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Search results for: CANTILEVERS DEEP BEAMS
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The method of analysis of damage reinforced concrete beams using terrestial laser scanning
PublicationThe authors present an analysis of the possibility to assess deformations and mechanisms of destructing bent reinforced concrete beams using the terrestrial laser scanning. As part of the experiments carried out at the Regional Laboratory of Construction of the Concrete Structures Division of the Civil and Environmental Engineering Faculty at Gdansk University of Technology, the reinforced concrete beams were subjected to destruction...
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Antifungal activity of propolis extracts produced with deep eutectic solvents.
Open Research DataThis dataset contains results of our investigation aiming in determination of antimicrobial potential of the propolis extracts produced with deep eutectic solvents. The activity was determined against C. albicans and C. glabarat strains. On the basis of these results MIC values can be calculated. Three samples of propolis were tested.
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Data obtained by computation for X-ray focusing using oriented Gaussian beams
Open Research DataThe propagation of X-ray waves through an optical system consisting of several X-ray refractive lenses is considered. Gaussian beams are exact solutions of the paraxial equation. The Helmholtz equation describes the propagation of a monochromatic electromagnetic wave. Since the widths of the beams are much larger than the wavelength of X-rays, Gaussian...
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RMS-based damage detection in reinforced concrete beams: numerical simulations
PublicationImage-based damage detection methods using guided waves are well known and widely applied approaches in structural diagnostics. They are usually utilized in detection of surface damages or defects of plate-like structures. The article presents results of the study of applicability of imaging wave-based methods in detection in miniscule internal damage in the form of debonding. The investigations were carried out on numerical models...
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Application of deep eutectic solvents in bioanalysis
PublicationThe application of deep eutectic solvents (DESs) is sharply surging as a green alternative to conventional solvents due to their unique properties in terms of simplicity of preparation, designability and low cost. A great deal of attention has been paid to the application of these green solvents in analytical chemistry in recent years, and a lot of interesting work has been reported. This review summarizes the most relevant applications...
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Size effect in concrete beams under bending – influence of the boundary layer and the numerical description of cracks
PublicationIn the paper the size effect phenomenon in concrete is analysed. The results of numerical simulations of using FEM on geometrically similar un-notched and notched concrete beams under bending are presented. Concrete beams of four different sizes and five different notch heights under three-point bending test were simulated. In total 18 beams were analysed. Two approaches were used to describe cracks in concrete. First, eXtended...
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Breast MRI segmentation by deep learning: key gaps and challenges
PublicationBreast MRI segmentation plays a vital role in early diagnosis and treatment planning of breast anomalies. Convolutional neural networks with deep learning have indicated promise in automating this process, but significant gaps and challenges remain to address. This PubMed-based review provides a comprehensive literature overview of the latest deep learning models used for breast segmentation. The article categorizes the literature...
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THE METHOD OF ANALYSIS OF DAMAGE REINFORCED CONCRETE BEAMS USING TERRESTRIAL LASER SCANNING
PublicationThe authors present an analysis of the possibility to assess deformations and mode of failure of R-C beams using terrestrial laser scanning. As part of experiments carried out at the Regional Laboratory of Construction (at Gdansk University of Technology), reinforced concrete beams were subjected to destruction by bending and by shear. The process of press impact on the reinforced concrete beam was recorded using terrestrial laser...
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NATURAL DEEP EUTECTIC SOLVENTS IN EXTRACTION PROCESS
PublicationDeveloping new, eco-friendly solvents which would meet technological and economic demands is perhaps the most popular aspects of Green Chemistry. Natural deep eutectic solvents (NADES) fully meet green chemistry principles. These solvents offer many advantages including biodegradability, low toxicity, sustainability, low costs and simple preparation. This paper provides an overview of knowledge regarding NADES with special emphasis...
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Sensitivity analysis of free torsional vibration frequencies of thin-walled laminated beams under axial load
PublicationThe paper addresses sensitivity analysis of free torsional vibration frequencies of thin-walled beams of bisymmetric open cross-section made of unidirectional fibre-reinforced laminate. The warping effect and the axial end load are taken into account. The consideration is based upon the classical theory of thin-walled beams of non-deformable cross-section. The first-order sensitivity variation of the frequencies is derived with...
