Next Issue
Volume 11, May-2
Previous Issue
Volume 11, April-2
 
 
Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
5.3
2.5
Journals
Applied Sciences
Volume 11
Issue 9
applsci-logo

Journal Menu

► Journal Menu

Journal Browser

► Journal Browser
share announcement

Appl. Sci., Volume 11, Issue 9 (May-1 2021) – 591 articles

Cover Story (view full-size image): This study analyzed coherent electron transport through metal–protein–metal junctions based on a blue copper azurin, in which the copper ion was replaced by three different metal ions (Co, Ni and Zn). The results show that neither the protein structure nor the transmission at the Fermi level changes significantly upon metal replacement. The discrepancy with previous experimental observations suggests that the transport mechanism taking place in these types of junctions is probably not fully coherent. 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
Show export options expand_more Show export options expand_less
Select all
Export citation of selected articles as:
16 pages, 4115 KiB  
Article
Segmentation of Brain Tumors from MRI Images Using Convolutional Autoencoder
by Milica M. Badža and Marko Č. Barjaktarović
Appl. Sci. 2021, 11(9), 4317; https://doi.org/10.3390/app11094317 - 10 May 2021
Cited by 23 | Viewed by 4264
Abstract
The use of machine learning algorithms and modern technologies for automatic segmentation of brain tissue increases in everyday clinical diagnostics. One of the most commonly used machine learning algorithms for image processing is convolutional neural networks. We present a new convolutional neural autoencoder [...] Read more.
The use of machine learning algorithms and modern technologies for automatic segmentation of brain tissue increases in everyday clinical diagnostics. One of the most commonly used machine learning algorithms for image processing is convolutional neural networks. We present a new convolutional neural autoencoder for brain tumor segmentation based on semantic segmentation. The developed architecture is small, and it is tested on the largest online image database. The dataset consists of 3064 T1-weighted contrast-enhanced magnetic resonance images. The proposed architecture’s performance is tested using a combination of two different data division methods, and two different evaluation methods, and by training the network with the original and augmented dataset. Using one of these data division methods, the network’s generalization ability in medical diagnostics was also tested. The best results were obtained for record-wise data division, training the network with the augmented dataset. The average accuracy classification of pixels is 99.23% and 99.28% for 5-fold cross-validation and one test, respectively, and the average dice coefficient is 71.68% and 72.87%. Considering the achieved performance results, execution speed, and subject generalization ability, the developed network has great potential for being a decision support system in everyday clinical practice. Full article
(This article belongs to the Special Issue Recent Developments in Machine Learning Techniques for Medical Image Analysis)
►▼ Show Figures

Figure 1

12 pages, 26205 KiB  
Article
Characterization of Three-Dimensional Internal Structure Evolution in Asphalt Mixtures during Freeze–Thaw Cycles
by Gang Xu, Xianhua Chen, Xing Cai, Yunhong Yu and Jun Yang
Appl. Sci. 2021, 11(9), 4316; https://doi.org/10.3390/app11094316 - 10 May 2021
Cited by 18 | Viewed by 2085
Abstract
This paper aims to characterize the three-dimensional (3D) internal structure evolution of asphalt mixtures under freeze–thaw cycles. Asphalt mixtures with three levels of design void content (3%, 5%, and 7%) were prepared in the laboratory. Subsequently, X-ray computed tomography (CT) tests were conducted [...] Read more.
This paper aims to characterize the three-dimensional (3D) internal structure evolution of asphalt mixtures under freeze–thaw cycles. Asphalt mixtures with three levels of design void content (3%, 5%, and 7%) were prepared in the laboratory. Subsequently, X-ray computed tomography (CT) tests were conducted to capture two-dimensional (2D) images of the internal structure of samples before and after freeze–thaw testing. A set of image processing techniques for reconstructing 3D images of the internal structure were utilized to extract the internal structure properties, which were then used to analyze the changes in the air void distributions and to evaluate the internal structure evolution under freeze–thaw cycles. 3D images reconstructed from X-ray CT images illustrated a dramatic degradation in the internal structure after cyclic freeze–thaw exposure. The change in internal structure occurs mainly in three ways: (1) expansion of existing individual voids, (2) combination of two separated air voids, and (3) generation of new voids. In addition, the parametric analysis of the three-dimensional reconstructed voids revealed that the asphalt mixture void ratio increased with the number of freeze–thaw cycles, while the larger the initial void content, the more pronounced the increase in the specimens. Therefore, asphalt mixture freeze–thaw resistance should be optimized in relation to the design void content. Full article
►▼ Show Figures

Figure 1

11 pages, 1013 KiB  
Communication
In Vitro Coliform Resistance to Bioactive Compounds in Urinary Infection, Assessed in a Lab Catheterization Model
by Emanuel Vamanu, Laura Dorina Dinu, Cristina Mihaela Luntraru and Alexandru Suciu
Appl. Sci. 2021, 11(9), 4315; https://doi.org/10.3390/app11094315 - 10 May 2021
Cited by 6 | Viewed by 2442
Abstract
Bioactive compounds and phenolic compounds are viable alternatives to antibiotics in recurrent urinary tract infections. This study aimed to use a natural functional product, based on the bioactive compounds’ composition, to inhibit the uropathogenic strains of Escherichia coli. E.coli ATCC 25922 [...] Read more.
Bioactive compounds and phenolic compounds are viable alternatives to antibiotics in recurrent urinary tract infections. This study aimed to use a natural functional product, based on the bioactive compounds’ composition, to inhibit the uropathogenic strains of Escherichia coli. E.coli ATCC 25922 was used to characterize the IVCM (new in vitro catheterization model). As support for reducing bacterial proliferation, the cytotoxicity against a strain of Candida albicans was also determined (over 75% at 1 mg/mL). The results were correlated with the analysis of the distribution of biologically active compounds (trans-ferulic acid-268.44 ± 0.001 mg/100 g extract and an equal quantity of Trans-p-coumaric acid and rosmarinic acid). A pronounced inhibitory effect against the uropathogenic strain E. coli 317 (4 log copy no./mL after 72 h) was determined. The results showed a targeted response to the product for tested bacterial strains. The importance of research resulted from the easy and fast characterization of the functional product with antimicrobial effect against uropathogenic strains of E. coli. This study demonstrated that the proposed in vitro model was a valuable tool for assessing urinary tract infections with E. coli. Full article
(This article belongs to the Special Issue Bioactive Compounds from Natural Products: Separation, Characterization and Applications)
►▼ Show Figures

