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Wyniki wyszukiwania dla: BUILDINGS, VIBRATIONS, MACHINE LEARNING, NUMERICAL ALGORITHM
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A Proposed Machine Learning Model for Forecasting Impact of Traffic-Induced Vibrations on Buildings
PublikacjaTraffic-induced vibrations may cause various damages to buildings located near the road, including cracking of plaster, cracks in load-bearing elements or even collapse of the whole structure. Measurements of vibrations of real buildings are costly and laborious. Therefore the aim of the research is to propose the original numerical algorithm which allows us to predict, with high probability, the nega-tive dynamic impact of traffic-induced...
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Application of Support Vector Machine for Determination of Impact of Traffic-Induced Vibrations on Buildings
PublikacjaThe aim of the article is to present an algorithm of Support Vector Machine created to forecast the impact of traffic-induced vibrations on residential buildings. The method is designed to classify the object into one of two classes. The classification into the first class means that there is no impact of vibrations on the building, while classification to the second class indicates the possible influence and suggests the execution...
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Predicting the impact of traffic–induced vibrations on buildings using artificial neural networks
PublikacjaTraffic–induced vibrations may constitute a considerable load to a building, cause cracking of plaster, cracks in load–bearing elements or even a global structural collapse of the whole structure [1-4]. Vibrations measurements of real structures are costly and laborious, not justified in all cases. The aim of the paper is to create an original algorithm, to predict the negative dynamic impact on the examined residential building...
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The Idea of Using Bayesian Networks in Forecasting Impact of Traffic-Induced Vibrations Transmitted through the Ground on Residential Buildings
PublikacjaTraffic–induced vibrations may constitute a considerable load to buildings. In this paper, vibrations transmitted through the ground caused by wheeled vehicles are considered. This phenomenon may cause cracking of plaster, cracks in load-bearing elements or even, in extreme cases, collapse of the whole structure. Measurements of vibrations of real structures are costly and laborious. Therefore, the aim of the present paper is to...
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Traffic-induced vibrations. The impact on buildings and people
PublikacjaTraffic-induced vibrations have recently been of major concern to engineers as one of the aspects of so called physical environmental pollution. The interest is related to the observations of serious negative effects of such kind of vibrations on buildings and their inhabitants. Traffic-induced vibrations may cause plaster cracks, structural damage and even failure and collapse of the structure. They may also be the reason of serious...
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The application of neural networks in forecasting the influence of traffic-induced vibrations on residential buildings
PublikacjaTraffic-induced vibrations may cause the cracking of plaster, damage to structural elements and, in extreme cases, may even lead to the structural collapse of residential buildings. The aim of this article is to analyse the effectiveness of a method of forecasting the impact of vibrations on residential buildings using the concept of artificial intelligence. The article presents several alternative forecasting systems for which...
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Comparing the Effectiveness of ANNs and SVMs in Forecasting the Impact of Traffic-Induced Vibrations on Building
PublikacjaTraffic - induced vibrations may cause damage to structural elements and may even lead to structural collapse. The aim of the article is to compare the effectiveness of algorithms in forecasting the impact of vibrations on buildings using the Machine Learning (ML) methods. The paper presents two alternative approaches by using Artificial Neural Networks (ANNs) and Support Vector Machines (SVMs). Factors that may affect traffic-induced...
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Assessment of Failure Occurrence Rate for Concrete Machine Foundations Used in Gas and Oil Industry by Machine Learning
PublikacjaConcrete machine foundations are structures that transfer loads from machines in operation to the ground. The design of such foundations requires a careful analysis of the static and dynamic effects caused by machine exploitation. There are also other substantial differences between ordinary concrete foundations and machine foundations, of which the main one is that machine foundations are separated from the building structure....
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Active Learning on Ensemble Machine-Learning Model to Retrofit Buildings Under Seismic Mainshock-Aftershock Sequence
PublikacjaThis research presents an efficient computational method for retrofitting of buildings by employing an active learning-based ensemble machine learning (AL-Ensemble ML) approach developed in OpenSees, Python and MATLAB. The results of the study shows that the AL-Ensemble ML model provides the most accurate estimations of interstory drift (ID) and residual interstory drift (RID) for steel structures using a dataset of 2-, to 9-story...
