Next Issue
Volume 9, October-2
Previous Issue
Volume 9, September-2
 
 
applsci-logo

Journal Browser

Journal Browser

Appl. Sci., Volume 9, Issue 19 (October-1 2019) – 256 articles

Cover Story (view full-size image): The research presents the development of the monolithic integration of electronic and photonic components using standard photonics fabrication processes offered by a commercial silicon photonics foundry technology. Grating couplers, strip waveguides, Ge photodiodes, and transimpedance amplifiers were included in the prototype silicon-on-insulator chip. We designed and implemented the transimpedance amplifiers using junction field-effect transistors (JFETs) with the existing silicon photonics process parameters. The fabricated JFETs demonstrated expected transfer characteristics, with the intention to further amplify the photocurrent produced from the integrated Ge photodiode. We believe that our work could be useful for waveguide sensors applications. View this paper.
  • Issues are regarded as officially published after their release is announced to the table of contents alert mailing list.
  • You may sign up for e-mail alerts to receive table of contents of newly released issues.
  • PDF is the official format for papers published in both, html and pdf forms. To view the papers in pdf format, click on the "PDF Full-text" link, and use the free Adobe Reader to open them.
Order results
Result details
Section
Select all
Export citation of selected articles as:
10 pages, 1838 KiB  
Article
Comparative Evaluation of Flexural Strength and Flexural Modulus of Different Periodontal Splint Materials: An In Vitro Study
by Shahabe Saquib, AlQarni Abdullah, Das Gotam, Naqash Talib, Sibghatullah Muhammad and AlHaid Sultana
Appl. Sci. 2019, 9(19), 4197; https://doi.org/10.3390/app9194197 - 08 Oct 2019
Cited by 2 | Viewed by 3536
Abstract
Splinting of the mobile teeth is a critical part of periodontal management to improve the prognosis and longevity of stable results of periodontally compromised teeth with increased mobility. Different types of splints are used in the dental field based on their mechanical and [...] Read more.
Splinting of the mobile teeth is a critical part of periodontal management to improve the prognosis and longevity of stable results of periodontally compromised teeth with increased mobility. Different types of splints are used in the dental field based on their mechanical and physical properties.The objective of the current in vitro study was to evaluate the flexure strength and flexural modulus of different types of splinting materials, such as: composite block, ligature wire, Ribbond®, InFibra®, and F-splint-Aid® bonded utilizing Flowable composites resin material. Seventy-five bar specimens were prepared with the dimensions of 25 × 4 × 2 mm, utilizing split metallic mold. Specimens were divided equally (n = 15) into five groups (one control group, four test groups). Different layers of splinting material were placed in between the layers of composite before curing. All the specimens were subjected to a three-point bending test by using a universal testing machine to calculate the flexural strength and flexural modulus. The entire data was subjected to statistical tests to evaluate the significance. Specimens from composite block groups showed the least mean value for flexural strength (89.15 ± 9.70 MPa) and flexural modulus (4.310 ± 0.912 GPa). Whereas, the highest mean value for flexural strength (168.04 ± 45.95 MPa) and flexural modulus (5.861 ± 0.501 GPa) were recorded by Ribbond® specimens. Inter group comparison of flexural strength showed statistically significant differences (P-value < 0.05), whereas comparison of flexural modulus showed non-significant difference among the groups (P-value > 0.05). Within the limitation of the present study, it was concluded that the Ribbond® exhibits maximum flexural strength and flexural modulus, whereas the composite blocks recorded the least values. Still, the decision making depends on the clinical scenario and the unique characteristic of each splint material. Full article
(This article belongs to the Special Issue Applied Sciences in Dentistry)
Show Figures

Figure 1

14 pages, 2872 KiB  
Article
Smart Cities Big Data Algorithms for Sensors Location
by Elsa Estrada, Martha Patricia Martínez Vargas, Judith Gómez, Adriana Peña Pérez Negron, Graciela Lara López and Rocío Maciel
Appl. Sci. 2019, 9(19), 4196; https://doi.org/10.3390/app9194196 - 08 Oct 2019
Cited by 9 | Viewed by 5131
Abstract
A significant and very extended approach for Smart Cities is the use of sensors and the analysis of the data generated for the interpretation of phenomena. The proper sensor location represents a key factor for suitable data collection, especially for big data. There [...] Read more.
A significant and very extended approach for Smart Cities is the use of sensors and the analysis of the data generated for the interpretation of phenomena. The proper sensor location represents a key factor for suitable data collection, especially for big data. There are different methodologies to select the places to install sensors. Such methodologies range from a simple grid of the area to the use of complex statistical models to provide their optimal number and distribution, or even the use of a random function within a set of defined positions. We propose the use of the same data generated by the sensor to locate or relocate them in real-time, through what we denominate as a ‘hot-zone’, a perimeter with significant data related to the observed phenomenon. In this paper, we present a process with four phases to calculate the best georeferenced locations for sensors and their visualization on a map. The process was applied to the Guadalajara Metropolitan Zone in Mexico where, during the last twenty years, air quality has been monitored through sensors in ten different locations. As a result, two algorithms were developed. The first one classifies data inputs in order to generate a matrix with frequencies that works along with a matrix of territorial adjacencies. The second algorithm uses training data with machine learning techniques, both running in parallel modes, in order to diagnose the installation of new sensors within the detected hot-zones. Full article
Show Figures

Figure 1

18 pages, 1872 KiB  
Article
Quality and Defect Inspection of Green Coffee Beans Using a Computer Vision System
by Mauricio García, John E. Candelo-Becerra and Fredy E. Hoyos
Appl. Sci. 2019, 9(19), 4195; https://doi.org/10.3390/app9194195 - 08 Oct 2019
Cited by 37 | Viewed by 9778
Abstract
There is an increased industry demand for efficient and safe methods to select the best-quality coffee beans for a demanding market. Color, morphology, shape and size are important factors that help identify the best quality beans; however, conventional techniques based on visual and/or [...] Read more.
There is an increased industry demand for efficient and safe methods to select the best-quality coffee beans for a demanding market. Color, morphology, shape and size are important factors that help identify the best quality beans; however, conventional techniques based on visual and/or mechanical inspection are not sufficient to meet the requirements. Therefore, this paper presents an image processing and machine learning technique integrated with an Arduino Mega board, to evaluate those four important factors when selecting best-quality green coffee beans. For this purpose, the k-nearest neighbor algorithm is used to determine the quality of coffee beans and their corresponding defect types. The system consists of logical processes, image processing and the supervised learning algorithms that were programmed with MATLAB and then burned into the Arduino board. The results showed this method has a high effectiveness in classifying each single green coffee bean by identifying its main visual characteristics, and the system can handle several coffee beans present in a single image. Statistical analysis shows the process can identify defects and quality with high accuracy. The artificial vision method was helpful for the selection of quality coffee beans and may be useful to increase production, reduce production time and improve quality control. Full article
Show Figures

