Search results for " PREDICTION"
showing 10 items of 366 documents
Training Deep Neural Networks with Novel Metaheuristic Algorithms for Fatigue Crack Growth Prediction in Aluminum Aircraft Alloys
2022
Fatigue cracks are a major defect in metal alloys, and specifically, their study poses defect evaluation challenges in aluminum aircraft alloys. Existing inline inspection tools exhibit measurement uncertainties. The physical-based methods for crack growth prediction utilize stress analysis models and the crack growth model governed by Paris’ law. These models, when utilized for long-term crack growth prediction, yield sub-optimum solutions and pose several technical limitations to the prediction problems. The metaheuristic optimization algorithms in this study have been conducted in accordance with neural networks to accurately forecast the crack growth rates in aluminum alloys. Through ex…
Modern small wind turbine design solutions comparison in terms of estimated cost to energy output ratio
2015
This paper presents a series of estimations performed in order to establish the actual cost-effectiveness of three different small wind turbines (SWTs) design solutions. Each of them was evaluated and based on their power curves and installation costs, using wind data from a numerical weather prediction (WNP) model, a return on investment (ROI) period was calculated. The chosen turbines are: a standard three bladed horizontal axis wind turbine (HAWT), an advanced diffuser augmented HAWT and a Darrieus type vertical axis wind turbine (VAWT). The conclusions drawn from this study entertain the idea that from the economical point of view, a price reduction of SWT systems is more important than…
Convolutional architectures for virtual screening
2020
Abstract Background A Virtual Screening algorithm has to adapt to the different stages of this process. Early screening needs to ensure that all bioactive compounds are ranked in the first positions despite of the number of false positives, while a second screening round is aimed at increasing the prediction accuracy. Results A novel CNN architecture is presented to this aim, which predicts bioactivity of candidate compounds on CDK1 using a combination of molecular fingerprints as their vector representation, and has been trained suitably to achieve good results as regards both enrichment factor and accuracy in different screening modes (98.55% accuracy in active-only selection, and 98.88% …
Visual mismatch negativity (vMMN): a prediction error signal in the visual modality
2015
Frontiers in Human Neuroscience, 8
Calibration of a knock prediction model for the combustion of a gasoline-natural gas mixture
2009
Gaseous fuels, such as Liquefied Petroleum Gas (LPG) and Natural Gas (NG), thank to their good mixing capabilities, allow complete and cleaner combustion than normal gasoline, resulting in lower pollutant emissions and particulate matter. Moreover natural gas, which is mainly constituted by methane, whose molecule has the highest hydrogen/carbon ratio, leads also to lower ozone depleting emissions. The authors in a previous work (1) experienced the simultaneous combustion of gasoline and natural gas in a bi-fuel S.I. engine, exploiting so the high knock resistance of methane to run the engine with an ‘overall stoichiometric’ mixture (thus lowering fuel consumption and emissions) and better …
Ethnographic context and spatial coherence of climate indicators for farming communities : a multi-regional comparative assessment
2015
Accurate seasonal predictions of rainfall may reduce climatic risks that farmers are usually faced with across the tropical and subtropical zones. However, although regional-scale seasonal amounts have regularly been forecasted since 1997/98, the practical use of these seasonal predictions is still limited by myriad factors. This paper synthesizes the main resultsof a multi-disciplinary ethnographic and climatic project (PICREVAT). Its main objective was to seek the climatic information ? beyond the seasonal amounts ? critical for crops, both as an actual constraint to crop yields and as identified by the current and past practices and perceptions of farmers. A second goal was to confront t…
Applying Numerical Weather Prediction Models to the Production of New European Wind Atlas : Sensitivity studies of the wind climate to the planetary …
2018
Reliable and precise information about the wind speed climate is crucial for the development of wind energy. Meteorological processes in the mesoscale (2 – 200 km) can be represented using Numerical Weather Prediction (NWP) models such as the Weather Research and Forecast model (WRF), but before their application for creating wind energy atlases, their results and sensitivity to modelling parameters should be investigated. Here the WRF model wind speed results for the year 2015 for the Baltic Sea region are investigated, and the effect of the planetary boundary layer parametrization scheme is analyzed.
Verification of Numerical Weather Prediction Model Results for Energy Applications in Latvia
2014
Abstract Wind power forecasting greatly relies on wind speed forecasts. Numerical Weather Prediction (NWP) models are a reliable source of meteorological forecasts and they can also be used in wind resource assessment. In this work we carry out the verification of wind speed results from the NWP model Weather Research and Forecast (WRF), grid resolution - 3 km. Results from 172 model runs in May and November 2013 are compared with meteorological observations in 24 stations in Latvia. The model usually predicts wind speed values that are larger than the observed and the diurnal cycle has a large impact on verification results. Verification results obtained by interpolating model results betw…
Multi-physical modelling of reverse electrodialysis
2017
Abstract Reverse electrodialysis (RED) is an electrochemical membrane process that directly converts the energy associated with the concentration difference between two salt solutions into electrical energy by means of a selective controlled mixing. The physics of RED involves the interaction of several phenomena of different nature and space-time scales. Therefore, mathematical modelling and numerical simulation tools are crucial for performance prediction. In this work, a multi-physical modelling approach for the simulation of RED units was developed. A periodic portion of a single cell pair was simulated in two dimensions. Fluid dynamics was simulated by the Navier-Stokes and continuity …
Dip Phenomenon in High-Curved Turbulent Flows and Application of Entropy Theory
2018
The estimation of velocity profile in turbulent open channels is a difficult task due to the significant effects of the secondary flow. The present paper investigates the mechanism of the velocity-dip phenomenon, whereby the location of the maximum velocity appears to be below the free surface. Previous studies conducted in straight channels relate the mechanism of the velocity-dip phenomenon to secondary flow induced by anisotropy of turbulence. This work focuses on high-curved channels where the secondary motion, which is also induced by the channel’s curvature, evolves along the bend. The width-to-depth ratio, B/h, is one of the most important parameters that are affecting the secondary …