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Search results for: CANTILEVERS DEEP BEAMS
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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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Novel “acid tuned” deep eutectic solvents based on protonated L-proline
PublicationThe paper presents new types of deep eutectic solvents (DESs) based on L-proline protonated using three different acids (hydrochloric, sulfuric and phosphoric)and playing the role of a hydrogen bond acceptor(HBA). Glucose and xylitol were used as hydrogen bond donors (HBD). A series of deep eutectic solvents with various mole ratios were obtained for the systems L-proline: glucose and L-proline: xylitol. Density, melting point,...
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Deep eutectic solvents vs ionic liquids: Similarities and differences
PublicationDeep eutectic solvents (DES) were introduced as an alternative to ionic liquids (IL) to overcome the drawbacks of IL solvents. However, some authors consider them to be a subclass of ILs. In contrast, other authors emphasize that these are by their nature independent, different groups of substances. Thus, the question arises: Which solvent group should DESs belong to? Maybe a new class should be added to the existing ones. The...
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Deep learning techniques for biometric security: A systematic review of presentation attack detection systems
PublicationBiometric technology, including finger vein, fingerprint, iris, and face recognition, is widely used to enhance security in various devices. In the past decade, significant progress has been made in improving biometric sys- tems, thanks to advancements in deep convolutional neural networks (DCNN) and computer vision (CV), along with large-scale training datasets. However, these systems have become targets of various attacks, with...
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Deep Learning-Based LOS and NLOS Identification in Wireless Body Area Networks
PublicationIn this article, the usage of deep learning (DL) in ultra-wideband (UWB) Wireless Body Area Networks (WBANs) is presented. The developed approach, using channel impulse response, allows higher efficiency in identifying the direct visibility conditions between nodes in off-body communication with comparison to the methods described in the literature. The effectiveness of the proposed deep feedforward neural network was checked on...
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Application of deep eutectic solvents in atomic absorption spectrometry
PublicationAtomic absorption spectrometry (AAS) is a widely applied technique for metal quantification due to its practicality, easy use and low cost. However, to improve the metrological characteristics of AAS, in particular the sensitivity and the detection limit, sample pretreatment is commonly used before the detection step itself. In consideration of the principles of Green Analytical Chemistry, new solvents are being introduced into...
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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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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...
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Deep Learning-Based, Multiclass Approach to Cancer Classification on Liquid Biopsy Data
PublicationThe field of cancer diagnostics has been revolutionized by liquid biopsies, which offer a bridge between laboratory research and clinical settings. These tests are less invasive than traditional biopsies and more convenient than routine imaging methods. Liquid biopsies allow studying of tumor-derived markers in bodily fluids, enabling the development of more precise cancer diagnostic tests for screening, disease monitoring, and...
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SYNTHESIZING MEDICAL TERMS – QUALITY AND NATURALNESS OF THE DEEP TEXT-TO-SPEECH ALGORITHM
PublicationThe main purpose of this study is to develop a deep text-to-speech (TTS) algorithm designated for an embedded system device. First, a critical literature review of state-of-the-art speech synthesis deep models is provided. The algorithm implementation covers both hardware and algorithmic solutions. The algorithm is designed for use with the Raspberry Pi 4 board. 80 synthesized sentences were prepared based on medical and everyday...
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Focused ion beam-based microfabrication of boron-doped diamond single-crystal tip cantilevers for electrical and mechanical scanning probe microscopy
PublicationIn this paper, the fabrication process and electromechanical properties of novel atomic force microscopy probes utilising single-crystal boron-doped diamond are presented. The developed probes integrate scanning tips made of chemical vapour deposition-grown, freestanding diamond foil. The fabrication procedure was performed using nanomanipulation techniques combined with scanning electron microscopy and focused ion beam technologies....
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Deep neural network architecture search using network morphism
PublicationThe paper presents the results of the research on neural architecture search (NAS) algorithm. We utilized the hill climbing algorithm to search for well-performing structures of deep convolutional neural network. Moreover, we used the function preserving transformations which enabled the effective operation of the algorithm in a short period of time. The network obtained with the advantage of NAS was validated on skin lesion classification...
