Applied Sciences

15 pages, 1237 KiB

Open AccessArticle

Will Bid/No-Bid Decision Factors for Construction Projects Be Different in Economic Downturns? A Chinese Study

by Jinxiu Wang, Lin Wang, Kunhui Ye and Yongwei Shan

Appl. Sci. 2020, 10(5), 1899; https://doi.org/10.3390/app10051899 - 10 Mar 2020

Cited by 12 | Viewed by 3792

Whether to bid on construction work is a traditional question that is often challenged in different economic situations. What will the decision factors be when contractors have to struggle to achieve growth in economic downturns? Since previous studies have not widely agreed with [...] Read more.

Whether to bid on construction work is a traditional question that is often challenged in different economic situations. What will the decision factors be when contractors have to struggle to achieve growth in economic downturns? Since previous studies have not widely agreed with each other on this issue, this study aims to examine China’s construction engineering contractors in recent “bad” years. The research findings reveal that the cluster related to expected profitability, including terms of payment, reputation of the client regarding his/her commitment to making timely payments, original price estimated by the client, profit track record for similar projects, and contract type, were the most significant determinants. The bid/no-bid decision-making process comprises three modules, including the contractor’s strategies, the contractor’s competency for a project, and expected competition. These results suggest that competing for survival is the dominant position of contractors in making bid/no-bid decisions in economic downturns. Full article

(This article belongs to the Special Issue Industrial Engineering and Management: Current Issues and Trends)

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5 pages, 196 KiB

Open AccessEditorial

Editorial “Biomechanical Spectrum of Human Sport Performance”

by Redha Taiar and Mario Bernardo-Filho

Appl. Sci. 2020, 10(5), 1898; https://doi.org/10.3390/app10051898 - 10 Mar 2020

Cited by 4 | Viewed by 2548

Abstract

Several parameters can influence our health capital today and can have a negative impact on our performance, whether physiological or mechanical. Indeed, our health and wellbeing are influenced by a range of social, cultural, economic, psychological, and environmental factors across our lives. These [...] Read more.

Several parameters can influence our health capital today and can have a negative impact on our performance, whether physiological or mechanical. Indeed, our health and wellbeing are influenced by a range of social, cultural, economic, psychological, and environmental factors across our lives. These change as we progress through the key transition points in life—from infancy and childhood through our teenage years to adulthood, working life, retirement and the end of life. Sport can be a vector that links many of these factors. Whether it is high-performance sport or sedentary practice, sport is very important for the improvement of psychological wellbeing and physical health. Our overarching aim was to increase quality of life. Sedentary practice can increase mobility and reduce the risk of disease, so changing adults’ behavior through sedentary practice could reduce illness and decrease costs to society concerning health problems. Furthermore, a higher frequency of practice can lead to improvements in technique and optimized performance. Our objective is to summarize the latest research in sport science and to quantify the most important parameters influencing human performance related to the health sciences for all age groups, throughout their lives. Full article

(This article belongs to the Special Issue Biomechanical Spectrum of Human Sport Performance)

20 pages, 10633 KiB

Open AccessArticle

The Influence of the Activation Function in a Convolution Neural Network Model of Facial Expression Recognition

by Yingying Wang, Yibin Li, Yong Song and Xuewen Rong

Appl. Sci. 2020, 10(5), 1897; https://doi.org/10.3390/app10051897 - 10 Mar 2020

Cited by 192 | Viewed by 12932

Abstract

The convolutional neural network (CNN) has been widely used in image recognition field due to its good performance. This paper proposes a facial expression recognition method based on the CNN model. Regarding the complexity of the hierarchic structure of the CNN model, the [...] Read more.

The convolutional neural network (CNN) has been widely used in image recognition field due to its good performance. This paper proposes a facial expression recognition method based on the CNN model. Regarding the complexity of the hierarchic structure of the CNN model, the activation function is its core, because the nonlinear ability of the activation function really makes the deep neural network have authentic artificial intelligence. Among common activation functions, the ReLu function is one of the best of them, but it also has some shortcomings. Since the derivative of the ReLu function is always zero when the input value is negative, it is likely to appear as the phenomenon of neuronal necrosis. In order to solve the above problem, the influence of the activation function in the CNN model is studied in this paper. According to the design principle of the activation function in CNN model, a new piecewise activation function is proposed. Five common activation functions (i.e., sigmoid, tanh, ReLu, leaky ReLus and softplus–ReLu, plus the new activation function) have been analysed and compared in facial expression recognition tasks based on the Keras framework. The Experimental results on two public facial expression databases (i.e., JAFFE and FER2013) show that the convolutional neural network based on the improved activation function has a better performance than most-of-the-art activation functions. Full article

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16 pages, 6057 KiB

Open AccessArticle

Soc Estimation of the Lithium-Ion Battery Pack using a Sigma Point Kalman Filter Based on a Cell’s Second Order Dynamic Model

by Chi Nguyen Van and Thuy Nguyen Vinh

Appl. Sci. 2020, 10(5), 1896; https://doi.org/10.3390/app10051896 - 10 Mar 2020

Cited by 25 | Viewed by 3735

Abstract

This paper deals with the state of charge (SoC) estimation of a lithium-ion battery pack (LiBP) connected by some cells in series and parallel. The voltage noise, noise and current bias of current through the LiBP are taken into account in the SoC [...] Read more.

This paper deals with the state of charge (SoC) estimation of a lithium-ion battery pack (LiBP) connected by some cells in series and parallel. The voltage noise, noise and current bias of current through the LiBP are taken into account in the SoC estimation problem. In order to describe the cell dynamic more accurately, especially for practical applications with charge and discharge amplitude varying suddenly, in this paper we use the second dynamic order model of the cell to estimate the SoC of the LiBP. By applying the sigma point Kalman filter (SPKF), the average SoC of the pack and bias current of current measurement are estimated by first estimator; the second estimator estimates the SoC differences of the cell modules from average SoC of the pack. The SoC of the cell modules are the sum of average SoCs of the pack and the SoC differences. By only using two estimators, the calculation complexity for SoC estimation is more reduced; this is very useful for the LiBP, which has the number of cells connected in a large series. This method was applied for the pack of SAMSUNG ICR18650-22P connected by seven cell modules; the cell modules were connected by nine cells in parallel; the LiBP was charged and discharged with amplitude varying suddenly. The estimated SoC of seven cell modules is smaller than 2% for a temperature operating range typically −5 °C to 45 °C. The comparison of the accuracy of SoC estimation based on the first and the second order dynamic models is made; the result shows that the SoC estimation used the second order dynamic model is more exact. Full article