Figure 1

15 pages, 4610 KiB  
Article
Direct Sailing Variable Acceleration Dynamics Characteristics of Water-Jet Propulsion with a Screw Mixed-Flow Pump
by Wei Han, Ting Shang, Min Su, Chengyong Gong, Rennian Li and Bin Meng
Appl. Sci. 2019, 9(19), 4194; https://doi.org/10.3390/app9194194 - 08 Oct 2019
Cited by 4 | Viewed by 2568
Abstract
Strong nonlinearity and the relevance of time-varying dynamic parameters in the maneuverable process of water-jet propulsion were major problems encountered in the prediction of variable acceleration dynamics characteristics. The relationships between the thrust and rotation speed of a screw mixed-flow pump, drag and [...] Read more.
Strong nonlinearity and the relevance of time-varying dynamic parameters in the maneuverable process of water-jet propulsion were major problems encountered in the prediction of variable acceleration dynamics characteristics. The relationships between the thrust and rotation speed of a screw mixed-flow pump, drag and submerged speed of water-jet propulsion were obtained from flume experiments and numerical calculations, based on which a dynamic model of pump-jet propulsion was established in this paper. As an initial condition, the numerical solution of the submerged speed with respect to time was inputted to computational fluid dynamics (CFD) for unsteady calculation based on a user-defined function (UDF). Thus, the relationships between the acceleration, drag, net thrust, propulsion torque and efficiency with respect to time were revealed. The results indicate that the relationship between the thrust and rotational speed of a water-jet propeller is a quadratic function, which agrees well with the experimental values. The variation of submerged speed with respect to time satisfies a hyperbolic tangent function distribution. The acceleration increases sharply at the beginning and then decreases gradually to zero, especially at high rotation speeds of the water-jet pump. The variations in drag and propulsion efficiency with respect to time coincide with the step response of a second-order system with critical damping. The method and results of this study can give a better understanding of the changes in dynamic parameters such as velocity, acceleration, thrust, and drag during the acceleration of a pump-jet submersible and helped to estimate the effects of pump performance on water-jet propulsion kinetic parameters. Full article
Show Figures

Figure 1

14 pages, 429 KiB  
Article
SmartFog: Training the Fog for the Energy-Saving Analytics of Smart-Meter Data
by Michele Scarpiniti, Enzo Baccarelli, Alireza Momenzadeh and Aurelio Uncini
Appl. Sci. 2019, 9(19), 4193; https://doi.org/10.3390/app9194193 - 08 Oct 2019
Cited by 3 | Viewed by 2515
Abstract
In this paper, we characterize the main building blocks and numerically verify the classification accuracy and energy performance of SmartFog, a distributed and virtualized networked Fog technological platform for the support for Stacked Denoising Auto-Encoder (SDAE)-based anomaly detection in data flows generated by [...] Read more.
In this paper, we characterize the main building blocks and numerically verify the classification accuracy and energy performance of SmartFog, a distributed and virtualized networked Fog technological platform for the support for Stacked Denoising Auto-Encoder (SDAE)-based anomaly detection in data flows generated by Smart-Meters (SMs). In SmartFog, the various layers of an SDAE are pretrained at different Fog nodes, in order to distribute the overall computational efforts and, then, save energy. For this purpose, a new Adaptive Elitist Genetic Algorithm (AEGA) is “ad hoc” designed to find the optimized allocation of the SDAE layers to the Fog nodes. Interestingly, the proposed AEGA implements a (novel) mechanism that adaptively tunes the exploration and exploitation capabilities of the AEGA, in order to quickly escape the attraction basins of local minima of the underlying energy objective function and, then, speed up the convergence towards global minima. As a matter of fact, the main distinguishing feature of the resulting SmartFog paradigm is that it accomplishes the joint integration on a distributed Fog computing platform of the anomaly detection functionality and the minimization of the resulting energy consumption. The reported numerical tests support the effectiveness of the designed technological platform and point out that the attained performance improvements over some state-of-the-art competing solutions are around 5%, 68% and 30% in terms of detection accuracy, execution time and energy consumption, respectively. Full article
Show Figures

Figure 1

20 pages, 7268 KiB  
Review
Advanced DSP for Coherent Optical Fiber Communication
by Jian Zhao, Yaping Liu and Tianhua Xu
Appl. Sci. 2019, 9(19), 4192; https://doi.org/10.3390/app9194192 - 08 Oct 2019
Cited by 35 | Viewed by 6917
Abstract
In this paper, we provide an overview of recent progress on advanced digital signal processing (DSP) techniques for high-capacity long-haul coherent optical fiber transmission systems. Not only the linear impairments existing in optical transmission links need to be compensated, but also, the nonlinear [...] Read more.
In this paper, we provide an overview of recent progress on advanced digital signal processing (DSP) techniques for high-capacity long-haul coherent optical fiber transmission systems. Not only the linear impairments existing in optical transmission links need to be compensated, but also, the nonlinear impairments require proper algorithms for mitigation because they become major limiting factors for long-haul large-capacity optical transmission systems. Besides the time domain equalization (TDE), the frequency domain equalization (FDE) DSP also provides a similar performance, with a much-reduced computational complexity. Advanced DSP also plays an important role for the realization of space division multiplexing (SDM). SDM techniques have been developed recently to enhance the system capacity by at least one order of magnitude. Some impressive results have been reported and have outperformed the nonlinear Shannon limit of the single-mode fiber (SMF). SDM introduces the space dimension to the optical fiber communication. The few-mode fiber (FMF) and multi-core fiber (MCF) have been manufactured for novel multiplexing techniques such as mode-division multiplexing (MDM) and multi-core multiplexing (MCM). Each mode or core can be considered as an independent degree of freedom, but unfortunately, signals will suffer serious coupling during the propagation. Multi-input–multi-output (MIMO) DSP can equalize the signal coupling and makes SDM transmission feasible. The machine learning (ML) technique has attracted worldwide attention and has been explored for advanced DSP. In this paper, we firstly introduce the principle and scheme of coherent detection to explain why the DSP techniques can compensate for transmission impairments. Then corresponding technologies related to the DSP, such as nonlinearity compensation, FDE, SDM and ML will be discussed. Relevant techniques will be analyzed, and representational results and experimental verifications will be demonstrated. In the end, a brief conclusion and perspective will be provided. Full article
Show Figures

