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Search results for: REINFORCED CONCRETE SHEAR WALL MACHINE LEARNING ALGORITHM SEISMIC FAILURE PROBABILITY OPTIMIZATION ALGORITHM SEISMIC PERFORMANCE CURVE SEISMIC RETROFIT
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Machine learning-based prediction of preplaced aggregate concrete characteristics
PublicationPreplaced-Aggregate Concrete (PAC) is a type of preplaced concrete where coarse aggregate is placed in the mold and a Portland cement-sand grout with admixtures is injected to fill the voids. Due to the complex nature of PAC, many studies were conducted to determine the effects of admixtures and the compressive and tensile strengths of PAC. Considering that a prediction tool is needed to estimate the compressive and tensile...
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Machine learning-based prediction of preplaced aggregate concrete characteristics
PublicationPreplaced-Aggregate Concrete (PAC) is a type of preplaced concrete where coarse aggregate is placed in the mold and a Portland cement-sand grout with admixtures is injected to fill the voids. Due to the complex nature of PAC, many studies were conducted to determine the effects of admixtures and the compressive and tensile strengths of PAC. Considering that a prediction tool is needed to estimate the compressive and tensile strengths...
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Computational Complexity and Its Influence on Predictive Capabilities of Machine Learning Models for Concrete Mix Design
PublicationThe design of concrete mixtures is crucial in concrete technology, aiming to produce concrete that meets specific quality and performance criteria. Modern standards require not only strength but also eco-friendliness and production efficiency. Based on the Three Equation Method, conventional mix design methods involve analytical and laboratory procedures but are insufficient for contemporary concrete technology, leading to overengineering...
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Machine Learning in Multi-Agent Systems using Associative Arrays
PublicationIn 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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Performance evaulation of video object tracking algorithm in autonomous surveillance system
PublicationResults of performance evaluation of a video object tracking algorithm are presented. The method of moving objects detection and tracking is based on background modelling with mixtures of Gaussians and Kalman filters. An emphasis is put on algorithm's efficiency with regards to its settings. Utilized methods of performance evaluation based on comparison of algorithm output to manually prepared reference data are introduced. The...
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Performance evaluation of video object tracking algorithm in autonomous surveillance system
PublicationResults of performance evaluation of a video object tracking algorithm are presented. The method of moving objects detection and tracking is based on background modelling with mixtures of Gaussians and Kalman filters. An emphasis is put on algorithm's efficiency with regards to its settings. Utilized methods of performance evaluation based on comparison of algorithm output to manually prepared reference data are introduced. The...
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Machine Learning Assisted Interactive Multi-objectives Optimization Framework: A Proposed Formulation and Method for Overtime Planning in Software Development Projects
PublicationMachine Learning Assisted Interactive Multi-objectives Optimization Framework: A Proposed Formulation and Method for Overtime Planning in Software Development Projects Hammed A. Mojeed & Rafal Szlapczynski Conference paper First Online: 14 September 2023 161 Accesses Part of the Lecture Notes in Computer Science book series (LNAI,volume 14125) Abstract Software development project requires proper planning to mitigate risk and...
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Machine Learning Algorithm-Based Tool and Digital Framework for Substituting Daylight Simulations In Early- Stage Architectural Design Evaluation
PublicationThe aim of this paper is to examine the new method of obtaining the simulation-based results using backpropagation of errors artificial neural networks. The primary motivation to conduct the research was to determine an alternative, more efficient and less timeconsuming method which would serve to achieve the results of daylight simulations. Three daylight metrics: Daylight Factor, Daylight Autonomy and Daylight Glare Probability have...
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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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Ireneusz Czarnowski Prof.
PeopleIRENEUSZ CZARNOWSKI is a graduate of the Faculty of Electrical Engineering at Gdynia Maritime University. He gained a doctoral degree in the field of computer science at Poznan University of Technology and a postdoctoral degree in the field of computer science at Wroclaw University of Science and Technology. Since 1998 is associated with Gdynia Maritime University, currently is a professor of computer science in the Department...
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Numerically efficient algorithm for compact microwave device optimization with flexible sensitivity updating scheme
PublicationAn efficient trust-region algorithm with flexible sensitivity updating management scheme for electromagnetic (EM)-driven design optimization of compact microwave components is proposed. During the optimization process, updating of selected columns of the circuit response Jacobian is performed using a rank-one Broyden formula (BF) replacing finite differentiation (FD). The FD update is omitted for directions sufficiently well aligned...
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Accuracy improvement of the prestressed concrete structures precise geometry assessment by use of bubble micro-sampling algorithm
PublicationPrestressed concrete structures are well-known technology for a vast period, but nevertheless, this very technology is a leading solution, currently used in construction industry. Prestressed concrete structures have a huge advantage over conventional methods because it uses the properties of concrete in a very efficient way. The main idea behind this technology is to introduce into the cross-section of the structure, the internal...
