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Search results for: MACHINE LEARNING, 3D-PRINTED FIBER REINFORCED CONCRETE, MODEL INTERPRETABILITY, COMPRESSIVE STRENGTH
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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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Forewarned Is Forearmed: Machine Learning Algorithms for the Prediction of Catheter-Induced Coronary and Aortic Injuries
PublicationCatheter-induced dissections (CID) of coronary arteries and/or the aorta are among the most dangerous complications of percutaneous coronary procedures, yet the data on their risk factors are anecdotal. Logistic regression and five more advanced machine learning techniques were applied to determine the most significant predictors of dissection. Model performance comparison and feature importance ranking were evaluated. We identified...
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Concrete-filled FRP tubular members in marine and bridge structures
PublicationConcrete core of the concrete-filled tubes (CFTs) with circular cross-section is in the case of an axial compression subjected to a spatial state of compressive stresses. This state leads to enhancement in the concrete strength. The enhancement is utilized in Eurocode 4 design procedures for CFSTs (i.e. CFTs with tube made of steel). The structural design of CFFTs (i.e. CFTs with tube made of Fibre Reinforced Polymer - FRP) is...
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Method for prediction of the frost resistance ability of air‐entrained concrete based on the 3D air void characteristics by x‐ray micro‐CT
PublicationIn modern construction, one of the most important factors in the execution of contracts is time. Standard procedures for assessing the frost resistance or concrete are usually very time-consuming and can take up to 40 days. The current paper is experimentally and practically oriented. It presents an alternative testing method, based on air void network, that allows to assess the frost resistance of concrete within just a few days...
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Mechanical properties of sisal fiber-reinforced soybean oil-based polyurethane biocomposites
PublicationIn this paper the results of the mechanical properties of polyurethane biocomposites reinforced with short sisal fibers are presented. The fillers were added in different amount: 5, 10 and 15% by mass. Tensile test, hardness, abrasion resistance, elasticity were determined according to the standards.
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Explainable machine learning for diffraction patterns
PublicationSerial crystallography experiments at X-ray free-electron laser facilities produce massive amounts of data but only a fraction of these data are useful for downstream analysis. Thus, it is essential to differentiate between acceptable and unacceptable data, generally known as ‘hit’ and ‘miss’, respectively. Image classification methods from artificial intelligence, or more specifically convolutional neural networks (CNNs), classify...
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Determination of Thermophysical Parameters Involved in The Numerical Model to Predict the Temperature Field of Cast-In-Place Concrete Bridge Deck
PublicationThe paper dealswith a concept of a practical computationmethod to simulate the temperature distribution in an extradosed bridge deck. The main goal of the study is to develop a feasible model of hardening of concrete consistent with in-situ measurement capabilities. The presented investigations include laboratory tests of high performance concrete, measurements of temperature evolution in the bridge deck and above all, numerical...
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Speed estimation of a car at impact with a W-beam guardrail using numerical simulations and machine learning
PublicationThis paper aimed at developing a new method of estimating the impact speed of a passenger car at the moment of a crash into a W-beam road safety barrier. The determination of such a speed based on the accident outcomes is demanding, because often there is no access to full accident data. However, accurate determination of the impact speed is one of the key elements in the reconstruction of road accidents. A machine learning algorithm...
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Simple empirical formula to estimate the main geomechanical parameters of preplaced aggregate concrete and conventional concrete
PublicationPreplaced aggregate concrete (PAC) or two-stage concrete is a specific type of concrete successfully employed in many projects including underwater concrete structures, massive concrete structures, structures made of reinforced concrete, and improvement of concrete structures. PAC is significantly different than the conventional concrete. In this type of concrete, aggregates are initially poured into the mold, the voids between...
