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Search results for: LIFE PREDICTION
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Load path sensitivity and multiaxial fatigue life prediction of metals under non-proportional loadings
PublicationEngineering components often operate under complex loadings, in which the variable amplitude multiaxial stresses are raised by geometric discontinuities including holes, grooves, fillets and shoulders, etc. Besides, the non-proportional loading will lead to the rotation of maximum principal stress/strain and additional fatigue damage of structural elements in service. Consequently, the multiaxial and non-proportional loading have...
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Model Based Monitoring of Dynamic Loads and Remaining Useful Life Prediction in Rolling Mills and Heavy Machinery
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Comparative Study of Pavement Rehabilitation Using Hot in-Place Recycling and Hot-Mix Asphalt: Performance Evaluation, Pavement Life Prediction, and Life Cycle Cost Analysis
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Fatigue life prediction of notched components under size effect using strain energy reformulated critical distance theory
PublicationNotch and size effects show significant impact on the fatigue performance of engineering components, which deserves special attention. In this work, a strain energy reformulated critical distance theory was developed for fatigue life prediction of notched components under size effect. Experimental data of different notched specimens manufactured from GH4169, TC4, TC11 alloys and low carbon steel En3B were used for model validation...
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Strain energy density and entire fracture surface parameters relationship for LCF life prediction of additively manufactured 18Ni300 steel
PublicationIn this study, the connection between total strain energy density and fracture surface topography is investigated in additively manufactured maraging steel exposed to low-cycle fatigue loading. The specimens were fabricated using laser beam powder bed fusion (LB-PBF) and examined under fully-reversed strain-controlled setup at strain amplitudes scale from 0.3% to 1.0%. The post-mortem fracture surfaces were explored using a non-contact...
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Self-Concept Clarity and Religious Orientations: Prediction of Purpose in Life and Self-Esteem
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Prediction of corrosion fatigue crack propagation life for welded joints under cathodic potentials
PublicationPrzy ochronie katodowej poniżej potencjału optymalnego obserwuje się przyspieszenie propagacji pęknięcia korozyjno-zmęczeniowego w porównaniu do konstrukcji nie chronionej. Zaproponowano własną formułę empiryczną na wpływ potencjału ochronnego na prędkość propagacji pęknięcia oraz własny wzór na [delta]K w złączu pachwinowym. Wyprowadzono wzór na krzywą ''S-Np'' (naprężenie - długość okresu propagacji pęknięcia). Zaprezentowana...
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Balanced Spider Monkey Optimization with Bi-LSTM for Sustainable Air Quality Prediction
PublicationA reliable air quality prediction model is required for pollution control, human health monitoring, and sustainability. The existing air quality prediction models lack efficiency due to overfitting in prediction model and local optima trap in feature selection. This study proposes the Balanced Spider Monkey Optimization (BSMO) technique for effective feature selection to overcome the local optima trap and overfitting problems....
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Effect of bending-torsion on fracture and fatigue life for 18Ni300 steel specimens produced by SLM
PublicationIn this study, different fracture surfaces caused by fatigue failure were generated from 18Ni300 steel produced by selective laser melting (SLM). Hollow round bars with a transverse hole were tested under bending-torsion to investigate the crack initiation mechanisms and fatigue life. Next, the post-failure fracture surfaces were examined by optical profilometer and scanning electron microscope. The focus is placed on the relationship...
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Multi-Criteria Knowledge-Based Recommender System for Decision Support in Complex Business Processes
PublicationIn this paper, we present a concept of a multi-criteria knowledge-based Recommender System (RS) designed to provide decision support in complex business process (BP) scenarios. The developed approach is based on the knowledge aspects of Stylistic Patterns, Business Sentiment and Decision-Making Logic extracted from the BP unstructured texts. This knowledge serves as an input for a multi-criteria RS algorithm. The output is prediction...
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FFT analysis of temperature modulated semiconductor gas sensor response for the prediction of ammonia concentration under humidity interference
PublicationThe increasing environmental contamination forces the need to design reliable devices for detecting of the volatile compounds present in the air. For this purpose semiconductor gas sensors, which have been widely used for years, are often utilized. Although they have many advantages such as low price and quite long life time, they still lack of long term stability and selectivity. Namely, environmental conditions have significant...