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4 pages, 165 KiB

Open AccessEditorial

Special Issue on Mathematical Modeling Using Differential Equations and Network Theory

by Ioannis Dassios

Appl. Sci. 2020, 10(5), 1895; https://doi.org/10.3390/app10051895 - 10 Mar 2020

Viewed by 1854

Abstract

This special issue collects the latest results on differential/difference equations, the mathematics of networks, and their applications to engineering, and physical phenomena [...] Full article

(This article belongs to the Special Issue Mathematical Modeling using Differential Equations, and Network Theory)

52 pages, 10778 KiB

Open AccessReview

A Survey on Computer-Aided Diagnosis of Brain Disorders through MRI Based on Machine Learning and Data Mining Methodologies with an Emphasis on Alzheimer Disease Diagnosis and the Contribution of the Multimodal Fusion

by Lilia Lazli, Mounir Boukadoum and Otmane Ait Mohamed

Appl. Sci. 2020, 10(5), 1894; https://doi.org/10.3390/app10051894 - 10 Mar 2020

Cited by 26 | Viewed by 7391

Abstract

Computer-aided diagnostic (CAD) systems use machine learning methods that provide a synergistic effect between the neuroradiologist and the computer, enabling an efficient and rapid diagnosis of the patient’s condition. As part of the early diagnosis of Alzheimer’s disease (AD), which is a major [...] Read more.

Computer-aided diagnostic (CAD) systems use machine learning methods that provide a synergistic effect between the neuroradiologist and the computer, enabling an efficient and rapid diagnosis of the patient’s condition. As part of the early diagnosis of Alzheimer’s disease (AD), which is a major public health problem, the CAD system provides a neuropsychological assessment that helps mitigate its effects. The use of data fusion techniques by CAD systems has proven to be useful, they allow for the merging of information relating to the brain and its tissues from MRI, with that of other types of modalities. This multimodal fusion refines the quality of brain images by reducing redundancy and randomness, which contributes to improving the clinical reliability of the diagnosis compared to the use of a single modality. The purpose of this article is first to determine the main steps of the CAD system for brain magnetic resonance imaging (MRI). Then to bring together some research work related to the diagnosis of brain disorders, emphasizing AD. Thus the most used methods in the stages of classification and brain regions segmentation are described, highlighting their advantages and disadvantages. Secondly, on the basis of the raised problem, we propose a solution within the framework of multimodal fusion. In this context, based on quantitative measurement parameters, a performance study of multimodal CAD systems is proposed by comparing their effectiveness with those exploiting a single MRI modality. In this case, advances in information fusion techniques in medical imagery are accentuated, highlighting their advantages and disadvantages. The contribution of multimodal fusion and the interest of hybrid models are finally addressed, as well as the main scientific assertions made, in the field of brain disease diagnosis. Full article

(This article belongs to the Special Issue Computer-aided Biomedical Imaging 2020: Advances and Prospects)

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12 pages, 1709 KiB

Open AccessArticle

Multi-Segmental Motion in Foot during Counter-Movement Jump with Toe Manipulation

by Liangliang Xiang, Qichang Mei, Datao Xu, Justin Fernandez and Yaodong Gu

Appl. Sci. 2020, 10(5), 1893; https://doi.org/10.3390/app10051893 - 10 Mar 2020

Cited by 12 | Viewed by 3768

Abstract

Human toes are crucial for vertical jumping performance. The purpose of this study is to investigate the acute effect of hallux abduction manipulation on foot inter-segment kinematic alterations and plantar loading redistribution during the countermovement jump (CMJ). Thirteen participants were recruited to join [...] Read more.

Human toes are crucial for vertical jumping performance. The purpose of this study is to investigate the acute effect of hallux abduction manipulation on foot inter-segment kinematic alterations and plantar loading redistribution during the countermovement jump (CMJ). Thirteen participants were recruited to join in this experiment, for the collection of the foot inter-segment kinematics and plantar pressure data. During the take-off phase, the contact area presented a significant increase while the pressure-time integral decreased in the second metatarsal (M2), whilst the third metatarsal (M3) and fourth metatarsal (M4) decreased significantly in pressure-time integral with Toe-Manipulation (TM). During the landing phase, maximum force and peak pressure were smaller in the big toe (BT) after hallux abduction manipulation. HXFFA (hallux-forefoot angle) showed a greater pronation after manipulation in the frontal plane (0%–26% and 50%–100%) with p = 0.002 and p < 0.001. In the transverse plane, the smaller adductions were found during 62%–82% in take-off and 62%–91% in landing (p = 0.003 and p < 0.001). There was a redistributed plantar loading during the landing phase from the medial to lateral forefoot. However, a reduced hallux range of motion in the TM session was exhibited, compared to Non-Toe-Manipulation (NTM). Full article

(This article belongs to the Section Applied Biosciences and Bioengineering)

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16 pages, 2371 KiB

Open AccessArticle

A Novel Approach for Software Defect prediction Based on the Power Law Function

by Junhua Ren and Feng Liu

Appl. Sci. 2020, 10(5), 1892; https://doi.org/10.3390/app10051892 - 10 Mar 2020

Cited by 3 | Viewed by 2704

Abstract

Power law describes a common behavior in which a few factors play decisive roles in one thing. Most software defects occur in very few instances. In this study, we proposed a novel approach that adopts power law function characteristics for software defect prediction. [...] Read more.

Power law describes a common behavior in which a few factors play decisive roles in one thing. Most software defects occur in very few instances. In this study, we proposed a novel approach that adopts power law function characteristics for software defect prediction. The first step in this approach is to establish the power law function of the majority of metrics in a software system. Following this, the power law function’s maximal curvature value is applied as the threshold value for determining higher metric values. Furthermore, the total number of higher metric values is counted in each instance. Finally, the statistical data are clustered into different categories as defect-free and defect-prone instances. Case studies and a comparison were conducted based on twelve public datasets of Promise, SoftLab, and ReLink by using five different algorithms. The results indicate that the precision, recall, and F-measure values obtained by the proposed approach are the most optimal among the tested five algorithms, the average values of recall and F-measure were improved by 14.3% and 6.0%, respectively. Furthermore, the complexity of the proposed approach based on the power law function is

O (2 n)

, which is the lowest among the tested five algorithms. The proposed approach is thus demonstrated to be feasible and highly efficient at software defect prediction with unlabeled datasets. Full article

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20 pages, 1821 KiB

Open AccessArticle

An Ensemble of Locally Reliable Cluster Solutions

by Huan Niu, Nasim Khozouie, Hamid Parvin, Hamid Alinejad-Rokny, Amin Beheshti and Mohammad Reza Mahmoudi

Appl. Sci. 2020, 10(5), 1891; https://doi.org/10.3390/app10051891 - 10 Mar 2020

Cited by 36 | Viewed by 3079

Abstract

Clustering ensemble indicates to an approach in which a number of (usually weak) base clusterings are performed and their consensus clustering is used as the final clustering. Knowing democratic decisions are better than dictatorial decisions, it seems clear and simple that ensemble (here, [...] Read more.

