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Appl. Sci., Volume 12, Issue 5 (March-1 2022) – 495 articles

Cover Story (view full-size image): Hazelnut is a relevant agro-food supply chain worldwide, whose cultivation is threatened by several biological adversities. Among them, bacterial blight, caused by Xanthomonas arboricola pv. corylina (Xac), is one of the most dangerous. In this work, the lignocellulosic biomasses obtained from hazelnut pruning and shelling residues were used as a renewable source for cellulose nanocrystal and lignin nanoparticle synthesis. Both nanomaterials were deeply characterized for the capability of inhibiting the in vitro growth of Xac and reducing the severity of the disease on hazelnut plants, showing at the same time a full biological compatibility. View this paper
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Article
Acoustic Emission Based Fault Detection of Substation Power Transformer
Appl. Sci. 2022, 12(5), 2759; https://doi.org/10.3390/app12052759 - 07 Mar 2022
Viewed by 524
Abstract
Fault detection of Substation Power Transformer by Non-contact measurement is important for the safety of machines, instruments, and human beings. To make non-contact measurement as convenient as possible, it is desirable that efficient algorithms based on AE (acoustic emission) discrimination are developed. This [...] Read more.
Fault detection of Substation Power Transformer by Non-contact measurement is important for the safety of machines, instruments, and human beings. To make non-contact measurement as convenient as possible, it is desirable that efficient algorithms based on AE (acoustic emission) discrimination are developed. This paper presents a system for quick and effective fault detection of substation power transformer, based on AE signals collected by non-contact single microphones. In the experiment, collected data were preprocessed in multiple ways and three machine learning algorithms were designed based on classifiers (Convolutional Neural Network (CNN), support vector machine (SVM), and k-nearest neighbors (KNN) algorithm) trained and tested by a tenfold cross-validation technique. After comparison among the designed classifiers, the results show the two-dimensional principal component analysis (2DPCA) preprocess combined with SVM achieved the best comprehensive effectiveness. Full article
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Article
A Rule-Based Grapheme-to-Phoneme Conversion System
Appl. Sci. 2022, 12(5), 2758; https://doi.org/10.3390/app12052758 - 07 Mar 2022
Viewed by 455
Abstract
This article presents a rule-based grapheme-to-phoneme conversion method and algorithm for Polish. It should be noted that the fundamental grapheme-to-phoneme conversion rules have been developed by Maria Steffen-Batóg and presented in her set of monographs dedicated to the automatic grapheme-to-phoneme conversion of texts [...] Read more.
This article presents a rule-based grapheme-to-phoneme conversion method and algorithm for Polish. It should be noted that the fundamental grapheme-to-phoneme conversion rules have been developed by Maria Steffen-Batóg and presented in her set of monographs dedicated to the automatic grapheme-to-phoneme conversion of texts in Polish. The author used previously developed rules and independently developed the grapheme-to-phoneme conversion algorithm.The algorithm has been implemented as a software application called TransFon, which allows the user to convert any text in Polish orthography to corresponding strings of phonemes, in phonemic transcription. Using TransFon, a phonemic Polish language corpus was created out of an orthographic corpus. The phonemic language corpusallows statistical analysis of the Polish language, as well as the development of phoneme- and word-based language models for automatic speech recognition using statistical methods. The developed phonemic language corpus opens up further opportunities for research to improve automatic speech recognition in Polish. The development of statistical methods for speech recognition and language modelling requires access to large language corpora, including phonemic corpora. The method presented here enables the creation of such corpora. Full article
(This article belongs to the Special Issue Automatic Speech Recognition)
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Article
Recursive Optimal Finite Impulse Response Filter and Its Application to Adaptive Estimation
Appl. Sci. 2022, 12(5), 2757; https://doi.org/10.3390/app12052757 - 07 Mar 2022
Cited by 2 | Viewed by 351
Abstract
In this paper, the recursive form of an optimal finite impulse response filter is proposed for discrete time-varying state-space models. The recursive form of the finite impulse response filter is derived by employing finite horizon Kalman filtering with optimally estimated initial conditions. The [...] Read more.
In this paper, the recursive form of an optimal finite impulse response filter is proposed for discrete time-varying state-space models. The recursive form of the finite impulse response filter is derived by employing finite horizon Kalman filtering with optimally estimated initial conditions. The horizon initial state and its error covariance on the horizon are optimally estimated by using recent finite measurements, in the sense of maximum likelihood estimation, then initiating the finite horizon Kalman filter. The optimality and unbiasedness of the proposed filter are proved by comparison with the conventional optimal finite impulse response filter in batch form. Moreover, an adaptive FIR filter is also proposed by applying the adaptive estimation scheme to the proposed recursive optimal FIR filter as its application. To evaluate the performance of the proposed algorithms, a computer simulation is performed to compare the conventional Kalman filter and adaptive Kalman filters for the gas turbine aircraft engine model. Full article
(This article belongs to the Special Issue Statistical Signal Processing: Theory, Methods and Applications)
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Article
Prestress Force Monitoring and Quantification of Precast Segmental Beams through Neutral Axis Location Identification
Appl. Sci. 2022, 12(5), 2756; https://doi.org/10.3390/app12052756 - 07 Mar 2022
Cited by 1 | Viewed by 390
Abstract
This paper proposes using neutral axis locations to monitor and quantify the prestress force in post-tensioned precast segmental beams. Strain measurements are used to obtain the neutral axis locations of specific cross-sections of the precast prestressed segmental beams, based on the plane–remains–plane and [...] Read more.
This paper proposes using neutral axis locations to monitor and quantify the prestress force in post-tensioned precast segmental beams. Strain measurements are used to obtain the neutral axis locations of specific cross-sections of the precast prestressed segmental beams, based on the plane–remains–plane and linear strain distribution assumption. A theoretical calculation method based on the static equilibrium of a specific cross-section is developed to calculate the prestress force in segmental beams based on the neutral axis location. To verify the accuracy of the proposed method, a post-tensioned prestressed segmental beam is built and tested in the laboratory. A corresponding high-fidelity finite element model is also developed based on the beam design and material properties. Experimental studies and numerical simulations are conducted to verify the feasibility and accuracy of the proposed method in quantifying the prestress force in precast segmental beams. Both experimental and numerical results demonstrate that the proposed method can reliably estimate the prestress force, which can be used to monitor the prestress force loss in post-tensioned structures. Full article
(This article belongs to the Special Issue Inspection and Monitoring Techniques for Bridges and Civil Structures)
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Article
Automation of Property Acquisition of Single Track Depositions Manufactured through Direct Energy Deposition
Appl. Sci. 2022, 12(5), 2755; https://doi.org/10.3390/app12052755 - 07 Mar 2022
Viewed by 471
Abstract
Metallic additive manufacturing processes have been significantly developed since their inception with modern systems capable of manufacturing components for structural applications. However, successful processing through these methods requires extensive experimentation before optimised parameters can be found. In laser-based processes, such as direct energy [...] Read more.