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Machine learning-based seismic response and performance assessment of reinforced concrete buildings
PublikacjaComplexity and unpredictability nature of earthquakes makes them unique external loads that there is no unique formula used for the prediction of seismic responses. Hence, this research aims to implement the most well-known Machine Learning (ML) methods in Python software to propose a prediction model for seismic response and performance assessment of Reinforced Concrete Moment-Resisting Frames (RC MRFs). To prepare 92,400 data...
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MACHINE VISION DETECTION OF THE CIRCULAR SAW VIBRATIONS
PublikacjaDynamical properties of rotating circular saw blades are crucial for both production quality and personnel safety. This paper presents a novel method for monitoring circular saw vibrations and deviations. A machine vision system uses a camera and a laser line projected on the saw’s surface to estimate vibration range. Changes of the dynamic behaviour of the saw were measured as a function of the rotational speed. The critical rotational...
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Machine learning-based seismic fragility and seismic vulnerability assessment of reinforced concrete structures
PublikacjaMany studies have been performed to put quantifying uncertainties into the seismic risk assessment of reinforced concrete (RC) buildings. This paper provides a risk-assessment support tool for purpose of retrofitting and potential design strategies of RC buildings. Machine Learning (ML) algorithms were developed in Python software by innovative methods of hyperparameter optimization, such as halving search, grid search, random...
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Optimization-based stacked machine-learning method for seismic probability and risk assessment of reinforced concrete shear walls
PublikacjaEfficient seismic risk assessment aids decision-makers in formulating citywide risk mitigation plans, providing insights into building performance and retrofitting costs. The complexity of modeling, analysis, and post-processing of the results makes it hard to fast-track the seismic probabilities, and there is a need to optimize the computational time. This research addresses seismic probability and risk assessment of reinforced...
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Polymeric Bearings as a new base isolation system suitable for mitigating machine-induced vibrations
PublikacjaThe present paper summarizes the preliminary results of the experimental shaking table investigation conducted in order to verify the effectiveness of a new base isolation system consisting of Polymeric Bearings in reducing strong horizontal machine-induced vibrations. Polymeric Bearing considered in the present study is a prototype base isolation system, which was constructed with the use of a specially prepared flexible polymer...
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Machine learning-based prediction of residual drift and seismic risk assessment of steel moment-resisting frames considering soil-structure interaction
PublikacjaNowadays, due to improvements in seismic codes and computational devices, retrofitting buildings is an important topic, in which, permanent deformation of buildings, known as Residual Interstory Drift Ratio (RIDR), plays a crucial role. To provide an accurate yet reliable prediction model, 32 improved Machine Learning (ML) algorithms were considered using the Python software to investigate the best method for estimating Maximum...
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Earthquake-Induced Pounding Between Asymmetric Steel Buildings
PublikacjaEarthquake-induced pounding between buildings has been the subject of numerous numerical and experimental studies in the resent years. The phenomenon may cause severe damage to structural elements as well as may also lead to the total collapse of colliding structures. A major reason leading to pounding between adjacent, insufficiently separated buildings results from the differences in their dynamic properties. The aim of this...
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Seismic response and performance prediction of steel buckling-restrained braced frames using machine-learning methods
PublikacjaNowadays, Buckling-Restrained Brace Frames (BRBFs) have been used as lateral force-resisting systems for low-, to mid-rise buildings. Residual Interstory Drift (RID) of BRBFs plays a key role in deciding to retrofit buildings after seismic excitation; however, existing formulas have limitations and cannot effectively help civil engineers, e.g., FEMA P-58, which is a conservative estimation method. Therefore, there is a need to...
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Earthquake-induced pounding between asymmetric steel buildings
PublikacjaEarthquake-induced pounding between buildings has been the subject of numerous numerical and experimental studies in the resent years. The phe-nomenon may cause severe damage to structural elements as well as may also lead to the total collapse of colliding structures. A major reason leading to pounding between adjacent, insufficiently separated buildings results from the differences in their dynamic properties. The aim of this...
