Reservoir Inflow Prediction by Employing Response Surface-Based Models Conjunction with Wavelet and Bootstrap Techniques

Reservoir inflow prediction is a vital subject in the field of hydrology because it determines the flood event. The negative impact of the floods could be minimized greatly if the flood frequency is predicted accurately in advance. In the present study, a novel hybrid model, bootstrap quadratic response surface is developed to test daily streamflow prediction. The developed bootstrap quadratic response surface model is compared with multiple linear regression model, first-order response surface model, quadratic response surface model, wavelet first-order response surface model, wavelet quadratic response surface model, and bootstrap first-order response surface model. Time series data of monsoon season (1 July to 30 September) for the year 2010 of the Chenab river basin are analyzed. The studied models are tested by using performance indices: Nash–Sutcliffe coefficient of efficiency, mean absolute error, persistence index, and root mean square error. Results reveal that the proposed model, i.e., bootstrap quadratic response surface shows good performance and produces optimum results for daily reservoir inflow prediction than other models used in the study.

Optimization for maximum specific energy density of a lithium-ion battery using progressive quadratic response surface method and design of experiments

The demand for high-capacity lithium-ion batteries (LIB) in electric vehicles has increased. In this study, optimization to maximize the specific energy density of a cell is conducted using the LIB electrochemical model and sequential approximate optimization (SAO). First, the design of experiments is performed to analyze the sensitivity of design factors important to the specific energy density, such as electrode and separator thicknesses, porosity, and particle size. Then, the design variables of the cell are optimized for maximum specific energy density using the progressive quadratic response surface method (PQRSM), which is one of the SAO techniques. As a result of optimization, the thickness ratio of the electrode was optimized and the porosity was reduced to keep the specific energy density high, while still maintaining the specific power density performance. This led to an increase in the specific energy density of 56.8% and a reduction in the polarization phenomenon of 11.5%. The specific energy density effectively improved through minimum computation despite the nonlinearity of the electrochemical model in PQRSM optimization.

Construction of twenty-six points specific optimum second order rotatable designs in three dimensions with a practical example

This quadratic response surface methodology focuses on finding the levels of some (coded) predictor variables x = (x1u, x2u, x3u)' that optimize the expected value of a response variable yu from natural levels. The experiment starts from some best guess or “control” combination of the predictor variables (usually coded to x = 0 for this case x1u=30, x2u=25 and x3u =40) and experiment is performed varying them in a region around this center point.We go further to construct a specific optimum second order rotatable design of three factors in twenty-six points. The achievement of this is done with estimation of the free parameters using calculus in an existing second order rotatable design of twenty-six points. Such a design permits a response surface to be fitted easily and provides spherical information contours besides the realizations of optimum combination of ingredients in Agriculture, horticulture and allied sciences which results in economic use of scarce resources in relevant production processes. The expected second order rotatable design model in three dimensions is available where the responses would then facilitate the estimation of the linear and quadratic coefficients. An example involving Phosphate (x1u), Nitrogen (x2u) and Potassium (x3u) is used to represent the three factors in the coded level and converted into natural levels.

Valorization of Industrial Vegetable Waste Using Dilute HCl Pretreatment

A solid vegetable waste stream was subjected to dilute acid (HCl) pretreatment with the goal of converting the waste into a form that is amenable to biochemical processes which could include microbial lipids, biohydrogen, and volatile organic acids production. Specifically, this study was conducted to identify the most suitable pretreatment condition that maximizes the yield or concentration of sugars while minimizing the production of compounds which are inhibitory to microbes (i.e., furfural, hydroxymethylfurfural, and organic acids). Temperatures from 50–150 °C and HCl loading from 0–7 wt % were studied to using an orthogonal central composite response surface design with eight center points. The effects of the variables under study on the resulting concentrations of sugars, organic acids, and furans were determined using the quadratic response surface model. Results indicated that the biomass used in this study contains about 5.7 wt % cellulose and 83.8 wt % hemicellulose/pectin. Within the experimental design, the most suitable pretreatment condition was identified to be at 50 °C and 3.5 wt % HCl. A kinetic study at this condition indicated process completion at 30 mins. that produced a hydrolyzate that contains 31.30 ± 0.44 g/L sugars and 7.40 ± 0.62 g/L organic acids. At this condition, a yield of ~0.47 g sugar/g of dry solid vegetable waste was obtained. The absence of furans suggests the suitability of the resulting hydrolyzate as feedstock for biochemical processes. The results suggested that the sugar concentration of the pretreated biomass is highly affected by the presence of other compounds such as amines, amino acids, and proteins. The effect however, is minimal at low levels of HCl where the highest total sugar production was observed.