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Properties of Old Concrete Built in the Former Leipziger Palace
PublicationThis research aims to determine the mechanical, chemical, and physical properties of old concrete used in the former Leipziger Palace in Wrocław, Poland. The cylindrical specimens were taken from the basement concrete walls using a concrete core borehole diamond drill machine. The determination of the durability and strength of old concrete was based on specified chosen properties of the old concrete obtained through the following...
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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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Effectiveness of various types of coating materials applied in reinforced concrete exposed to freeze–thaw cycles and chlorides
PublicationThis study assesses the durability of coated and uncoated concrete surfaces protected with four different coating materials: water-soluble (BW), solvent-based (BR), mineral (MI), and epoxy (EP). The durability assessment includes evaluating the absorption rate of water, pull-off adhesion strength, and coating material thickness. Concrete samples were subjected to immersion in regular water and a 7% urea solution, followed by...
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Effectiveness of various types of coating materials applied in reinforced concrete exposed to freeze–thaw cycles and chlorides
PublicationThis study assesses the durability of coated and uncoated concrete surfaces protected with four Different coating materials: water-soluble (BW), solvent-based (BR), mineral (MI), and epoxy (EP). The durability assessment includes evaluating the absorption rate of water, pull-of adhesion strength, and coating material thickness. Concrete samples were subjected to immersion in regular water and a 7% urea solution, followed by cyclic...
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Study of various machine learning approaches for Sentinel-2 derived bathymetry
PublicationIn recent years precise and up-to-date information regarding seabed depth has become more and more important for companies and institutions that operate on coastlines. While direct, in-situ measurements are performed regularly, they are expensive, time-consuming and impractical to be performed in short time intervals. At the same time, an ever-increasing amount of satellite imaging data becomes available. With these images, it...
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Characterization of fracture process in polyolefin fibre-reinforced concrete using ultrasonic waves and digital image correlation
PublicationThis study explores the monitoring of the fracture process in concrete beams and aims to characterize the evolution of damage in polyolefin fibre-reinforced concrete beams by utilizing the integrated application of two measurement techniques, digital image correlation and ultrasonic testing. The interpretation of registered wave time histories data was provided by the calculation of the magnitude-phase-composite metrics. An efficient...
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Assessment Of the Relevance of Best Practices in The Development of Medical R&D Projects Based on Machine Learning
PublicationMachine learning has emerged as a fundamental tool for numerous endeavors within health informatics, bioinformatics, and medicine. However, novices among biomedical researchers and IT developers frequently lack the requisite experience to effectively execute a machine learning project, thereby increasing the likelihood of adopting erroneous practices that may result in common pitfalls or overly optimistic predictions. The paper...
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Remote sensing and photogrammetry techniques in diagnostics of concrete structures
PublicationRecently laser scanning technologies become widely used in many areas of the modern economy. In the following paper authors show a potential spectrum of use Terrestrial Laser Scanning (TLS) in diagnostics of reinforced concrete elements. Based on modes of failure analysis of reinforcement concrete beam authors describe downsides and advantages of adaptation of terrestrial laser scanning to this purpose, moreover reveal under which...
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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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Chemical and Mechanical Properties of 70-Year-Old Concrete
PublicationThe aim of this research is to determine the durability and strength of concrete continuous footing based on the chosen mechanical, physical, and chemical properties of the concrete. The presented investigations constitute some opinions from experts on the bearing capacity of concrete continuous footing and the possibilities of carrying additional loads and extended working life. The cylindrical specimens were taken from continuous...
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Komputerowy model 3D stawu biodrowego
PublicationW pracy przedstawiono stworzony w programie ANSYS komputerowy model 3D stawu biodrowego. Model wykonano w oparciu o budowę anatomiczną oraz zebrane dane dotyczące stałych materiałowych kości i elementów chrzęstnych. Analiza i porównanie modelu biochemicznego, lepkosprężystego, mieszanego oraz molekularno – agregacyjnego służy ułatwieniu stworzenia modelu najbliższego rzeczywistości, który można by wykorzystać w projektowaniu endoprotez...
