Chaotic Features of Decomposed Time Series from Tidal River Water Level

This study assessed the characteristics of water-level time series of a tidal river by decomposing it into tide, wave, rainfall-runoff, and noise components. Especially, the analysis for chaotic behavior of each component was done by estimating the correlation dimension with phase-space reconstruction of time series and by using a close returns plot (CRP). Among the time series, the tide component showed chaotic characteristics to have a correlation dimension of 1.3. It was found out that the water level has stochastic characteristics showing the increasing trend of the correlation exponent in the embedding dimension. Other components also showed the stochastic characteristics. Then, the CRP was used to examine the characteristics of each component. The tide component showed the chaotic characteristics in its CRP. The CRP of water level showed an aperiodic characteristic which slightly strayed away from its periodicity, and this might be related to the tide component. This study showed that a low water level is mainly affected by a chaotic tide component through entropy information. Even though the water level did not show chaotic characteristics in the correlation dimension, it showed stochastic chaos characteristics in the CRP. Other components showed stochastic characteristics in the CRP. It was confirmed that the water level showed chaotic characteristics when it was not affected by rainfall and stochastic characteristics deviating from the bounded trajectory when water level rises due to rainfall. Therefore, we have shown that the water level related to the chaotic tide component can also have chaotic properties because water level is influenced by chaotic tide and rainfall shock, thus it showed stochastic chaos characteristics.

Inertially enhanced mass transport using 3D-printed porous flow-through electrodes with periodic lattice structures

Electrochemical reactors utilizing flow-through electrodes (FTEs) provide an attractive path toward the efficient utilization of electrical energy, but their commercial viability and ultimate adoption hinge on attaining high currents to drive productivity and cost competitiveness. Conventional FTEs composed of random, porous media provide limited opportunity for architectural control and engineering of microscale transport. Alternatively, the design freedom engendered by additively manufacturing FTEs yields additional opportunities to further drive performance via flow engineering. Through experiment and validated continuum computation we analyze the mass transfer in three-dimensional (3D)–printed porous FTEs with periodic lattice structures and show that, in contrast to conventional electrodes, the mesoscopic length scales in 3D-printed electrodes lead to an increase in the mass correlation exponent as inertial flow effects dominate. The inertially enhanced mass transport yields mass transfer coefficients that exceed previously reported 3D-printed FTEs by 10 to 100 times, bringing 3D-printed FTE performance on par with conventional materials.

Equivalent Permeability Distribution for Fractured Porous Rocks: Correlating Fracture Aperture and Length

Estimating equivalent permeability at grid block scale of numerical models is a critical issue for large-scale fractured porous rocks. However, it is difficult to constrain the permeability distributions for equivalent fracture models as these are strongly influenced by complex fracture properties. This study quantitatively investigated equivalent permeability distributions for fractured porous rocks, considering the impact of the correlated fracture aperture and length model. Two-dimensional discrete fracture models are generated with varied correlation exponent ranges from 0.5 to 1, which indicates different geomechanical properties of fractured porous rock. The equivalent fracture models are built by the multiple boundary upscaling method. Results indicate that the spatial distribution of equivalent permeability varied with the correlation exponent. When the minimum fracture length and the number of fractures increase, the process that the diagonal equivalent permeability tensor components change from a power law like to a lognormal like and to a normal-like distribution slows down as the correlation exponent increases. The average dimensionless equivalent permeability for the equivalent fracture models is well described by an exponential relationship with the correlation exponent. A power law model is built between the equivalent permeability of equivalent fracture models and fracture density of discrete fracture models for the correlated aperture-length models. The results demonstrate that both the fracture density and length-aperture model influence the equivalent permeability of equivalent fracture models interactively.

Analysis of the Characteristics of Monthly Rainfall Pattern in Katsina

Aims: This paper seeks to analyse the characteristics of monthly rainfall pattern in Katsina City in a view to unveiling the trends and describing its dynamics so that adequate recommendations can be made for its modelling. Study Design: The analysis involves a complete statistical, trend, spectral and nonlinear analysis of the monthly rainfall time series recorded in Katsina. Place and Duration of Study: Location: Katsina City, Katsina State, Nigeria from 1990 to 2015; a period of 26 years. Methodology: Secondary data of daily rainfall recorded in Katsina city from 1990 to 2015 was collected from the Nigerian Meteorological Agency (NiMet), and monthly averages were taken to obtain the monthly rainfall data. The data was then subjected to statistical, trend, spectral and nonlinear analysis techniques to reveal the behavioural patterns in the rainfall and also to reveal its underlying dynamics for its future modelling and prediction. Results: The outcome of this analysis indicates that the monthly rainfall in Katsina exhibits an increasing trend with high variance and right-skewed distribution requiring a maximum of 6 independent variables to model its dynamics. The correlation exponent plot reached a saturation value of 5.892 confirming that the monthly rainfall in Katsina over the last 26 years exhibits low dimensional chaotic behavior while the largest Lyapunov exponent for the monthly rainfall time series in Katsina was also computed and found to be positive, having a value of 0.006055/month confirming the presence of deterministic chaos dynamics and is predictable for the next 165 months. Conclusion: Since from the findings of this work it is confirmed that the rainfall in Katsina exhibits chaotic behavior with an increasing trend, it is recommended that more drainages and dams be built to provide steady supply of water for agricultural and domestic purposes as well as curtail the menace of flooding and drought which may occur as a result of global warming and climate change.