Clustering ensemble indicates to an approach in which a number of (usually weak) base clusterings are performed and their consensus clustering is used as the final clustering. Knowing democratic decisions are better than dictatorial decisions, it seems clear and simple that ensemble (here, clustering ensemble) decisions are better than simple model (here, clustering) decisions. But it is not guaranteed that every ensemble is better than a simple model. An ensemble is considered to be a better ensemble if their members are valid or high-quality and if they participate according to their qualities in constructing consensus clustering. In this paper, we propose a clustering ensemble framework that uses a simple clustering algorithm based on kmedoids clustering algorithm. Our simple clustering algorithm guarantees that the discovered clusters are valid. From another point, it is also guaranteed that our clustering ensemble framework uses a mechanism to make use of each discovered cluster according to its quality. To do this mechanism an auxiliary ensemble named reference set is created by running several kmeans clustering algorithms. Full article

(This article belongs to the Special Issue Data Preprocessing in Pattern Recognition: Recent Progress, Trends and Applications)

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11 pages, 498 KiB

Open AccessArticle

Examining and Adapting the Psychometric Properties of the Maslach Burnout Inventory-Health Services Survey (MBI-HSS) among Healthcare Professionals

by Abbas Al Mutair, Alya Al Mutairi, Hiba Chagla, Khalid Alawam, Khulud Alsalman and Azeem Ali

Appl. Sci. 2020, 10(5), 1890; https://doi.org/10.3390/app10051890 - 10 Mar 2020

Cited by 18 | Viewed by 7304

Abstract

Burnout is known to negatively impact healthcare providers both physically and mentally and is assessed using the Maslach Burnout Inventory-Human Services Survey (MBI-HSS). Many versions of this tool have been developed for different parts of the world, but there is currently no valid [...] Read more.

Burnout is known to negatively impact healthcare providers both physically and mentally and is assessed using the Maslach Burnout Inventory-Human Services Survey (MBI-HSS). Many versions of this tool have been developed for different parts of the world, but there is currently no valid version specifically designed for use in the Gulf Cooperation Council Region. This study aims to use data collected across six different regions in the Gulf Cooperation Council Region to assess the validity and reliability of the MBI-HSS model and develop a version of the MBI-HSS best suited for evaluating burnout levels among the healthcare providers in this region. The MBI-HSS questionnaire adapted by Maslach was distributed to 888 healthcare providers aged 32 years ± 7 years, 231 (26.1%) of whom were males and 651 (73.9%) of whom were females, between 2017 and 2018. The data collected were randomly divided into two subsamples, resulting in a sample with the data of 300 healthcare professionals for exploratory factor analysis (EFA) and 588 healthcare professionals for confirmatory factor analysis (CFA). The CFA of the original version of the MBI-HSS yielded a chi-square value of 1897 (p < 0.001), indicating the need for revision. EFA was then used to construct a new model of the MBI-HSS, and a CFA was performed on the second subsample to evaluate the model fit to the data. The EFA produced a 3-factor version that accounted for 56.3% of the total variance, with item 11 of the MBI moved to the Emotional Exhaustion (EE) subscale and item 16 loaded onto Depersonalisation (DP) instead of EE. Additionally, items 18 and 20 were omitted. The reconstructed version had a Root Mean Square Error of Approximation (RMSEA) value of 0.065 (<0.08), a goodness of fit index (GFI) value of 0.915 (>0.90) and an adjusted goodness of fit index (AGFI) value of 0.893 (>0.8). These results when compared to the CFA of the original model, which produced a GFI value of 0.79, an AGFI value of 0.74 and an RMSEA value of 0.09 (>0.08), indicate that this new version has a more satisfactory fit to the data and should be used when assessing burnout in the Gulf Cooperation Council Region. Full article

(This article belongs to the Section Applied Biosciences and Bioengineering)

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19 pages, 6621 KiB

Open AccessArticle

Insights into the Effect of WJ-7 Fastener Rubber Pad to Vehicle-Rail-Viaduct Coupled Dynamics

by Linya Liu, Zhiyuan Zuo, Yunlai Zhou and Jialiang Qin

Appl. Sci. 2020, 10(5), 1889; https://doi.org/10.3390/app10051889 - 10 Mar 2020

Cited by 19 | Viewed by 3032

Abstract

The high-speed railway (HSR) has been a long-term hotspot in both scientific and engineering societies to enhance the long-term high quality HSR service. This study aims to investigate the WJ-7B type small resistance fastener rubber pad applied in HSR, and temperature sweep test [...] Read more.

The high-speed railway (HSR) has been a long-term hotspot in both scientific and engineering societies to enhance the long-term high quality HSR service. This study aims to investigate the WJ-7B type small resistance fastener rubber pad applied in HSR, and temperature sweep test is applied to determine the mechanical parameters of the fastener rubber pad, which are hereafter introduced into the vehicle-track-viaduct vertical coupling model via dynamic flexibility method. The track irregularity spectrum is considered as fixed-point excitation to investigate the temperature-dependent effect of fastener rubber pad on the dynamic responses. The results reveal that the rigidity of the fastener rubber pad is low temperature sensitive and high temperature stable, and the temperature variation has little effect on the vertical dynamic responses of the vehicle. The dynamic flexibility of the rail increases in amplitude and the dominant frequency decreases as the temperature of the fastener rubber pad increases. The vertical dynamic responses of the wheel-rail force, the wheelset and the rail-viaduct system gradually decrease as the temperature of the fastener rubber pad increases, and the peak frequency follows the similar rule. While under high temperature circumstances, the temperature dependent stiffness of the fastener rubber pad has little influence on the peak of the dominant frequency in the vertical dynamic response of the track-viaduct system. Full article

(This article belongs to the Section Acoustics and Vibrations)

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14 pages, 741 KiB

Open AccessArticle

An Integrated Two-Stage Medical Pre-Checkup and Subsequent Validation Key Agreement Authentication Mechanism

by Tsung-Hung Lin and Ming-Te Chen

Appl. Sci. 2020, 10(5), 1888; https://doi.org/10.3390/app10051888 - 10 Mar 2020

Cited by 2 | Viewed by 2092

Abstract

In the global village era, several competitions require pre-checkups for the participants who are qualified to participate that must be passed before the competition, so the accuracy of the checkup data must be confirmed and must not be leaked or tampered with. This [...] Read more.