Figure 1

14 pages, 6382 KiB  
Article
Piezoelectric Composite Vibrator with a Bilaminated Structure for Bending Vibration
by Xia Liu, Likun Wang, Chao Zhong, Yanjun Zhang, Shaohua Hao and Ruiqing Sun
Appl. Sci. 2019, 9(19), 4191; https://doi.org/10.3390/app9194191 - 08 Oct 2019
Cited by 8 | Viewed by 3452
Abstract
A piezoelectric composite vibrator with a bilaminated structure is designed and fabricated, in this work by applying bending vibration to increase vibration displacement and reduce resonance frequency. The finite element software ANSYS (ANSYS, Inc. USA) is used to simulate the 2-2 and 1-3 [...] Read more.
A piezoelectric composite vibrator with a bilaminated structure is designed and fabricated, in this work by applying bending vibration to increase vibration displacement and reduce resonance frequency. The finite element software ANSYS (ANSYS, Inc. USA) is used to simulate the 2-2 and 1-3 piezoelectric composite bilaminated vibrators under free boundary condition and optimize their design. Simulation results show that the vibration displacement of the 2-2 vibrator is higher than that of the 1-3 vibrator, and the resonance frequency of the former is lower than the latter. Five pieces each of the 2-2 and piezoelectric ceramic vibrators are prepared. In addition, simulation and experimental results indicate that the vibration displacement of the 2-2 vibrator increases by 2.3 times, whereas its resonance frequency decreases by nearly 100 Hz, in comparison with those of the piezoelectric ceramic bilaminated vibrator. Full article
(This article belongs to the Section Acoustics and Vibrations)
Show Figures

Figure 1

21 pages, 5419 KiB  
Article
Thermodynamic Analysis of Partitioned Combined Cycle using Simple Gases
by Aqeel Ahmad Taimoor, Muhammad Ehtisham Siddiqui and Salem S. Abdel Aziz
Appl. Sci. 2019, 9(19), 4190; https://doi.org/10.3390/app9194190 - 08 Oct 2019
Cited by 5 | Viewed by 3332
Abstract
In combined cycle gas turbines, most of the energy loss is usually due to the high temperature of the exhaust gases. Different heat recuperation methods are used. In this study, a novel direct method for heat recovery is investigated. Confidence in the results [...] Read more.
In combined cycle gas turbines, most of the energy loss is usually due to the high temperature of the exhaust gases. Different heat recuperation methods are used. In this study, a novel direct method for heat recovery is investigated. Confidence in the results is established by accounting for all the losses and simulation errors while comparing with the conventional cycle. Aspen HYSYS and MATLAB are the simulation tools used. The General Electric (GE) 9HA.02 combined cycle is taken as a base case. Five gases, air, argon, hydrogen, nitrogen, and carbon dioxide, are studied with the proposed modification. The efficiency maximization function is updated and the pressure and temperature ratios of individual Brayton and Rankine cycles are discussed. The combustor/heat exchanger is modified and simulated according to the known principles of heat and momentum transfer. The whole simulation algorithm is provided. Equation of state (EOS-PR) is used to calculate the properties at every discretized step (for H2, critical properties are modified/HYSYS inbuilt feature). Different gases are analyzed according to their property profiles over the whole cycle. The effect of fluid properties on efficiency is discussed as a guideline for any tailored fluid. Full article
(This article belongs to the Section Energy Science and Technology)
Show Figures

Figure 1

16 pages, 4545 KiB  
Article
Modeling the Response of Magnetorheological Fluid Dampers under Seismic Conditions
by Darson Dezheng Li, Declan Finn Keogh, Kevin Huang, Qing Nian Chan, Anthony Chun Yin Yuen, Chris Menictas, Victoria Timchenko and Guan Heng Yeoh
Appl. Sci. 2019, 9(19), 4189; https://doi.org/10.3390/app9194189 - 08 Oct 2019
Cited by 13 | Viewed by 4083
Abstract
Magnetorheological (MR) fluid is a smart material fabricated by mixing magnetic-responsive particles with non-magnetic-responsive carrier fluids. MR fluid dampers are able to provide rapid and reversible changes to their damping coefficient. To optimize the efficiency and effectiveness of such devices, a computational model [...] Read more.
Magnetorheological (MR) fluid is a smart material fabricated by mixing magnetic-responsive particles with non-magnetic-responsive carrier fluids. MR fluid dampers are able to provide rapid and reversible changes to their damping coefficient. To optimize the efficiency and effectiveness of such devices, a computational model is developed and presented where the flow field is simulated using the computational fluid dynamics approach, coupled with the magnetohydrodynamics model. Three different inlet pressure profiles were designed to replicate real loading conditions are examined, namely a constant pressure, a sinusoidal pressure profile, and a pressure profile mimicking the 1994 Northbridge earthquake. When the MR fluid damper was in its off-state, a linear pressure drop between the inlet and the outlet was observed. When a uniform perpendicular external magnetic field was applied to the annular orifice of the MR damper, a significantly larger pressure drop was observed across the annular orifice for all three inlet pressure profiles. It was shown that the fluid velocity within the magnetized annular orifice decreased proportionally with respect to the strength of the applied magnetic field until saturation was reached. Therefore, it was clearly demonstrated that the present model was capable of accurately capturing the damping characteristics of MR fluid dampers. Full article
(This article belongs to the Section Nanotechnology and Applied Nanosciences)
Show Figures