Metallic additive manufacturing processes have been significantly developed since their inception with modern systems capable of manufacturing components for structural applications. However, successful processing through these methods requires extensive experimentation before optimised parameters can be found. In laser-based processes, such as direct energy deposition, it is common for single track beads to be deposited and subjected to analysis, yielding information on how the input parameters influence characteristics such as the output’s adhesion to the substrate. These characteristics are often determined using specialised software, from images obtained by cross-section cutting the line beads. The proposed approach was based on a Python algorithm, using the scikit-image library and optical microscopy imaging from produced 18Ni300 Maraging steel on H13 tool steel, and it computes the relevant properties of DED-produced line beads, such as the track height, width, penetration, wettability angles, cross-section areas above and below the substrate and dilution proportion. 18Ni300 Maraging steel depositions were optimised with a laser power of 1550 W, feeding rate of 12 gmin1, scanning speed of 12 mm s1, shielding gas flow rate of 25 Lmin1 and carrier gas flow rate of 4 Lmin1 for a laser spot diameter of 2.1mm. Out of the cross-sectioned beads, their respective height, width and penetration were calculated with 2.71%, 4.01% and 9.35% errors; the dilution proportion was computed with 14.15% error, the area above the substrate with 5.27% error and the area below the substrate with 17.93% error. The average computational time for the processing of one image was 12.7s. The developed approach was purely segmentational and could potentially benefit from machine-learning implementations. Full article
(This article belongs to the Topic Additive Manufacturing)
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Article
A Cloud Microservices Architecture for Data Integrity Verifiability Based on Blockchain
Appl. Sci. 2022, 12(5), 2754; https://doi.org/10.3390/app12052754 - 07 Mar 2022
Viewed by 728
Abstract
The current digital age, mainly characterized by an economy based upon information technology, demands a data integrity service, even more so because organizations and companies are migrating their services over the cloud. This is not a simple task; it is cumbersome since traditional [...] Read more.
The current digital age, mainly characterized by an economy based upon information technology, demands a data integrity service, even more so because organizations and companies are migrating their services over the cloud. This is not a simple task; it is cumbersome since traditional schemes in databases could be subject to modifications. However, it can be solved using blockchain technology. This paper provides a data integrity verifiability architecture for cloud systems based on blockchain. The architecture provides a mechanism to store events (as logs) within a blockchain platform from any cloud system. Users can then consult data integrity through a microservice, acting as an intermediate server that carries out a set of verification steps within the blockchain, which confirms the integrity of a previously stored log. Our architecture takes advantage of the blockchain strength concerning integrity, providing a traceability track of the stored logs. A prototype system and a case study were implemented based on the proposed architecture. Our experimental results show that the proposed decentralized architecture can be adapted to cloud existing systems that were born without blockchain technology and require a modular and scalable audit characteristic. Full article
(This article belongs to the Special Issue Cybersecurity in Cloud Computing)
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Article
Typology of Pure Deodar Forests Driven by Vegetation–Environment Relations in Manoor Valley, Northwestern Himalaya
Appl. Sci. 2022, 12(5), 2753; https://doi.org/10.3390/app12052753 - 07 Mar 2022
Viewed by 500
Abstract
The current research was carried out to characterize the phytosociology of the forests of one of Pakistan’s most valuable tree species (Deodar) across its native range. In this context, our main hypothesis was that, along the altitudinal gradient, we would find different plant [...] Read more.
The current research was carried out to characterize the phytosociology of the forests of one of Pakistan’s most valuable tree species (Deodar) across its native range. In this context, our main hypothesis was that, along the altitudinal gradient, we would find different plant communities that would be driven by different environmental variables (climatic, edaphic, and physiographic). Therefore, to assess the vegetation structure of the pure Deodar forests of the unexplored Manoor Valley (Northwestern Himalaya), Pakistan, frequent field visits were carried out during different seasons of 2015–2018. Ecological methods: Line transects sampling (23 stands) and phytosociological attributes were evaluated in relation to geographical and environmental variables. Various statistical software applications (i.e., PCORD, RStudio 4.0, and R 3.6.1) were used to examine all of the gathered data of plant species and environmental variables. A total of three different plant communities (Cedrus–Isodon–Cynodon, Cedrus–Cynodon–Dryopteris, and Sambucus–Cedrus–Desmodium) were identified by grouping 162 species and 23 stands in pure Deodar forests under the influence of geographic, slope, edaphic, and climatic variables, ranging from 1580.8 to 2373.8 m. The altitude (1936–2373 m), slope angle (25–85°), sandy (29–48%) and loamy soil texture, wind speed (1.45 ms−1), and temperature (25.8 °C) all had a strong influence on the Sambucus–Cedrus–Desmodium community. In contrast with this, the Cedrus–Cynodon–Dryopteris community showed a positively significant relationship with the northeastern slope, silty (32–58%) and sandy (15.8–55%) loamy soil texture, and barometric pressure (814.3 pa). Nonetheless, the Cedrus–Isodon–Cynodon community revealed a significant positive association with the northeastern to southwestern slope, pH (6.3), wet bulb (19.7), and dew point (17.7). We found significant differences (p < 0.001) among the three communities found in the pure Deodar forests in the four diversity indexes. The Sambucus–Cedrus–Desmodium community has the maximum number of plants (129 species), Shannon’s diversity (H’ = 3.7), and Simpson’s dominance (0.98) values among the recorded communities. The Pielou’s evenness index value was led by the Cedrus–Isodon–Cynodon community (0.97). Beta diversity showed a dissimilarity lower than 50% among the three communities. Simple term effects in the canonical correspondence analysis model revealed significant (p < 0.05) differences in altitude, slope angle, slope (southeastern), and wind speed variables. The present investigation sheds light on vegetation pattern and species contribution as a function of environmental gradients and provides a baseline for future studies. Full article
(This article belongs to the Special Issue Plant Biodiversity Patterns and Their Driving Forces)
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Review
Damage Characteristics of Thermally Deteriorated Carbonate Rocks: A Review
Appl. Sci. 2022, 12(5), 2752; https://doi.org/10.3390/app12052752 - 07 Mar 2022
Viewed by 399
Abstract
This review paper summarizes the recent and past experimental findings to evaluate the damage characteristics of carbonate rocks subjected to thermal treatment (20–1500 °C). The outcomes of published studies show that the degree of thermal damage in the post-heated carbonate rocks is attributed [...] Read more.