Graphical abstract

11 pages, 9672 KiB  
Article
Selecting Bioassay Test Species at the Screening Level of Soil Ecological Risk Assessments
by Dokyung Kim, Tae-Yang Lee, Lia Kim, Rongxue Cui, Jin Il Kwak, Haemi Kim, Sun-Hwa Nam, Minjin Kim, Wonjae Hwang, Ji-In Kim, Seunghun Hyun and Youn-Joo An
Appl. Sci. 2021, 11(9), 4314; https://doi.org/10.3390/app11094314 - 10 May 2021
Cited by 5 | Viewed by 2626
Abstract
For site-specific soil ecological risk assessments (SERAs), an integrated chemical, ecotoxicological, and ecological analysis needs to be performed. The SERA guidelines of international institutions and countries recommend that a SERA be initiated at the screening level to save time and social economic cost; [...] Read more.
For site-specific soil ecological risk assessments (SERAs), an integrated chemical, ecotoxicological, and ecological analysis needs to be performed. The SERA guidelines of international institutions and countries recommend that a SERA be initiated at the screening level to save time and social economic cost; however, they provide no unified test species for this screening level. This study performed SERAs for field soils and confirmed the importance of selecting bioassay test species that reflect the ecotoxicity of field soils at the screening level. To confirm test species that reflect the ecological risk of field soils, correlation analysis was performed on the results of each bioassay with the integrated ecotoxicological risk index (EtoxRI). Our results showed that soil algae, nematodes, and plants were the most representative species in soil assays, with high correlation coefficients with EtoxRI. The results imply the importance of selecting test species that represent ecological risk for the screening level of SERAs. Based on these findings, when using SERAs, species sensitivity, ecological relevance, and economic aspects should be considered when selecting the bioassay test species. Full article
(This article belongs to the Special Issue Bioremediation in Environmental Engineering)
►▼ Show Figures

Figure 1

22 pages, 2115 KiB  
Article
Heat Treatment and Wounding as Abiotic Stresses to Enhance the Bioactive Composition of Pineapple By-Products
by Diana I. Santos, Diana L. Faria, Sofia C. Lourenço, Vitor D. Alves, Jorge A. Saraiva, António A. Vicente and Margarida Moldão-Martins
Appl. Sci. 2021, 11(9), 4313; https://doi.org/10.3390/app11094313 - 10 May 2021
Cited by 3 | Viewed by 2411
Abstract
Abiotic stress, like heat treatment and wounding, applied to pineapple by-products induce the accumulation of new compounds and add value. In this work the effect of the individual or combined application of wounding and heat treatment stresses on total phenolic content, antioxidant activity [...] Read more.
Abiotic stress, like heat treatment and wounding, applied to pineapple by-products induce the accumulation of new compounds and add value. In this work the effect of the individual or combined application of wounding and heat treatment stresses on total phenolic content, antioxidant activity through complementary methods (DPPH, FRAP, and ABTS) and enzymatic activity (bromelain, phenylalanine ammonia lyase (PAL) and polyphenol oxidase) were evaluated. Whole and wounded pineapple shell and core were dipped in a hot water bath at 30 ± 1 °C or 40 ± 1 °C for 10 min and stored under refrigeration conditions (4 ± 1 °C) for 24 h or 48 h. Results allowed that pineapple by-products reacted differently to the tested stresses. For the core, the application of wounding and heat treatment (40 °C) before storage (24 h) induced a synergistic effect on the accumulation of phenols (increased 17%) and antioxidant activity (4–22%). For the shell samples, the treatment that most increased the content of phenols (14%) and antioxidant activity (38–45%) was heat treatment at 30 °C and storage for 48 h. Treatments that positively influenced the content of phenols and antioxidant activity of the samples did not affect the activity of bromelain or PAL. This study showed that proper abiotic stresses could increase the functional value of by-products. Full article
(This article belongs to the Special Issue Functional Properties in Preharvest and Postharvest Fruit and Vegetables)
►▼ Show Figures

Figure 1

23 pages, 2705 KiB  
Article
Analysis of the Effectiveness of Promotion Strategies of Social Platforms for the Elderly with Different Levels of Digital Literacy
by Xiaoyan Xu, Yi Mei, Yanhong Sun and Xiaoli Zhu
Appl. Sci. 2021, 11(9), 4312; https://doi.org/10.3390/app11094312 - 10 May 2021
Cited by 5 | Viewed by 4470
Abstract
This paper aimed to examine the effectiveness of social platform promotion strategies for the elderly with different digital literacy. Despite extensive research on the development of youth-oriented social platforms, research on the development of social platforms specifically targeting older adults with varying levels [...] Read more.
This paper aimed to examine the effectiveness of social platform promotion strategies for the elderly with different digital literacy. Despite extensive research on the development of youth-oriented social platforms, research on the development of social platforms specifically targeting older adults with varying levels of digital literacy is lacking. The elderly population is divided into passive information receivers (PIRs) and active information seekers (AISs) according to their information seeking expertise, and an empirical study was conducted to assess the behavioral characteristics of PIRs and AISs. Grounded in innovation diffusion research and our empirical results, an agent-based model was developed, and the impact of the proportion of PIRs on the macro result of the social platform adoption (i.e., market penetration) and the impact of promotional strategies on market penetration under different proportions of PIRs were analyzed. The results demonstrate a direct negative effect of the proportion of PIRs on market penetration and a moderating effect on the effectiveness of various promotional strategies. Full article
(This article belongs to the Special Issue Smart Service Technology for Industrial Applications)
►▼ Show Figures

Figure 1

19 pages, 7353 KiB  
Article
Thermal Characteristics Study of the Bump Foil Thrust Gas Bearing
by Xiaomin Liu, Changlin Li, Jianjun Du and Guodong Nan
Appl. Sci. 2021, 11(9), 4311; https://doi.org/10.3390/app11094311 - 10 May 2021
Cited by 19 | Viewed by 3887
Abstract
In this paper, a thermo-hydrodynamic model of the bump foil thrust gas bearing is developed, which solves the coupled gas film three-dimensional energy equation, non-isothermal Reynolds equation, and the foil deformation equation. The effects of bearing speed, thrust load, and external cooling gas [...] Read more.
In this paper, a thermo-hydrodynamic model of the bump foil thrust gas bearing is developed, which solves the coupled gas film three-dimensional energy equation, non-isothermal Reynolds equation, and the foil deformation equation. The effects of bearing speed, thrust load, and external cooling gas on the bearing temperature field are calculated and analyzed. The test rig of foil thrust gas bearing was built to measure the bearing temperature under different working conditions. Both simulation and experiment results show that there exist temperature gradients on the top foil both in the circumferential and radial directions. The simulation results also shows that the top foil side of the gas film has the highest temperature value in the entire lubrication field, and the position of highest temperature moves radially inward on the thrust plate side as the rotor speed increases. The gas film temperature increases with the increasing rotor speed and bearing static load, and rotor speed has greater effects on the temperature variation. Cooling air flow passing through the bump foil is also considered in the simulations, and the cooling efficiency decreases as the mass of gas flow increases. Full article
(This article belongs to the Special Issue Gas Bearings: Modelling, Design and Applications)
►▼ Show Figures

