high refractive index dielectric resonators, such as silicon, germanium or tellurium, which can support electric and magnetic dipole responses based on Mie resonances. The responses of plasmonic and dielectric metasurfaces are all relevant to the characteristics of unit structure, such as dimensions and materials. One can manipulate the electromagnetic field of light wave scattered by the metasurfaces through designing the dimension parameters of each unit structure in the metasurfaces. In this review article, we give…

Accurate and reliable forecasting on annual electricity consumption will be valuable for social projectors and power grid operators. With the acceleration of electricity market reformation and the development of smart grid and the energy Internet, the modern electric power system is becoming increasingly complex in terms of structure and function. Therefore, electricity consumption forecasting has become a more difficult and challenging task. In this paper, a new hybrid electricity consumption forecasting method, namely grey model (1,1) (GM (1,1)), optimized by moth-flame optimization (MFO) algorithm with rolling mechanism (Rolling-MFO-GM (1,1)), was put forward. The parameters a and b of GM (1,1) were optimized by employing moth-flame optimization algorithm (MFO), which is the latest natured-inspired meta-heuristic algorithm proposed in 2015. Furthermore, the rolling mechanism was also introduced to improve the precision of prediction. The Inner Mongolia case discussion shows the superiority of proposed Rolling-MFO-GM (1,1) for annual electricity consumption prediction when…

This study reports the biological synthesis of gold nanoparticles (AuNPs) by the reduction of HAuCl4 by using of Eclipta prostrata leaf extract as the reducing and stabilizing agent. AuNPs were characterized using Ultraviolet–visible (UV-vis) spectroscopy, X-ray diffraction (XRD), Fourier Transform-Infrared (FTIR) spectroscopy, Scanning Electron Microscopy (SEM), High Resolution-Transmission Electron Microscopy (HRTEM), and Energy Dispersive X-ray analysis (EDAX). The UV-visible spectrum of the synthesized AuNPs showed surface plasmon resonance (SPR) around 534 nm. The face-centered cubic (FCC) structure of the AuNPs was confirmed by XRD peaks at 38.10°, 44.13°, 64.43°, and 77.32°, which correspond to (111), (200), (220), and (311) miller indices, respectively, with clear circular spots in the selected area electron diffraction (SAED). FTIR measurements showed the AuNPs having a coating of phenolic compounds, indicating a possible role of biomolecules responsible for capping and efficient stabilization of the AuNPs. The HRTEM images determined the particles are spherical, hexagonal,…

Time-scale modification (TSM) is the task of speeding up or slowing down an audio signal’s playback speed without changing its pitch. In digital music production, TSM has become an indispensable tool, which is nowadays integrated in a wide range of music production software. Music signals are diverse—they comprise harmonic, percussive, and transient components, among others. Because of this wide range of acoustic and musical characteristics, there is no single TSM method that can cope with all kinds of audio signals equally well. Our main objective is to foster a better understanding of the capabilities and limitations of TSM procedures. To this end, we review fundamental TSM methods, discuss typical challenges, and indicate potential solutions that combine different strategies. In particular, we discuss a fusion approach that involves recent techniques for harmonic-percussive separation along with time-domain and frequency-domain TSM procedures.

Double- and triple-walled carbon nanotubes (DWNTs and TWNTs) consist of coaxially-nested two and three single-walled carbon nanotubes (SWNTs). They act as the geometrical bridge between SWNTs and multi-walled carbon nanotubes (MWNTs), providing an ideal model for studying the coupling interactions between different shells in MWNTs. Within this context, this article comprehensively reviews various synthetic routes of DWNTs’ and TWNTs’ production, such as arc discharge, catalytic chemical vapor deposition and thermal annealing of pea pods (i.e., SWNTs encapsulating fullerenes). Their structural features, as well as promising applications and future perspectives are also discussed.