In the global village era, several competitions require pre-checkups for the participants who are qualified to participate that must be passed before the competition, so the accuracy of the checkup data must be confirmed and must not be leaked or tampered with. This is a new challenge to the accuracy of medical checkups data in the information and communication era. How to protect the rights of participants and the non-repudiation of participants are the main issues of this study. We have designed a two-phase user identity embedding and authentication scheme for pre-checkups and subsequent validations. A participant’s private key is added to the physical examination data, and the identity of the examinations data is confirmed by the contestant before the competitions. Our work integrates lightweight Exclusive-OR (XOR) operations, fuzzy extractor biometric personal passwords, and a fixed-length hash operation accords with post-quantum operations to solve the problem of two-stage medical pre-checkup and subsequent validation key agreement authentication. The random oracle authentication mechanism proves the security of the protocols, and the security analysis proves that the protocols can resist the vulnerability attacks. Full article

(This article belongs to the Special Issue Big Data Analytics in Healthcare)

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12 pages, 2086 KiB

Open AccessFeature PaperArticle

New Hybrid Tomato Cultivars: An NMR-Based Chemical Characterization

by Cinzia Ingallina, Anatoly P. Sobolev, Simone Circi, Mattia Spano, Anna Maria Giusti and Luisa Mannina

Appl. Sci. 2020, 10(5), 1887; https://doi.org/10.3390/app10051887 - 10 Mar 2020

Cited by 15 | Viewed by 3535

Abstract

Bamano, King Creole, Sugarland, and DulceMiel hybrid tomato cultivars have been recently introduced in the Lazio area (Central Italy) to expand and valorize the regional/national market. Tomatoes from these cultivars, together with tomatoes from the native Fiaschetta cultivar, were sampled at the proper [...] Read more.

Bamano, King Creole, Sugarland, and DulceMiel hybrid tomato cultivars have been recently introduced in the Lazio area (Central Italy) to expand and valorize the regional/national market. Tomatoes from these cultivars, together with tomatoes from the native Fiaschetta cultivar, were sampled at the proper ripening time for the fresh market and characterized to obtain and compare their metabolite profiles. The Bligh–Dyer extraction protocol was carried out, and the resulting organic and hydroalcoholic fractions were analyzed by high-field Nuclear Magnetic Resonance (NMR) spectroscopy. NMR data relative to quantified metabolites (sugars, amino acids, organic acids, sterols, and fatty acids) allowed to point out similarities and differences among cultivars. DulceMiel hybrid and Fiaschetta native cultivars showed some common aspects having the highest levels of the most abundant amino acids as well as comparable amounts of organic acids, amino acids, stigmasterol, and linoleic and linolenic acids. However, DulceMiel turned out to have higher levels of glucose, fructose, and galactose with respect to Fiaschetta, reflecting the particular taste of the DulceMiel product. King Creole, Bamano, and Sugarland hybrid cultivars were generally characterized by the lowest content of amino acids and organic acids. King Creole showed the highest content of malic acid, whereas Bamano was characterized by the highest levels of glucose and fructose. Full article

(This article belongs to the Special Issue Nuclear Magnetic Resonance (NMR) Spectroscopy in Food Science and Processing)

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16 pages, 1929 KiB

Open AccessFeature PaperReview

Microalgae Water Bioremediation: Trends and Hot Topics

by Diana Pacheco, Ana Cristina Rocha, Leonel Pereira and Tiago Verdelhos

Appl. Sci. 2020, 10(5), 1886; https://doi.org/10.3390/app10051886 - 10 Mar 2020

Cited by 70 | Viewed by 8911

Abstract

The need to reduce costs associated with the production of microalgae biomass has encouraged the coupling of process with wastewater treatment. Emerging pollutants in municipal, industrial, and agricultural wastewaters, ranging from pharmaceuticals to metals, endanger public health and natural resources. The use of [...] Read more.

The need to reduce costs associated with the production of microalgae biomass has encouraged the coupling of process with wastewater treatment. Emerging pollutants in municipal, industrial, and agricultural wastewaters, ranging from pharmaceuticals to metals, endanger public health and natural resources. The use of microalgae has, in fact, been shown to be an efficient method in water-treatment processes and presents several advantages, such as carbon sequestration, and an opportunity to develop innovative bioproducts with applications to several industries. Using a bibliometric analysis software, SciMAT, a mapping of the research field was performed, analyzing the articles produced between 1981 and 2018, aiming to identifying the hot topics and trends studied until now. The application of microalgae on water bioremediation is an evolving research field that currently focuses on developing efficient and cost-effective treatments methods that also enable the production of add-value products, leading to a blue and circular economy. Full article

(This article belongs to the Special Issue Physiology and Biotechnology of Microalgae)

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16 pages, 1377 KiB

Open AccessArticle

Energy Efficient and Reliable Routing Algorithm for Wireless Sensors Networks

by Liangrui Tang, Zhilin Lu and Bing Fan

Appl. Sci. 2020, 10(5), 1885; https://doi.org/10.3390/app10051885 - 10 Mar 2020

Cited by 54 | Viewed by 3056

Abstract

In energy-constrained wireless sensor networks, low energy utilization and unbalanced energy distribution are seriously affecting the operation of the network. Therefore, efficient and reasonable routing algorithms are needed to achieve higher Quality of Service (QoS). For the Dempster–Shafer (DS) evidence theory, it can [...] Read more.