Figure 1

20 pages, 6324 KiB  
Article
MR Imaging–Pathologic Correlation of Uveal Melanomas Undergoing Secondary Enucleation after Proton Beam Radiotherapy
by Pietro Valerio Foti, Corrado Inì, Mario Travali, Renato Farina, Stefano Palmucci, Corrado Spatola, Rocco Luca Emanuele Liardo, Roberto Milazzotto, Luigi Raffaele, Vincenzo Salamone, Rosario Caltabiano, Giuseppe Broggi, Lidia Puzzo, Andrea Russo, Michele Reibaldi, Antonio Longo, Paolo Vigneri, Massimo Venturini and Antonio Basile
Appl. Sci. 2021, 11(9), 4310; https://doi.org/10.3390/app11094310 - 10 May 2021
Cited by 8 | Viewed by 2481
Abstract
Background: Currently, radiotherapy represents the most widely employed therapeutic option in patients with uveal melanoma. Although the effects of proton beam radiotherapy on uveal melanoma end ocular tissues have been histologically documented, their appearance at MR imaging is still poorly understood. The purpose [...] Read more.
Background: Currently, radiotherapy represents the most widely employed therapeutic option in patients with uveal melanoma. Although the effects of proton beam radiotherapy on uveal melanoma end ocular tissues have been histologically documented, their appearance at MR imaging is still poorly understood. The purpose of our study was to elucidate the magnetic resonance (MR) semiotics of radiotherapy-induced changes to neoplastic tissues and ocular structures in patients with uveal melanoma undergoing secondary enucleation after proton beam radiotherapy. Methods: Nine patients with uveal melanoma who had undergone proton beam radiotherapy, MR imaging, and subsequent secondary enucleation were retrospectively selected. The histopathologic findings evaluated for irradiated tumors were necrosis, fibrosis, and viable tumor, while the histopathologic findings evaluated for extratumoral ocular/periocular tissues were radiation-related intraocular inflammation, vitreous hemorrhage, optic nerve degeneration, iris neovascularization, and periocular fibrotic adhesions. On MR images, the appearance of the abovementioned histologic features was assessed on conventional and diffusion-weighted sequences. Results: T2-weighted sequences performed better in detecting radiation-induced necrosis, fibrosis, optic nerve degeneration, and periocular fibrotic adhesions. T1-weighted sequences were preferable for identifying cataracts, vitreous hemorrhage, and inflammatory complications. Contrast-enhanced T1-weighted sequences were irreplaceable in assessing iris neovascularization, and in confirming inflammatory complications. Conclusions: In the light of their increasing role in the multidisciplinary management of patients with uveal melanoma, radiologists should be aware of the MR appearance of the effects of radiotherapy on neoplastic and ocular tissue, in order to improve the accuracy of follow-up MR examinations. Full article
(This article belongs to the Special Issue Ocular Melanoma: Current Concepts)
►▼ Show Figures

Figure 1

15 pages, 6957 KiB  
Article
Textile-Based Coils for Inductive Wireless Power Transmission
by Sebastian Micus, Laura Padani, Michael Haupt and Götz T. Gresser
Appl. Sci. 2021, 11(9), 4309; https://doi.org/10.3390/app11094309 - 10 May 2021
Cited by 11 | Viewed by 2926
Abstract
We developed and evaluated different textile-based inductive coils for near-field wireless power transmission. The technology uses electromagnetic induction for the contactless transfer of electrical energy. Therefore, we investigated various methods for the attachment of conductive materials on a textile-based material and the production [...] Read more.
We developed and evaluated different textile-based inductive coils for near-field wireless power transmission. The technology uses electromagnetic induction for the contactless transfer of electrical energy. Therefore, we investigated various methods for the attachment of conductive materials on a textile-based material and the production of textile-based coils based on QI standard. Afterwards, the textile-based coils were examined and evaluated due to their specific quality characteristics. This happens by calculating the transmission quality and the maximum efficiency of the system which enables comparison of different coil systems and indicates the transmission efficiency of the systems. Full article
(This article belongs to the Section Electrical, Electronics and Communications Engineering)
►▼ Show Figures

Figure 1

11 pages, 3104 KiB  
Article
Individual Adjustment of Contraction Parameters for Effective Swing Assist Using a Pneumatic Artificial Muscle in the Elderly
by Haruki Toda, Tsubasa Maruyama, Yuichi Kurita and Mitsunori Tada
Appl. Sci. 2021, 11(9), 4308; https://doi.org/10.3390/app11094308 - 10 May 2021
Cited by 4 | Viewed by 2341
Abstract
Leg swing during walking is controlled by hip and knee flexion motions. This study examined the effect of swing assist using a pneumatic artificial muscle (PAM) driver system on hip and knee motions and gait performance in the elderly. The participants consisted of [...] Read more.
Leg swing during walking is controlled by hip and knee flexion motions. This study examined the effect of swing assist using a pneumatic artificial muscle (PAM) driver system on hip and knee motions and gait performance in the elderly. The participants consisted of 10 healthy elderly individuals. Two PAMs were attached to each participant’s left hip joint, and a pressure sensor was inserted under the right heel as the trigger. PAM contraction parameters could be controlled through a smartphone, i.e., the delay from trigger to contraction and the contraction duration. These parameters were randomly changed to 0, 100, or 200 ms for the delay and 100, 200, or 300 ms for the contraction. Four combination patterns of delay and contraction duration were observed as the parameter settings for maximizing the hip flexion angle. During walking with the PAM assistance, the hip and knee flexion angles in the swing phase and hip angular excursion of the elderly were significantly increased without altering the gait performance. The findings show that our PAM driver system can realize effective swing assist through changing temporal parameter settings for the PAM contraction in the elderly. Full article
(This article belongs to the Special Issue Haptics for Tele-Communication and Tele-Training)
►▼ Show Figures

Figure 1

11 pages, 9895 KiB  
Article
Effect of Fine Particle Peening Using Hydroxyapatite Particles on Rotating Bending Fatigue Properties of β-Type Titanium Alloy
by Yuki Nakamura, Koichiro Nambu, Toshikazu Akahori, Toshihiro Shimizu and Shoichi Kikuchi
Appl. Sci. 2021, 11(9), 4307; https://doi.org/10.3390/app11094307 - 10 May 2021
Cited by 9 | Viewed by 2299
Abstract
Fine particle peening (FPP) using hydroxyapatite (HAp) shot particles was performed to improve the fatigue strength and form a HAp transfer layer on a beta titanium alloy (Ti–22V–4Al). The surface microstructures of the FPP-treated specimen were characterized using scanning electron microscopy, micro-Vickers hardness [...] Read more.
Fine particle peening (FPP) using hydroxyapatite (HAp) shot particles was performed to improve the fatigue strength and form a HAp transfer layer on a beta titanium alloy (Ti–22V–4Al). The surface microstructures of the FPP-treated specimen were characterized using scanning electron microscopy, micro-Vickers hardness testing, energy dispersive X-ray spectrometry, X-ray diffraction, and electron backscattered diffraction. A HAp transfer layer with a thickness of 5.5 μm was formed on the surface of the Ti–22V–4Al specimen by FPP. In addition, the surface hardness of the Ti–22V–4Al was increased, and high compressive residual stress was generated on the specimen surface by FPP. Rotating bending fatigue tests were performed at room temperature in laboratory air over a wide cycle-life region (103–109 cycles). In the long cycle-life regime, the fatigue strength at 107 cycles of the FPP-treated specimen became higher than that of the untreated specimen. This result is attributed to the formation of a work-hardened layer with high compressive residual stress by FPP. However, the fatigue strength was not improved by FPP in the short cycle-life regime, because fatigue cracks were initiated at surface defects formed during the FPP process. The fatigue fracture mode of the FPP-treated specimens shifted from surface-initiated fracture to subsurface-initiated fracture at a stress amplitude level of 600 MPa. Full article
(This article belongs to the Special Issue Advances in Very-High-Cycle Fatigue)
►▼ Show Figures