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Performance Evaluation of the Parallel Codebook Algorithm for Background Subtraction in Video Stream
PublicationA background subtraction algorithm based on the codebook approach was implemented on a multi-core processor in a parallel form, using the OpenMP system. The aim of the experiments was to evaluate performance of the multithreaded algorithm in processing video streams recorded from monitoring cameras, depending on a number of computer cores used, method of task scheduling, image resolution and degree of image content variability....
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Rapid Surrogate-Aided Multi-Criterial Optimization of Compact Microwave Passives Employing Machine Learning and ANNs
PublicationThis article introduces an innovative method for achieving low-cost and reliable multi-objective optimization (MO) of microwave passive circuits. The technique capitalizes on the attributes of surrogate models, specifically artificial neural networks (ANNs), and multi-resolution electromagnetic (EM) analysis. We integrate the search process into a machine learning (ML) framework, where each iteration produces multiple infill points...
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Performance evaluation of the parallel object tracking algorithm employing the particle filter
PublicationAn algorithm based on particle filters is employed to track moving objects in video streams from fixed and non-fixed cameras. Particle weighting is based on color histograms computed in the iHLS color space. Particle computations are parallelized with CUDA framework. The algorithm was tested on various GPU devices: a desktop GPU card, a mobile chipset and two embedded GPU platforms. The processing speed depending on the number...
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Optimal retrofit strategy using viscous dampers between adjacent RC and SMRFs prone to earthquake‑induced pounding
PublicationNowadays, retrofitting-damaged buildings is an important challenge for engineers. Finding the optimal placement of Viscous Dampers (VDs) between adjacent structures prone to earthquake-induced pounding can help designers to implement VDs with optimizing the cost of construction and achieving higher performance levels for both structures. In this research, the optimal placement of linear and nonlinear VDs between the 3-story, 5-story,...
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Shear fracture of longitudinally reinforced concrete beams under bending using Digital Image Correlation and FE simulations with concrete micro-structure based on X-ray micro-computed tomography images
PublicationThe paper presents experimental and numerical investigations of the shear fracture in rectangular concrete beams longitudinally reinforced with steel or basalt bar under quasi-static three point bending. Shear fracture process zone formation and development on the surface of beams was investigated by Digital Image Correlation (DIC) whereas thorough analyses of 3D material micro-structure, air voids, width and curvature of shear...
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Complex Concrete Structures (CE) - 2021/2022
e-Learning CoursesThe following issues in the field of concrete structures will be discussed in the lecture part: Mechanical properties of concrete and reinforcing steel; Calculation of reinforced concrete cross-sections bending; Calculation of reinforced concrete cross-sections shear; Serviceability limit state in reinforced concrete structures; Reinforced concrete slabs, one-way and cross-reinforced; Reinforced concrete stairs; Reinforced...
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Complex Concrete Structures (CE) - 2023/2024
e-Learning CoursesThe following issues in the field of concrete structures will be discussed in the lecture part: Mechanical properties of concrete and reinforcing steel; Calculation of reinforced concrete cross-sections bending; Calculation of reinforced concrete cross-sections shear; Serviceability limit state in reinforced concrete structures; Reinforced concrete slabs, one-way and cross-reinforced; Reinforced concrete stairs; Reinforced...
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Curve Curvature Analysis of a Grain Trajectories in Variable Honing of Cylindrical Holes of Thin Wall Cylinder Liners as a Honing Process Optimization Strategy
PublicationThe main problem of honing of thin wall cylinder liners is a thermal distortion of honed holes. The higher the value of the temperature of the honed workpiece, the greater its holes deformation. The paper presents a method of reducing the temperature occurring in the honing process as a result of the application of a variable honing kinematics conditions with particular emphasis on the analysis of the effect of the value of the...
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Mathematical Modelling of a Seismic Isolation System to Protect Structures during Damaging Earthquakes
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Modeling of a rock fall using the discrete element method and study of the seismic signal
PublicationW artykule przedstawiono opis fal sejsmicznych, zastosowanie dyskretnej metody elementów do opisu obrywu skalnego, opis programów obliczeniowych oraz obliczenia numeryczne wg. podanych programów obliczeniowych.
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Modeling of a rock fall using the discrete element method and study of the seismic signal
PublicationMechanizm dużego spadającego bloku skalnego lub lawiny pozostaje nadal słabo rozpoznany zarówno w zakresie pęknięć jak i procesów propagacji. Jedynie ilościowe dane, które aktualnie są mierzone i uchwytne podczas spadania skały, zarejestrowane są jako sejsmiczne sygnały przez szereg sejsmografów. Właściwości sygnału (amplituda, trwanie, częstotliwość) są wyraźnie powiązane z cechami spadania (masa, wysokość spadania, odległość...