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Using LSTM networks to predict engine condition on large scale data processing framework
PublicationAs the Internet of Things technology is developing rapidly, companies have an ability to observe the health of engine components and constructed systems through collecting signals from sensors. According to output of IoT sensors, companies can build systems to predict the conditions of components. Practically the components are required to be maintained or replaced before the end of life in performing their assigned task. Predicting...
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Evaluation of the Electronic Nose Used for Monitoring Environmental Pollution
PublicationAir pollution is a one of the major concern of civilized world, which has a significant impact on human health and the environment. Recent studies highlight that the exposure to polluted air can increase the incidence of diseases and deteriorate the quality of life. Hence, it is necessary to develop tools for real-time air quality monitoring. Electronic-nose systems based on sensors are an interesting and promising technology in...
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Chained machine learning model for predicting load capacity and ductility of steel fiber–reinforced concrete beams
PublicationOne of the main issues associated with steel fiber–reinforced concrete (SFRC) beams is the ability to anticipate their flexural response. With a comprehensive grid search, several stacked models (i.e., chained, parallel) consisting of various machine learning (ML) algorithms and artificial neural networks (ANNs) were developed to predict the flexural response of SFRC beams. The flexural performance of SFRC beams under bending was...
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Study on the accuracy of axle load spectra used for pavement design
PublicationWeigh-in-Motion (WIM) systems are used in order to reduce the number of overloaded vehicles. Data collected from WIM provide characteristics of vehicle axle loads that are crucial for pavement design as well as for the development of pavement distress prediction models. The inaccuracy of WIM data lead to erroneous estimation of traffic loads and in consequence inaccurate prediction of pavement distress process. The objective of...
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Influence of pitting corrosion on fatigue and corrosion fatigue of ship and offshore structures. Part II: Load - pit crack interaction
PublicationIn the paper has been discussed influence of stresses on general corrosion rate and corrosion pit nucleation and growth rate, whose presence has been questioned by some authors but accepted by most of them. Influence of pit walls roughness on fatigue life of a plate suffering pit corrosion and presence of so called "non damaging" pits which never lead to initiation of fatigue crack, has been presented. Possibility of prediction...
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„Eulerian – Eulerian” versus ,,Eulerian –Lagrangean” models of condensation
PublicationLiquid phase in the flowing vapor through stages of the steam turbine is the cause of a lot of failures. Nowadays, due to work of steam turbines at partial load, process of homogeneous and heterogeneous condensation still is current. The formation of drops of condensate under conditions other than nominal operation of turbine is a process still unknown. Engineers and designers involved in the development of power station machines...
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Fractographical quantitative analysis of EN-AW 2024 aluminum alloy after creep pre-strain and LCF loading
PublicationThis paper explores the applicability of a new damage parameter combining both fracture surface topography and loading features to estimate the fatigue lifetime under creep pre-strain and low-cycle fatigue loading. Fractures of EN-AW 2024 aluminum alloy caused by mixed creep and low-cycle fatigue loading are experimentally characterized and quantified via surface topography analysis. The specimens were preliminary damaged in a...
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Performance Modeling and Prediction of Real Application Workload in a Volunteer-based System
PublicationThe goal of this paper is to present a model that predicts the real workload placed on a volunteer based system by an application, with incorporation of not only performance but also availability of volunteers. The application consists of multiple data packets that need to be processed. Knowing the computational workload demand of a single data packet we show how to estimate the application workload in a volunteer based system. Furthermore,...
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Modelling of the Baumann turbine stage operation Part II. Free and kinetic vibrations
PublicationIn this paper has been presented a methodology of validation a novel mathematical model dedicated to evaluation and prediction of material degradation and demage of steam turbine elements such as blades, valves and pipes due to three mechanisms: stress-corosion, high-temperature creep and low-cyclic fatigue. The validation concept is based on an experimental setup manufactured in the Laboratory of Faculty of Mechanical and Power...