Figure 1

18 pages, 7769 KiB  
Article
An Analysis of Mechanical Properties for Ultrasonically Welded Multiple C1220-Al1050 Layers
by Jisun Kim, Jaewoong Kim, In-ju Kim, Sungwook Kang and Kwangsan Chun
Appl. Sci. 2019, 9(19), 4188; https://doi.org/10.3390/app9194188 - 08 Oct 2019
Cited by 4 | Viewed by 4391
Abstract
This study analyzed the characteristics of aluminum and copper sheets under multi-layer ultrasonic welding, and observed the strength, fracture type, and interface of the weld zone according to location. In addition, an experimental plan was developed using the Taguchi method to optimize the [...] Read more.
This study analyzed the characteristics of aluminum and copper sheets under multi-layer ultrasonic welding, and observed the strength, fracture type, and interface of the weld zone according to location. In addition, an experimental plan was developed using the Taguchi method to optimize the quadruple lap ultrasonic welding process conditions of 0.4t aluminum and copper sheets, and the experiment was performed for each of 25 welding condition. For strength evaluation, the ultrasonic welding performance was evaluated by measuring the tensile strength as a composite material and the shear force at the weld interface through two types of tensile tests: simultaneous tensile and individual tensile. To identify the individual shear strengths of the multi-layer dissimilar ultrasonic welds, three types of tensile tests were performed for each specimen depending on the location of the welded, and as the distance from the horn increased, each of shear strength decreased while the difference in strength value increased. For quadruple lap welding of pure aluminum and copper sheets, the S/N (Signal to Noise Ratio) was the highest at 64.48 with a coarse-grain pattern and optimal welding conditions, and this was selected as the optimal condition. To evaluate the optimized welding condition, additional tests were conducted using the welding conditions that showed the maximum strength values and the welding conditions optimized using the Taguchi method through simple tests. A strength evaluation of the optimized weldment was performed, and for a simultaneous tensile test, it was found that the strength of the optimized weldment was improved by 45% compared to other cases. Full article
(This article belongs to the Section Mechanical Engineering)
Show Figures

Figure 1

16 pages, 893 KiB  
Article
Labeled Multi-Bernoulli Filter Joint Detection and Tracking of Radar Targets
by Rang Liu, Hongqi Fan and Huaitie Xiao
Appl. Sci. 2019, 9(19), 4187; https://doi.org/10.3390/app9194187 - 08 Oct 2019
Cited by 11 | Viewed by 2549
Abstract
A labeled multi-Bernoulli (LMB) filter is presented to jointly detect and track radar targets. A relevant LMB filter is recently proposed by Rathnayake which assumes that the measurements of different targets do not overlap, leading to the favorable separable likelihood assumption. However, new [...] Read more.
A labeled multi-Bernoulli (LMB) filter is presented to jointly detect and track radar targets. A relevant LMB filter is recently proposed by Rathnayake which assumes that the measurements of different targets do not overlap, leading to the favorable separable likelihood assumption. However, new or close tracks often violate the assumption and lead to a bias in the cardinality estimate. To address this problem, a one-to-one association method between measurements and tracks is proposed. In our method, any target only corresponds to its associated measurements and different tracks have little mutual interference. In addition, an approximate method for calculating the point spread function of radar is developed to improve the computational efficiency of likelihood function. The simulation under low signal-to-noise ratio scenario with closely spaced targets have demonstrated the effectiveness and efficiency of the proposed algorithm. Full article
(This article belongs to the Special Issue Multi-Channel and Multi-Agent Signal Processing)
Show Figures

Figure 1

2 pages, 140 KiB  
Editorial
Special Issue on Photoacoustic Tomography
by Xueding Wang, Xinmai Yang and Xose Luis Dean-Ben
Appl. Sci. 2019, 9(19), 4186; https://doi.org/10.3390/app9194186 - 08 Oct 2019
Viewed by 1755
Abstract
Biomedical photoacoustic (or optoacoustic) tomography (PAT), or more generally, photoacoustic imaging (PAI), has been an active area of study and development in the last two decades [...] Full article
(This article belongs to the Special Issue Photoacoustic Tomography (PAT))
9 pages, 788 KiB  
Review
Mycoremediation of PCBs by Pleurotus ostreatus: Possibilities and Prospects
by Se Chul Chun, Manikandan Muthu, Nazim Hasan, Shadma Tasneem and Judy Gopal
Appl. Sci. 2019, 9(19), 4185; https://doi.org/10.3390/app9194185 - 08 Oct 2019
Cited by 26 | Viewed by 6141
Abstract
With the rising awareness on environmental issues and the increasing risks through industrial development, clean up remediation measures have become the need of the hour. Bioremediation has become increasingly popular owing to its environmentally friendly approaches and cost effectiveness. Polychlorinated biphenyls (PCBs) are [...] Read more.
With the rising awareness on environmental issues and the increasing risks through industrial development, clean up remediation measures have become the need of the hour. Bioremediation has become increasingly popular owing to its environmentally friendly approaches and cost effectiveness. Polychlorinated biphenyls (PCBs) are an alarming threat to human welfare as well as the environment. They top the list of hazardous xenobiotics. The multiple effects these compounds render to the niche is not unassessed. Bioremediation does appear promising, with myco remediation having a clear edge over bacterial remediation. In the following review, the inputs of white-rot fungi in PCB remediation are examined and the lacunae in the practical application of this versatile technology highlighted. The unique abilities of Pleurotus ostreatus and its deliverables with respect to removal of PCBs are presented. The need for improvising P. ostreatus-mediated remediation is emphasized. Full article
(This article belongs to the Special Issue Bioactive Substances: Properties, Applications and or Toxicities)
Show Figures

Figure 1

15 pages, 3192 KiB  
Article
Short-Term Deformability of Three-Dimensional Printable EVA-Modified Cementitious Mortars
by Jaeheum Yeon
Appl. Sci. 2019, 9(19), 4184; https://doi.org/10.3390/app9194184 - 08 Oct 2019
Cited by 5 | Viewed by 2367
Abstract
This study experimentally examined the deformability of cementitious mortars modified with ethylene-vinyl acetate (EVA) for use in extrusion-based additive construction. The research was based on the author’s previous study of the properties of fresh EVA-modified cementitious mixtures for use in additive construction via [...] Read more.
This study experimentally examined the deformability of cementitious mortars modified with ethylene-vinyl acetate (EVA) for use in extrusion-based additive construction. The research was based on the author’s previous study of the properties of fresh EVA-modified cementitious mixtures for use in additive construction via extrusion. The particular focus was on these mortars’ short-term deformation factors, including the modulus of elasticity, drying shrinkage, and thermal expansion. The experimental results indicate that as the EVA/cement ratio was increased, the compressive strength and elastic modulus tended to decrease but the maximum compressive strain increased. At 28 days, the drying shrinkage tended to increase as the EVA/cement ratio was increased. The coefficient of thermal expansion was also found to increase as the EVA/cement ratio was increased. A very high correlation was found between these three deformation factors and the EVA/cement ratio. Given these results, it was determined that the addition of EVA powder to EVA-modified cementitious mortars used in extrusion-based additive construction could adversely affect their short-term deformation factors. However, increasing the EVA/cement ratio resulted in a decrease in the modulus of elasticity, thereby reducing the level of stress caused by drying shrinkage and thermal expansion. This effect will eventually lead to improvements in the degree of extensibility, thereby offsetting the negative impacts. However, it is still desirable to minimize the EVA/cement ratio to the extent that adequate properties for the fresh material can be obtained. Full article
(This article belongs to the Special Issue Low Binder Concrete and Mortars)
Show Figures