Figure 1

23 pages, 8173 KiB  
Article
Color Texture Image Complexity—EEG-Sensed Human Brain Perception vs. Computed Measures
by Irina E. Nicolae and Mihai Ivanovici
Appl. Sci. 2021, 11(9), 4306; https://doi.org/10.3390/app11094306 - 10 May 2021
Cited by 3 | Viewed by 3312
Abstract
In practical applications, such as patient brain signals monitoring, a non-invasive recording system with fewer channels for an easy setup and a wireless connection for remotely monitor physiological signals will be beneficial. In this paper, we investigate the feasibility of using such a [...] Read more.
In practical applications, such as patient brain signals monitoring, a non-invasive recording system with fewer channels for an easy setup and a wireless connection for remotely monitor physiological signals will be beneficial. In this paper, we investigate the feasibility of using such a system in a visual perception scenario. We investigate the complexity perception of color natural and synthetic fractal texture images, by studying the correlations between four types of data: image complexity that is expressed by computed color entropy and color fractal dimension, human subjective evaluation by scoring, and the measured brain EEG responses via Event-Related Potentials. We report on the considerable correlation experimentally observed between the recorded EEG signals and image complexity while considering three complexity levels, as well on the use of an EEG wireless system with few channels for practical applications, with the corresponding electrodes placement in accordance with the type of neural activity recorded. Full article
(This article belongs to the Special Issue Recent Trends, Applications, and Challenges of Brain–Machine Interfaces)
►▼ Show Figures

Figure 1

27 pages, 12063 KiB  
Review
Surface Functionalization of PLGA Nanoparticles to Increase Transport across the BBB for Alzheimer’s Disease
by Laura Del Amo, Amanda Cano, Miren Ettcheto, Eliana B. Souto, Marta Espina, Antoni Camins, Maria Luísa García and Elena Sánchez-López
Appl. Sci. 2021, 11(9), 4305; https://doi.org/10.3390/app11094305 - 10 May 2021
Cited by 32 | Viewed by 6335
Abstract
Alzheimer’s disease (AD) is a chronic neurodegenerative disorder that accounts for about 60% of all diagnosed cases of dementia worldwide. Although there are currently several drugs marketed for its treatment, none are capable of slowing down or stopping the progression of AD. The [...] Read more.
Alzheimer’s disease (AD) is a chronic neurodegenerative disorder that accounts for about 60% of all diagnosed cases of dementia worldwide. Although there are currently several drugs marketed for its treatment, none are capable of slowing down or stopping the progression of AD. The role of the blood-brain barrier (BBB) plays a key role in the design of a successful treatment for this neurodegenerative disease. Nanosized particles have been proposed as suitable drug delivery systems to overcome BBB with the purpose of increasing bioavailability of drugs in the brain. Biodegradable poly (lactic-co-glycolic acid) nanoparticles (PLGA-NPs) have been particularly regarded as promising drug delivery systems as they can be surface-tailored with functionalized molecules for site-specific targeting. In this review, a thorough discussion about the most recent functionalization strategies based on PLGA-NPs for AD and their mechanisms of action is provided, together with a description of AD pathogenesis and the role of the BBB in brain targeting. Full article
(This article belongs to the Special Issue Nanotechnology for Biomedical Applications)
►▼ Show Figures

Figure 1

25 pages, 8309 KiB  
Article
Characterization of Geometry and Surface Texture of AlSi10Mg Laser Powder Bed Fusion Channels Using X-ray Computed Tomography
by Christopher G. Klingaa, Filippo Zanini, Sankhya Mohanty, Simone Carmignato and Jesper H. Hattel
Appl. Sci. 2021, 11(9), 4304; https://doi.org/10.3390/app11094304 - 10 May 2021
Cited by 5 | Viewed by 2387
Abstract
Channels manufactured by laser powder bed fusion have an inherent process-induced dross formation and surface texture that require proper characterization for design and process optimization. This work undertakes surface texture characterization of AlSi10Mg channels of nominal diameter sizes ranging from 1 mm to [...] Read more.
Channels manufactured by laser powder bed fusion have an inherent process-induced dross formation and surface texture that require proper characterization for design and process optimization. This work undertakes surface texture characterization of AlSi10Mg channels of nominal diameter sizes ranging from 1 mm to 9 mm using X-ray computed tomography. Profile parameters, including Pa, Pz, and Pq, were found to be interchangeable for qualitative characterization of surface texture variation. Psk, Pvv, and the fractal dimension could identify the presence of extreme dross and sintered particles on the measured profiles. A method for predicting the equivalent diameter of the unobstructed cross-sectional area (Deq) was presented and its reduction was found to follow a logarithmic trend, as a function of channel length. An empirical model Pa (β, D), as a function of local angular position (β) and channel diameter (D), was demonstrated on a perfect channel geometry, resulting in well-predicted roughness and internal geometry. Full article
(This article belongs to the Topic Additive Manufacturing)
►▼ Show Figures

Figure 1

41 pages, 3103 KiB  
Review
Inertial Parameter Identification in Robotics: A Survey
by Quentin Leboutet, Julien Roux, Alexandre Janot, Julio Rogelio Guadarrama-Olvera and Gordon Cheng
Appl. Sci. 2021, 11(9), 4303; https://doi.org/10.3390/app11094303 - 10 May 2021
Cited by 46 | Viewed by 9046
Abstract
This work aims at reviewing, analyzing and comparing a range of state-of-the-art approaches to inertial parameter identification in the context of robotics. We introduce “BIRDy (Benchmark for Identification of Robot Dynamics)”, an open-source Matlab toolbox, allowing a systematic and formal performance assessment [...] Read more.
This work aims at reviewing, analyzing and comparing a range of state-of-the-art approaches to inertial parameter identification in the context of robotics. We introduce “BIRDy (Benchmark for Identification of Robot Dynamics)”, an open-source Matlab toolbox, allowing a systematic and formal performance assessment of the considered identification algorithms on either simulated or real serial robot manipulators. Seventeen of the most widely used approaches found in the scientific literature are implemented and compared to each other, namely: the Inverse Dynamic Identification Model with Ordinary, Weighted, Iteratively Reweighted and Total Least-Squares (IDIM-OLS, -WLS, -IRLS, -TLS); the Instrumental Variables method (IDIM-IV), the Maximum Likelihood (ML) method; the Direct and Inverse Dynamic Identification Model approach (DIDIM); the Closed-Loop Output Error (CLOE) method; the Closed-Loop Input Error (CLIE) method; the Direct Dynamic Identification Model with Nonlinear Kalman Filtering (DDIM-NKF), the Adaline Neural Network (AdaNN), the Hopfield-Tank Recurrent Neural Network (HTRNN) and eventually a set of Physically Consistent (PC-) methods allowing the enforcement of parameter physicality using Semi-Definite Programming, namely the PC-IDIM-OLS, -WLS, -IRLS, PC-IDIM-IV, and PC-DIDIM. BIRDy is robot-agnostic and features a complete inertial parameter identification pipeline, from the generation of symbolic kinematic and dynamic models to the identification process itself. This includes functionalities for excitation trajectory computation as well as the collection and pre-processing of experiment data. In this work, the proposed methods are first evaluated in simulation, following a Monte Carlo scheme on models of the 6-DoF TX40 and RV2SQ industrial manipulators, before being tested on the real robot platforms. The robustness, precision, computational efficiency and context of application the different methods are investigated and discussed. Full article
(This article belongs to the Special Issue Robots Dynamics: Application and Control)
►▼ Show Figures