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An adaptive-noise Augmented Kalman Filter approach for input-state estimation in structural dynamics
PublicationThe establishment of a Digital Twin of an operating engineered system can increase the potency of Structural Health Monitoring (SHM) tools, which are then bestowed with enhanced predictive capabilities. This is particularly relevant for wind energy infrastructures, where the definition of remaining useful life is a main driver for assessing the efficacy of these systems. In order to ensure a proper representation of the physical...
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Framework for Integration Decentralized and Untrusted Multi-vendor IoMT Environments
PublicationLack of standardization is highly visible while we use historical data sets or compare our model with others that use IoMT devices from different vendors. The problem also concerns the trust in highly decentralized and anonymous environments where sensitive data are transferred through the Internet and then are analyzed by third-party companies. In our research we propose a standard that has been implemented in the form of framework...
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Prediction of the fatigue lifetime of PUR structural elements using a combined experimental-numerical approach
PublicationThis paper presents a method for estimating the fatigue life of polyurethane elastomeric components. A rubber replacement - polyurethane of hardness 80ShA commonly used in vibration damping systems, for example, in motor vehicle suspensions, was used for the study. A metal-rubber bushing component was selected for analysis, and numerical analysis was carried out along with a fatigue model proposal based on a modification of the...
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SkinDepth - synthetic 3D skin lesion database
Open Research DataSkinDepth is the first synthetic 3D skin lesion database. The release of SkinDepth dataset intends to contribute to the development of algorithms for:
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Evaluating the risk of endometriosis based on patients’ self-assessment questionnaires
PublicationBackground Endometriosis is a condition that significantly affects the quality of life of about 10 % of reproductive-aged women. It is characterized by the presence of tissue similar to the uterine lining (endometrium) outside the uterus, which can lead lead scarring, adhesions, pain, and fertility issues. While numerous factors associated with endometriosis are documented, a wide range of symptoms may still be undiscovered. Methods In...
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An Intelligent Approach to Short-Term Wind Power Prediction Using Deep Neural Networks
PublicationIn this paper, an intelligent approach to the Short-Term Wind Power Prediction (STWPP) problem is considered, with the use of various types of Deep Neural Networks (DNNs). The impact of the prediction time horizon length on accuracy, and the influence of temperature on prediction effectiveness have been analyzed. Three types of DNNs have been implemented and tested, including: CNN (Convolutional Neural Networks), GRU (Gated Recurrent...
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Employing flowgraphs for forward route reconstruction in video surveillance system
PublicationPawlak’s flowgraphs were utilized as a base idea and knowledge container for prediction and decision making algorithms applied to experimental video surveillance system. The system is used for tracking people inside buildings in order to obtain information about their appearance and movement. The fields of view of the cameras did not overlap. Therefore, when an object was moving through unsupervised areas, prediction was needed...
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Prediction of Overall In Vitro Microsomal Stability of Drug Candidates Based on Molecular Modeling and Support Vector Machines. Case Study of Novel Arylpiperazines Derivatives
PublicationOther than efficacy of interaction with the molecular target, metabolic stability is the primary factor responsible for the failure or success of a compound in the drug development pipeline. The ideal drug candidate should be stable enough to reach its therapeutic site of action. Despite many recent excellent achievements in the field of computational methods supporting drug metabolism studies, a well-recognized procedure to model...
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A Computationally Efficient Model for Predicting Successful Memory Encoding Using Machine-Learning-based EEG Channel Selection
PublicationComputational cost is an important consideration for memory encoding prediction models that use data from dozens of implanted electrodes. We propose a method to reduce computational expense by selecting a subset of all the electrodes to build the prediction model. The electrodes were selected based on their likelihood of measuring brain activity useful for predicting memory encoding better than chance (in terms of AUC). A logistic...
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MP3vec: A Reusable Machine-Constructed Feature Representation for Protein Sequences
Publication—Machine Learning (ML) methods have been used with varying degrees of success on protein prediction tasks, with two inherent limitations. First, prediction performance often depends upon the features extracted from the proteins. Second, experimental data may be insufficient to construct reliable ML models. Here we introduce MP3vec, a transferable representation for protein sequences that is designed to be used specifically for sequence-to-sequence...