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Proceedings of the fib Symposium 2019: Concrete - Innovations in Materials, Design and Structures 2019
PublicationDesigning a concrete mix is a process of synthesizing many components, it is not a simple process and requires extensive technical knowledge. The design process itself focuses on obtaining the required strength of concrete. Very often designing a concrete mix takes into account the need to maintain the proper water-demand and frost-resistance features. The parameters that influence the concrete class most significantly are the...
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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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Blended Learning Model for Computer Techniques for Students of Architecture
PublicationAbstract: The article summarizes two-year experience of implementing hybrid formula for teaching Computer Techniques at the Faculty of Architecture at the Gdansk University of Technology. Original educational e-materials, consisting of video clips, text and graphics instructions, as well as links to online resources are embedded in the university e-learning educational platform. The author discusses technical constraints associated...
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Personalized prediction of the secondary oocytes number after ovarian stimulation: A machine learning model based on clinical and genetic data
PublicationControlled ovarian stimulation is tailored to the patient based on clinical parameters but estimating the number of retrieved metaphase II (MII) oocytes is a challenge. Here, we have developed a model that takes advantage of the patient’s genetic and clinical characteristics simultaneously for predicting the stimulation outcome. Sequence variants in reproduction-related genes identified by next-generation sequencing were matched...
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A machine learning approach to classifying New York Heart Association (NYHA) heart failure
PublicationAccording to the European Society of Cardiology, globally the number of patients with heart failure nearly doubled from 33.5 million in 1990 to 64.3 million in 2017, and is further projected to increase dramatically in this decade, still remaining a leading cause of morbidity and mortality. One of the most frequently applied heart failure classification systems that physicians use is the New York Heart Association (NYHA) Functional...
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Evaluation of Machine Learning Methods for the Experimental Classification and Clustering of Higher Education Institutions
PublicationHigher education institutions have a big impact on the future of skills supplied on the labour market. It means that depending on the changes in labour market, higher education institutions are making changes to fields of study or adding new ones to fulfil the demand on labour market. The significant changes on labour market caused by digital transformation, resulted in new jobs and new skills. Because of the necessity of computer...
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COVID-19 severity forecast based on machine learning and complete blood count data
PublicationProper triage of COVID-19 patients is a key factor in eective case management, especially with limited and insucient resources. In this paper, we propose a machine-aided diagnostic system to predict how badly a patient with COVID-19 will develop disease. The prognosis of this type is based on the parameters of commonly used complete blood count tests, which makes it possible to obtain data from a wide range of patients.We chose...
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COVID-19 severity forecast based on machine learning and complete blood count data
PublicationProper triage of COVID-19 patients is a key factor in eective case management, especially with limited and insucient resources. In this paper, we propose a machine-aided diagnostic system to predict how badly a patient with COVID-19 will develop disease. The prognosis of this type is based on the parameters of commonly used complete blood count tests, which makes it possible to obtain data from a wide range of patients.We chose...
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Integrating Experience-Based Knowledge Representation and Machine Learning for Efficient Virtual Engineering Object Performance
PublicationMachine learning and Artificial Intelligence have grown significant attention from industry and academia during the past decade. The key reason behind interest is such technologies capabilities to revolutionize human life since they seamlessly integrate classical networks, networked objects and people to create more efficient environments. In this paper, the Knowledge Representation technique of Set of Experience...
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3D Computer Model of the Hip Joint Cartilage
PublicationThis paper presents 3D computer model of the hip joint cartilage in the ANSYS program. Model is made on the basis of anatomy and collected data on the material constants of bone and cartilage components. Analysis and comparison of biochemical model, viscoelastic and molecular mixed - aggregation serves to facilitate the creation of the next model of reality, which could be used in the design of joint prostheses. The correctness...