Figure 1

12 pages, 13570 KiB  
Article
Palladium Nanocatalysts on Hydroxyapatite: Green Oxidation of Alcohols and Reduction of Nitroarenes in Water
by Mohammadreza Shokouhimehr, Samaneh Mahmoudi-Gom Yek, Mahmoud Nasrollahzadeh, Aejung Kim and Rajender S. Varma
Appl. Sci. 2019, 9(19), 4183; https://doi.org/10.3390/app9194183 - 07 Oct 2019
Cited by 86 | Viewed by 4283
Abstract
A green procedure is described for supporting Pd nanoparticles on hydroxyapatite (HAP), which serves as a highly-stable heterogeneous catalyst displaying excellent activity for the aqueous expeditious reduction of nitroaromatics to the corresponding amines with sodium borohydride, and oxidation of primary and secondary alcohols [...] Read more.
A green procedure is described for supporting Pd nanoparticles on hydroxyapatite (HAP), which serves as a highly-stable heterogeneous catalyst displaying excellent activity for the aqueous expeditious reduction of nitroaromatics to the corresponding amines with sodium borohydride, and oxidation of primary and secondary alcohols by hydrogen peroxide with high yields and selectivities. The structural features of the prepared catalyst are confirmed by latest techniques including field emission scanning electron microscopy, transmission electron microscopy, energy-dispersive X-ray spectroscopy, and X-ray photoelectron spectroscopy. The reusability of the heterogeneous catalyst was affirmed in the aqueous reduction of nitrobenzene and oxidation of cycloheptanol for six consecutive runs without significant loss of catalytic activity. Full article
(This article belongs to the Special Issue Sustainable Utilization of Primary and Secondary Raw Materials)
Show Figures

Graphical abstract

12 pages, 1462 KiB  
Article
Pedestrian Attributes Recognition in Surveillance Scenarios Using Multi-Task Lightweight Convolutional Neural Network
by Pu Yan, Li Zhuo, Jiafeng Li, Hui Zhang and Jing Zhang
Appl. Sci. 2019, 9(19), 4182; https://doi.org/10.3390/app9194182 - 07 Oct 2019
Cited by 6 | Viewed by 2404
Abstract
Pedestrian attributes (such as gender, age, hairstyle, and clothing) can effectively represent the appearance of pedestrians. These are high-level semantic features that are robust to illumination, deformation, etc. Therefore, they can be widely used in person re-identification, video structuring analysis and other applications. [...] Read more.
Pedestrian attributes (such as gender, age, hairstyle, and clothing) can effectively represent the appearance of pedestrians. These are high-level semantic features that are robust to illumination, deformation, etc. Therefore, they can be widely used in person re-identification, video structuring analysis and other applications. In this paper, a pedestrian attributes recognition method for surveillance scenarios using a multi-task lightweight convolutional neural network is proposed. Firstly, the labels of the attributes for each pedestrian image are integrated into a label vector. Then, a multi-task lightweight Convolutional Neural Network (CNN) is designed, which consists of five convolutional layers, three pooling layers and two fully connected layers to extract the deep features of pedestrian images. Considering that the data distribution of the datasets is unbalanced, the loss function is improved based on the sigmoid cross-entropy, and the scale factor is added to balance the amount of various attributes data. Through training the network, the mapping relationship model between the deep features of pedestrian images and the integration label vector of their attributes is established, which can be used to predict each attribute of the pedestrian. The experiments were conducted on two public pedestrian attributes datasets in surveillance scenarios, namely PETA and RAP. The results show that, compared with the state-of-the-art pedestrian attributes recognition methods, the proposed method can achieve a superior accuracy by 91.88% on PETA and 87.44% on RAP respectively. Full article
Show Figures

Figure 1

16 pages, 3298 KiB  
Article
Dynamics of a Turbine Blade with an Under-Platform Damper Considering the Bladed Disc’s Rotation
by Shangwen He, Wenzhen Jia, Zhaorui Yang, Bingbing He and Jun Zhao
Appl. Sci. 2019, 9(19), 4181; https://doi.org/10.3390/app9194181 - 07 Oct 2019
Cited by 7 | Viewed by 2585
Abstract
High-cycle fatigue (HCF) failure of the turbine blades of aero-engines caused by high vibrational stresses is one of the main causes of aero-engine incidents [...] Full article
(This article belongs to the Special Issue Advances in Mechanical Systems Dynamics)
Show Figures

Graphical abstract

21 pages, 4250 KiB  
Article
Deep Neural Network for Ore Production and Crusher Utilization Prediction of Truck Haulage System in Underground Mine
by Jieun Baek and Yosoon Choi
Appl. Sci. 2019, 9(19), 4180; https://doi.org/10.3390/app9194180 - 07 Oct 2019
Cited by 27 | Viewed by 3436
Abstract
A new method using a deep neural network (DNN) model is proposed to predict the ore production and crusher utilization of a truck haulage system in an underground mine. An underground limestone mine was selected as the study area, and the DNN model [...] Read more.
A new method using a deep neural network (DNN) model is proposed to predict the ore production and crusher utilization of a truck haulage system in an underground mine. An underground limestone mine was selected as the study area, and the DNN model input/output nodes were designed to reflect the truck haulage system characteristics. Big data collected on-site for 1 month were processed to create learning datasets. To select the optimal DNN learning model, the numbers of hidden layers and hidden layer nodes were set to various values for analyzing the training and test data. The optimal DNN model structure for ore production prediction was set to five hidden layers and 40 hidden layer nodes. The test data exhibited a coefficient of determination of 0.99 and mean absolute percentage error (MAPE) of 2.80%. The optimal configuration for the crusher utilization prediction was set to four hidden layers and 40 hidden layer nodes, and the test data exhibited a coefficient of determination of 0.99 and MAPE of 2.49%. The trained DNN model was used to predict the ore production and crusher utilization, which were similar to the actual observed values. Full article
(This article belongs to the Section Energy Science and Technology)
Show Figures