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Challenges and Possibilities of Deep Eutectic Solvent-Based Membranes
PublicationDeep eutectic solvents (DES) are a category of a new class of solvents that can overcome some of the main drawbacks of typical solvents and ionic liquids (ILs). DES have been widely investigated and applied by the research community in several applications since their invention. Over the past years, the use of DES has been directed to the production of new materials and items for new products and processes. This is the case for...
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Deep learning based thermal image segmentation for laboratory animals tracking
PublicationAutomated systems for behaviour classification of laboratory animals are an attractive alternative to manual scoring. However, the proper animals separation and tracking, especially when they are in close contact, is the bottleneck of the behaviour analysis systems. In this paper, we propose a method for the segmentation of thermal images of laboratory rats that are in close contact during social behaviour tests. For this, we are...
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Deep CNN based decision support system for detection and assessing the stage of diabetic retinopathy
PublicationThe diabetic retinopathy is a disease caused by long-standing diabetes. Lack of effective treatment can lead to vision impairment and even irreversible blindness. The disease can be diagnosed by examining digital color fundus photographs of retina. In this paper we propose deep learning approach to automated diabetic retinopathy screening. Deep convolutional neural networks (CNN) - the most popular kind of deep learning algorithms...
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Relativistic electron beams above thunderclouds
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Sorbents modified by deep eutectic solvents in microextraction techniques
PublicationIn recent years, considerable attention has been directed towards the employment of green solvents, specifically deep eutectic solvents (DES), in liquid phase microextraction techniques. However, comprehensive and organized knowledge regarding the modification of sorbent surface structures with DES remains limited. Therefore, this paper reviews the application of DES in modifying and improving the properties of sorbents for microextraction...
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Deep eutectic solvents – Ideal solution for clean air or hidden danger?
PublicationThe industrial sector is one of the fastest-growing sources of greenhouse gases, due to its excessive energy consumption to meet the rapidly growing demand for energy-intensive products. The use of deep eutectic solvents (DESs) has been studied extensively in order to cope with these harmful gases, but their usage can be an issue in respect to ecological reasons. Do deep eutectic solvents harm the atmosphere? Yes, these solvents...
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Decision making process using deep learning
PublicationEndüstri 4.0, dördüncü endüstri devrimi veya Endüstriyel Nesnelerin İnterneti (IIoT) olarak adlandırılan sanayi akımı, işletmelere, daha verimli, daha büyük bir esneklikle, daha güvenli ve daha çevre dostu bir şekilde üretim yapma imkanı sunmaktadır. Nesnelerin İnterneti ile bağlantılı yeni teknoloji ve hizmetler birçok endüstriyel uygulamada devrim niteliği taşımaktadır. Fabrikalardaki otomasyon, tahminleyici bakım (PdM – Predictive...
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Unusual dynamics and nonlinear thermal self-focusing of initially focused magnetoacoustic beams in a plasma
PublicationUnusual thermal self-focusing of two-dimensional beams in plasma which axis is parallel to the equilibrium straight magnetic field is considered. The equi- librium parameters of plasma determine scenario of a beam divergence (usual or unusual) which is stronger as compared with a flow without magnetic field. Nonlinear thermal self-action of a magnetosonic beam behaves differently in the ordinary and unusual cases. Damping of wave...
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Verification of Selected Calculation Methods Regarding Shear Strength in Reinforced and Prestressed Concrete Beams
PublicationThe purpose of this article was an attempt to compare selected calculation methods regarding shear strength in reinforced and prestressed concrete beams. Several calculation methods were tested. This included codes: PN-EN 1992-1-1:2008 [1], ACI 318- 14 [2] and fib Model Code for Concrete Structures 2010 [3]. The analysis also consists of methods published in technical literature. Calculations of shear strengths were made based...