Multi-Objective Optimization of Multistage Centrifugal Pump Based on Surrogate Model

In this paper, the hydraulic efficiency optimization calculation method of a ten-stage centrifugal pump is researched. According to the hydraulic loss model, a multi-objective optimization calculation method based on surrogate models is proposed. In order to study the highly nonlinear relationship between key design variables and centrifugal pump external characteristic values, this paper builds the quadratic response surface, the radial basis Gaussian response surface, and Kriging three surrogate models using computer fluid dynamics (CFD) simulation analysis. Two types of calculation models (hydraulic loss model and three surrogate models) combined NSGA-Π genetic algorithm are applied to optimize the key design variables and to find the optimal solution of each model. The accuracy and effectiveness of the efficiency optimization methods based on the two types of calculation models are compared and analyzed. The results show that the calculation method of hydraulic loss model based on the semitheoretical and semi-empirical formula is less time-consuming but inaccurate. In contrast, the optimization method based on surrogate models using CFD simulation is accurate. What's more, comparing the surrogate models, the results based on the complete quadratic response surface model which make the efficiency of the first stage centrifugal pump reach 77.26% are more accurate.

High-Order RSM for Dynamic Reliability of UHV Transmission Tower

As transmission tower system has the characteristics of large-span and spatial truss structure, the study of the reliability is also developed on the basis of space truss research and large-span structure system. As simple and suitable, RSM (response surface method), in particular, quadratic response surface without considering the cross term is often used in reliability calculation. However, strong nonlinear limit that corresponding to a complex surface, the accuracy of quadratic response surface is inadequate, causing greater reliability estimation error. High-order response surface solves it well. To this end, based on univariate analysis of multivariate function, a reasonable algorithm as to assure that the form of higher-order response surface is proposed; on the algorithm is verified by given examples, the result shows better accuracy and efficiency .

Jumping behaviour for a wheeled quadruped robot: simulation and experiments

In this paper, we describe a new jumping behaviour developed for the quadruped robot, PAW (Platform for Ambulating Wheels). The robot has very few degrees of freedom and no knee joints. It employs springy legs and wheels at the distal ends of the legs to achieve various modes of legged, wheeled, and hybrid locomotion, such as high-speed breaking, bounding, and presently jumping. The jumping maneuver developed in this manuscript is designed specifically to take advantage of the wheels on the robot and compliance in its legs and it involves the following principal stages: acceleration to jumping speed, body positioning via front hip thrusting, rear leg compression and thrusting, and flight. A high-fidelity MSC.ADAMS/Simulink co-simulation was developed and used to test and optimize the jumping process. Because of the strong coupling between the parameters defining the jump maneuver, manual parameter tuning is difficult and thus a genetic algorithm is employed for the optimization process. The data generated by the genetic algorithm is further used for the fitting of a quadratic response surface, which allows identifying those parameters that contribute most to a successful jump. Finally, the jumping maneuver is implemented on the physical PAW to demonstrate its feasibility on a hybrid quadruped, and to provide insights into the robot response during this highly dynamic maneuver.

Optimization of Capacitive Deionization for Salt Removal from Water with Response Surface Methodology

A efficient treatment method capacitive deionization (also called electrosorption) against high salinity and ionic concentration in wastewater or groundwater was discussed. Response surface methodology was used to investigate the effect of electrodes potentials, distance between electrodes plates and flow rates on the desalination rate from water. A quadratic response surface model and optimum level values were obtained based on experimental data under box-behnken design (BBD) of software Design-Expert 8.0. The results showed that the maximum desalination rate was 59.05% on the optimal conditions of potentials, distance between electrodes plates and flow rates were 1.6 V, 2 mm, and 21.32 ml/min, respectively. The analysis of variance on quadratic response surface model indicated that regression model reached significant level, fit well and its reliability and accuracy were in the practicable extent, coinciding with the experimental results perfectly.