In energy-constrained wireless sensor networks, low energy utilization and unbalanced energy distribution are seriously affecting the operation of the network. Therefore, efficient and reasonable routing algorithms are needed to achieve higher Quality of Service (QoS). For the Dempster–Shafer (DS) evidence theory, it can fuse multiple attributes of sensor nodes with reasonable theoretical deduction and has low demand for prior knowledge. Based on the above, we propose an energy efficient and reliable routing algorithm based on DS evidence theory (DS-EERA). First, DS-EERA establishes three attribute indexes as the evidence under considering the neighboring nodes’ residual energy, traffic, the closeness of its path to the shortest path, etc. Then we adopt the entropy weight method to objectively determine the weight of three indexes. After establishing the basic probability assignment (BPA) function, the fusion rule of DS evidence theory is applied to fuse the BPA function of each index value to select the next hop. Finally, each node in the network transmits data through this routing strategy. Theoretical analysis and simulation results show that DS-EERA is promising, which can effectively prolong the network lifetime. Meanwhile, it can also reach a lower packet loss rate and improve the reliability of data transmission. Full article

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20 pages, 5141 KiB

Open AccessArticle

Adaptive Performance Tuning for Voltage-Sourced Converters with Frequency Responses

by Weichao Zhang, Xiangwu Yan and Hanyan Huang

Appl. Sci. 2020, 10(5), 1884; https://doi.org/10.3390/app10051884 - 10 Mar 2020

Cited by 2 | Viewed by 2178

Abstract

Renewable generation brings both new energies and significant challenges to the evolving power system. To cope with the loss of inertia caused by inertialess power electronic interfaces (PEIs), the concept of the virtual synchronous generator (VSG) has been proposed. The PEIs under VSG [...] Read more.

Renewable generation brings both new energies and significant challenges to the evolving power system. To cope with the loss of inertia caused by inertialess power electronic interfaces (PEIs), the concept of the virtual synchronous generator (VSG) has been proposed. The PEIs under VSG control could mimic the external properties of the traditional synchronous generators. Therefore, the frequency stability of the entire system could be sustained against disturbances mainly caused by demand changes. Moreover, as the parameters in the emulation control processes are adjustable rather than fixed, the flexibility could be enhanced by proper tuning. This paper presents a parameter tuning method adaptive to the load deviations. First, the concept and implementation of the VSG algorithm performing an inertia response (IR) and primary frequency responses (PFR) are introduced. Then, the simplification of the transfer function of the dynamic system of the stand-alone VSG-PEI is completed according to the distributed poles and zeros. As a result, the performance indices during the IR and PFR stages are deduced by the inverse Laplace transformation. Then, the composite influences on the performances by different parameters (including the inertia constant, the speed droop, and the load deviations) are analyzed. Based on the composite influences and the time sequences, an adaptive parameter tuning method is presented. The feasibility of the proposed method is verified by simulation. Full article

(This article belongs to the Special Issue Advancing Grid-Connected Renewable Generation Systems 2019)

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17 pages, 3622 KiB

Open AccessArticle

Control System Applied to the Microinjection of Artificial Tears for Severe Dry Eye Treatment

by Narcisse Meni-Babakidi, Gonzalo Viramontes-Gamboa, Laura Alicia Ibarra-Bracamontes and Israel Luna-Reyes

Appl. Sci. 2020, 10(5), 1883; https://doi.org/10.3390/app10051883 - 10 Mar 2020

Cited by 3 | Viewed by 2985

Abstract

This paper presents a portable automated teardrop microinjection system as a practical solution for patients suffering from severe dry eye. The electronic device for the controlled and continuous injection of artificial tears is designed, assembled, and tested for performance and stability. It is [...] Read more.

This paper presents a portable automated teardrop microinjection system as a practical solution for patients suffering from severe dry eye. The electronic device for the controlled and continuous injection of artificial tears is designed, assembled, and tested for performance and stability. It is controlled via Wi-Fi from an Android programmable device. Its design is based on the physicochemical properties of artificial tears, and with both production costs and portability in mind. The system was modeled according to the V methodology of the association for professional German engineers VDI 2206 standard. The microinjector handles a wide range of internal variables such as tears flow rate (0.13 to 60 μL/min), tears viscosity (up to 600 Pa·s), temperature (up to 60 °C), injected volume of tears, and time between consecutive injections. For evaluation purposes, a comprehensive set of experimental tests were carried out to the system, comparing the actually delivered amount of tears, flow rate, and prescribed time vs. programmed values, the error was ∼0.2% for commercially available artificial tears. Full article

(This article belongs to the Special Issue Biomicrofluidic Systems for Diagnostics and Clinical Applications)

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17 pages, 5534 KiB

Open AccessFeature PaperArticle

Karst Spring Recharge Areas and Discharge Relationship by Oxygen-18 and Deuterium Isotopes Analyses: A Case Study in Southern Latium Region, Italy

by Silvia Iacurto, Gerardo Grelle, Francesco Maria De Filippi and Giuseppe Sappa

Appl. Sci. 2020, 10(5), 1882; https://doi.org/10.3390/app10051882 - 10 Mar 2020

Cited by 15 | Viewed by 2950

Abstract

Karst aquifer recharge areas are usually difficult to identify because of the complexity of these aquifers’ characteristics. On the other hand, their identification is very important in the aim of protecting the groundwater resources that these aquifers host. Regarding this topic, this paper [...] Read more.

Karst aquifer recharge areas are usually difficult to identify because of the complexity of these aquifers’ characteristics. On the other hand, their identification is very important in the aim of protecting the groundwater resources that these aquifers host. Regarding this topic, this paper presents an approach aimed at identifying karst aquifer recharge areas by the application of oxygen-18 and deuterium isotopes composition of groundwater coupled with hydrological features. Oxygen-18 and deuterium isotope composition of Capodacqua di Spigno Spring, in the South of the Latium Region, has been applied with rainfall and discharge values related to the feeding aquifer of this spring. As δ¹⁸O and δ²H values of groundwater samples are natural tracers of the recharge area’s elevation, we propose a model, based on the distribution of the basin surfaces involved as recharge areas, in relation to elevations. The model estimates, for any discharge value, the percentage of the topographic area involved in the aquifer recharge. The setting up of this simulated distribution is supported by a Weibull cumulative probability function. The results show that the measured discharges increase as larger areas with lower elevations are involved in the recharge process. Full article

(This article belongs to the Special Issue Advances in Geohydrology: Methods and Applications)

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13 pages, 243 KiB

Open AccessArticle

Comparison of Image Fusion Techniques Using Satellite Pour l’Observation de la Terre (SPOT) 6 Satellite Imagery

by Paidamwoyo Mhangara, Willard Mapurisa and Naledzani Mudau

Appl. Sci. 2020, 10(5), 1881; https://doi.org/10.3390/app10051881 - 10 Mar 2020

Cited by 35 | Viewed by 4276

Abstract

Preservation of spectral and spatial information is an important requirement for most quantitative remote sensing applications. In this study, we use image quality metrics to evaluate the performance of several image fusion techniques to assess the spectral and spatial quality of pansharpened images. [...] Read more.