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Debonding Size Estimation in Reinforced Concrete Beams Using Guided Wave-Based Method
PublicationThe following paper presents the results of the theoretical and experimental analysis of the influence of debonding size on guided wave propagation in reinforced concrete beams. The main aim of the paper is a development of a novel, baseline-free method for determining the total area of debonding between steel rebar embedded in a concrete cover on the basis of the average wave velocity or the time of flight. The correctness of...
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On the exact equilibrium conditions of irregular shells reinforced by beams along the junctions
PublicationThe exact, resultant equilibrium conditions for irregular shells reinforced by beams along the junctions are formulated. The equilibrium conditions are derived by performing direct integration of the global equilibrium conditions of continuum mechanics. New, exact resultant static continuity conditions along the singular curve modelling reinforced junction are presented. The results do not depend on shell thickness, internal through-the-thickness...
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Deep Learning: A Case Study for Image Recognition Using Transfer Learning
PublicationDeep learning (DL) is a rising star of machine learning (ML) and artificial intelligence (AI) domains. Until 2006, many researchers had attempted to build deep neural networks (DNN), but most of them failed. In 2006, it was proven that deep neural networks are one of the most crucial inventions for the 21st century. Nowadays, DNN are being used as a key technology for many different domains: self-driven vehicles, smart cities,...
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Chained machine learning model for predicting load capacity and ductility of steel fiber–reinforced concrete beams
PublicationOne of the main issues associated with steel fiber–reinforced concrete (SFRC) beams is the ability to anticipate their flexural response. With a comprehensive grid search, several stacked models (i.e., chained, parallel) consisting of various machine learning (ML) algorithms and artificial neural networks (ANNs) were developed to predict the flexural response of SFRC beams. The flexural performance of SFRC beams under bending was...
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Wave propagation signals in concrete beams under 3-point bending
Open Research DataThe DataSet contains the results of the mechanical behaviour of a concrete beams with dimensions 40 x 40 x 160 cm3under the 3-point bending. The beams were made of concrete with the following ingredients: CEM I 42.5R (450 kg/m3), water (177 kg/m3), sand 0-2 (675 kg/m3) and gravel 2-8 (675 kg/m3). The bending test was performed using a Zwick/Roell Z10...
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Integration of Fluorescent, NV-Rich Nanodiamond Particles with AFM Cantilevers by Focused Ion Beam for Hybrid Optical and Micromechanical Devices
PublicationIn this paper, a novel fabrication technology of atomic force microscopy (AFM) probes integrating cantilever tips with an NV-rich diamond particle is presented. Nanomanipulation techniques combined with the focused electron beam-induced deposition (FEBID) procedure were applied to position the NV-rich diamond particle on an AFM cantilever tip. Ultrasonic treatment of nanodiamond suspension was applied to reduce the size of diamond...
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Reference-free determination of debonding length in reinforced concrete beams using guided wave propagation
PublicationThis paper presents theoretical and experimental investigations of guided wave propagation in reinforced concrete beams, with pre-existing debonding between steel rebars and concrete blocks, for the purpose of damage detection. The primary aim of these investigations was a detailed analysis of the possible applications of wave propagation in single and multiple debonding detection in reinforced concrete structures and reference-free...
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Verification of selected calculation methods regarding shear strength in beams without web reinforcement
PublicationThe purpose of the article was to compare selected calculation methods regarding shear strength in reinforced concrete beams without web reinforcement. Several calculation methods were tested. This included codes: PN-EN 1992-1-1:2008, ACI 318-14 and fib Model Code for Concrete Structures 2010. The analysis also consists of authorial methods published in technical literature. Calculations of shear strengths were made based on experimental...
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Hydrogen bonding part sigma profile of deep eutectic solvents and pure components
Open Research DataThe set includes raw data of hydrogen bonding part sigma profiles of deep eutectic solvents and pure components generated by the ADF COSMO-RS software (SCM, Netherlands).
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Experimental Tests Of Sandwich Beams In The Design Process Of GFRP Shell Footbridge Structure
PublicationThe paper includes selected aspects of the study to elaborate architectural, material and construction design of pedestrian footbridge spans made of composite materials. The considered footbridge is a sandwich-type shell structure. The cooperation of PET foam core with outer lining surfaces is crucial for its load bearing capacity. The paper is aimed to experimental investigation of sandwich beams subjected to bending loading....