Figure 1

21 pages, 86366 KiB  
Article
Behavior of an Internally Confined Hollow Reinforced Concrete Column with a Polygonal Cross-Section
by Sungwon Kim, Hyemin Hong and Taekhee Han
Appl. Sci. 2021, 11(9), 4302; https://doi.org/10.3390/app11094302 - 10 May 2021
Cited by 3 | Viewed by 2523
Abstract
The new supporting structure, internally confined hollow reinforced concrete (ICH RC), was suggested by former researchers. It maintains the material saving effect, which is the advantage of the hollow concrete structure, and it solves the brittle fracture problem of the inner wall by [...] Read more.
The new supporting structure, internally confined hollow reinforced concrete (ICH RC), was suggested by former researchers. It maintains the material saving effect, which is the advantage of the hollow concrete structure, and it solves the brittle fracture problem of the inner wall by the inner steel pipe to make it into the 3-axis confinement state. However, until now, its design and analysis model has been limited to a circular cross-section. In this study, to expand the applicability, research and development of an ICH RC structure with a polygonal cross-section were performed. The material model was developed by defining the constraint stress in the members of the concrete and deriving a reasonable stress-strain relationship. For the column model, it was developed to predict the behavior of the polygonal ICH RC columns by analyzing the axial force-moment correlation, moment-curvature, and lateral force-displacement relationship. Each model was verified not only by comparing with the results of previous experiments but also by analyzing the results according to parameters. The maximum load and ultimate displacement values through the developed model showed the difference with the experimental results within 6% of mean error. It was verified that the proposed analytical model reasonably reflects the behavior of actual columns. Full article
(This article belongs to the Topic Industrial Engineering and Management)
►▼ Show Figures

Figure 1

16 pages, 8118 KiB  
Article
Stochastic Predictions of Ore Production in an Underground Limestone Mine Using Different Probability Density Functions: A Comparative Study Using Big Data from ICT System
by Dahee Jung, Jieun Baek and Yosoon Choi
Appl. Sci. 2021, 11(9), 4301; https://doi.org/10.3390/app11094301 - 10 May 2021
Cited by 10 | Viewed by 2728
Abstract
This study stochastically predicted ore production through discrete event simulation using four different probability density functions for truck travel times. An underground limestone mine was selected as the study area. The truck travel time was measured by analyzing the big data acquired from [...] Read more.
This study stochastically predicted ore production through discrete event simulation using four different probability density functions for truck travel times. An underground limestone mine was selected as the study area. The truck travel time was measured by analyzing the big data acquired from information and communications technology (ICT) systems in October 2018, and probability density functions (uniform, triangular, normal, and observed probability distribution of real data) were determined using statistical values. A discrete event simulation model for a truck haulage system was designed, and truck travel times were randomly generated using a Monte Carlo simulation. The ore production that stochastically predicted fifty times for each probability density function was analyzed and represented as a value of lower 10% (P10), 50% (P50), and 90% (P90). Ore production was underestimated when a uniform and triangular distribution was used, as the actual ore production was similar to that of P90. Conversely, the predicted ore production of P50 was relatively consistent with the actual ore production when using the normal and observed probability distribution of real data. The root mean squared error (RMSE) for predicting ore production for ten days in October 2018 was the lowest (24.9 ton/day) when using the observed probability distribution. Full article
(This article belongs to the Special Issue Recent Advances in Smart Mining Technology)
►▼ Show Figures

Figure 1

14 pages, 1818 KiB  
Article
Evaluation of Oak-Specific Consumption, Efficiency, and Losses from an Aesthetic Veneer Factory
by Gneorghe Cosmin Spirchez, Aurel Lunguleasa and Valentina Doina Ciobanu
Appl. Sci. 2021, 11(9), 4300; https://doi.org/10.3390/app11094300 - 10 May 2021
Cited by 1 | Viewed by 1860
Abstract
The paper aimed to investigate the losses on the manufacturing flow of an aesthetic veneer factory, in order to know their value and to take measures to limit or use them efficiently. For the analysis, the oak species (Quercus robur) was [...] Read more.
The paper aimed to investigate the losses on the manufacturing flow of an aesthetic veneer factory, in order to know their value and to take measures to limit or use them efficiently. For the analysis, the oak species (Quercus robur) was taken into account, through 25 analyzed logs. Statistical investigation has used the Minitab 18 program, for a 95% confidence interval. Minimum values of losses were obtained for the sectioning-grooming operations with 0.6% and debarking with 4.9%, and the highest values were obtained when cutting veneers with 15.9% and formatting veneers with 22.8%. Based on the losses on the manufacturing flow of 67.3%, the specific consumption index of 2.75 m3/m3 or 1.84 m3/1000 m2 of veneer was determined when the average thickness of the veneers was 0.67 mm. The paper highlights the methodology and the values resulting from the investigation of the technological losses and of the specific consumption from an aesthetic veneer factory. Full article
(This article belongs to the Special Issue Advances in Wood Engineering and Forestry)
►▼ Show Figures

Figure 1

15 pages, 3595 KiB  
Article
Beneficial Health Potential of Algerian Polysaccharides Extracted from Plantago ciliata Desf. (Septentrional Sahara) Leaves and Seeds
by Noura Addoun, Zakaria Boual, Cédric Delattre, Toufik Chouana, Christine Gardarin, Pascal Dubessay, Fatima Benaoun, Seddik Addaoud, Mohamed Didi Ould El Hadj, Philippe Michaud and Guillaume Pierre
Appl. Sci. 2021, 11(9), 4299; https://doi.org/10.3390/app11094299 - 10 May 2021
Cited by 4 | Viewed by 2678
Abstract
Today, an ethnobotanical approach makes sense for identifying new active bioactive chemicals from uses of indigenous plants. Two water-soluble enriched polysaccharide fractions (L-PSPN and S-PSPN) were extracted by hot water extraction from the leaves and seeds of Plantago ciliata Desf. (1798), a Mzab [...] Read more.
Today, an ethnobotanical approach makes sense for identifying new active bioactive chemicals from uses of indigenous plants. Two water-soluble enriched polysaccharide fractions (L-PSPN and S-PSPN) were extracted by hot water extraction from the leaves and seeds of Plantago ciliata Desf. (1798), a Mzab indigenous herb currently used in Algeria by traditional healers. Primary investigation was performed for describing the main structural features of these polysaccharides (pectin- and heteroxylan-like compositions) by using colorimetric assays, FTIR spectroscopy, HPAEC/PAD and GC/MS-EI analyses. Some biological activities were also monitored, such as anticomplement, anti-inflammatory (phagocytic ability, NOX2 and MPO inhibitions) and anti-diabetic (α-amylase and α-glucosidase inhibitions). L-PSPC seems able to moderately modulate innate immune system (IC50 around 100 µg/mL) and contribute to wound-healing processes (IC50 close to 217 vs. 443 µg/mL for sodium heparin). S-PSPC shows some potential as an anti-hyperglycemic (IC50 around 4.7 mg/mL) and anti-inflammatory (IC50 ranging from 111 to 203 µg/mL) agent, as well as other (fiber) psyllium-like polysaccharides extracted from Plantago species. Full article
(This article belongs to the Section Applied Biosciences and Bioengineering)
►▼ Show Figures