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Response of high voltage disconnector under seismic excitation - experimental and numerical study
PublicationThe efficiency of the energetic infrastructure system is a very import safety issue in the region experienced by the ground motion. The aim of the present paper is to show the results of the experimental and numerical study focused on the earthquake-induced response of the high voltage disconnector, which is an important element of energetic network. First, the impact tests as well as the sweep-sine shaking table tests were conducted....
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Pareto Ranking Bisection Algorithm for Expedited Multi-Objective Optimization of Antenna Structures
PublicationThe purpose of this letter is introduction of a novel methodology for expedited multi-objective design of antenna structures. The key component of the presented approach is fast identification of the initial representation of the Pareto front (i.e., a set of design representing the best possible trade-offs between conflicting objectives) using a Pareto-ranking bisection algorithm. The algorithm finds a discrete set of Pareto-optimal...
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Evaluation of pounding effects between reinforced concrete frames subjected to far-field earthquakes in terms of damage index
PublicationIn this paper, three different damage indexes were used to detect nonlinear damages in two adjacent Reinforced Concrete (RC) structures considering pounding effects. 2-, 4- and 8-story benchmark RC Moment Resisting Frames (MRFs) were selected for this purpose with 60%, 75%, and 100% of minimum separation distance and also without any in-between separation gap. These structures were analyzed using the incremental dynamic analysis...
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Experimental investigations on concrete beams reinforced with CFRP lamellas
PublicationPaper presents experimental investigation made on two concrete beams reinforced with internal Carbon Fibre Reinforced Polymer (CFRP) lamellas (i.e. strips, bands). The reinforcement geometrical arrangement was similar as in normal concrete beams reinforced with steel bars and stirrups. The beams were destroyed by the shear forces, as intended. Obtained load-carrying capacities were lower as expected: below 40% of a calculated value....
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Proximal primal–dual best approximation algorithm with memory
PublicationWe propose a new modified primal–dual proximal best approximation method for solving convex not necessarily differentiable optimization problems. The novelty of the method relies on introducing memory by taking into account iterates computed in previous steps in the formulas defining current iterate. To this end we consider projections onto intersections of halfspaces generated on the basis of the current as well as the previous...
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Magdalena Rucka prof. dr hab. inż.
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Low-Cost Multi-Objective Optimization of Antennas By Means Of Generalized Pareto Ranking Bisection Algorithm
PublicationThis paper introduces a generalized Pareto ranking bisection algorithm for low-cost multi-objective design optimization of antenna structures. The algorithm allows for identifying a set of Pareto optimal sets of parameters (that represent the best trade-offs between considered objectives) by iterative partitioning of the intervals connecting previously found designs and executing a Pareto-ranking-based poll search. The initial...
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Acoustic emission signals in concrete beams under 3-point bending (plain concrete, steel fibre reinforced concrete, steel bar reinforced concrete)
Open Research DataThe DataSet contains the results of the mechanical behaviour of concrete beams with dimensions 40 x 40 x 160 cm3under the 3-point bending. Two concrete mixes, both based on the same design, were produced in the test programme. Mixture #1 was the plain concrete (PC), consisting of cement CEM I 42.5R (380 kg/m3), water (165 kg/m3), aggregate 0/2 mm (648...
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Performance of Watermarking-based DTD Algorithm Under Time-varying Echo Path Conditions
PublicationA novel double-talk detection (DTD) algorithm based on techniques similar to those used for audio signal watermarking was introduced by the authors. The application of the described DTD algorithm within acoustic echo cancellation system is presented. The problem of DTD robustness to time-varying conditions of acoustic echo path is discussed and explanation as to why such conditions occur in practical situations is provided. The...
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Speech Analytics Based on Machine Learning
PublicationIn 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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Relation between benchmark displacement velocity and seismic activity caused by underground longwall exploitation
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Numerical Evaluation of Dynamic Response of a Steel Structure Model under Various Seismic Excitations
PublicationThe present paper reports the results of the study, which was designed to perform a numerical evaluation of dynamic response of a single-storey steel structure model. The experimental model was previously subjected to a number of different earthquake ground motions during an extensive shaking table investigation. The analyzed structure model was considered as a 1-DOF system with lumped parameters, which were determined by conducting...
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Numerical investigation on dynamic response of a steel lattice tower under various seismic events
PublicationThe present paper presents the results of the numerical study designed to investigate the soil-structure flexibility effects on modal parameters (i.e. fundamental frequencies) and time-history analysis response (represented by the top relative displacements) of a 46.8 m high steel lattice tower subjected to a number of ground motions including also one mining tremor. In addition to the fixed-base condition, three different soil...