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SIMULATIONS OF FRACTURE IN CONCRETE BEAMS UNDER BENDING USING A CONTINUUM AND DISCRETE APPROACH
PublicationThe paper describes two-dimensional meso-scale results of fracture in notched concrete beams under bending. Concrete was modelled as a random heterogeneous 4-phase material composed of aggregate particles, cement matrix, interfacial transitional zones and air voids. Within continuum mechanics, the simulations were carried out with the finite element method based on a isotropic damage constitutive model enhanced by a characteristic...
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FE investigations of the effect of fluctuating local tensile strength on coupled energetic-statistical size effect in concrete beams
PublicationThe effect of fluctuating local tensile strength on a coupled energetic-statistical size effect in plain concrete beams under bending was numerically investigated. First, the influence of varying autocorrelation length of the random field describing a spatial variation of local tensile strength was studied. Next, the influence of the coefficient of variation of local tensile strength was analyzed. The numerical FE investigations...
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Deep learning for recommending subscription-limited documents
PublicationDocuments recommendation for a commercial, subscription-based online platform is important due to the difficulty in navigation through a large volume and diversity of content available to clients. However, this is also a challenging task due to the number of new documents added every day and decreasing relevance of older contents. To solve this problem, we propose deep neural network architecture that combines autoencoder with...
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Hydrophobic deep eutectic solvents in microextraction techniques–A review
PublicationOver the past decade, deep eutectic solvents (DES) have been widely studied and applied in sample preparation techniques. Until recently, most of the synthesized DES were hydrophilic, which prevented their use in the extraction of aqueous samples. However, after 2015 studies on the synthesis and application of hydrophobic deep eutectic solvents (HDES) has rapidly expanded. Due to unique properties of HDES i.e. density, viscosity,...
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Split-beam echosounder data from Gdansk Deep Summer 2019
Open Research DataThe acoustic data was collected in 2019, in the Gdansk Deep, in the season: Summer. Data was collected during the day and night. Three split-beam echosounders with frequencies of 38 kHz, 120 kHz and 333 kHz were used to collect the data. The data was collected while the ship was sailing. To ensure data quality, echosounders were calibrated and passive...
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Vibration signals collected for concrete beams with GFRP reinforcement subjected to elevated temperatures (120C-240C)
Open Research DataThe dataset contains the time domain signals obtained during dynamic tests of concrete beams reinforced with GFRP bars. The vibration were induced with the use of modal hammer, while the signals were collected by the accelerometers attached at the beam surface. The signals were captured before and after subjecting the concrete beams to elevated temperatures.
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Local and global response of sandwich beams made of GFRP facings and PET foam core in three point bending test
PublicationIn the paper behaviour of laminated sandwich beams (FRP face sheet – PET foam core – FRP face sheet) subjected to three point bending is studied. The paper aim is to find practical descriptions enabling effective and accurate estimation of the elastic response, damage and failure of the beams, basing on experiments and static calculations. Therefore a number of tests are described, that were done on laminated coupons and foam specimens...
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Explainable AI for Inspecting Adversarial Attacks on Deep Neural Networks
PublicationDeep Neural Networks (DNN) are state of the art algorithms for image classification. Although significant achievements and perspectives, deep neural networks and accompanying learning algorithms have some important challenges to tackle. However, it appears that it is relatively easy to attack and fool with well-designed input samples called adversarial examples. Adversarial perturba-tions are unnoticeable for humans. Such attacks...
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Experimental Investigations of Fracture Process Using DIC in Plain and Reinforced Concrete Beams under Bending
PublicationThe fracture behaviour of concrete and reinforced concrete beams under quasi-static three-point bending was comprehensively investigated with experiments at laboratory scale. The eight various concrete mixes were tested. The influence of the shape, volume and size of aggregate particles and reinforcement on concrete fracture under bending was studied. Displacements on the surface of concrete beams were measured by means of the...
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Ionic Liquids and Deep Eutectic Mixtures: Sustainable Solvents for Extraction Processes
PublicationIn recent years, ionic liquids and deep eutectic mixtures have demonstrated great potential in extraction processes relevant to several scientific and technological activities. This review focuses on the applicability of these sustainable solvents in a variety of extraction techniques, including but not limited to liquid- and solid-phase (micro) extraction, microwave-assisted extraction, ultrasound-assisted extraction and pressurized...