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Mechanics of Micro- and Nano-Size Materials and Structures
PublicationNanotechnology knowledge is always looking to expand its boundaries to achieve the mostsignificant benefit to human life and meet the growing needs of today. In this case, we can refer tomicro- and nanosensors in micro/nano-electromechanical systems (MEMS/NEMS). These electricaldevices can detect minimal physical stimuli up to one nanometer in size. Today, micro/nano-sensordevices are widely used in the...
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Constrained aerodynamic shape optimization using neural networks and sequential sampling
PublicationAerodynamic shape optimization (ASO) involves computational fluid dynamics (CFD)-based search for an optimal aerodynamic shape such as airfoils and wings. Gradient-based optimization (GBO) with adjoints can be used efficiently to solve ASO problems with many design variables, but problems with many constraints can still be challenging. The recently created efficient global optimization algorithm with neural network (NN)-based prediction...
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Color prediction from first principle quantum chemistry computations: a case of alizarin dissolved in methanol
PublicationThe electronic spectrum of alizarin (AZ) in methanol solution was measured and used as reference data for color prediction. The visible part of the spectrum was modelled by different DFT functionals within the TD-DFT framework. The results of a broad range of functionals applied for theoretical spectrum prediction were compared against experimental data by a direct color comparison. The tristimulus model of color expressed in terms...
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Road noise mapping in the city area: measurements compared to model-based estimations
PublicationThe paper presents an approach to the verification of noise prediction models in selected localization in the city of Gdansk. The experiments described include a comparison between environmentalmeasurement results performed in the terrain and the noise level prediction results. The NMPB-96 (Nouvelle Méthode de Prévision du Bruit) and Harmonoise models outcomes provide the subject ofthe analysis. The proposed solution of continuous...
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Evaluation of Response Amplitude Operator of Ship Roll Motions Based on the Experiments in White Noise Waves
PublicationEvaluation of the response amplitude operator (RAO) function for ship wave frequency motions by means of scale model tests in regular waves is a standard procedure conducted by hydrodynamic model testing institutions. The resulting RAO function allows for evaluating sufficiently reliable seakeeping predictions for low to moderate sea states. However, for standard hull forms, correct prediction of roll motion in irregular wave (and...
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Improving the prediction of biochar production from various biomass sources through the implementation of eXplainable machine learning approaches
PublicationExamining the game-changing possibilities of explainable machine learning techniques, this study explores the fast-growing area of biochar production prediction. The paper demonstrates how recent advances in sensitivity analysis methodology, optimization of training hyperparameters, and state-of-the-art ensemble techniques have greatly simplified and enhanced the forecasting of biochar output and composition from various biomass...
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Detection of impulsive disturbances in archive audio signals
PublicationIn this paper the problem of detection of impulsive disturbances in archive audio signals is considered. It is shown that semi-causal/noncausal solutions based on joint evaluation of signal prediction errors and leave-one-out signal interpolation errors, allow one to noticeably improve detection results compared to the prediction-only based solutions. The proposed approaches are evaluated on a set of clean audio signals contaminated...
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Impact of Low Switching-to-Fundamental Frequency Ratio on Predictive Current Control of PMSM: A simulation study
PublicationPredictive current control algorithms for permanent magnet synchronous (PMSM) drives rely on an assumption that within short intervals motor currents can be approximated with linear functions. This approximation may result either from discretizing the motor model or from simplifications applied to the continuous-time model. As the linear current approximation has been recognized as inaccurate in case when the drive operates with...
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In silico modelling for predicting the cationic hydrophobicity and cytotoxicity of ionic liquids towards the Leukemia rat cell line, Vibrio fischeri and Scenedesmus vacuolatus based on molecular interaction potentials of ions
PublicationIn this study we present prediction models for estimating in silico the cationic hydrophobicity and the cytotoxicity (log [1/EC50]) of ionic liquids (ILs) towards the Leukemia rat cell line (IPC-81), the marine bacterium Vibrio fischeri and the limnic green algae Scenedesmus vacuolatus using linear free energy relationship (LFER) descriptors computed by COSMO calculations. The LFER descriptors used for the prediction model (i.e....