Preservation of spectral and spatial information is an important requirement for most quantitative remote sensing applications. In this study, we use image quality metrics to evaluate the performance of several image fusion techniques to assess the spectral and spatial quality of pansharpened images. We evaluated twelve pansharpening algorithms in this study; the Local Mean and Variance Matching (IMVM) algorithm was the best in terms of spectral consistency and synthesis followed by the ratio component substitution (RCS) algorithm. Whereas the IMVM and RCS image fusion techniques showed better results compared to other pansharpening methods, it is pertinent to highlight that our study also showed the credibility of other pansharpening algorithms in terms of spatial and spectral consistency as shown by the high correlation coefficients achieved in all methods. We noted that the algorithms that ranked higher in terms of spectral consistency and synthesis were outperformed by other competing algorithms in terms of spatial consistency. The study, therefore, concludes that the selection of image fusion techniques is driven by the requirements of remote sensing application and a careful trade-off is necessary to account for the impact of scene radiometry, image sharpness, spatial and spectral consistency, and computational overhead. Full article

(This article belongs to the Special Issue Advances in Image Processing, Analysis and Recognition Technology)

18 pages, 20624 KiB

Open AccessArticle

Numerical-Experimental Investigation into the Tensile Behavior of a Hybrid Metallic–CFRP Stiffened Aeronautical Panel

by Andrea Sellitto, Salvatore Saputo, Angela Russo, Vincenzo Innaro, Aniello Riccio, Francesco Acerra and Salvatore Russo

Appl. Sci. 2020, 10(5), 1880; https://doi.org/10.3390/app10051880 - 10 Mar 2020

Cited by 13 | Viewed by 2694

Abstract

In this work, the tensile behavior of a hybrid metallic–composite stiffened panel is investigated. The analyzed structure consists of an omega-reinforced composite fiber-reinforced plastic (CFRP) panel joined with a Z-reinforced aluminum plate by fasteners. The introduced numerical model, able to simulate geometrical and [...] Read more.

In this work, the tensile behavior of a hybrid metallic–composite stiffened panel is investigated. The analyzed structure consists of an omega-reinforced composite fiber-reinforced plastic (CFRP) panel joined with a Z-reinforced aluminum plate by fasteners. The introduced numerical model, able to simulate geometrical and material non-linearities, has been preliminary validated by means of comparisons with experimental test results, in terms of strain distributions in both composite and metallic sub-components. Subsequently, the inter-laminar damage behavior of the investigated hybrid structure has been studied numerically by assessing the influence of key structural subcomponents on the damage evolution of an artificial initial debonding between the composite skin and stringers. Full article

(This article belongs to the Special Issue Progress of Fiber-Reinforced Composites: Design and Applications)

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14 pages, 3389 KiB

Open AccessArticle

Non-Energy Valorization of Residual Biomasses via HTC: CO₂ Capture onto Activated Hydrochars

by Katia Gallucci, Luca Taglieri, Alessandro Antonio Papa, Francesco Di Lauro, Zaheer Ahmad and Alberto Gallifuoco

Appl. Sci. 2020, 10(5), 1879; https://doi.org/10.3390/app10051879 - 10 Mar 2020

Cited by 13 | Viewed by 3259

Abstract

This study aims to investigate the CO₂ sorption capacity of hydrochar, obtained via hydrothermal carbonization (HTC). Silver fir sawdust was used as a model material. The batch runs went at 200 °C and up to 120 min. The hydrochar was activated with [...] Read more.

This study aims to investigate the CO₂ sorption capacity of hydrochar, obtained via hydrothermal carbonization (HTC). Silver fir sawdust was used as a model material. The batch runs went at 200 °C and up to 120 min. The hydrochar was activated with potassium hydroxide impregnation and subsequent thermal treatment (600 °C, 1 h). CO₂ capture was assayed using a pressure swing adsorption (PSA) process. The morphology and porosity of hydrochar, characterized through Brunauer-Emmett-Teller, Barrett-Joyner-Halenda (BET-BJH) and scanning electron microscopy (SEM) analyses, were reported and the sorbent capacity was compared with traditional sorbents. The hydrochar recovered immediately after the warm-up of the HTC reactor had better performances. The Langmuir equilibrium isotherm fits the experimental data satisfactorily. Selectivity tests performed with a model biogas mixture indicated a possible use of hydrochar for sustainable upgrading of biogas to bio-methane. It is conceivably a new, feasible, and promising option for CO₂ capture with low cost, environmentally friendly materials. Full article

(This article belongs to the Special Issue Thermochemical Conversion Processes for Solid Fuels and Renewable Energies)

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16 pages, 738 KiB

Open AccessReview

Review on Computer Aided Weld Defect Detection from Radiography Images

by Wenhui Hou, Dashan Zhang, Ye Wei, Jie Guo and Xiaolong Zhang

Appl. Sci. 2020, 10(5), 1878; https://doi.org/10.3390/app10051878 - 10 Mar 2020

Cited by 68 | Viewed by 7625

Abstract

The weld defects inspection from radiography films is critical for assuring the serviceability and safety of weld joints. The various limitations of human interpretation made the development of innovative computer-aided techniques for automatic detection from radiography images an interest point of recent studies. [...] Read more.

The weld defects inspection from radiography films is critical for assuring the serviceability and safety of weld joints. The various limitations of human interpretation made the development of innovative computer-aided techniques for automatic detection from radiography images an interest point of recent studies. The studies of automatic defect inspection are synthetically concluded from three aspects: pre-processing, defect segmentation and defect classification. The achievement and limitations of traditional defect classification method based on the feature extraction, selection and classifier are summarized. Then the applications of novel models based on learning(especially deep learning) were introduced. Finally, the achievement of automation methods were discussed and the challenges of current technology are presented for future research for both weld quality management and computer science researchers. Full article

(This article belongs to the Special Issue Intelligent Processing on Image and Optical Information)

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8 pages, 4967 KiB

Open AccessArticle

Self-Expandable Retainer for Endoscopic Visualization in the External Auditory Canal: Proof of Concept in Human Cadavers

by Yehree Kim, Jeon Min Kang, Ho-Young Song, Woo Seok Kang, Jung-Hoon Park and Jong Woo Chung

Appl. Sci. 2020, 10(5), 1877; https://doi.org/10.3390/app10051877 - 10 Mar 2020

Cited by 4 | Viewed by 3380

Abstract

This study was conducted to investigate the efficacy of a self-expandable retainer (SER) for endoscopic visualization of the external auditory canal (EAC). Tympanomeatal flap (TMF) elevation was performed in six cadaveric heads. Two different types of SER were placed. The procedural feasibility was [...] Read more.