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Performance of isotropic constitutive laws in simulating failure mechanisms in scaled RC beams
PublicationResults of numerical calculations of reinforced concrete (RC) beams are presented. Based on experimental results on longitudinally reinforced specimens of different sizes and shapes are investigated. Four different continuum constitutive laws with isotropic softening are used: one defined within continuum damage mechanics, an elasto-plastic with the Rankine criterion in tension and the Drucker-Prager criterion in compression, a...
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Training of Deep Learning Models Using Synthetic Datasets
PublicationIn order to solve increasingly complex problems, the complexity of Deep Neural Networks also needs to be constantly increased, and therefore training such networks requires more and more data. Unfortunately, obtaining such massive real world training data to optimize neural networks parameters is a challenging and time-consuming task. To solve this problem, we propose an easy-touse and general approach to training deep learning...
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Deep Eutectic Solvents: Properties and Applications in CO2 Separation
PublicationNowadays, many researchers are focused on finding a solution to the problem of global warming. Carbon dioxide is considered to be responsible for the “greenhouse” effect. The largest global emission of industrial CO2 comes from fossil fuel combustion, which makes power plants the perfect point source targets for immediate CO2 emission reductions. A state-of-the-art method for capturing carbon dioxide is chemical absorption using...
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Optimized Deep Learning Model for Flood Detection Using Satellite Images
PublicationThe increasing amount of rain produces a number of issues in Kerala, particularly in urban regions where the drainage system is frequently unable to handle a significant amount of water in such a short duration. Meanwhile, standard flood detection results are inaccurate for complex phenomena and cannot handle enormous quantities of data. In order to overcome those drawbacks and enhance the outcomes of conventional flood detection...
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Benchmarking Deep Neural Network Training Using Multi- and Many-Core Processors
PublicationIn the paper we provide thorough benchmarking of deep neural network (DNN) training on modern multi- and many-core Intel processors in order to assess performance differences for various deep learning as well as parallel computing parameters. We present performance of DNN training for Alexnet, Googlenet, Googlenet_v2 as well as Resnet_50 for various engines used by the deep learning framework, for various batch sizes. Furthermore,...
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Data augmentation for improving deep learning in image classification problem
PublicationThese days deep learning is the fastest-growing field in the field of Machine Learning (ML) and Deep Neural Networks (DNN). Among many of DNN structures, the Convolutional Neural Networks (CNN) are currently the main tool used for the image analysis and classification purposes. Although great achievements and perspectives, deep neural networks and accompanying learning algorithms have some relevant challenges to tackle. In this...
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Non-Destructive Diagnostics of Concrete Beams Strengthened with Steel Plates Using Modal Analysis and Wavelet Transform
PublicationExternally bonded reinforcements are commonly and widely used in civil engineering objects made of concrete to increase the structure load capacity or to minimize the negative effects of long-term operation and possible defects. The quality of adhesive bonding between a strengthened structure and steel or composite elements is essential for effective reinforcement; therefore, there is a need for non-destructive diagnostics of adhesive...
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SFEM Analysis of Beams with Scaled Lengths including Spatially Varying and Cross-Correlated Concrete Properties
PublicationThis paper presents the results obtained for plain concrete beams under four-point bending with spatially varying material properties. Beams of increasing length but constant depth were analyzed using the stochastic finite element method. Spatial fluctuation of a uniaxial tensile strength, fracture energy and elastic modulus was defined within cross-correlated random fields. The symmetrical Gauss probability distribution function...
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Application of deep eutectic solvents (DES) in analytical chemistry
PublicationRecent years have been associated with efforts to reduce the impact on the natural environment. A greener approach has been introduced in various areas of science, including analytical chemistry. One of the basic procedures for preparing a sample for analysis is its extraction. Traditional methods involve the use of large amounts of organic compounds, often toxic, with an unfavorable impact on the environment. A representative...
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Are deep eutectic solvents useful in chromatography? A short review
PublicationA literature update has been done concerning Deep Eutectic Solvents (DES) use in chromatography applications. The literature survey was based on the period from 2010 till 2020 and manuscripts reported in the data bases Web of Science and Scopus. The use of DES as mobile phase and mobile phase additives, stationary phases and solid phase modifiers and the use of DES as reaction solvents for chromatography use, were evaluated. Emphasis...