The thermal behavior of a commercial paraffin with a melting temperature of 58 °C is analyzed as a phase change material (PCM) candidate for industrial waste heat recovery and domestic hot water applications. A full and complete characterization of this PCM is performed based on two different approaches: a laboratory characterization (mass range of milligrams) and an analysis in a pilot plant (mass range of kilograms). In the laboratory characterization, its thermal and cycling stability, its health hazard as well as its phase change thermal range, enthalpy and specific heat are analyzed using a differential scanning calorimeter, thermogravimetric analysis, thermocycling and infrared spectroscopy. Laboratory analyses showed its suitability up to 80 °C and for 1200 cycles. In the pilot plant analysis, its thermal behavior was analyzed in a shell-and-tube heat exchanger under different heat transfer fluid mass flow rates in terms of temperature, power and energy rates. Results from the pilot plant analysis allowed understanding the different methods of heat transfer in real charging…

We present a method that generates passive-guaranteed stable simulations of analog audio circuits from electronic schematics for real-time issues. On one hand, this method is based on a continuous-time power-balanced state-space representation structured into its energy-storing parts, dissipative parts, and external sources. On the other hand, a numerical scheme is especially designed to preserve this structure and the power balance. These state-space structures define the class of port-Hamiltonian systems. The derivation of this structured system associated with the electronic circuit is achieved by an automated analysis of the interconnection network combined with a dictionary of models for each elementary component. The numerical scheme is based on the combination of finite differences applied on the state (with respect to the time variable) and on the total energy (with respect to the state). This combination provides a discrete-time version of the power balance. This set of algorithms is valid for both the linear and nonlinear case. Finally, three applications of increasing…

As a successful solution applied to hard machining, the minimum quantity lubricant (MQL) has already been established as an alternative to flood coolant processing. The optimization of MQL parameters and cutting parameters under MQL condition are essential and pressing. The study was divided into two parts. In the first part of this study, the Taguchi method was applied to find the optimal values of MQL condition in the hard milling of AISI H13 with consideration of reduced surface roughness. The L9 orthogonal array, the signal-to-noise (S/N) ratio and analysis of variance (ANOVA) were employed to analyze the effect of the performance characteristics of MQL parameters (i.e., cutting fluid type, pressure, and fluid flow) on good surface finish. In the results section, lubricant and pressure of MQL condition are determined to be the most influential factors which give a statistically significant effect on machined surfaces. A verifiable experiment was conducted to demonstrate the reliability of the results. In the second section, the optimized MQL parameters were applied in a series…

To reduce dust generated from drilling processes, a reverse circulation drilling method based on a supersonic nozzle is proposed. The suction performance is evaluated by the entrainment ratio. A series of preliminary laboratory experiments based on orthogonal experimental design were conducted to test the suction performance and reveal the main factors. Computational fluid dynamics (CFD) were conducted to thoroughly understand the interaction mechanism of the flows. The Schlieren technique was further carried out to reveal the flow characteristic of the nozzle. The results show that the supersonic nozzle can significantly improve the reverse circulation effect. A high entrainment ratio up to 0.76 was achieved, which implied strong suction performance. The CFD results agreed well with experimental data with a maximum difference of 17%. This work presents the great potential for supersonic nozzles and reverse circulation in dust control, which is significant to protect the envrionment and people’s health.

In this study, an artificial neural network (ANN) model is developed to predict the stability number of breakwater armor stones based on the experimental data reported by Van der Meer in 1988. The harmony search (HS) algorithm is used to determine the near-global optimal initial weights in the training of the model. The stratified sampling is used to sample the training data. A total of 25 HS-ANN hybrid models are tested with different combinations of HS algorithm parameters. The HS-ANN models are compared with the conventional ANN model, which uses a Monte Carlo simulation to determine the initial weights. Each model is run 50 times and the statistical analyses are conducted for the model results. The present models using stratified sampling are shown to be more accurate than those of previous studies. The statistical analyses for the model results show that the HS-ANN model with proper values of HS algorithm parameters can give much better and more stable prediction than the conventional ANN model.