Figure 1

12 pages, 2788 KiB  
Article
Efficient Near-Field Analysis of the Electromagnetic Scattering Based on the Dirichlet-to-Neumann Map
by Antea M. Perrotta, Antonio Maffucci, Salvatore Ventre and Antonello Tamburrino
Appl. Sci. 2019, 9(19), 4179; https://doi.org/10.3390/app9194179 - 06 Oct 2019
Cited by 1 | Viewed by 1951
Abstract
This paper proposes an efficient technique to solve the electromagnetic scattering problem, in the near zone of scatterers illuminated by external fields. The technique is based on a differential formulation of the Helmholtz equation discretized in terms of a finite element method (FEM). [...] Read more.
This paper proposes an efficient technique to solve the electromagnetic scattering problem, in the near zone of scatterers illuminated by external fields. The technique is based on a differential formulation of the Helmholtz equation discretized in terms of a finite element method (FEM). In order to numerically solve the problem, it is necessary to truncate the unbounded solution domain to obtain a bounded computational domain. This is usually done by defining fictitious boundaries where absorbing conditions are imposed, for example by applying the perfect matching layer (PML) approach. In this paper, these boundary conditions are expressed in an analytical form by using the Dirichlet-to-Neumann (DtN) operator. Compared to classical solutions such as PML, the proposed approach based on the DtN: (i) avoids the errors related to approximated boundary conditions; (ii) allows placing the boundary in close proximity to the scatterers, thus, reducing the solution domain to be meshed and the related computational cost; (iii) allows dealing with objects of arbitrary shapes and materials, since the shape of the boundary independent from those of the scatterers. Case-studies on problems related to the scattering from cable bundles demonstrate the accuracy and the computational advantage of the proposed technique, compared to existing ones. Full article
(This article belongs to the Section Electrical, Electronics and Communications Engineering)
Show Figures

Figure 1

14 pages, 7388 KiB  
Article
Discriminative Local Feature for Hyperspectral Hand Biometrics by Adjusting Image Acutance
by Wei Nie, Bob Zhang and Shuping Zhao
Appl. Sci. 2019, 9(19), 4178; https://doi.org/10.3390/app9194178 - 06 Oct 2019
Cited by 8 | Viewed by 2475
Abstract
Image acutance or edge contrast in an image plays a crucial role in hyperspectral hand biometrics, especially in the local feature representation phase. However, the study of acutance in this application has not received a lot of attention. Therefore, in this paper we [...] Read more.
Image acutance or edge contrast in an image plays a crucial role in hyperspectral hand biometrics, especially in the local feature representation phase. However, the study of acutance in this application has not received a lot of attention. Therefore, in this paper we propose that there is an optimal range of image acutance in hyperspectral hand biometrics. To locate this optimal range, a thresholded pixel-wise acutance value (TPAV) is firstly proposed to assess image acutance. Then, through convolving with Gaussian filters, a hyperspectral hand image was preprocessed to obtain different TPAVs. Afterwards, based on local feature representation, the nearest neighbor method was used for matching. The experiments were conducted on hyperspectral dorsal hand vein (HDHV) and hyperspectral palm vein (HPV) databases containing 53 bands. The results that achieved the best performance were those where image acutance was adjusted to the optimal range. On average, the samples with adjusted acutance compared to the original improved by a recognition rate (RR) of 29.5% and 45.7% for the HDHV and HPV datasets, respectively. Furthermore, our method was validated on the PolyU multispectral palm print database producing similar results to that of the hyperspectral. From this we can conclude that image acutance plays an important role in hyperspectral hand biometrics. Full article
(This article belongs to the Section Computing and Artificial Intelligence)
Show Figures

Figure 1

16 pages, 3994 KiB  
Article
SOC Estimation with an Adaptive Unscented Kalman Filter Based on Model Parameter Optimization
by Xiangwei Guo, Xiaozhuo Xu, Jiahao Geng, Xian Hua, Yan Gao and Zhen Liu
Appl. Sci. 2019, 9(19), 4177; https://doi.org/10.3390/app9194177 - 06 Oct 2019
Cited by 20 | Viewed by 2848
Abstract
State of charge (SOC) estimation is generally acknowledged to be one of the most important functions of the battery management system (BMS) and is thus widely studied in academia and industry. Based on an accurate SOC estimation, the BMS can optimize energy efficiency [...] Read more.
State of charge (SOC) estimation is generally acknowledged to be one of the most important functions of the battery management system (BMS) and is thus widely studied in academia and industry. Based on an accurate SOC estimation, the BMS can optimize energy efficiency and protect the battery from being over-charged or over-discharged. The accurate online estimation of the SOC is studied in this paper. First, it is proved that the second-order resistance capacitance (RC) model is the most suitable equivalent circuit model compared with the Thevenin and multi-order models. The second-order RC equivalent circuit model is established, and the model parameters are identified. Second, the reasonable optimization of model parameters is studied, and a reasonable optimization method is proposed to improve the accuracy of SOC estimation. Finally, the SOC is estimated online based on the adaptive unscented Kalman filter (AUKF) with optimized model parameters, and the results are compared with the results of an estimation based on pre-optimization model parameters. Simulation experiments show that, without affecting the convergence of the initial error of the AUKF, the model after parameter optimization has a higher online SOC estimation accuracy. Full article
(This article belongs to the Special Issue Battery Management System for Future Electric Vehicles)
Show Figures

Figure 1

10 pages, 1571 KiB  
Article
Patellofemoral Joint Loads during Running Immediately Changed by Shoes with Different Minimalist Indices: A Cross-sectional Study
by Chenhao Yang, Songlin Xiao, Yang Yang, Xini Zhang, Junqing Wang and Weijie Fu
Appl. Sci. 2019, 9(19), 4176; https://doi.org/10.3390/app9194176 - 06 Oct 2019
Cited by 14 | Viewed by 6249
Abstract
Purpose: Given the high incidence of patellofemoral pain syndrome (PFPS) in runners, this study aimed to investigate the immediate effect of shoes with different minimalist indices (MI) on the mechanical loads of the patellofemoral joint. Methods: Fifteen healthy male rearfoot strike runners were [...] Read more.
Purpose: Given the high incidence of patellofemoral pain syndrome (PFPS) in runners, this study aimed to investigate the immediate effect of shoes with different minimalist indices (MI) on the mechanical loads of the patellofemoral joint. Methods: Fifteen healthy male rearfoot strike runners were recruited to complete overground running trials at 3.33 m/s (±5%) in two running shoe conditions (MI = 26% versus MI = 86%). The amount of ten Vicon infrared cameras (100 Hz) and two Kistler force plates (1000 Hz) were used to collect kinematic and ground reaction force (GRF) data simultaneously. Quadriceps strength, patellofemoral contact force, patellofemoral contact area, and patellofemoral contact stress were calculated. Results: No significant differences were observed in the impact force and the second peak of the vertical GRF between the two shoe conditions. Compared to wearing low-MI shoes, wearing high-MI shoes showed that the maximum flexion angle of the knee, the contact area of patellofemoral joint and the peak knee extension moment reduced significantly (p < 0.01), and the peak patellofemoral contact force and stress decreased significantly (p < 0.05). Conclusion: These findings suggest that wearing high-MI shoes significantly decreases the patellofemoral contact force and patellofemoral joint stress by reducing the moment of knee extension, thus effectively reducing the load of the patellofemoral joint during the stance phase of running and potentially lowering the risk of PFPS. Full article
(This article belongs to the Special Issue Biomechanical Spectrum of Human Sport Performance)
Show Figures