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Optimization algorithm and filtration using the adaptive TIN model at the stage of initial processing of the ALS point cloud
PublicationAirborne laser scanning (ALS) provides survey results in the form of a point cloud. The ALS point cloud is a source of data used primarily for constructing a digital terrain model (DTM). To generate a DTM, the set of ALS observations must be first subjected to the point cloud processing methodology. A standard methodology is composed of the following stages: acquisition of the ALS data, initial processing (including filtration),...
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A Multi-Fidelity Surrogate-Model-Assisted Evolutionary Algorithm for Computationally Expensive Optimization Problems
PublicationIntegrating data-driven surrogate models and simulation models of different accuracies (or fideli-ties) in a single algorithm to address computationally expensive global optimization problems has recently attracted considerable attention. However, handling discrepancies between simulation models with multiple fidelities in global optimization is a major challenge. To address it, the two major contributions of this paper include:...
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Designing acoustic scattering elements using machine learning methods
PublicationIn 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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A Novel Trust-Region-Based Algorithm with Flexible Jacobian Updates for Expedited Optimization of High-Frequency Structures
PublicationSimulation-driven design closure is mandatory in the design of contemporary high-frequency components. It aims at improving the selected performance figures through adjustment of the structure’s geometry (and/or material) parameters. The computational cost of this process when employing numerical optimization is often prohibitively high, which is a strong motivation for the development of more efficient methods. This is especially...
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A Machine Learning Approach for Estimating Overtime Allocation in Software Development Projects
PublicationOvertime planning in software projects has traditionally been approached with search-based multi-objective optimization algorithms. However, the explicit solutions produced by these algorithms often lack applicability and acceptance in the software industry due to their disregard for project managers' intuitive knowledge. This study presents a machine learning model that learns the preferred overtime allocation patterns from solutions...
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Tool Wear Monitoring Using Improved Dragonfly Optimization Algorithm and Deep Belief Network
PublicationIn recent decades, tool wear monitoring has played a crucial role in the improvement of industrial production quality and efficiency. In the machining process, it is important to predict both tool cost and life, and to reduce the equipment downtime. The conventional methods need enormous quantities of human resources and expert skills to achieve precise tool wear information. To automatically identify the tool wear types, deep...
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Efficient algorithm for blinking LED detection dedicated to embedded systems equipped with high performance cameras
PublicationThis paper presents the concept and implementation of an efficient algorithm for detection of blinking LED or similar signal sources. Algorithm is designed for embedded devices equipped with high performance cameras being a part of an indoor positioning embedded system. An algorithm to be implemented in such a system should be efficient in terms of computational power what is hard to be achieved when large amount of data from camera...
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Satellite Image Classification Using a Hierarchical Ensemble Learning and Correlation Coefficient-Based Gravitational Search Algorithm
PublicationSatellite image classification is widely used in various real-time applications, such as the military, geospatial surveys, surveillance and environmental monitoring. Therefore, the effective classification of satellite images is required to improve classification accuracy. In this paper, the combination of Hierarchical Framework and Ensemble Learning (HFEL) and optimal feature selection is proposed for the precise identification...
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A Proposed Machine Learning Model for Forecasting Impact of Traffic-Induced Vibrations on Buildings
PublicationTraffic-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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Task Assignments in Logistics by Adaptive Multi-Criterion Evolutionary Algorithm with Elitist Selection
PublicationAn evolutionary algorithm with elitist selection has been developed for finding Pareto-optimal task assignments in logistics. A multi-criterion optimization problem has been formulated for finding a set of Pareto- optimal solutions. Three criteria have been applied for evaluation of task assignment: the workload of a bottleneck machine, the cost of machines, and the numerical performance of system. The machine constraints have...
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Mechanical Performance and Environmental Assessment of Sustainable Concrete Reinforced with Recycled End-of-Life Tyre Fibres
PublicationThe presented research’s main objective was to develop the solution to the global problem of using steel waste obtained during rubber recovery during the tire recycling. A detailed comparative analysis of mechanical and physical features of the concrete composite with the addition of recycled steel fibres (RSF) in relation to the steel fibre concrete commonly used for industrial floors was conducted. A study was carried out using...
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Load effect impact on the exploitation of concrete machine foundations used in the gas and oil industry
PublicationMachine foundations is a critical topic in the gas and oil industry, which design and exploitation require extensive technical knowledge. Machine foundations are the constructions which are intended for mounting on it a specific type of machine. The foundation has to transfer dynamic and static load from machine to the ground. The primary difference between machine foundations and building foundations is that the machine foundations...
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Adversarial attack algorithm for traffic sign recognition
PublicationDeep learning suffers from the threat of adversarial attacks, and its defense methods have become a research hotspot. In all applications of deep learning, intelligent driving is an important and promising one, facing serious threat of adversarial attack in the meanwhile. To address the adversarial attack, this paper takes the traffic sign recognition as a typical object, for it is the core function of intelligent driving. Considering...
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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...