This review paper summarizes the recent and past experimental findings to evaluate the damage characteristics of carbonate rocks subjected to thermal treatment (20–1500 °C). The outcomes of published studies show that the degree of thermal damage in the post-heated carbonate rocks is attributed to their rock fabric, microstructural patterns, mineral composition, texture, grain cementations, particle orientations, and grain contact surface area. The expressive variations in the engineering properties of these rocks subjected to the temperature (>500 °C) are the results of chemical processes (hydration, dehydration, deionization, melting, mineral phase transformation, etc.), intercrystalline and intergranular thermal cracking, the separation between cemented particles, removal of bonding agents, and internal defects. Thermally deteriorated carbonate rocks experience a significant reduction in their fracture toughness, static–dynamic strength, static–dynamic elastic moduli, wave velocities, and thermal transport properties, whereas their porous network properties appreciate with the temperature. The stress–strain curves illustrate that post-heated carbonate rocks show brittleness below a temperature of 400 °C, brittle–ductile transformation at a temperature range of 400 to 500 °C, and ductile behavior beyond this critical temperature. The aspects discussed in this review comprehensively describe the damage mechanism of thermally exploited carbonate rocks that can be used as a reference in rock mass classification, sub-surface investigation, and geotechnical site characterization. Full article
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Article
Studies Regarding the Antibacterial Effect of Plant Extracts Obtained from Epilobium parviflorum Schreb
Appl. Sci. 2022, 12(5), 2751; https://doi.org/10.3390/app12052751 - 07 Mar 2022
Viewed by 461
Abstract
The present study was carried out to develop an experimental endodontic irrigant solution based on plant extracts obtained from Epilobium parviflorum Schreb. that largely replenish the properties of the usual antiseptics used in dentistry. Background: This study investigated the phytochemical contents of plant [...] Read more.
The present study was carried out to develop an experimental endodontic irrigant solution based on plant extracts obtained from Epilobium parviflorum Schreb. that largely replenish the properties of the usual antiseptics used in dentistry. Background: This study investigated the phytochemical contents of plant extracts obtained from Epilobium parviflorum Schreb. and their potential antibacterial activity. Methods: Identification and quantification of biologically active compounds were made by UV field photo spectrometry, adapting the Folin-Ciocalteu test method. Antibacterial activity was tested on pathological bacterial cultures collected from tooth with endodontic infections using a modified Kirby-Bauer diffuse metric method. Results: Polyphenols and flavonoids were present in all plant extracts; the hydroalcoholic extract had the highest amount of polyphenols—17.44 pyrogallol equivalent (Eq Pir)/mL and flavonoids—3.13 quercetin equivalent (Eq Qr)/mL. Plant extracts had antibacterial activity among the tested bacterial species with the following inhibition diameter: White Staphylococcus (16.5 mm), Streptococcus mitis (25 mm), Streptococcus sanguis (27 mm), Enterococcus faecalis (10 mm). Conclusions: All plant extracts contain polyphenols and flavonoids; the antibacterial activity was in direct ratio with the amount of the bioactive compounds. Full article
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Article
Dynamic Virtual Energy Storage System Operation Strategy for Smart Energy Communities
Appl. Sci. 2022, 12(5), 2750; https://doi.org/10.3390/app12052750 - 07 Mar 2022
Viewed by 351
Abstract
The concept of a virtual energy storage system (VESS) is based on the sharing of a large energy storage system by multiple units; however, the capacity allocation for each unit limits the operation performance of the VESS. This study proposes an operation strategy [...] Read more.
The concept of a virtual energy storage system (VESS) is based on the sharing of a large energy storage system by multiple units; however, the capacity allocation for each unit limits the operation performance of the VESS. This study proposes an operation strategy of a dynamic VESS for smart energy communities. The proposed VESS operation strategy considers the usage-limited constraint rather than the capacity allocation constraint and it guarantees the usage of VESS resources of each participant for an operation period. Therefore, the degrees of freedom for VESS operation can be increased at each operation time. The dynamic VESS operation problem is formulated as a mixed-integer linear problem that could be solved optimally by applying gradient methods and dual decomposition. The dataset of a VESS in Korea is used for simulation. The simulation results demonstrate that, when the proposed operation strategy is used, the cost efficiency achieved is more than twice that achieved when the existing VESS operation strategy is used. Furthermore, the proposed strategy accurately reflects the characteristics of the participants; thus, more units can participate in the VESS operation service. The proposed VESS operation can improve the system performance of the utility grid and increase the net benefit of the participants. Full article
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Article
Application of Tucker Decomposition in Temperature Distribution Reconstruction
Appl. Sci. 2022, 12(5), 2749; https://doi.org/10.3390/app12052749 - 07 Mar 2022
Viewed by 334
Abstract
Constrained by cost, measuring conditions and excessive calculation, it is difficult to reconstruct a 3D real-time temperature field. For the purpose of solving these problems, a three-dimensional temperature distribution reconstruction algorithm based on Tucker decomposition algorithm is proposed. The Tucker decomposition algorithm is [...] Read more.
Constrained by cost, measuring conditions and excessive calculation, it is difficult to reconstruct a 3D real-time temperature field. For the purpose of solving these problems, a three-dimensional temperature distribution reconstruction algorithm based on Tucker decomposition algorithm is proposed. The Tucker decomposition algorithm is used to reduce the dimension of the measured data, and the processed core tensor is used for the temperature field reconstruction of sparse data. Theoretical analysis and simulations show that the proposed method is feasible; the overall optimization is realized by selecting the appropriate core tensor dimensions; and the reconstruction error is less than 3%. Results indicate that the proposed method can yield a reliable reconstruction solution and can be applied to real-time applications. Full article
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Article
Analysis of Adhesive Joints in a GFRP Bridge Deck under Bidirectional Bending Due to Traffic Wheel Loads
Appl. Sci. 2022, 12(5), 2748; https://doi.org/10.3390/app12052748 - 07 Mar 2022
Viewed by 364
Abstract
Glass-fiber-reinforced polymer (GFRP) decks have been widely used in the rehabilitation and construction of bridges as a replacement for conventional deck materials, such as steel, concrete, and wood. In this study, an analysis method for checking the local safety of joints in adhesively [...] Read more.