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The impact of the AC922 Architecture on Performance of Deep Neural Network Training
PublicationPractical deep learning applications require more and more computing power. New computing architectures emerge, specifically designed for the artificial intelligence applications, including the IBM Power System AC922. In this paper we confront an AC922 (8335-GTG) server equipped with 4 NVIDIA Volta V100 GPUs with selected deep neural network training applications, including four convolutional and one recurrent model. We report...
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An isogeometric finite element formulation for geometrically exact Timoshenko beams with extensible directors
PublicationAn isogeometric finite element formulation for geometrically and materially nonlinear Timoshenko beams is presented, which incorporates in-plane deformation of the cross-section described by two extensible director vectors. Since those directors belong to the space R3, a configuration can be additively updated. The developed formulation allows direct application of nonlinear three-dimensional constitutive equations without zero...
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Classifying Emotions in Film Music - A Deep Learning Approach
PublicationThe paper presents an application for automatically classifying emotions in film music. A model of emotions is proposed, which is also associated with colors. The model created has nine emotional states, to which colors are assigned according to the color theory in film. Subjective tests are carried out to check the correctness of the assumptions behind the adopted emotion model. For that purpose, a statistical analysis of the...
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The role of water in deep eutectic solvent-base extraction
PublicationDeep eutectic solvents (DESs) are currently being used in different sectors, such as electrochemistry, electrodeposition, organic synthesis, nanoparticle preparation, bioactive compound separation, etc. Their use in analytical chemistry has only recently begun to expand. Despite the publication of a sufficient number of DES-based analytical extraction procedures, some details, such as interaction of DESwith the sample and target...
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Remarks on use of the term “deep eutectic solvent” in analytical chemistry
PublicationAbout 20 years ago, Abbott and co-workers researched new solvents that were based on mixtures of choline chloride with urea and carboxylic acids and that were liquid at ambient temperature. The term “deep eutectic solvent” (DES) was later adopted for similar mixtures. As DESs have a number of interesting features, they quickly attracted the attention of researchers and found application in various branches of chemical and materials...
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Selected Technical Issues of Deep Neural Networks for Image Classification Purposes
PublicationIn recent years, deep learning and especially Deep Neural Networks (DNN) have obtained amazing performance on a variety of problems, in particular in classification or pattern recognition. Among many kinds of DNNs, the Convolutional Neural Networks (CNN) are most commonly used. However, due to their complexity, there are many problems related but not limited to optimizing network parameters, avoiding overfitting and ensuring good...
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Characterization of corrosion in reinforced concrete beams using destructive and non-destructive tests
PublicationThe paper presents both non-destructive and destructive experimental tests on steel-reinforced concrete beams subjected to electrochemical corrosion. To examine the condition and behavior of the specimens, destructive tests were carried out, i.e., a three-point bending together with a modulated ultrasonic wave test. In addition, a series of non-destructive experiments were conducted, such as the potential measurement method, low-frequency...
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Nonlocalized thermal behavior of rotating micromachined beams under dynamic and thermodynamic loads
PublicationRotating micromachined beams are one of the most practical devices with several applications from power generation to aerospace industries. Moreover, recent advances in micromachining technology have led to huge interests in fabricating miniature turbines, gyroscopes and microsensors thanks to their high quality/reliability performances. To this end, this article is organized to examine the axial dynamic reaction of a rotating...
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Outlier detection method by using deep neural networks
PublicationDetecting outliers in the data set is quite important for building effective predictive models. Consistent prediction can not be made through models created with data sets containing outliers, or robust models can not be created. In such cases, it may be possible to exclude observations that are determined to be outlier from the data set, or to assign less weight to these points of observation than to other points of observation....
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Composite Beams with glass and reinforced or prestressed concrete - early stage of a theorethical and experimental analysis of a shear zone
PublicationThe aim of this article is to present a forgoing preparation for a theoretical and experimental analysis of a shear zone of a composite beams with glass and reinforced or prestressed concrete. Authors present their current knowledge, achievements and predicted challenges in later stages of the research. Properties of component materials are presented in the context of compensating weaknesses of one material with strengths of the...