Figure 1

30 pages, 13748 KiB  
Article
Semantic Mediation Model to Promote Improved Data Sharing Using Representation Learning in Heterogeneous Healthcare Service Environments
by Sajjad Ali and Ilyoung Chong
Appl. Sci. 2019, 9(19), 4175; https://doi.org/10.3390/app9194175 - 05 Oct 2019
Cited by 6 | Viewed by 5795
Abstract
Interoperability has become a major challenge for the development of integrated healthcare applications. This is mainly because of the reason that data is collected, processed, and managed using heterogeneous protocols, different data formats, and diverse technologies, respectively. Moreover, interoperability among healthcare applications has [...] Read more.
Interoperability has become a major challenge for the development of integrated healthcare applications. This is mainly because of the reason that data is collected, processed, and managed using heterogeneous protocols, different data formats, and diverse technologies, respectively. Moreover, interoperability among healthcare applications has been limited because of the lack of mutually agreed standards. This article proposes a semantic mediation model for the interoperability provision in heterogeneous healthcare service environments. To enhance semantic mediation, the Web of Objects (WoO) framework has been used to support abstraction and aggregation of healthcare concepts using virtual objects and composite virtual objects with ontologies. Besides, semantic annotation of healthcare data has been achieved with a simplified annotation algorithm. The alignment of diverse data models has been supported with the deep representation learning method. Semantic annotation and alignment provide a common understanding of data and cohesive integration, respectively. The semantic mediation model is backed with a target ontology catalog and standard vocabulary. Healthcare data is modeled using the standard Resource Description Framework (RDF), which provides triples structure to describe the healthcare concepts in a unified way. We demonstrate the semantic mediation process with the experimental settings and provide details on the utilization of the proposed model. Full article
Show Figures

Figure 1

13 pages, 1785 KiB  
Article
Multi-Scenario Cooperative Evolutionary Algorithm for the β-Robust p-Median Problem with Demand Uncertainty
by Jianmai Shi, Xiaolei Zheng, Bo Jiao and Rui Wang
Appl. Sci. 2019, 9(19), 4174; https://doi.org/10.3390/app9194174 - 05 Oct 2019
Cited by 2 | Viewed by 2367
Abstract
In this paper, we studied the solution approach for the β-robust p-median problem with a large number of scenarios for the uncertain demands. The concept of neighborhood scenarios was introduced to describe the scenarios with a higher similarity than others. By [...] Read more.
In this paper, we studied the solution approach for the β-robust p-median problem with a large number of scenarios for the uncertain demands. The concept of neighborhood scenarios was introduced to describe the scenarios with a higher similarity than others. By utilizing knowledge from the solutions of neighborhood scenarios and the parallel search strategy, a novel multi-scenario cooperative evolutionary algorithm was proposed to solve the problem for all scenarios in one run. The proposed algorithm was compared with the widely used location–allocation heuristic and genetic algorithm through two practical cases, which were a network with 95 cities and a network with 668 demand nodes in an urban area. The computational results indicate that our algorithm can obtain better solutions in a much shorter time. Full article
Show Figures

Figure 1

12 pages, 2663 KiB  
Article
Research on Polarization and Phase Fading Compensation in Michelson Interferometer Based on 3 × 3 Coupler and Novel Probe with Built-in Faraday Rotator
by Shuaiqi Jing, Jian Rong and Jiayan Tian
Appl. Sci. 2019, 9(19), 4173; https://doi.org/10.3390/app9194173 - 05 Oct 2019
Cited by 1 | Viewed by 2879
Abstract
A self-designed probe and a feedback control scheme based on the Michelson interferometer with a 3 × 3 fiber coupler are proposed. A 45° Faraday rotator is built into the self-designed probe, and a feedback control scheme is used to judge the direction [...] Read more.
A self-designed probe and a feedback control scheme based on the Michelson interferometer with a 3 × 3 fiber coupler are proposed. A 45° Faraday rotator is built into the self-designed probe, and a feedback control scheme is used to judge the direction of increase or decrease for the phase compensation, so as to solve the problems of polarization and phase fading. In addition, a result-normalized method is applied in a micro-vibration measurement experiment. The experimental interferometer system achieves a high frequency of 1 MHz micro-vibration. The normalized results keep stable with a maximum deviation from the mean of 1.9% when the power of light reflected back into the self-designed probe is altered. Applied research is carried out by detecting the displacement due to a photoacoustic wave. Therefore, the experimental interferometer system is available for the practical application of micro-displacement measurements, noncontact high-frequency detection, and point-by-point image scanning in biological tissue. Full article
(This article belongs to the Collection Optical Design and Engineering)
Show Figures

Figure 1

26 pages, 22961 KiB  
Article
An Intelligent and Smart Environment Monitoring System for Healthcare
by Hina Sattar, Imran Sarwar Bajwa, Riaz Ul-Amin, Aqsa Mahmood, Waheed Anwar, Bakhtiar Kasi, Rafaqut Kazmi and Umar Farooq
Appl. Sci. 2019, 9(19), 4172; https://doi.org/10.3390/app9194172 - 05 Oct 2019
Cited by 6 | Viewed by 5371
Abstract
Skin wound healing is influenced by two kinds of environment i.e., exterior environment that is nearby to wound surface and interior environment that is the environment of the adjacent part under wound surface. Both types of environment play a vital role in wound [...] Read more.
Skin wound healing is influenced by two kinds of environment i.e., exterior environment that is nearby to wound surface and interior environment that is the environment of the adjacent part under wound surface. Both types of environment play a vital role in wound healing, which may contribute to continuous or impaired wound healing. Although, different previous studies provided wound care solutions, but they focused on single environmental factors either wound moisture level, pH value or healing enzymes. Practically, it is insignificant to consider environmental effect by determination of single factors or two, as both types of environment contain a lot of other factors which must be part of investigation e.g., smoke, air pollution, air humidity, temperature, hydrogen gases etc. Also, previous studies didn’t classify overall healing either as continuous or impaired based on exterior environment effect. In current research work, we proposed an effective wound care solution based on exterior environment monitoring system integrated with Neural Network Model to consider exterior environment effect on wound healing process, either as continuous or impaired. Current research facilitates patients by providing them intelligent wound care solution to monitor and control wound healing at their home. Full article
(This article belongs to the Special Issue Artificial Intelligence for Smart Systems)
Show Figures