Glass-fiber-reinforced polymer (GFRP) decks have been widely used in the rehabilitation and construction of bridges as a replacement for conventional deck materials, such as steel, concrete, and wood. In this study, an analysis method for checking the local safety of joints in adhesively connected GFRP decks under bidirectional bending due to traffic wheel loads is newly presented. This method can be applied for designing and evaluating the joints of other FRP decks. The orthotropic material properties of the deck were approximately assumed according to the test results and previous research. Three-dimensional solid elements were used to simulate the local behavior of the adhesive and deck substrates at the joints. Global deflections of the deck and local deformations of the adhesive were evaluated for serviceability. The local stresses in the adhesive and deck substrate are evaluated at the joint to check for local failure modes of the joint under serviceability and ultimate limit states. The analysis results indicate that local failures of the adhesive and deck substrate at the joint occurred. Recommendations for avoiding these local failures and performing more precise analysis are suggested. Full article
(This article belongs to the Special Issue Selected Papers from ICAET 2022)
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Review
Unveiling the Bioactive Potential of Fresh Fruit and Vegetable Waste in Human Health from a Consumer Perspective
Appl. Sci. 2022, 12(5), 2747; https://doi.org/10.3390/app12052747 - 07 Mar 2022
Viewed by 513
Abstract
Food supply disruption and shortage verified during the current pandemic events are a scenario that many anticipate for the near future. The impact of climate changes on food production, the continuous decrease in arable land, and the exponential growth of the human population [...] Read more.
Food supply disruption and shortage verified during the current pandemic events are a scenario that many anticipate for the near future. The impact of climate changes on food production, the continuous decrease in arable land, and the exponential growth of the human population are important drivers for this problem. In this context, adding value to food waste is an obvious strategy to mitigate food shortages, but there is a long way to go in this field. Globally, it is estimated that one-third of all food produced is lost. This is certainly due to many different factors, but the lack of awareness of the consumer about the nutritional value of certain foods parts, namely peels and seeds, is certainly among them. In this review, we will unveil the nutritional and bioactive value of the waste discarded from the most important fresh fruit and vegetables consumed worldwide as a strategy to decrease food waste. This will span the characterization of the bioactive composition of selected waste from fruits and vegetables, particularly their seeds and peels, and their possible uses, whether in our diet or recycled to other ends. Full article
(This article belongs to the Special Issue Future Foods: Health and Sustainability)
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Article
An Analysis of Agricultural Systems Modelling Approaches and Examples to Support Future Policy Development under Disruptive Changes in New Zealand
Appl. Sci. 2022, 12(5), 2746; https://doi.org/10.3390/app12052746 - 07 Mar 2022
Viewed by 561
Abstract
Agricultural systems have entered a period of significant disruption due to impacts from change drivers, increasingly stringent environmental regulations and the need to reduce unwanted discharges, and emerging technologies and biotechnologies. Governments and industries are developing strategies to respond to the risks and [...] Read more.
Agricultural systems have entered a period of significant disruption due to impacts from change drivers, increasingly stringent environmental regulations and the need to reduce unwanted discharges, and emerging technologies and biotechnologies. Governments and industries are developing strategies to respond to the risks and opportunities associated with these disruptors. Modelling is a useful tool for system conceptualisation, understanding, and scenario testing. Today, New Zealand and other nations need integrated modelling tools at the national scale to help industries and stakeholders plan for future disruptive changes. In this paper, following a scoping review process, we analyse modelling approaches and available agricultural systems’ model examples per thematic applications at the regional to national scale to define the best options for the national policy development. Each modelling approach has specificities, such as stakeholder engagement capacity, complex systems reproduction, predictive or prospective scenario testing, and users should consider coupling approaches for greater added value. The efficiency of spatial decision support tools working with a system dynamics approach can help holistically in stakeholders’ participation and understanding, and for improving land planning and policy. This model combination appears to be the most appropriate for the New Zealand national context. Full article
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Article
The Use of Multi-Geophysical Methods to Determine the Geothermal Potential: A Case Study from the Humenné Unit (The Eastern Slovak Basin)
Appl. Sci. 2022, 12(5), 2745; https://doi.org/10.3390/app12052745 - 07 Mar 2022
Viewed by 359
Abstract
The exploration of the geothermal potential of a geological unit has multiple aspects. The most important elements are the geological structure, the hydrogeological conditions, and heat flow. The analysis of the above-mentioned elements attempts to help maximize the use of a geothermal aquifer’s [...] Read more.
The exploration of the geothermal potential of a geological unit has multiple aspects. The most important elements are the geological structure, the hydrogeological conditions, and heat flow. The analysis of the above-mentioned elements attempts to help maximize the use of a geothermal aquifer’s potential. When choosing the most appropriate geophysical method, it is important to consider various factors, such as basic structural parameters as well as the total cost of exploration. This is especially true for low-thermal areas. Comparison of multi-geophysical exploration methods used in the study of the carbonate aquifer of the Humenné Unit identified the advantages and weaknesses of each method. The Humenné Unit is the north basement unit of the Eastern Slovak Basin (with a heat flow value ranging from 100 to 125 mW·m−2), which is part of the Pannonian Basin (with a high heat flow ranging from 50 to 130 mW·m−2). The calculation of the geothermal potential was based on the results of several methods. Some important geophysical survey methods resulted in: (a) deep seismic cross-sections which clarified the position and overall internal structure of the aquifer (b) gravimetric measurements in the form of a map of the Complete Bouguer Anomalies (calculated for density 2.67 g·cm−3) which confirmed the presence of structural elevations and depressions. These elevations and depressions intensified the water yield, heat flow and raised the overall temperature (c) the use of geoelectric resistivity profiling, which is a fast and cheap method, but is limited by depth. The similar resistivities ρ: 80–360 Ωm of carbonates and andesites was a serious problem. The specific heat-energy potential has a wide range of 0.337–19.533 GJ/m2. The highest values above 15 GJ/m2 are reached in areas where the temperature on the surface of the Triassic carbonates exceeds 90 °C. Full article
(This article belongs to the Special Issue Seismic Exploration and Geothermal Energy)
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Review
Joining of Fibre-Reinforced Thermoplastic Polymer Composites by Friction Stir Welding—A Review
Appl. Sci. 2022, 12(5), 2744; https://doi.org/10.3390/app12052744 - 07 Mar 2022
Cited by 1 | Viewed by 578
Abstract
The objective of the current work is to show the potential of the friction stir welding (FSW) and its variants to join fibre-reinforced thermoplastic polymer (FRTP) composites. To accomplish that, the FSW technique and two other important variants, the friction stir spot welding [...] Read more.