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Optical method supported by machine learning for urinary tract infection detection and urosepsis risk assessment
PublicationThe study presents an optical method supported by machine learning for discriminating urinary tract infections from an infection capable of causing urosepsis. The method comprises spectra of spectroscopy measurement of artificial urine samples with bacteria from solid cultures of clinical E. coli strains. To provide a reliable classification of results assistance of 27 algorithms was tested. We proved that is possible to obtain...
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Preeclampsia Risk Prediction Using Machine Learning Methods Trained on Synthetic Data
PublicationThis paper describes a research study that investigates the use of machine learning algorithms on synthetic data to classify the risk of developing preeclampsia by pregnant women. Synthetic datasets were generated based on parameter distributions from three real patient studies. Four models were compared: XGBoost, Support Vector Machine (SVM), Random Forest, and Explainable Boosting Machines (EBM). The study found that the XGBoost...
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Three-dimensional printed trachea helps to design tailored treatment for tracheobronchomalacia
PublicationTracheobronchomalacia is a rare respiratory disease that is manifesting by impaired ventilation with expiratory collapse of the tracheal wall due to softening of the supporting cartilage and hypotonia of myoelastic elements [1]. Surgery is the mainstay of treatment. We report the case of 39 -year old man with exacerbation of chronic respiratory distress. The membranous wall of the trachea and the large bronchi was stretched to...
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Optical method supported by machine learning for dynamics of C‐reactive protein concentrations changes detection in biological matrix samples
PublicationIn this article we present the novel spectroscopy method supported with machine learning for real-time detection of infectious agents in wastewater. In the case of infectious diseases, wastewater monitoring can be used to detect the presence of inflammation biomarkers, such as the proposed C-reactive protein, for monitoring inflammatory conditions and mass screening during epidemics for early detection in communities of concern,...
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Experimental Study of Hardened Young’s Modulus for 3D Printed Mortar
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Experimental tuning of AuAg nanoalloy plasmon resonances assisted by machine learning method
PublicationPlasmonic nanostructures based on AuAg nanoalloys were fabricated by thermal annealing of metallic films in an argon atmosphere. The nanoalloys were chosen because they can extend the wavelength range in which plasmon resonance occurs and thus allow the design of plasmonic platforms with the desired parameters. The influence of initial fabrication parameters and experimental conditions on the formation of nanostructures was investigated....
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Monitoring of concrete curing in extradosed bridge supported by numerical simulation
PublicationThe paper describes a mathematical model of concrete curing taking into account kinetics of setting reactions. The numerical model is implemented in the author’s program that was used to monitor thermal effects recorded in the concrete bottom plate of the extradosed bridge. Numerical approach was verified by experimental measurements and used for assessment of the current compressive strength due to degree of hydration of fresh...
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Corrosion behavior of concrete produced with diatomite and zeolite exposed to chlorides
PublicationChloride induced reinforcement corrosion is widely accepted to be the most frequent mechanism causing premature degradation of reinforced concrete structures. The electrochemical impedance of reinforcing steel in diatomite- and zeolite-containing concrete exposed to sodium chloride was assessed. Chemical, physical and mineralogical properties of three concrete samples (20% diatomite, 20% zeolite, and a reference containing neither)...
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3-D finite-difference time-domain modelling of ground penetrating radar for identification of rebars in complex reinforced concrete structures
PublicationThis paper presents numerical and experimental investigations to identify reinforcing bars using the ground penetrating radar (GPR) method. A novel element of the paper is the inspection of different arrangements of reinforcement bars. Two particular problems, i.e. detection of few adjacent transverse bars and detection of a longitudinal bar located over or under transverse reinforcement, have been raised. An attention was also...
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Real and Virtual Instruments in Machine Learning – Training and Comparison of Classification Results
PublicationThe continuous growth of the computing power of processors, as well as the fact that computational clusters can be created from combined machines, allows for increasing the complexity of algorithms that can be trained. The process, however, requires expanding the basis of the training sets. One of the main obstacles in music classification is the lack of high-quality, real-life recording database for every instrument with a variety...