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Modeling of wood frame structures with different insulation materials under damaging dynamic loading
PublikacjaWood frame buildings are very popular in regions that are exposed to different dynamic excitations, such as damaging earthquakes. Their seismic resistance is really important in order to prevent structural damages and human losses. This paper presents the results of advanced numerical investigation carried out using the FEM. Based on the models of wall panels, the numerical model of real structure of the wood frame building has...
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Vibration testing in buildings and safety of their operation
PublikacjaThe paper presents the issue of vibrations in residential buildings located near roads. It describes the measurement methodology and criteria for assessing the impact of vibrations generated by passing trucks. The article specifies a method to establish the impact on the operation of the examined facilities and it promotes the idea of employing a Bayesian network to determine probabilistically the level of risk to single-family...
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Diagnosis of damages in family buildings using neural networks
PublikacjaThe article concerns a problem of damages in family buildings, which result from traffic-induced vibrations. These vibrations arise from various causes and their size is influenced by many factors. The most important is the type of a road, type and weight of vehicles that run on the road, type and condition of the road surface, the distance from the house to the source of vibrations and many others which should be taken into account....
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Earthquake-induced pounding between equal height multi-storey buildings considering soil-structure interaction
PublikacjaThe present paper investigates the coupled effect of the supporting soil flexibility and pounding between neighbouring, insufficiently separated equal height buildings under earthquake excitation. Two adjacent three-storey structures, modelled as inelastic lumped mass systems with different structural characteristics, have been considered in the study. The models have been excited using a suit of ground motions with different peak...
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Experimental and computational study on mechanical behaviour of carpentry corner log joints
PublikacjaThis work concerns experimental and numerical research on carpentry joints used in historic wooden buildings in southeastern Poland and western Ukraine. These structures are mainly sacred buildings, and the types of corner log joints characteristic of this region are primarily saddle-notch and dovetail joints; thus, these two types of joints were analysed in this study. The modelling of historic timber structures is a complex...
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Non-linear behaviour of base-isolated building supported on flexible soil under damaging earthquakes
PublikacjaSeismic isolation is a strategy to reduce damage of structures exposed to devastating earthquake excitations. Isolation systems, applied at the base of buildings, lower the fundamental frequency of the structure below the range of dominant frequencies of the ground motion as well as allow to dissipate more energy during structural vibrations. The effectiveness of the base-isolated buildings in damage reduction has been confirmed...
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The reduction of vibrations in circular sawing machines
PublikacjaThe presented in this paper the main objectives of the research were to explore vibrations signals of the main spindle system, the machine tool body and a circular saw to extract informative features for assessment of the designs of the panel saw Fx3 and its follower Fx550.Even though the main spindle of the new table sliding saw Fx550 has its rotational speeds larger about 20% in comparison to the Fx3, peak values of the vibrational...
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EMPIRICAL ASSESMENT OF THE MAIN DRIVING SYSTEM OF THE CIRCULAR SAWING MACHINE
PublikacjaThe producers of panel saws tend to improve sawing accuracy and minimise a level of vibrations, to increase their competitiveness at the market. Mechanical vibrations in the main saw driving system, which level depend on a plethora independent factors, may really affect sawing accuracy and general machine tool vibrations. The objective of the research was to explore vibrations signals of the main spindle system, and to extract...
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Prevention of resonance oscillations in gear mechanisms using non-circular gears
PublikacjaOne of the main disadvantages of gear mechanisms is the occurrence of noise and vibrations. This study investigated the applicability of non-circular gears for preventing resonance oscillations in gear mechanisms. The influence of a small deviation of the gear centrodes from the nominal circles on kinematic and oscillatory characteristics was analysed. It was shown that a larger deviation results in a smaller resonance amplitude...
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Effect of Pendolino high-speed rail on the structure of buildings located the proximity of the railway tracks
PublikacjaThe following research focuses on the dynamic analysis of the impact of the high-speed train inducted vibrations on the structures located near railway tracks. The office complex chosen as the subject of calculations is located in the northern part of Poland, in Gdańsk, in the proximity of Pendolino, the high speed train route. The high speed trains are the response for the growing needs for more efficient railway system. However...