The objective of the current work is to show the potential of the friction stir welding (FSW) and its variants to join fibre-reinforced thermoplastic polymer (FRTP) composites. To accomplish that, the FSW technique and two other important variants, the friction stir spot welding (FSSW) and the refill friction stir spot welding (RFSSW), are presented and explained in a brief but complete way. Since the joining of FRTP composites by FSSW has not yet been demonstrated, the literature review will be focused on the FSW and RFSSW techniques. In each review, the welding conditions and parameters studied by the different authors are presented and discussed, as well as the most important conclusions taken from them. About FSW, it can be concluded that the rotational speed and the welding speed have great influence on heat generation, mixture quality, and fibre fragmentation degree, while the tilt angle only has residual influence on the process. The reduction of internal and external defects can be achieved by adjusting axial force and plunge depth. Threaded or grooved conical pins achieved better results than other geometries. Stationary shoulder tools showed better performance than conventional tools. Regarding the RFSSW, it has not yet been possible to deepen conclusions about most of the welding parameters, but its feasibility is demonstrated. Full article
(This article belongs to the Special Issue Fracture Mechanics and Structural Integrity of Composite Materials)
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Review
Seismic Behavior of Micropiles and Micropiled Structures Used for Increasing Resilience: A Literature Review
Appl. Sci. 2022, 12(5), 2743; https://doi.org/10.3390/app12052743 - 07 Mar 2022
Viewed by 549
Abstract
The aim of this paper is to present the relevant information and development available in the scientific literature regarding the seismic behavior of micropiles (MPs) and micropiled structures (MPed). The seismic behavior of MPs is not very well studied, but MPs are used [...] Read more.
The aim of this paper is to present the relevant information and development available in the scientific literature regarding the seismic behavior of micropiles (MPs) and micropiled structures (MPed). The seismic behavior of MPs is not very well studied, but MPs are used in retrofitting of old buildings and for new resilient buildings, and in terms of seismic behavior they have a high potential. Additionally, their association with seismic dampers for improving the seismic behavior of buildings is not yet fully studied and it represents a major topic of interest for both new structures and historical monuments. After the introductory part, the paper describes all relevant information regarding MPs, as types and technology, seismic behavior, applications for increasing seismic resilience, and experimental and numerical modeling. Full article
(This article belongs to the Special Issue Urban Sustainability and Resilience of the Built Environments)
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Article
Potential for Coastal and Offshore Aquaculture in Portugal: Insights from Physico-Chemical and Oceanographic Conditions
Appl. Sci. 2022, 12(5), 2742; https://doi.org/10.3390/app12052742 - 07 Mar 2022
Viewed by 739
Abstract
Physico-chemical and biological parameters along the Portuguese coast were analyzed to evaluate the potential to produce aquatic species of economic interest. Water samples were collected in 2018 and 2019 in five different areas of the Portuguese coast. Currents data were collected between 2018 [...] Read more.
Physico-chemical and biological parameters along the Portuguese coast were analyzed to evaluate the potential to produce aquatic species of economic interest. Water samples were collected in 2018 and 2019 in five different areas of the Portuguese coast. Currents data were collected between 2018 and 2020 and historical waves height data from 1988 to 2019. According to the results, there is a wide variety of species that can be considered for production. The northernmost area presented the lowest temperature, as well as the highest levels of chlorophyll a, and nitrate. Under such conditions, the rearing of salmon Salmo salar, mussel Mytilus edulis, scallop Pecten maximus, macroalgae Porphyra umbilicalis, and Undaria pinnatifida can be considered. Regarding the southernmost area, due to the highest temperature, this area seems appropriate for the production of meager Argyrosomus regius, sea bream Sparus aurata, sea bass Dicentrarchus labrax, and greater amberjack Seriola dumerili. This study highlights the challenges in deploying aquaculture structures on the Atlantic coast due to its oceanographic conditions. Site selection for aquaculture is a complex process and pilot studies are essential to analyze the feasibility of developing offshore aquaculture along the coast of Portugal. Full article
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Article
Structural Design and Parameter Optimization of Bionic Exhaust Tailpipe of Tractors
Appl. Sci. 2022, 12(5), 2741; https://doi.org/10.3390/app12052741 - 07 Mar 2022
Viewed by 370
Abstract
The exhaust tailpipe of a certain type of tractor was improved from the perspective of bionics, and bionic triangular convex texture was added to the inner surface of the exhaust tailpipe. The bionic tailpipe was proposed to improve noise reduction performance without changing [...] Read more.
The exhaust tailpipe of a certain type of tractor was improved from the perspective of bionics, and bionic triangular convex texture was added to the inner surface of the exhaust tailpipe. The bionic tailpipe was proposed to improve noise reduction performance without changing the overall size parameters of the prototype tailpipe. Acoustics simulation software was used to predict the aeroacoustics noise and transmission loss of the exhaust tailpipe. Bionic exhaust tailpipes with triangular textures of different numbers of circumferential columns, height, and top angles were analyzed to study the noise reduction performance. The results showed that the proposed bionic exhaust tailpipes with triangular convex textures reduced the total sound pressure level and improved the transmission loss of the prototype exhaust tailpipe. To increase the transmission loss, a genetic algorithms (GA) optimized back-propagation neural network (BP) was used to optimize the bionic triangular convex texture parameters. By studying the aerodynamic noise reduction mechanism of bionic tailpipes, the research suggested that a secondary vortex appeared near the bionic texture and reduced aerodynamic drag and aeroacoustics noise. In addition, the sound pressure level amplitude nephogram, velocity vector nephogram, and velocity amplitude nephogram of the exhaust tailpipes were analyzed to study the vibration noise reduction mechanism of the bionic tailpipes. Then, the noise reduction performance was experimentally evaluated. The experimental results of the bionics exhaust tailpipes with triangular convex textures were analyzed and compared to that of the prototype tailpipe. The results demonstrated that the bionic exhaust tailpipes were able to attenuate noise. Full article
(This article belongs to the Special Issue Bionic Design and Manufacturing of Innovative Aircraft)
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Review
Development and Characterization of Bioadsorbents Derived from Different Agricultural Wastes for Water Reclamation: A Review
Appl. Sci. 2022, 12(5), 2740; https://doi.org/10.3390/app12052740 - 07 Mar 2022
Viewed by 689
Abstract
The presence of dangerous pollutants in different water sources has restricted the availability of this natural resource. Thus, the development of new low-cost and environmentally-friendly technologies is currently required to ensure access to clean water. Various approaches to the recovery of contaminated water [...] Read more.