Assessment of several nonlinear methods in forecasting suspended sediment concentration in streams

In this paper, the use of nonlinear nearest trajectory based on phase space reconstruction along with several data-driven methods, including two types of perceptron artificial neural networks with Levenberg–Marquardt (ANN-LM) and particle swarm optimization learning algorithms (ANN-PSO), adaptive neuro-fuzzy inference system (ANFIS) and gene expression programming for forecasting suspended sediment concentration (SSC) dynamics in streamflow is studied. The nonlinearity of the series was tested using the method of surrogate data at 0.01 significance level as well as correlation exponent method. The proper time delay is calculated using the average mutual information function. Obtained results of different models are compared using root mean square error (RMSE), Pearson's correlation coefficient (PCC) and Nash–Sutcliffe efficiency with logarithmic values (Eln). Of the applied nonlinear methods, ANFIS generates a slightly better fit under whole daily SSC values (the least amount of RMSE = 10.5 mg/l), whereas ANN-PSO shows superiority based on the Eln criterion (the highest amount of Eln = 0.885). According to the non-parametric Mann–Whitney test, all data-driven models represent the same forecasted results and are significantly superior to the nearest trajectory-based model at the 99% confidence level.

Effect of Prandtl Number on the Heat Transfer From a Rotating Disk: An Experimental Study

Heat transfer coefficients were experimentally determined for a free rotating disk in still air and water. These were obtained with an electrically heated disk placed in a cylindrical pool. The accuracy of the employed experimental apparatus was assessed by heat transfer measurements in air. For this fluid, an excellent agreement with reliable literature data was found. Essentially new experimental data were obtained for water as fluid. Based upon the experimental data, the validity of theoretical correlations and the effect of the Prandtl number on the convective heat transfer from a rotating disk were discussed. It was found that in laminar water flow, the value of the correlation exponent for the Prandtl number is practically identical to 1/2 as theoretically predicted in 1948 by Dorfman. In turbulent flow, its value is better given by 1/3 as in case of the classical turbulent boundary layer theory.

Multifractal Detrended Cross-Correlation Analysis of Geochemical Element Concentration

We use multifractal detrended cross -fluctuation analysis (MF-DXA) to investigate nonlinear behavior of geochemical element concentration, Au-Cu-Pb-Zn-Ag, in Shangzhuang Deposit, Shandong Province, China. We find that the generalized Hurst exponent h(q) and cross-correlation exponent hxy(q) decrease with the increase of q, which indicate that all element concentration series and their cross pairs exhibit multifractal phenomena. By comparing the variability of h(q) and hxy(q), we have found that the multifractal behavior is more obvious when q > 0 than q < 0 for the element Au- Cu-Pb-Zn and their cross pairs. These analyses, given quantitative information about the complexity of the element concentration, lead to a better understanding of the geochemical phenomena underlying mineralization process.

Ambiguity Resolution with Single Epoch for GNSS Reference Network Based on Atmospheric Delay Information

Correct resolution of ambiguities for GNSS reference network is prerequisite for generation of corrections for network RTK. Due to the presence of atmospheric delay in the double-differenced observations, the convergence time of ambiguity is about a dozen minutes and even dozens of minutes for medium and long baselines. And in the case of loss-of-lock or new rising satellites, the integer ambiguities have to be redetermined over and over again. But for the application of GNSS network RTK, the resolution of ambiguity needs to be determined real time as possible. Atmospheric delays of previous epochs are used to predict atmospheric delays of following epochs, and then wide and narrow lane combination of carrier-phase observations as well as ionosphere-free combination is used to resolve ambiguities with single epoch. Our test results show that the precision of predicted double-differenced tropospheric and ionospheric delays is about 2-3 cm using temporal-and spatial-correlation exponent model, and the success rates of L1 ambiguities resolution with single epoch reach above 90% for medium and long distance GNSS reference station network.

Chaotic air pressure fluctuations during departure of air bubbles from two neighbouring nozzles

Chaotic air pressure fluctuations during departure of air bubbles from two neighbouring nozzlesIn the experiment, bubbles were generated from two brass nozzles with inner diameters of 1.1 mm. They were submerged in the glass tank filled with distilled water. There have been measured the air pressure fluctuations and the signal from the laser-phototransistor sensor. For analysis of the pressure signal the correlation (the normalized cross - correlation exponent) and non-linear analyses have been used. It has been shown that hydrodynamic interactions between bubbles can lead to bubble departure synchronization. In this case the bubble departures become periodic. The results of calculation of correlation dimension and the largest Lyapunov exponent confirm that hydrodynamic bubble interactions observed for 4 mm spacing between nozzels cause the periodic bubble departures from two neighbouring nozzles.