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Seismic Response of High-Rise Buildings Equipped with Base Isolation and Non-Traditional Tuned Mass Dampers
PublikacjaOne of the methods in structural control is the application of combinational control systems in order to reduce the response of structures during earthquakes. The aim of the present paper is to verify the effectiveness of a hybrid control strategy, combining base isolation and non-traditional tuned mass dampers (TMDs) (i.e., TMDs with dashpots directly connected to the ground) in suppressing structural vibrations of high-rise buildings....
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Study on Polymer Elements for Mitigation of Earthquake-Induced Pounding Between Buildings in Complex Arrangements
PublikacjaPounding between neighboring structures during seismic events has been revealed as one of the most commonly observed reasons for severe damage or even total collapse of the adjacent buildings. Therefore, pounding effects have recently become an issue of great interest of many numerical and experimental investigations in many earthquake-prone regions of the world. It has also been observed that the differences in dynamic characteristics...
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Experimental and numerical study on deformed steel columns subjected to impact load during earthquakes
PublikacjaThe soft-storey failure is one of the most typical types of damage observed in buildings during earthquakes. The failure of an upper soft storey of a structure results in large impact load acting on the lower floors and if the resistance of the structural members of the lower storeys is not sufficient it may further lead to progressive collapse of the whole building. The aim of the present paper is to investigate the dynamic behaviour...
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Agricultural products' storage control system
PublikacjaThe paper discusses the idea and the design of a remote control system for storage management of agricultural products which temperature may rise as the result of biological processes during the storage. An actual potatoes storehouse is discussed as an application for the proposed automation system. Because of existing buildings and infrastructure at the farm, wireless data transfer system has been proposed for communication between...
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Speed estimation of a car at impact with a W-beam guardrail using numerical simulations and machine learning
PublikacjaThis 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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Earthquake-Induced Pounding of Medium-to-High-Rise Base-Isolated Buildings
PublikacjaDuring earthquakes, out-of-phase vibrations in adjacent buildings with limited distance may cause pounding between them. In recent years, the use of seismic isolation has expanded considerably as an effective approach to reduce seismic damage. However, the isolated building experiences large displacements during earthquakes, and there is a possibility of collisions with adjacent structures. The research on earthquake-induced pounding...
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Experimentally Aided Operational Virtual Prototyping to Predict Best Clamping Conditions for Face Milling of Large-Size Structures
PublikacjaVibrations occurring during milling operations are one of the main issues disturbing the pursuit of better efficiency of milling operations and product quality. Even in the case of a stable cutting process, vibration reduction is still an important goal. One of the possible solutions to obtain it is selection of the favorable conditions for clamping the workpiece to the machine table. In this paper, a method for predicting and...
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TensorHive: Management of Exclusive GPU Access for Distributed Machine Learning Workloads
PublikacjaTensorHive is a tool for organizing work of research and engineering teams that use servers with GPUs for machine learning workloads. In a comprehensive web interface, it supports reservation of GPUs for exclusive usage, hardware monitoring, as well as configuring, executing and queuing distributed computational jobs. Focusing on easy installation and simple configuration, the tool automatically detects the available computing...
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Speech Analytics Based on Machine Learning
PublikacjaIn this chapter, the process of speech data preparation for machine learning is discussed in detail. Examples of speech analytics methods applied to phonemes and allophones are shown. Further, an approach to automatic phoneme recognition involving optimized parametrization and a classifier belonging to machine learning algorithms is discussed. Feature vectors are built on the basis of descriptors coming from the music information...
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Machine Learning in Multi-Agent Systems using Associative Arrays
PublikacjaIn this paper, a new machine learning algorithm for multi-agent systems is introduced. The algorithm is based on associative arrays, thus it becomes less complex and more efficient substitute of artificial neural networks and Bayesian networks, which is confirmed by performance measurements. Implementation of machine learning algorithm in multi-agent system for aided design of selected control systems allowed to improve the performance...
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Study on polymer elements for mitigation of earthquake-induced pounding between buildings in complex arrangements
PublikacjaPounding between neighbouring buildings during earthquakes has been identified as one of the reasons for substantial damage or even total collapse of colliding structures, so it has been the subject of numerous studies in the recent years. A major reason leading to interactions between adjacent, insufficiently separated structures results from the differences in their dynamic properties. The problem is much more complicated for...