The presence of dangerous pollutants in different water sources has restricted the availability of this natural resource. Thus, the development of new low-cost and environmentally-friendly technologies is currently required to ensure access to clean water. Various approaches to the recovery of contaminated water have been considered, including the generation of biomaterials with adsorption capacity for dangerous compounds. Research on bioadsorbents has boomed in recent years, as they constitute one of the most sustainable options for water treatment thanks to their abundance and high cellulose content. Thanks to the vast amount of information published to date, the present review addresses the current status of different biosorbents and the principal processes and characterization methods involved, focusing on base biomaterials such as fruits and vegetables, grains and seeds, and herbage and forage. In comparison to other reviews, this work reports more than 60 adsorbents obtained from agricultural wastes. The removal efficiencies and/or maximum adsorption capacities for heavy metals, industrial contaminants, nutrients and pharmaceuticals are presented as well. In addition to the valuable information provided in the literature investigation, challenges and perspectives concerning the implementation of bioadsorbents are discussed in order to comprehensively guide selection of the most suitable biomaterials according to the target contaminant and the available biowastes. Full article
(This article belongs to the Special Issue Biowaste Treatment and Valorization)
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Article
Synthesis and Characterisation of Alginate-Based Capsules Containing Waste Cooking Oil for Asphalt Self-Healing
Appl. Sci. 2022, 12(5), 2739; https://doi.org/10.3390/app12052739 - 07 Mar 2022
Cited by 2 | Viewed by 490
Abstract
This paper presents the synthesis and characterisation of biopolymeric capsules for asphalt self-healing. A sodium alginate biopolymer extracted from the cell wall of brown algae was used as the encapsulating material to contain Waste Cooking Oil (WCO) as a potential encapsulated rejuvenating agent [...] Read more.
This paper presents the synthesis and characterisation of biopolymeric capsules for asphalt self-healing. A sodium alginate biopolymer extracted from the cell wall of brown algae was used as the encapsulating material to contain Waste Cooking Oil (WCO) as a potential encapsulated rejuvenating agent for aged bitumen. Polynuclear capsules were synthesised by ionic gelation. The size, surface aspect and internal structure of the WCO capsules were evaluated using Optical and Scanning Electron Microscopy. The physical-chemical properties and thermal stability of the WCO capsules and their components were also evaluated. Moreover, the diffusion process and self-healing capability of the released WCO on cracked bitumen test samples were determined by image analysis through fluorescence microscopy. The main results of this study showed that the WCO capsules presented a suitable morphology to be mixed in asphalt mixtures. WCO capsules and their components presented mechanical and thermal stability and physical-chemical properties which suggest their feasibility for self-healing applications. It was proven that the encapsulated WCO can diffuse in the aged bitumen, reducing its viscosity and promoting the self-healing of microcracks. Full article
(This article belongs to the Special Issue Selected Papers in the Section Materials 2022)
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Article
Sensitivity Analysis for Transient Thermal Problems Using the Complex-Variable Finite Element Method
Appl. Sci. 2022, 12(5), 2738; https://doi.org/10.3390/app12052738 - 07 Mar 2022
Viewed by 507
Abstract
Solving transient heat transfer equations is required to understand the evolution of temperature and heat flux. This physics is highly dependent on the materials and environmental conditions. If these factors change with time and temperature, the process becomes nonlinear and numerical methods are [...] Read more.
Solving transient heat transfer equations is required to understand the evolution of temperature and heat flux. This physics is highly dependent on the materials and environmental conditions. If these factors change with time and temperature, the process becomes nonlinear and numerical methods are required to predict the thermal response. Numerical tools are even more relevant when the number of parameters influencing the model is large, and it is necessary to isolate the most influential variables. In this regard, sensitivity analysis can be conducted to increase the process understanding and identify those variables. Here, we combine the complex-variable differentiation theory with the finite element formulation for transient heat transfer, allowing one to compute efficient and accurate first-order sensitivities. Although this approach takes advantage of complex algebra to calculate sensitivities, the method is implemented with real-variable solvers, facilitating the application within commercial software. We present this new methodology in a numerical example using the commercial software Abaqus. The calculation of sensitivities for the temperature and heat flux with respect to temperature-dependent material properties, boundary conditions, geometric parameters, and time are demonstrated. To highlight, the new sensitivity method showed step-size independence, mesh perturbation independence, and reduced computational time contrasting traditional sensitivity analysis methods such as finite differentiation. Full article
(This article belongs to the Section Applied Thermal Engineering)
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Article
Predicting Children with ADHD Using Behavioral Activity: A Machine Learning Analysis
Appl. Sci. 2022, 12(5), 2737; https://doi.org/10.3390/app12052737 - 07 Mar 2022
Viewed by 597
Abstract
Attention deficit hyperactivity disorder (ADHD) is one of childhood’s most frequent neurobehavioral disorders. The purpose of this study is to: (i) extract the most prominent risk factors for children with ADHD; and (ii) propose a machine learning (ML)-based approach to classify children as [...] Read more.