Figure 1

30 pages, 1487 KiB  
Article
Investigation of Nanogrids for Improved Navy Installation Energy Resilience
by Alissa Kain, Douglas L. Van Bossuyt and Anthony Pollman
Appl. Sci. 2021, 11(9), 4298; https://doi.org/10.3390/app11094298 - 10 May 2021
Cited by 10 | Viewed by 3082
Abstract
Military bases perform important national security missions. In order to perform these missions, specific electrical energy loads must have continuous, uninterrupted power even during terrorist attacks, adversary action, natural disasters, and other threats of specific interest to the military. While many global military [...] Read more.
Military bases perform important national security missions. In order to perform these missions, specific electrical energy loads must have continuous, uninterrupted power even during terrorist attacks, adversary action, natural disasters, and other threats of specific interest to the military. While many global military bases have established microgrids that can maintain base operations and power critical loads during grid disconnect events where outside power is unavailable, many potential threats can cause microgrids to fail and shed critical loads. Nanogrids are of specific interest because they have the potential to protect individual critical loads in the event of microgrid failure. We present a systems engineering methodology that analyzes potential nanogrid configurations to understand which configurations may improve energy resilience and by how much for critical loads from a national security perspective. This then allows targeted deployment of nanogrids within existing microgrid infrastructures. A case study of a small military base with an existing microgrid is presented to demonstrate the potential of the methodology to help base energy managers understand which options are preferable and justify implementing nanogrids to improve energy resilience. Full article
(This article belongs to the Special Issue Advances in Ancillary Services by DRES in Distribution Grids)
►▼ Show Figures

Figure 1

14 pages, 4461 KiB  
Article
Safety Evaluation of a RC Structure with Multiple Openings under High Water Depth Inundations
by Yohei Endo and Takaharu Yasue
Appl. Sci. 2021, 11(9), 4297; https://doi.org/10.3390/app11094297 - 10 May 2021
Viewed by 2076
Abstract
Experimental and numerical studies were conducted to examine the resistance of a newly developed residential building to inundations. Natural disasters including inundations have occurred frequently in recent decades. Once inundations submerge urban areas, water may remain there for days. This can cause substantial [...] Read more.
Experimental and numerical studies were conducted to examine the resistance of a newly developed residential building to inundations. Natural disasters including inundations have occurred frequently in recent decades. Once inundations submerge urban areas, water may remain there for days. This can cause substantial economic and social costs. Flood hazards have been widely discussed and investigated. However, sufficient research contributions have not been made on the behaviour of individual buildings under inundations. The objective of the research was to develop a prototype residential building in which residents can stay during inundations without the need of evacuation. A 3-m water depth was the target for safety evaluation in this research. This paper dealt with three tasks. First, three-point bending tests were performed on window components. Second, a hydrostatic pressure test was carried out on a full-scale reinforced concrete (RC) specimen. Third, taking advantage of the preceding two tasks, numerical simulations were performed to examine the behaviour of the prototype building under hydrostatic and hydrodynamic pressures. The experiments and numerical analyses showed that the prototype building had sufficient resistance and waterproofness against the inundations of a 3-m water depth. This research contributed to the improvements of the safety of RC structures against inundations and flood-risk reduction in urban areas. Full article
(This article belongs to the Section Civil Engineering)
►▼ Show Figures

Figure 1

14 pages, 6858 KiB  
Article
Research on a Low Melting Point Al-Si-Cu (Ni) Filler Metal for 6063 Aluminum Alloy Brazing
by Chengyin Peng, Dandan Zhu, Kaifeng Li, Xiang Du, Fei Zhao, Mingpan Wan and Yuanbiao Tan
Appl. Sci. 2021, 11(9), 4296; https://doi.org/10.3390/app11094296 - 10 May 2021
Cited by 14 | Viewed by 3391
Abstract
A new type of low melting point Al-Si-Cu (Ni) filler metal for brazed 6063 aluminum alloy was designed, and the microstructure and properties of the filler metal were systematically studied. The results show that when the content of Cu in the Al-Si-Cu filler [...] Read more.
A new type of low melting point Al-Si-Cu (Ni) filler metal for brazed 6063 aluminum alloy was designed, and the microstructure and properties of the filler metal were systematically studied. The results show that when the content of Cu in the Al-Si-Cu filler metal increased from 10 wt.% to 20 wt.%, the liquidus temperature of the filler metal decreased from 587.8 °C to 533.4 °C. Its microstructures were mainly composed of the α-Al phase, a primary Si phase, and a θ(Al2Cu) phase. After a proper amount of Ni was added to the Al-Si-20Cu filler metal, its melting range was narrowed, the spreading wettability was improved, and the microstructure was refined. Its microstructure mainly includes α-Al solid solution, Si particles, and θ(Al2Cu) and δ(Al3Ni2) intermetallic compounds. The results of the shear strength test indicate that the shear strength of the brazed joint with Al-6.5Si-20Cu-2.0Ni filler metal was 150.4 MPa, which was 28.32% higher than that of the brazed joint with Al-6.5Si-20Cu filler metal. Full article
(This article belongs to the Topic Metallurgical and Materials Engineering)
►▼ Show Figures

Figure 1

8 pages, 1316 KiB  
Article
Influence of Applied Stress on the Ferroelectricity of Thin Zr-Doped HfO2 Films
by Yuwei Cai, Qingzhu Zhang, Zhaohao Zhang, Gaobo Xu, Zhenhua Wu, Jie Gu, Junjie Li, Jinjuan Xiang and Huaxiang Yin
Appl. Sci. 2021, 11(9), 4295; https://doi.org/10.3390/app11094295 - 10 May 2021
Cited by 9 | Viewed by 4196
Abstract
HfO2-based ferroelectric materials have been widely studied for their application in ferroelectric FETs, which are compatible with conventional CMOS processes; however, problems with the material’s inherent fatigue properties have limited its potential for device application. This paper systematically investigates the effects [...] Read more.
HfO2-based ferroelectric materials have been widely studied for their application in ferroelectric FETs, which are compatible with conventional CMOS processes; however, problems with the material’s inherent fatigue properties have limited its potential for device application. This paper systematically investigates the effects of tensile stress and annealing temperature on the endurance and ferroelectric properties faced by Zr-doped HfO2 ferroelectric film. The remnant polarization (Pr) shows an increasing trend with annealing temperature, while the change in the coercive electric field (Ec) is not obvious in terms of the relationship with tensile stress or annealing temperature. In addition, the application of tensile stress does help to improve the endurance characteristics by about two orders of magnitude for the ferroelectric material, and the endurance properties show a tendency to be negatively correlated with annealing temperature. Overall, although the effect of stress on the ferroelectricity of a HZO material is not obvious, it has a great influence on its endurance properties and can optimize the endurance of the material, and ferroelectricity exhibits a higher dependence on temperature. The optimization of the endurance properties of HZO materials by stress can facilitate their development and application in future integrated circuit technology. Full article
(This article belongs to the Section Electrical, Electronics and Communications Engineering)
►▼ Show Figures