Figure 1

7 pages, 1436 KiB  
Article
Design of 3D Structure Membrane for the Increased Sensitivity in Enzyme Linked Immunosorbent Assay (mELISA)
by Anna Go, Young Ju Park and Min-Ho Lee
Appl. Sci. 2019, 9(19), 4171; https://doi.org/10.3390/app9194171 - 05 Oct 2019
Cited by 1 | Viewed by 2346
Abstract
The Enzyme Linked Immunosorbent Assay (ELISA) technique has been widely used for the identification and quantification of biochemical markers. The typical ELISA requires a number of washing steps to eliminate the unbound proteins which sometimes cause the desorption of protein due to their [...] Read more.
The Enzyme Linked Immunosorbent Assay (ELISA) technique has been widely used for the identification and quantification of biochemical markers. The typical ELISA requires a number of washing steps to eliminate the unbound proteins which sometimes cause the desorption of protein due to their weak bonding between protein and well plate. In this study, we have developed a meshed type of plastic membrane in order to increase the reliable binding efficiency between proteins and the membrane surface, and to provide easy steps of washing. The use of our developed solid membrane has significantly increased the binding capacity of the biomolecules because this membrane ELISA (mELISA) provides 3D binding surfaces which increases the surface area when compared to the conventional 2D surface well plate. The columns were pretreated to form a self-assembled layer (SAM) on the surface for the stable conjugation of a target antibody. The SAM-coated membranes could be stored for one month without any further deterioration of stability. The measured optical density (O.D.) shows a 1.2-fold increase in IgG antigen (25 μg/mL) from the plastic membrane as compared with the conventional ELISA method. The concentrations of thyroid stimulating hormone were also monitored using the mELISA method and it shows good linearity against the concentrations. Full article
(This article belongs to the Special Issue Multifunctional Composite Materials)
Show Figures

Figure 1

14 pages, 5975 KiB  
Article
The Effect of Voltage Dataset Selection on the Accuracy of Entropy-Based Capacity Estimation Methods for Lithium-Ion Batteries
by Xin Sui, Daniel-Ioan Stroe, Shan He, Xinrong Huang, Jinhao Meng and Remus Teodorescu
Appl. Sci. 2019, 9(19), 4170; https://doi.org/10.3390/app9194170 - 04 Oct 2019
Cited by 11 | Viewed by 2738
Abstract
It is important to accurately estimate the capacity of the battery in order to extend the service life of the battery and ensure the reliable operation of the battery energy storage system. As entropy can quantify the regularity of a dataset, it can [...] Read more.
It is important to accurately estimate the capacity of the battery in order to extend the service life of the battery and ensure the reliable operation of the battery energy storage system. As entropy can quantify the regularity of a dataset, it can serve as a feature to estimate the capacity of batteries. In order to analyze the effect of voltage dataset selection on the accuracy of entropy-based estimation methods, six voltage datasets were collected, considering the current direction (i.e., charging or discharging) and the state of charge level. Furthermore, three kinds of entropies (approximate entropy, sample entropy, and multiscale entropy) were introduced, and the relationship between the entropies and the battery capacity was established by using first-order polynomial fitting. Finally, the interaction between the test conditions, entropy features, and estimation accuracy was analyzed. Moreover, the results can be used to select the correct voltage dataset and improve the estimation accuracy. Full article
(This article belongs to the Section Energy Science and Technology)
Show Figures

Figure 1

23 pages, 3238 KiB  
Review
Deep Eutectic Solvents as Extraction Media for Valuable Flavonoids from Natural Sources
by Dimitris Skarpalezos and Anastasia Detsi
Appl. Sci. 2019, 9(19), 4169; https://doi.org/10.3390/app9194169 - 04 Oct 2019
Cited by 97 | Viewed by 7977
Abstract
The present review article attempts to summarize the use of deep eutectic solvents in the extraction of flavonoids, one of the most important classes of plant secondary metabolites. All of the applications reviewed have reported success in isolation and extraction of the target [...] Read more.
The present review article attempts to summarize the use of deep eutectic solvents in the extraction of flavonoids, one of the most important classes of plant secondary metabolites. All of the applications reviewed have reported success in isolation and extraction of the target compounds; competitive, if not superior, extraction rates compared with conventional solvents; and satisfactory behavior of the extract in the latter applications (such as direct analysis, synthesis, or catalysis), wherever attempted. Full article
(This article belongs to the Special Issue High-Performance Green Extraction of Natural Products)
Show Figures

Figure 1

9 pages, 1395 KiB  
Article
Toolpath Strategies for 5DOF and 6DOF Extrusion-Based Additive Manufacturing
by Mathias Laustsen Jensen, Rasoul Mahshid, Greta D’Angelo, Jeppe U. Walther, Malte K. Kiewning, Jon Spangenberg, Hans Nørgaard Hansen and David Bue Pedersen
Appl. Sci. 2019, 9(19), 4168; https://doi.org/10.3390/app9194168 - 04 Oct 2019
Cited by 10 | Viewed by 3304
Abstract
This paper introduces two new deposition-strategies for five degrees of freedom (5DOF) and 6DOF extrusion-based additive manufacturing (AM), called the tool path projection- and parent-child-approach, respectively. The tool path projection method can be automated, and allows for the generation of concentric shells layers, [...] Read more.
This paper introduces two new deposition-strategies for five degrees of freedom (5DOF) and 6DOF extrusion-based additive manufacturing (AM), called the tool path projection- and parent-child-approach, respectively. The tool path projection method can be automated, and allows for the generation of concentric shells layers, which remedy geometrical deviations (known as the stair-case effect) that are typically seen in 3DOF AM processes that potentially require secondary post treatment by machining or grinding of the final part. In the parent-child approach, the designer specifies the manufacturing direction for each distinct feature, thereby helping to remove the need for support material, as well as enabling new features to be dynamically added to the part. Full article
(This article belongs to the Section Mechanical Engineering)
Show Figures

Figure 1

Previous Issue
Next Issue
Back to TopTop