Attention deficit hyperactivity disorder (ADHD) is one of childhood’s most frequent neurobehavioral disorders. The purpose of this study is to: (i) extract the most prominent risk factors for children with ADHD; and (ii) propose a machine learning (ML)-based approach to classify children as either having ADHD or healthy. We extracted the data of 45,779 children aged 3–17 years from the 2018–2019 National Survey of Children’s Health (NSCH, 2018–2019). About 5218 (11.4%) of children were ADHD, and the rest of the children were healthy. Since the class label is highly imbalanced, we adopted a combination of oversampling and undersampling approaches to make a balanced class label. We adopted logistic regression (LR) to extract the significant factors for children with ADHD based on p-values (<0.05). Eight ML-based classifiers such as random forest (RF), Naïve Bayes (NB), decision tree (DT), XGBoost, k-nearest neighborhood (KNN), multilayer perceptron (MLP), support vector machine (SVM), and 1-dimensional convolution neural network (1D CNN) were adopted for the prediction of children with ADHD. The average age of the children with ADHD was 12.4 ± 3.4 years. Our findings showed that RF-based classifier provided the highest classification accuracy of 85.5%, sensitivity of 84.4%, specificity of 86.4%, and an AUC of 0.94. This study illustrated that LR with RF-based system could provide excellent accuracy for classifying and predicting children with ADHD. This system will be helpful for early detection and diagnosis of ADHD. Full article
(This article belongs to the Special Issue Biomedical Signal Processing, Data Mining and Artificial Intelligence)
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Article
Discriminative Frequencies and Temporal EEG Segmentation in the Motor Imagery Classification Approach
Appl. Sci. 2022, 12(5), 2736; https://doi.org/10.3390/app12052736 - 07 Mar 2022
Cited by 1 | Viewed by 543
Abstract
A linear discriminant analysis transformation-based approach to the classification of three different motor imagery types for brain–computer interfaces was considered. The study involved 16 conditionally healthy subjects (12 men, 4 women, mean age of 21.5 years). First, the search for subject-specific discriminative frequencies [...] Read more.
A linear discriminant analysis transformation-based approach to the classification of three different motor imagery types for brain–computer interfaces was considered. The study involved 16 conditionally healthy subjects (12 men, 4 women, mean age of 21.5 years). First, the search for subject-specific discriminative frequencies was conducted in the task of movement-related activity. This procedure was shown to increase the classification accuracy compared to the conditional common spatial pattern (CSP) algorithm, followed by a linear classifier considered as a baseline approach. In addition, an original approach to finding discriminative temporal segments for each motor imagery was tested. This led to a further increase in accuracy under the conditions of using Hjorth parameters and interchannel correlation coefficients as features calculated for the EEG segments. In particular, classification by the latter feature led to the best accuracy of 71.6%, averaged over all subjects (intrasubject classification), and, surprisingly, it also allowed us to obtain a comparable value of intersubject classification accuracy of 68%. Furthermore, scatter plots demonstrated that two out of three pairs of motor imagery were discriminated by the approach presented. Full article
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Article
An Effective Tangent Stiffness of Train–Track–Bridge Systems Based on Artificial Neural Network
Appl. Sci. 2022, 12(5), 2735; https://doi.org/10.3390/app12052735 - 07 Mar 2022
Cited by 1 | Viewed by 473
Abstract
Dynamic response analysis of a train–track–bridge (TTB) system is a challenging task for researchers and engineers, partially due to the complicated nature of the wheel–rail interaction (WRI). When Newton’s method is used to solve implicit nonlinear finite element equations of a TTB system, [...] Read more.
Dynamic response analysis of a train–track–bridge (TTB) system is a challenging task for researchers and engineers, partially due to the complicated nature of the wheel–rail interaction (WRI). When Newton’s method is used to solve implicit nonlinear finite element equations of a TTB system, consistent tangent stiffness (CTS) is essential to guarantee the quadratic convergence rate. However, the derivation and software implementation of CTS for the WRI element require significant efforts. Artificial neural network (ANN) can directly obtain a potentially good tangent stiffness by a trained relationship between input nodal displacement/velocity and output tangent stiffness. In this paper, the backpropagation neural-network-based tangent stiffness (BPTS) of the WRI element is derived and implemented into a general finite element software, OpenSees, and verified by dynamic response analysis of a high-speed train running on a seven span simply supported beam bridge. The accuracy and efficiency are compared between the use of BPTS and CTS. The results demonstrate that BPTS can not only save the significant efforts of deriving and software implementing CTS but also improve computational efficiency while ensuring good accuracy. Full article
(This article belongs to the Special Issue Design of Track System and Railway Vehicle Dynamics Analysis)
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Review
An Overview on Deep Learning Techniques for Video Compressive Sensing
Appl. Sci. 2022, 12(5), 2734; https://doi.org/10.3390/app12052734 - 07 Mar 2022
Viewed by 523
Abstract
The use of compressive sensing in several applications has allowed to capture impressive results, especially in various applications such as image and video processing and it has become a promising direction of scientific research. It provides extensive application value in optimizing video surveillance [...] Read more.
The use of compressive sensing in several applications has allowed to capture impressive results, especially in various applications such as image and video processing and it has become a promising direction of scientific research. It provides extensive application value in optimizing video surveillance networks. In this paper, we introduce recent state-of-the-art video compressive sensing methods based on neural networks and categorize them into different categories. We compare these approaches by analyzing the networks architectures. Then, we present their pros and cons. The general conclusion of the paper identify open research challenges and point out future research directions. The goal of this paper is to overview the current approaches in image and video compressive sensing and demonstrate their powerful impact in computer vision when using well designed compressive sensing algorithms. Full article
(This article belongs to the Topic Applied Computer Vision and Pattern Recognition)
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Article
Lubrication Force Saturation Matters for the Critical Separation Size of the Non-Colloidal Spherical Particle in the Deterministic Lateral Displacement Device
Appl. Sci. 2022, 12(5), 2733; https://doi.org/10.3390/app12052733 - 07 Mar 2022
Viewed by 426
Abstract
Deterministic lateral displacement (DLD) is a popular technique for separating micro-scale and nano-scale particles continuously. In this paper, an efficient three-dimensional fictitious domain method is developed for the direct numerical simulation of the motion of a non-colloidal spherical particle in the DLD device [...] Read more.