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Fatigue Performance of Double-Layered Asphalt Concrete Beams Reinforced with New Type of Geocomposites
PublicationThe reinforcement of asphalt layers with geosynthetics has been used for several decades, but proper evaluation of the influence of these materials on pavement fatigue life is still a challenging task. The presented study investigates a novel approach to the reinforcement of asphalt layers using a new type of geogrid composite, in which square or hexagonal polypropylene stiff monolithic paving grid with integral junctions is bonded...
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MagMax: Leveraging Model Merging for Seamless Continual Learning
PublicationThis paper introduces a continual learning approach named MagMax, which utilizes model merging to enable large pre-trained models to continuously learn from new data without forgetting previously acquired knowledge. Distinct from traditional continual learning methods that aim to reduce forgetting during task training, MagMax combines sequential fine-tuning with a maximum magnitude weight selection for effective knowledge integration...
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DNAffinity: a machine-learning approach to predict DNA binding affinities of transcription factors
PublicationWe present a physics-based machine learning approach to predict in vitro transcription factor binding affinities from structural and mechanical DNA properties directly derived from atomistic molecular dynamics simulations. The method is able to predict affinities obtained with techniques as different as uPBM, gcPBM and HT-SELEX with an excellent performance, much better than existing algorithms. Due to its nature, the method can...
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Effect of steel fibres on concrete behavior in 2D and 3D simulations using lattice model.
PublicationW artykule przedstawiono wyniki numerycznej symulacji betonu zbrojonego włóknami stalowymi. Beton został opisany w skali mezo jako materiał 3-fazowy przy zastosowaniu modelu sieciowego. Obliczenia wykonano dla rozciągania jednoosiowego. Porównano ze sobą wyniki dwu- i trójwymiarowe.
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Electrochemical investigations of conductive coatings applied as anodes in cathodic protection of reinforced concrete
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Solubility of dapsone in deep eutectic solvents: Experimental analysis, molecular insights and machine learning predictions
PublicationBackground. Dapsone (DAP) is an anti-inflammatory and antimicrobial active pharmaceutical ingredient used to treat, e.g., AIDS-related diseases. However, low solubility is a feature hampering its efficient use. Objectives. First, deep eutectic solvents...
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Machine learning approach to packaging compatibility testing in the new product development process
PublicationThe paper compares the effectiveness of selected machine learning methods as modelling tools supporting the selection of a packaging type in new product development process. The main goal of the developed model is to reduce the risk of failure in compatibility tests which are preformed to ensure safety, durability, and efficacy of the finished product for the entire period of its shelf life and consumer use. This kind of testing...
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Rediscovering Automatic Detection of Stuttering and Its Subclasses through Machine Learning—The Impact of Changing Deep Model Architecture and Amount of Data in the Training Set
PublicationThis work deals with automatically detecting stuttering and its subclasses. An effective classification of stuttering along with its subclasses could find wide application in determining the severity of stuttering by speech therapists, preliminary patient diagnosis, and enabling communication with the previously mentioned voice assistants. The first part of this work provides an overview of examples of classical and deep learning...
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Investigations on strength and fracture in RC beams scaled along height or length
PublicationThe objective of the present paper is to identify experimentally and theoretically differing failure mechanisms in reinforced concrete beams subjected to four-point bending for a separate variation of the depth and length at the constant thickness. Experiments were performed on reinforced concrete beams under four-point bending. Different failure mechanisms included steel yielding, diagonal tension or shear- compression depending...
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Seismic probabilistic assessment of steel and reinforced concrete structures including earthquake-induced pounding
PublicationRecent earthquakes demonstrate that prioritizing the retrofitting of buildings should be of the utmost importance for enhancing the seismic resilience and structural integrity of urban structures. To have a realistic results of the pounding effects in modeling process of retrofitting buildings, the present research provides seismic Probability Factors (PFs), which can be used for estimating collision effects without engaging in...