Figure 1

21 pages, 18539 KiB  
Article
Vibration-Based Fingerprint Algorithm for Structural Health Monitoring of Wind Turbine Blades
by Theresa Loss and Alexander Bergmann
Appl. Sci. 2021, 11(9), 4294; https://doi.org/10.3390/app11094294 - 10 May 2021
Cited by 6 | Viewed by 3105
Abstract
Monitoring the structural health of wind turbine blades is essential to increase energy capture and operational safety of turbines, and therewith enhance competitiveness of wind energy. With the current trends of designing blades ever longer, detailed knowledge of the vibrational characteristics at any [...] Read more.
Monitoring the structural health of wind turbine blades is essential to increase energy capture and operational safety of turbines, and therewith enhance competitiveness of wind energy. With the current trends of designing blades ever longer, detailed knowledge of the vibrational characteristics at any point along the blade is desirable. In our approach, we monitor vibrations during operation of the turbine by wirelessly measuring accelerations on the outside of the blades. We propose an algorithm to extract so-called vibration-based fingerprints from those measurements, i.e., dominant vibrations such as eigenfrequencies and narrow-band noise. These fingerprints can then be used for subsequent analysis and visualisation, e.g., for comparing fingerprints across several sensor positions and for identifying vibrations as global or local properties. In this study, data were collected by sensors on two test turbines and fingerprints were successfully extracted for vibrations with both low and high operational variability. An analysis of sensors on the same blade indicates that fingerprints deviate for positions at large radial distance or at different blade sides and, hence, an evaluation with larger datasets of sensors at different positions is promising. In addition, the results show that distributed measurements on the blades are needed to gain a detailed understanding of blade vibrations and thereby reduce loads, increase energy harvesting and improve future blade design. In doing so, our method provides a tool for analysing vibrations with relation to environmental and operational variability in a comprehensive manner. Full article
(This article belongs to the Special Issue Vibration-Based Structural Health Monitoring Ⅱ)
►▼ Show Figures

Figure 1

15 pages, 692 KiB  
Article
Constructing 3D Underwater Sensor Networks without Sensing Holes Utilizing Heterogeneous Underwater Robots
by Jonghoek Kim
Appl. Sci. 2021, 11(9), 4293; https://doi.org/10.3390/app11094293 - 10 May 2021
Cited by 7 | Viewed by 2043
Abstract
This article handles building underwater sensor networks autonomously using multiple surface ships. For building underwater sensor networks in 3D workspace with many obstacles, this article considers surface ships dropping underwater robots into the underwater workspace. We assume that every robot is heterogeneous, such [...] Read more.
This article handles building underwater sensor networks autonomously using multiple surface ships. For building underwater sensor networks in 3D workspace with many obstacles, this article considers surface ships dropping underwater robots into the underwater workspace. We assume that every robot is heterogeneous, such that each robot can have a distinct sensing range while moving with a distinct speed. The proposed strategy works by moving a single robot at a time to spread out the underwater networks until the 3D cluttered workspace is fully covered by sensors of the robots, such that no sensing hole remains. As far as we know, this article is novel in enabling multiple heterogeneous robots to build underwater sensor networks in a 3D cluttered environment, while satisfying the following conditions: (1) Remove all sensing holes. (2) Network connectivity is maintained. (3) Localize all underwater robots. In addition, we address how to handle the case where a robot is broken, and we discuss how to estimate the number of robots required, considering the case where an obstacle inside the workspace is not known a priori. Utilizing MATLAB simulations, we demonstrate the effectiveness of the proposed network construction methods. Full article
(This article belongs to the Special Issue Advances in Robot Path Planning)
►▼ Show Figures

Figure 1

23 pages, 3095 KiB  
Article
Enhanced Convolutional-Neural-Network Architecture for Crop Classification
by Mónica Y. Moreno-Revelo, Lorena Guachi-Guachi, Juan Bernardo Gómez-Mendoza, Javier Revelo-Fuelagán and Diego H. Peluffo-Ordóñez
Appl. Sci. 2021, 11(9), 4292; https://doi.org/10.3390/app11094292 - 10 May 2021
Cited by 12 | Viewed by 4036
Abstract
Automatic crop identification and monitoring is a key element in enhancing food production processes as well as diminishing the related environmental impact. Although several efficient deep learning techniques have emerged in the field of multispectral imagery analysis, the crop classification problem still needs [...] Read more.
Automatic crop identification and monitoring is a key element in enhancing food production processes as well as diminishing the related environmental impact. Although several efficient deep learning techniques have emerged in the field of multispectral imagery analysis, the crop classification problem still needs more accurate solutions. This work introduces a competitive methodology for crop classification from multispectral satellite imagery mainly using an enhanced 2D convolutional neural network (2D-CNN) designed at a smaller-scale architecture, as well as a novel post-processing step. The proposed methodology contains four steps: image stacking, patch extraction, classification model design (based on a 2D-CNN architecture), and post-processing. First, the images are stacked to increase the number of features. Second, the input images are split into patches and fed into the 2D-CNN model. Then, the 2D-CNN model is constructed within a small-scale framework, and properly trained to recognize 10 different types of crops. Finally, a post-processing step is performed in order to reduce the classification error caused by lower-spatial-resolution images. Experiments were carried over the so-named Campo Verde database, which consists of a set of satellite images captured by Landsat and Sentinel satellites from the municipality of Campo Verde, Brazil. In contrast to the maximum accuracy values reached by remarkable works reported in the literature (amounting to an overall accuracy of about 81%, a f1 score of 75.89%, and average accuracy of 73.35%), the proposed methodology achieves a competitive overall accuracy of 81.20%, a f1 score of 75.89%, and an average accuracy of 88.72% when classifying 10 different crops, while ensuring an adequate trade-off between the number of multiply-accumulate operations (MACs) and accuracy. Furthermore, given its ability to effectively classify patches from two image sequences, this methodology may result appealing for other real-world applications, such as the classification of urban materials. Full article
(This article belongs to the Section Computing and Artificial Intelligence)
►▼ Show Figures