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Prediction based on integration of Decisional DNA and a feature selection algorithm Relief-F
PublicationThe paper presents prediction model based on Decisional DNA and Set of experienced integrated with Relief_F algorithm for feature selection
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Machine learning-based prediction of residual drift and seismic risk assessment of steel moment-resisting frames considering soil-structure interaction
PublicationNowadays, 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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Identification of ship’s hull mathematical model with numerical methods
PublicationThe modern maritime industry is moving toward the development of technology that will allow for full or partial autonomy of ship operation. This innovation places high demands on ship performance prediction techniques at the design stage. The researchwork presented in the article is related to the design stage of the ship and concerns methods for prognosis and evaluation of the specific operational condition of the ship, namely...
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Wireless intelligent audio-video surveillance prototyping system
PublicationThe presented system is based on the Virtex6 FPGA and several supporting devices like a fast DDR3 memory, small HD camera, microphone with A/D converter, WiFi radio communication module, etc. The system is controlled by the Linux operating system. The Linux drivers for devices implemented in the system have been prepared. The system has been successfully verified in a H.264 compression accelerator prototype in which the most demanding...
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Elimination of impulsive disturbances from archive audio files – comparison of three noise pulse detection schemes
PublicationThe problem of elimination of impulsive disturbances (such as clicks, pops, ticks, crackles, and record scratches) from archive audio recordings is considered and solved using autoregressive modeling. Three classical noise pulse detection schemes are examined and compared: the approach based on open-loop multi-step-ahead signal prediction, the approach based on decision-feedback signal prediction, and the double threshold approach,...
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Efficient uncertainty quantification using sequential sampling-based neural networks
PublicationUncertainty quantification (UQ) of an engineered system involves the identification of uncertainties, modeling of the uncertainties, and the forward propagation of the uncertainties through a system analysis model. In this work, a novel surrogate-based forward propagation algorithm for UQ is proposed. The proposed algorithm is a new and unique extension of the recent efficient global optimization using neural network (NN)-based...
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Operational Enhancement of Numerical Weather Prediction with Data from Real-time Satellite Images
PublicationNumerical weather prediction (NWP) is a rapidly expanding field of science, which is related to meteorology, remote sensing and computer science. Authors present methods of enhancing WRF EMS (Weather Research and Forecast Environmental Modeling System) weather prediction system using data from satellites equipped with AMSU sensor (Advanced Microwave Sounding Unit). The data is acquired with Department of Geoinformatics’ ground...
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Ship Resistance Prediction with Artificial Neural Networks
PublicationThe paper is dedicated to a new method of ship’s resistance prediction using Artificial Neural Network (ANN). In the initial stage selected ships parameters are prepared to be used as a training and validation sets. Next step is to verify several network structures and to determine parameters with the highest influence on the result resistance. Finally, other parameters expected to impact the resistance are proposed. The research utilizes...
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On ship roll resonance frequency
PublicationThe paper deals with the problem of modeling of rolling motion under a variety of excitation parameters. Special emphasis is put on the analysis and prediction of the frequency of the resonant mode of rolling, since it is often an essential issue in terms of motion of a ship related to her safety against capsizing or excessive amplitudes of roll. The research is performed for both free rolling and excited rolling and it is based...
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Elimination of clicks from archive speech signals using sparse autoregressive modeling
PublicationThis paper presents a new approach to elimination of impulsivedisturbances from archive speech signals. The proposedsparse autoregressive (SAR) signal representation is given ina factorized form - the model is a cascade of the so-called formantfilter and pitch filter. Such a technique has been widelyused in code-excited linear prediction (CELP) systems, as itguarantees model stability. After detection of noise pulses usinglinear...
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New semi-causal and noncausal techniques for detection of impulsive disturbances in multivariate signals with audio applications
PublicationThis paper deals with the problem of localization of impulsive disturbances in nonstationary multivariate signals. Both unidirectional and bidirectional (noncausal) detection schemes are proposed. It is shown that the strengthened pulse detection rule, which combines analysis of one-step-ahead signal prediction errors with critical evaluation of leave-one-out signal interpolation errors, allows one to noticeably improve detection results...