Increasing population and modern lifestyle have raised energy demands globally. Demand Side Management (DSM) is one important tool used to manage energy demands. It employs an advanced power infrastructure along with bi-directional information flow among utilities and users in order to achieve a balanced load curve and minimize demand-supply mismatch. Traditionally, this involves shifting the electricity demand from peak hours to other times of the day in an optimized manner. Multiple users equipped with renewable resources work in coordination with each other in order to achieve mutually beneficial energy management. This, in turn, has generated the concept of cooperative DSM. Such users, called prosumers, consume and produce energy using renewable resources (solar, wind etc.). Prosumers with surplus energy sell to the grid as well as to other consumers. In this paper, a novel Prosumer-based Energy Sharing and Management (PESM) scheme for cooperative DSM has been proposed. A simulation model has been developed for testing the proposed method. Different variations of the proposed…

This paper thermo-physically characterizes salt hydrate, paraffin wax and milk fat as phase change materials (PCMs). The three PCMs are compared in terms of improving heat sink (HS) performance for cooling electronic packaging. An experimental study is carried out on commercially available finned HS with and without PCM under natural ventilation (NV) and forced ventilation (FV) at different heat loads (4 W to 10 W). The results indicate that integration of all of the PCMs into the HS improves its cooling performance; however, milk fat lags behind the other two PCMs in terms of cooling produced. A three-dimensional pressure-based conjugate heat transfer model has been developed and validated with experimental results. The model predicts the parametric influence of PCM melting range, thermal conductivity and density on HS thermal management performance. The HS cooling performance improves with increased density and conductivity while it deteriorates with the wider melting range of the PCMs.

This paper reports a novel green approach for the synthesis of silver nanoparticles (AgNPs) using aqueous seed extract of Dracocephalum moldavica (L.) under ambient conditions. Processes such as Ultraviolet-visible (UV-vis) spectrometer, field emission scanning electron microscopy (FESEM), X-ray diffraction (XRD), Fourier transform infrared spectroscopy (FTIR), energy dispersive X-ray analysis (EDX), and transmission electron microscopy (TEM) were carry out to characterize AgNPs. The presence of AgNPs in the prepared solution was approved by a peak to occur at 443 nm. XRD pattern indicated the crystalline structure of the nanoparticles (NPs) while the FTIR spectra confirm the attendance of plant residues adsorbed by these NPs. TEM images revealed a near spherical shape of these NPs, and EDX provided the expected elemental composition. The synthesized AgNPs showed excellent antimicrobial activities against Escherichia coli, Pseudomonas aeruginosa, Staphylococcus aureus, Serratia marcescens, Staphylococcus epidermidis and Bacillus subtilis.

Stringent emissions limits introduced for internal combustion engines impose a major challenge for the research community. The technological solution adopted by the manufactures of diesel engines to meet the NOx and particle matter values imposed in the EURO VI regulation relies on using selective catalytic reduction and particulate filter systems, which increases the complexity and cost of the engine. Alternatively, several new combustion modes aimed at avoiding the formation of these two pollutants by promoting low temperature combustion reactions, are the focus of study nowadays. Among these new concepts, the dual-fuel combustion mode known as reactivity controlled compression ignition (RCCI) seems more promising because it allows better control of the combustion process by means of modulating the fuel reactivity depending on the engine operating conditions. The present experimental work explores the potential of different strategies for reducing the energy losses with RCCI in a single-cylinder research engine, with the final goal of providing the guidelines to define an…

In wildfire science, spotting refers to non-local creation of new fires, due to downwind ignition of brands launched from a primary fire. Spotting is often mentioned as being one of the most difficult problems for wildfire management, because of its unpredictable nature. Since spotting is a stochastic process, it makes sense to talk about a probability distribution for spotting, which we call the spotting distribution. Given a location ahead of the fire front, we would like to know how likely is it to observe a spot fire at that location in the next few minutes. The aim of this paper is to introduce a detailed procedure to find the spotting distribution. Most prior modelling has focused on the maximum spotting distance, or on physical subprocesses. We will use mathematical modelling, which is based on detailed physical processes, to derive a spotting distribution. We discuss the use and measurement of this spotting distribution in fire spread, fire management and fire breaching. The appendix of this paper contains a comprehensive review of the relevant underlying physical…