Figure 1

14 pages, 5118 KiB  
Article
Locally Optimal Subsampling Strategies for Full Matrix Capture Measurements in Pipe Inspection
by Fabian Krieg, Jan Kirchhof, Eduardo Pérez, Thomas Schwender, Florian Römer and Ahmad Osman
Appl. Sci. 2021, 11(9), 4291; https://doi.org/10.3390/app11094291 - 10 May 2021
Cited by 2 | Viewed by 2134
Abstract
In ultrasonic non-destructive testing, array and matrix transducers are being employed for applications that require in-field steerability or which benefit from a higher number of insonification angles. Having many transmit channels, on the other hand, increases the measurement time and renders the use [...] Read more.
In ultrasonic non-destructive testing, array and matrix transducers are being employed for applications that require in-field steerability or which benefit from a higher number of insonification angles. Having many transmit channels, on the other hand, increases the measurement time and renders the use of array transducers unfeasible for many applications. In the literature, methods for reducing the number of required channels compared to the full matrix capture scheme have been proposed. Conventionally, these are based on choosing the aperture that is as wide as possible. In this publication, we investigate a scenario from the field of pipe inspection, where cracks have to be detected in specific areas near the weld. Consequently, the width of the aperture has to be chosen according to the region of interest at hand. On the basis of ray-tracing simulations which incorporate a model of the transducer directivity and beam spread at the interface, we derive application specific measures of the energy distribution over the array configuration for given regions of interest. These are used to determine feasible subsampling schemes. For the given scenario, the validity/quality of the derived subsampling schemes are compared on the basis of reconstructions using the conventional total focusing method as well as sparsity driven-reconstructions using the Fast Iterative Shrinkage-Thresholding Algorithm. The results can be used to effectively improve the measurement time for the given application without notable loss in defect detectability. Full article
(This article belongs to the Special Issue Structural Health Monitoring & Nondestructive Testing)
►▼ Show Figures

Figure 1

15 pages, 6922 KiB  
Article
Tuning ANN Hyperparameters for Forecasting Drinking Water Demand
by Andrea Menapace, Ariele Zanfei and Maurizio Righetti
Appl. Sci. 2021, 11(9), 4290; https://doi.org/10.3390/app11094290 - 10 May 2021
Cited by 22 | Viewed by 3550
Abstract
The evolution of smart water grids leads to new Big Data challenges boosting the development and application of Machine Learning techniques to support efficient and sustainable drinking water management. These powerful techniques rely on hyperparameters making the models’ tuning a tricky and crucial [...] Read more.
The evolution of smart water grids leads to new Big Data challenges boosting the development and application of Machine Learning techniques to support efficient and sustainable drinking water management. These powerful techniques rely on hyperparameters making the models’ tuning a tricky and crucial task. We hence propose an insightful analysis of the tuning of Artificial Neural Networks for drinking water demand forecasting. This study focuses on layers and nodes’ hyperparameters fitting of different Neural Network architectures through a grid search method by varying dataset, prediction horizon and set of inputs. In particular, the architectures involved are the Feed Forward Neural Network, the Long Short Term Memory, the Simple Recurrent Neural Network and the Gated Recurrent Unit, while the prediction interval ranges from 1 h to 1 week. To avoid the problem of the Neural Networks tuning stochasticity, we propose the selection of the median model among several repetitions for each hyperparameter’s configurations. The proposed iterative tuning procedure highlights the change of the required number of layers and nodes depending on Neural Network architectures, prediction horizon and dataset. Significant trends and considerations are pointed out to support Neural Network application in drinking water prediction. Full article
(This article belongs to the Special Issue Machine Learning Algorithms for Hydraulic Engineering)
►▼ Show Figures

Figure 1

19 pages, 5434 KiB  
Article
Enhancement of the Supercapacitive Performance of Cobalt-tin-cyanate Layered Structures through Conversion from 2D Materials to 1D Nanofibers
by Osama Saber, Sajid Ali Ansari and Abdullah Aljaafari
Appl. Sci. 2021, 11(9), 4289; https://doi.org/10.3390/app11094289 - 10 May 2021
Cited by 4 | Viewed by 2316
Abstract
Rational design of the micro-nanomorphology is highly desired for metal hydroxides to achieve overall high-performance electrodes for supercapacitor and energy storage applications. Here, in the current study, we have succeeded in controlling the morphology of Sn/Co nanolayered structures to obtain plate and nanofibrous [...] Read more.
Rational design of the micro-nanomorphology is highly desired for metal hydroxides to achieve overall high-performance electrodes for supercapacitor and energy storage applications. Here, in the current study, we have succeeded in controlling the morphology of Sn/Co nanolayered structures to obtain plate and nanofibrous morphologies. Additionally, the plate nanostructures could be transformed to obtain plate-nanofibrous morphologies. In this trend, dual anions such as cyanate and nitrate are applied to intercalate among the nanolayers of cobalt-tin and act as building blocks or pillars, producing a series of nanolayered structures. By repulsion forces among the intercalated anions, the nanolayers of Sn/Co are curled and converted to nanofibers. This conversion was confirmed by scanning electron microscopy. In addition, the intercalation reactions and nanolayered structures were indicated by X-ray diffraction, thermal analyses and Fourier-transform infrared spectroscopy. The electrochemical supercapacitive behavior of the different nanostructures of Sn/Co HDS and Sn/Co LDH, such as plate, Plate-nanofiber and nanofibrous morphology has been investigated in three assembly electrode system. The results suggested that the nanofiber morphology of Sn/Co LDH exhibited better specific capacitance performance than the other two morphologies. The enhanced specific capacitance (658 Fg−1) and excellent cyclic stability (89%) of the nanofibers of the Sn/Co LDH could be attributed to the synergistic effects between the electric double layer capacitive character of the tin and the pseudocapacitance nature of the cobalt. Full article
(This article belongs to the Special Issue Topology- and Geometry-Controlled Functionalization of Nanostructured Metamaterials)
►▼ Show Figures

Figure 1

15 pages, 3083 KiB  
Article
Impact of Grid Strength and Impedance Characteristics on the Maximum Power Transfer Capability of Grid-Connected Inverters
by Liang Huang, Chao Wu, Dao Zhou and Frede Blaabjerg
Appl. Sci. 2021, 11(9), 4288; https://doi.org/10.3390/app11094288 - 10 May 2021
Cited by 28 | Viewed by 5988
Abstract
Continuously expanding deployments of distributed power generation systems are transforming conventional centralized power grids into mixed distributed electrical networks. The higher penetration and longer distance from the renewable energy source to the main power grid result in lower grid strength, which stimulates the [...] Read more.
Continuously expanding deployments of distributed power generation systems are transforming conventional centralized power grids into mixed distributed electrical networks. The higher penetration and longer distance from the renewable energy source to the main power grid result in lower grid strength, which stimulates the power limitation problem. Aimed at this problem, case studies of inductive and resistive grid impedance with different grid strengths have been carried out to evaluate the maximum power transfer capability of grid-connected inverters. It is revealed that power grids with a higher short circuit ratio (SCR) or lower resistance-inductance ratio (R/X) provide higher power transfer capability. Moreover, under the resistive grid conditions, a higher voltage at the point of common coupling (PCC) is beneficial to increase the power transfer capability. Based on mathematical analysis, the maximum power curves in the inductive and resistive grids can be found. Moreover, a performance index is proposed in this paper to quantify the performance of the system with different parameter values. Finally, the effectiveness of the analysis is verified by simulation. Full article
(This article belongs to the Section Energy Science and Technology)
►▼ Show Figures

Figure 1

Show export options expand_more Show export options expand_less
Select all
Export citation of selected articles as:
 
Displaying articles 1-591
Previous Issue
Next Issue
Back to TopTop