Deterministic lateral displacement (DLD) is a popular technique for separating micro-scale and nano-scale particles continuously. In this paper, an efficient three-dimensional fictitious domain method is developed for the direct numerical simulation of the motion of a non-colloidal spherical particle in the DLD device (i.e., cylinder array), based on substantial modification of our previous FD method. A combination of the fast Fourier transformation (FFT) and a tri-diagonal solver is developed to efficiently solve the pressure Poisson equation for a DLD unit with a shifted periodic boundary condition in the streamwise direction. The lubrication force correction is adopted in the fictitious domain method to correct the unresolved hydrodynamic force when the particle is close to the cylinder with the gap distance below one mesh, and the lubrication force is assumed to saturate at a smaller critical gap distance as a result of the surface roughness effect. The proposed method is then employed to investigate the effect of the critical gap distance of the lubrication force saturation on the motion mode (i.e., separation size) of the particle in the DLD device. Our results indicate that the lubrication force saturation is important to the particle critical separation size, and a smaller saturation distance generally makes the particle more prone to the zigzag mode. Full article
(This article belongs to the Special Issue Advances in Multiphase Flows)
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Article
The Properties and Durability of Self-Leveling and Thixotropic Mortars with Recycled Sand
Appl. Sci. 2022, 12(5), 2732; https://doi.org/10.3390/app12052732 - 07 Mar 2022
Viewed by 545
Abstract
In recent decades, relevant environmental and economic reasons have driven an increasing interest in using a large amount of recycled aggregate in replacement of natural ones to produce mortar and concrete. The present study aims to investigate the effect of substituting 100% of [...] Read more.
In recent decades, relevant environmental and economic reasons have driven an increasing interest in using a large amount of recycled aggregate in replacement of natural ones to produce mortar and concrete. The present study aims to investigate the effect of substituting 100% of natural sand with recycled aggregate on fresh properties, mechanical properties, and the durability of a thixotropic and a self-leveling mortar. Recycled aggregate was characterized using X-ray diffractometry and energy-dispersive X-ray spectroscopy. Its morphology was investigated using scanning electron microscopy and automated morphological imaging. Recycled aggregate mortars showed a moderate decline in initial workability, as well as higher shrinkage and porosity than the control ones. The compressive strength of self-leveling mortars produced with recycled aggregate was only 6% lower than mortars produced with natural sand. The gap increased to 40% in the case of thixotropic mortars. The self-leveling recycled aggregate mortar showed equivalent resistance to freeze–thaw cycles and better sulfate resistance than the control one. The thixotropic recycled aggregate mortar showed comparable sulphate resistance and only slightly lower resistance to freeze–thaw cycles than the control one. Their capacity to relief stresses, due to hydraulic pressures and the formation of expansive products, arises from their higher porosity. Thermal stability of the prepared mortars, after a curing period of 90 days, up to 700 °C, was also investigated. A significant decrease in ultrasonic pulse velocity is observed in the 200–400 °C interval for all the mortars, due to the dehydration–dehydroxylation of calcium silicate hydrate. The overall decline in the strength of both the recycled aggregate mortars was comparable to the control ones. The results reported in the present investigation suggest that the selection of high-quality recycled aggregate helps to obtain good-quality mortars when a large amount of natural sand is replaced. Full article
(This article belongs to the Special Issue Sustainable and Durable Building Materials)
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Article
Axial Bearing Mechanism of Post-Grouted Piles in Calcareous Sand
Appl. Sci. 2022, 12(5), 2731; https://doi.org/10.3390/app12052731 - 07 Mar 2022
Cited by 1 | Viewed by 449
Abstract
Post-grouted piles, as a foundation form for large-span and large-scale structures on calcareous sand, are expected to provide a high bearing capacity, but research on the response of post-grouted piles subjected to axial load in calcareous sand is still in the exploratory stage. [...] Read more.
Post-grouted piles, as a foundation form for large-span and large-scale structures on calcareous sand, are expected to provide a high bearing capacity, but research on the response of post-grouted piles subjected to axial load in calcareous sand is still in the exploratory stage. In this paper, a model test is constructed for static pressure piles in calcareous sand under axial loading. The response of axial compressive piles, with and without post-grouting, in calcareous sand were investigated, and the test results were compared with those of axial compressive piles, with and without post-grouting, in siliceous sand. The influence of post-side-grouting on the response of a single pile subjected to axial compressive load in calcareous sand and its bearing mechanism were further analyzed. The results show that the change in shaft resistance, caused by the lateral extrusion of calcareous sand, is less than the negative effect caused by particle breakage during pile driving, so single piles without post-grouting in calcareous sand exhibit weaker axial bearing behavior than that in siliceous sand. A single pile with post-side-grouting in calcareous sand can provide a higher bearing capacity by increasing the shaft resistance and tip resistance compared with a single pile without post-side-grouting, and the increased ratio of the bearing capacity of piles, after grouting in calcareous sand, is better than that of piles in siliceous sand. Post-side-grouting can not only strengthen the surrounding soil by the solidification effect of injected cement grout, but it can also have a strengthening effect on the tip resistance. In addition, ideal-geometry grouting has more obvious advantages in improving the bearing behavior of pile foundations than annular point grouting, and higher stability in improving the bearing properties of pile foundations is evident for ideal-geometry grouting. Therefore, it is suggested that a directional grouting device should be adopted in actual projects in the future to form a more stable pile-soil interaction system and to expand the application prospect of pile foundations in calcareous sand. Full article
(This article belongs to the Special Issue Recent Progress on Advanced Foundation Engineering)
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Article
Evaluating the Effect of Noise from Traffic on HYB Magnetic Observatory Data during COVID-19 Lockdown
Appl. Sci. 2022, 12(5), 2730; https://doi.org/10.3390/app12052730 - 07 Mar 2022
Viewed by 425
Abstract
Continuous time series data from geomagnetic observatories are increasingly contaminated by anthropogenic noise related to developing socio-economic activities. More and more sophisticated techniques of data processing are used to eliminate this noise; nonetheless, some of it cannot be removed. The main sources of [...] Read more.
Continuous time series data from geomagnetic observatories are increasingly contaminated by anthropogenic noise related to developing socio-economic activities. More and more sophisticated techniques of data processing are used to eliminate this noise; nonetheless, some of it cannot be removed. The main sources of noise in the Hyderabad (HYB) data are vehicular traffic, power lines and a power station, 500 m to 1 km away. During the nationwide COVID-19 pandemic lockdown from 24 March to 17 May 2020, both road and metro rail traffic came to a complete halt. The data from this time interval give us an opportunity to evaluate the effects of the absence of traffic-generated noise sources. We found noticeable differences in the noise levels present in vector and scalar variation data, due to the vehicular noise observed before and during the lockdown periods. Noise spectrum estimates quantify the reduction in the noise levels during this period. We also noticed decreased scatter in absolute values of the H (horizontal), D (declination), Z (vertical) and I (inclination) components of the geomagnetic field during lockdown. The details of increased data quality in the absence of traffic-generated noise sources are discussed. Full article
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