This study was conducted to investigate the efficacy of a self-expandable retainer (SER) for endoscopic visualization of the external auditory canal (EAC). Tympanomeatal flap (TMF) elevation was performed in six cadaveric heads. Two different types of SER were placed. The procedural feasibility was assessed by endoscopic images. Technical success rate, procedure time, endoscopy lens cleaning, and presence of mucosal injuries were analyzed. TMF elevation and SER placement were successful in all specimens and there were no procedure-related complications. The mean procedure time with the SERs was significantly shorter than without (p < 0.001). The mean number of times the endoscopy lens was cleaned during the procedure was significantly lower in the SER group (p < 0.001). In the SER group, endoscopy insertion into the EAC was easier without tissue contact with the lens during the TMF elevation compared with the non-SER group. There were no mucosal injuries. SER placement is effective for endoscopic visualization via the expanded and straightened EAC. A fully covered type of SER is preferable. The device can be useful for endoscopic ear surgery, reducing procedure time and reducing the need for endoscopy lens cleaning during the procedure. Full article

(This article belongs to the Special Issue Active Materials for Medical Applications)

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14 pages, 1908 KiB

Open AccessArticle

Monte Carlo Optimization for Sliding Window Size in Dixon Quality Control of Environmental Monitoring Time Series Data

by Zhongya Fan, Huiyun Feng, Jingang Jiang, Changjin Zhao, Ni Jiang, Wencai Wang and Fantang Zeng

Appl. Sci. 2020, 10(5), 1876; https://doi.org/10.3390/app10051876 - 09 Mar 2020

Cited by 6 | Viewed by 2906

Abstract

Outliers are often present in large datasets of water quality monitoring time series data. A method of combining the sliding window technique with Dixon detection criterion for the automatic detection of outliers in time series data is limited by the empirical determination of [...] Read more.

Outliers are often present in large datasets of water quality monitoring time series data. A method of combining the sliding window technique with Dixon detection criterion for the automatic detection of outliers in time series data is limited by the empirical determination of sliding window sizes. The scientific determination of the optimal sliding window size is very meaningful research work. This paper presents a new Monte Carlo Search Method (MCSM) based on random sampling to optimize the size of the sliding window, which fully takes advantage of computers and statistics. The MCSM was applied in a case study to automatic monitoring data of water quality factors in order to test its validity and usefulness. The results of comparing the accuracy and efficiency of the MCSM show that the new method in this paper is scientific and effective. The experimental results show that, at different sample sizes, the average accuracy is between 58.70% and 75.75%, and the average computation time increase is between 17.09% and 45.53%. In the era of big data in environmental monitoring, the proposed new methods can meet the required accuracy of outlier detection and improve the efficiency of calculation. Full article

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17 pages, 3877 KiB

Open AccessArticle

Potential Use of Time-Lapse Surface Seismics for Monitoring Thawing of the Terrestrial Arctic

by Helene Meling Stemland, Tor Arne Johansen and Bent Ole Ruud

Appl. Sci. 2020, 10(5), 1875; https://doi.org/10.3390/app10051875 - 09 Mar 2020

Cited by 2 | Viewed by 2443

Abstract

The terrestrial Arctic is warming rapidly, causing changes in the degree of freezing of the upper sediments, which the mechanical properties of unconsolidated sediments strongly depend upon. This study investigates the potential of using time-lapse surface seismics to monitor thawing of currently (partly) [...] Read more.

The terrestrial Arctic is warming rapidly, causing changes in the degree of freezing of the upper sediments, which the mechanical properties of unconsolidated sediments strongly depend upon. This study investigates the potential of using time-lapse surface seismics to monitor thawing of currently (partly) frozen ground utilizing synthetic and real seismic data. First, we construct a simple geological model having an initial temperature of −5 °C, and infer constant surface temperatures of −5 °C, +1 °C, +5 °C, and +10 °C for four years to this model. The geological models inferred by the various thermal regimes are converted to seismic models using rock physics modeling and subsequently seismic modeling based on wavenumber integration. Real seismic data reflecting altered surface temperatures were acquired by repeated experiments in the Norwegian Arctic during early autumn to mid-winter. Comparison of the surface wave characteristics of both synthetic and real seismic data reveals time-lapse effects that are related to thawing caused by varying surface temperatures. In particular, the surface wave dispersion is sensitive to the degree of freezing in unconsolidated sediments. This demonstrates the potential of using surface seismics for Arctic climate monitoring, but inversion of dispersion curves and knowledge of the local near-surface geology is important for such studies to be conclusive. Full article

(This article belongs to the Special Issue Surface Waves for Monitoring of Materials at Different Scales)

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19 pages, 6250 KiB

Open AccessArticle

A Machine-Learning Model Based on Morphogeometric Parameters for RETICS Disease Classification and GUI Development

by José M. Bolarín, F. Cavas, J.S. Velázquez and J.L. Alió

Appl. Sci. 2020, 10(5), 1874; https://doi.org/10.3390/app10051874 - 09 Mar 2020

Cited by 10 | Viewed by 2874

Abstract

This work pursues two objectives: defining a new concept of risk probability associated with suffering early-stage keratoconus, classifying disease severity according to the RETICS (Thematic Network for Co-Operative Research in Health) scale. It recruited 169 individuals, 62 healthy and 107 keratoconus diseased, grouped [...] Read more.

This work pursues two objectives: defining a new concept of risk probability associated with suffering early-stage keratoconus, classifying disease severity according to the RETICS (Thematic Network for Co-Operative Research in Health) scale. It recruited 169 individuals, 62 healthy and 107 keratoconus diseased, grouped according to the RETICS classification: 44 grade I; 18 grade II; 15 grade III; 15 grade IV; 15 grade V. Different demographic, optical, pachymetric and eometrical parameters were measured. The collected data were used for training two machine-learning models: a multivariate logistic regression model for early keratoconus detection and an ordinal logistic regression model for RETICS grade assessments. The early keratoconus detection model showed very good sensitivity, specificity and area under ROC curve, with around 95% for training and 85% for validation. The variables that made the most significant contributions were gender, coma-like, central thickness, high-order aberrations and temporal thickness. The RETICS grade assessment also showed high-performance figures, albeit lower, with a global accuracy of 0.698 and a 95% confidence interval of 0.623–0.766. The most significant variables were CDVA, central thickness and temporal thickness. The developed web application allows the fast, objective and quantitative assessment of keratoconus in early diagnosis and RETICS grading terms. Full article

(This article belongs to the Special Issue Real-Time Diagnosis Algorithms in Biomedical Applications and Decision Support Tools)

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17 pages, 5135 KiB

Open AccessArticle

Performance-Based Reliability Estimates for Highway Bridges Considering Previous Inspection Data

by Won-Ho Heo

Appl. Sci. 2020, 10(5), 1873; https://doi.org/10.3390/app10051873 - 09 Mar 2020

Cited by 4 | Viewed by 1927

Abstract

This paper proposes a performance-based resistance deterioration model that reflects the site environment and inspection data for highway bridges. Traffic characteristics and corrosive environment are considered as the site environment. The corrosive environments and traffic characteristics are classified into three categories, namely mild, [...] Read more.