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Data Reduction Algorithm for Machine Learning and Data Mining
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Designing acoustic scattering elements using machine learning methods
PublikacjaIn the process of the design and correction of room acoustic properties, it is often necessary to select the appropriate type of acoustic treatment devices and make decisions regarding their size, geometry, and location of the devices inside the room under the treatment process. The goal of this doctoral dissertation is to develop and validate a mathematical model that allows predicting the effects of the application of the scattering...
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Raw data of AuAg nanoalloy plasmon resonances used for machine learning method
Dane BadawczeRaw data used for machine learning process. UV-vis measurements of AuAg alloyed nanostructures created from thin films. Plasmonic band position dependence on fabrication parameters. Small presentation reviewing achieved structures and their properties.
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An algorithm for selecting a machine learning method for predicting nitrous oxide emissions in municipal wastewater treatment plants
PublikacjaThis study presents an advanced algorithm for selecting machine learning (ML) models for nitrous oxide (N2O) emission prediction in wastewater treatment plants (WWTPs) employing the activated sludge process. The examined ML models comprised multivariate adaptive regression spline (MARS), support vector machines (SVM), and extreme gradient boosting (XGboost). The study explores the concept that involves new criteria to select the...
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How Machine Learning Contributes to Solve Acoustical Problems
PublikacjaMachine learning is the process of learning functional relationships between measured signals (called percepts in the artificial intelligence literature) and some output of interest. In some cases, we wish to learn very specific relationships from signals such as identifying the language of a speaker (e.g. Zissman, 1996) which has direct applications such as in call center routing or performing a music information retrieval task...
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Machine Learning Techniques in Concrete Mix Design
PublikacjaConcrete mix design is a complex and multistage process in which we try to find the best composition of ingredients to create good performing concrete. In contemporary literature, as well as in state-of-the-art corporate practice, there are some methods of concrete mix design, from which the most popular are methods derived from The Three Equation Method. One of the most important features of concrete is compressive strength, which...
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Introduction to the special issue on machine learning in acoustics
PublikacjaWhen we started our Call for Papers for a Special Issue on “Machine Learning in Acoustics” in the Journal of the Acoustical Society of America, our ambition was to invite papers in which machine learning was applied to all acoustics areas. They were listed, but not limited to, as follows: • Music and synthesis analysis • Music sentiment analysis • Music perception • Intelligent music recognition • Musical source separation • Singing...
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Advancing Solar Energy: Machine Learning Approaches for Predicting Photovoltaic Power Output
PublikacjaThis research is primarily concentrated on predicting the output of photovoitaic power, an essential field in the study of renewable energy. The paper comprehensively reviews various forecasting methodologies, transitioning from conventional physical and statistical methods to advanced machine learning (ML) techniques. A significant shift has been observed from traditional point forecasting to machine learning-based forecasting...
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Machine Learning and Electronic Noses for Medical Diagnostics
PublikacjaThe need for noninvasive, easy-to-use, and inexpensive methods for point-of-care diagnostics of a variety of ailments motivates researchers to develop methods for analyzing complex biological samples, in particular human breath, that could aid in screening and early diagnosis. There are hopes that electronic noses, that is, devices based on arrays of semiselective or nonselective chemical sensors, can fill this niche. Electronic...
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Predictions of cervical cancer identification by photonic method combined with machine learning
PublikacjaCervical cancer is one of the most commonly appearing cancers, which early diagnosis is of greatest importance. Unfortunately, many diagnoses are based on subjective opinions of doctors—to date, there is no general measurement method with a calibrated standard. The problem can be solved with the measurement system being a fusion of an optoelectronic sensor and machine learning algorithm to provide reliable assistance for doctors...
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Predicting emotion from color present in images and video excerpts by machine learning
PublikacjaThis work aims at predicting emotion based on the colors present in images and video excerpts using a machine-learning approach. The purpose of this paper is threefold: (a) to develop a machine-learning algorithm that classifies emotions based on the color present in an image, (b) to select the best-performing algorithm from the first phase and apply it to film excerpt emotion analysis based on colors, (c) to design an online survey...