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A series of compressor and cascade test recordings are studied to investigate the off-design loss prediction method. The blade design performance is used to predict the off-design loss changing rate at all operating conditions through analytical derivations and statistical correlation studies. The linear correlation between the incidence and a non-dimensional blade loading factor is the foundation of the prediction method. The off-design incidence is normalized using the off-design blade loading factor for different series of blade designs. An analytical method is introduced to predict the off-design blade loading factor based on design parameters and linear correlation. The changing rate of the off-design loss against the blade loading factor is empirically given through statistical analysis. In application, the prediction method can be used to demonstrate the design space of the off-design incidence for a blade series. The modification of the endwall and the rotor tip loss is recommended to give a more accurate prediction in those regions.
Santos is the most important Brazilian port, handling about 114 million of tons in 2016. In 2010, there was a great capital dredging in order to deepen the Access Channel to 15m deep (Chart Datum - CD). This depth was not achieved, due to inefficiency on dredging procedures. As deepening and maintaining design depths are indispensable, this study presents an analysis of sediment deposition in Santos Port Access Channel and an annual dredging volumes prediction, considering current bathymetric survey and design depths of 15, 16 and 17 m (CD).A numerical hydrodynamic and morphological model was developed for the interest area, by using Delft3D®, calibrated with waves, currents and water level data measured within Santos Port adjacen-cies. Sediment transport model was calibrated with suspended sediment data and historic series of dredged volumes from Santos Port Access Channel. Two different scenarios were simulated for each design depth, according to the regional environmental characteristics. For current bathymetric scenario, the model estimates that it would be necessary to dredge an annual average of about 4,325,000 m³ from Santos Port access chan-nel to maintain current depth condition. Regarding design depths of 15, 16, 17 meters, it would be an in-crease of 15%, 55%, and 80%.
Content available remote Research Progress on Prediction of Mining Subsidence in China
The study of mining subsidence in China started in 1950s, which learned from the successful experience of the former Soviet Union, Poland, Germany and other countries. Over the past 60 years, remarkable progress has been made in subsidence prediction methods and control techniques. This paper introduces Chinese research situation of subsidence prediction methods, models, parameters and so on. The research methods of subsidence prediction under special geological mining conditions such as steep seam, thick soil layer and mountainous terrain are expounded. The research progress on prediction method of movement and deformation under subcritical mining and residual displacement are introduced. The research results provide the theoretical and technical support for the successful application of coal mining under buildings, railways, and waterbodies in China.
Content available remote Metoda przewidywania stanu technicznego budynku mieszkalnego
Trafne określenie stanu technicznego budynku, przyczyn jego zniszczeń oraz prognozy niekorzystnych zmian w nim zachodzących są niezbędne w określaniu potrzeb naprawczych. W artykule przedstawiona została metoda opisu zagrożeń starzeniowych w nieremontowanym budynku mieszkalnym wykonanym w technologii tradycyjnej. Model zmian właściwości użytkowych budynku PRRD (Prediction of Reliability according to Rayleigh Distribution) posłużył do określenia tempa jego starzenia.
The accurate assessment of the technical condition of a building, reasons behind damage or prognoses of unfavourable changes are essential to determining renovation needs. The article presents a method of describing aging threats in a residential building constructed using traditional technology which had not undergone renovation works. The proposed description of the aging rate of a building is based on the PRRD (Prediction of Reliability according to Rayleigh Distribution) model of changes in the operational properties of a building.
Prediction of reservoir pressure and so its values at an early stage of wellbore designing significantly increases the profitability of exploration and production wells design. The prediction of rock mass pressures can be performed in a number of ways. The prediction methods have been reviewed since the 1950s. The methods of empirical forecasting of pressures proposed by Eaton B.A. as well as Hottman and Johnson were described in the paper. The paper also refers to the prediction of rock mass pressures on the basis of seismic well log results obtained from works performed on the same geologic unit. A relation between basic parameters of rocks along the wellbore profile is shown. The Eaton method was used for empirical determining pressure for a planned well based on seismic data form the existing well.
Content available remote Protein intrachain contact prediction with most interacting residues (MIR)
The transition state ensemble during the folding process of globular proteins occurs when a sufficient number of intrachain contacts are formed, mainly, but not exclusively, due to hydrophobic interactions. These contacts are related to the folding nucleus, and they contribute to the stability of the native structure, although they may disappear after the energetic barrier of transition states has been passed. A number of structure and sequence analyses, as well as protein engineering studies, have shown that the signature of the folding nucleus is surprisingly present in the native three-dimensional structure, in the form of closed loops, and also in the early folding events. These findings support the idea that the residues of the folding nucleus become buried in the very first folding events, therefore helping the formation of closed loops that act as anchor structures, speed up the process, and overcome the Levinthal paradox. We present here a review of an algorithm intended to simulate in a discrete space the early steps of the folding process. It is based on a Monte Carlo simulation where perturbations, or moves, are randomly applied to residues within a sequence. In contrast with many technically similar approaches, this model does not intend to fold the protein but to calculate the number of non-covalent neighbors of each residue, during the early steps of the folding process. Amino acids along the sequence are categorized as most interacting residues (MIRs) or least interacting residues. The MIR method can be applied under a variety of circumstances. In the cases tested thus far, MIR has successfully identified the exact residue whose mutation causes a switch in conformation. This follows with the idea that MIR identifies residues that are important in the folding process. Most MIR positions correspond to hydrophobic residues; correspondingly, MIRs have zero or very low accessible surface area. Alongside the review of the MIR method, we present a new postprocessing method called smoothed MIR (SMIR), which refines the original MIR method by exploiting the knowledge of residue hydrophobicity. We review known results and present new ones, focusing on the ability of MIR to predict structural changes, secondary structure, and the improved precision with the SMIR method.
The paper presents an empirical verification of the method for forecasting non-stationary processes. The forecast and the estimation of its error are obtained as a result of solving two forecast parameter estimation problems. The verification is presented by means of such a real process as the power system load. The analysis of predicting the quality changes, depending on the changes in values of its determinants, is carried out. The analysis proves that the prediction method being verified yields good results - the forecasts computed based on it are reliable, because their errors do not exceed 3%.
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