This paper proposes a performance-based resistance deterioration model that reflects the site environment and inspection data for highway bridges. Traffic characteristics and corrosive environment are considered as the site environment. The corrosive environments and traffic characteristics are classified into three categories, namely mild, normal, and severe for the former and light, normal, and heavy for the latter. The deterioration of the resistance capacity due to corrosive environments is evaluated considering both the service period and the concrete crack widths in the pre-stressed concrete (PSC) girder and the reinforced concrete (RC) slab. The deterioration model of the resistance capacity is calibrated by combining the performance degradation model. The performance degradation model is also calibrated using previous bridge inspection results from the standard performance degradation model, which has been developed based on the large amount of data available on many pre-stressed concrete-I (PSC-I) type girder bridges. The developed performance-based resistance deterioration model is used to evaluate the reliability of a bridge in the future. The results show that the performance inspection outcomes, either based on the current status or lifetime inspection history, are critical in estimating the future degradation of the reliability level, inherent to the bridge. Full article

(This article belongs to the Special Issue Short-Term Forecasting in Civil Engineering with Multidisciplinary Approaches: Combined Numerical, Experimental and Statistical Methods)

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14 pages, 1628 KiB

Open AccessArticle

A General User-Friendly Tool for Kinetic Calculations of Multi-Step Reactions within the Virtual Multifrequency Spectrometer Project

by Surajit Nandi, Bernardo Ballotta, Sergio Rampino and Vincenzo Barone

Appl. Sci. 2020, 10(5), 1872; https://doi.org/10.3390/app10051872 - 09 Mar 2020

Cited by 7 | Viewed by 2978

Abstract

We discuss the implementation of a computer program for accurate calculation of the kinetics of chemical reactions integrated in the user-friendly, multi-purpose Virtual Multifrequency Spectrometer tool. The program is based on the ab initio modeling of the involved molecular species, the adoption of [...] Read more.

We discuss the implementation of a computer program for accurate calculation of the kinetics of chemical reactions integrated in the user-friendly, multi-purpose Virtual Multifrequency Spectrometer tool. The program is based on the ab initio modeling of the involved molecular species, the adoption of transition-state theory for each elementary step of the reaction, and the use of a master-equation approach accounting for the complete reaction scheme. Some features of the software are illustrated through examples including the interconversion reaction of hydroxyacetone and 2-hydroxypropanal and the production of HCN and HNC from vinyl cyanide. Full article

(This article belongs to the Special Issue The Application of Quantum Mechanics in Reactivity of Molecules)

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21 pages, 6109 KiB

Open AccessArticle

Prediction of Pile Axial Bearing Capacity Using Artificial Neural Network and Random Forest

by Tuan Anh Pham, Hai-Bang Ly, Van Quan Tran, Loi Van Giap, Huong-Lan Thi Vu and Hong-Anh Thi Duong

Appl. Sci. 2020, 10(5), 1871; https://doi.org/10.3390/app10051871 - 09 Mar 2020

Cited by 56 | Viewed by 7227

Abstract

Axial bearing capacity of piles is the most important parameter in pile foundation design. In this paper, artificial neural network (ANN) and random forest (RF) algorithms were utilized to predict the ultimate axial bearing capacity of driven piles. An unprecedented database containing 2314 [...] Read more.

Axial bearing capacity of piles is the most important parameter in pile foundation design. In this paper, artificial neural network (ANN) and random forest (RF) algorithms were utilized to predict the ultimate axial bearing capacity of driven piles. An unprecedented database containing 2314 driven pile static load test reports were gathered, including the pile diameter, length of pile segments, natural ground elevation, pile top elevation, guide pile segment stop driving elevation, pile tip elevation, average standard penetration test (SPT) value along the embedded length of pile, and average SPT blow counts at the tip of pile as input variables, whereas the ultimate load on pile top was considered as output variable. The dataset was divided into the training (70%) and testing (30%) parts for the construction and validation phases, respectively. Various error criteria, namely mean absolute error (MAE), root mean squared error (RMSE), and the coefficient of determination (R²) were used to evaluate the performance of RF and ANN algorithms. In addition, the predicted results of pile load tests were compared with five empirical equations derived from the literature and with classical multi-variable regression. The results showed that RF outperformed ANN and other methods. Sensitivity analysis was conducted to reveal that the average SPT value and pile tip elevation were the most important factors in predicting the axial bearing capacity of piles. Full article

(This article belongs to the Special Issue Soft Computing Techniques in Structural Engineering and Materials)

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18 pages, 5899 KiB

Open AccessArticle

Very Large-Eddy Simulations of the Flow Past an Oscillating Cylinder at a Subcritical Reynolds Number

by Zhongying Xiong and Xiaomin Liu

Appl. Sci. 2020, 10(5), 1870; https://doi.org/10.3390/app10051870 - 09 Mar 2020

Cited by 3 | Viewed by 2604

Abstract

This work focuses on flow past a circular cylinder at a subcritical Reynolds number. Although this classical study has been a concern for many years, it is still a challenging task due to the complexity of flow characteristics. In this paper, a high-efficiency [...] Read more.

This work focuses on flow past a circular cylinder at a subcritical Reynolds number. Although this classical study has been a concern for many years, it is still a challenging task due to the complexity of flow characteristics. In this paper, a high-efficiency very large-eddy simulation method is adopted and verified in order to handle the oscillating boundary. A series of numerical simulations are conducted to investigate the transient flow around the oscillating cylinder. The results show that the vortex shedding mode varies with an increase in the excitation amplitude and the excitation frequency. Vortex shedding is a lasting process under the condition of a low excitation amplitude that leads to irregular fluctuations of the lift and drag coefficients. For a vortex shedding mode that exhibits a strong vortex pair and a weak vortex pair or a weak single vortex, the temporal evolution of the lift coefficient of the oscillating cylinder shows irregular ”jumping” at a specific time per cycle corresponding to the shedding of the strong vortex pair. The vortex shedding mode and the frequency and time of the vortex shedding co-determine the temporal evolutions of the lift and drag coefficient. Full article

(This article belongs to the Section Applied Physics General)

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