Effect of calibration data series length on performance and optimal parameters of hydrological model

In order to assess the effects of calibration data series length on the performance and optimal parameter values of a hydrological model in ungauged or data-limited catchments （data are non-continuous and fragmental in some catchments）, we used non-continuous calibration periods for more independent streamflow data for SIMHYD （simple hydrology） model calibration. Nash-Sutcliffe efficiency and percentage water balance error were used as performance measures. The particle swarm optimization （PSO） method was used to calibrate the rainfall-runoff models. Different lengths of data series ranging from one year to ten years, randomly sampled, were used to study the impact of calibration data series length. Fifty-five relatively unimpaired catchments located all over Australia with daily precipitation, potential evapotranspiration, and streamflow data were tested to obtain more general conclusions. The results show that longer calibration data series do not necessarily result in better model performance. In general, eight years of data are sufficient to obtain steady estimates of model performance and parameters for the SIMHYD model. It is also shown that most humid catchments require fewer calibration data to obtain a good performance and stable parameter values. The model performs better in humid and semi-humid catchments than in arid catchments. Our results may have useful and interesting implications for the efficiency of using limited observation data for hydrological model calibration in different climates.

Optimal Parameter and Uncertainty Estimation of a Land Surface Model: Sensitivity to Parameter Ranges and Model Complexities

Most previous land-surface model calibration studies have defined globalranges for their parameters to search for optimal parameter sets. Little work has been conducted tostudy the impacts of realistic versus global ranges as well as model complexities on the calibrationand uncertainty estimates. The primary purpose of this paper is to investigate these impacts byemploying Bayesian Stochastic Inversion (BSI) to the Chameleon Surface Model (CHASM). The CHASM wasdesigned to explore the general aspects of land-surface energy balance representation within acommon modeling framework that can be run from a simple energy balance formulation to a complexmosaic type structure. The BSI is an uncertainty estimation technique based on Bayes theorem,importance sampling, and very fast simulated annealing. The model forcing data and surface flux datawere collected at seven sites representing a wide range of climate and vegetation conditions. Foreach site, four experiments were performed with simple and complex CHASM formulations as well asrealistic and global parameter ranges. Twenty eight experiments were conducted and 50 000 parametersets were used for each run. The results show that the use of global and realistic ranges givessimilar simulations for both modes for most sites, but the global ranges tend to produce someunreasonable optimal parameter values. Comparison of simple and complex modes shows that the simplemode has more parameters with unreasonable optimal values. Use of parameter ranges and modelcomplexities have significant impacts on frequency distribution of parameters, marginal posteriorprobability density functions, and estimates of uncertainty of simulated sensible and latent heatfluxes. Comparison between model complexity and parameter ranges shows that the former has moresignificant impacts on parameter and uncertainty estimations.

Optimal parameterization of conic curves

Optimal parameterization of specified segment on the algebraic curves is a hot issue in CAGD and CG. Take the optimal approximation of arc-length parameterization as the criterion of optimal parameterization, and the optimal or close to optimal rational parameterization formula of any specified segment on the conic curves is obtained. The new method proposed in this paper has ad- vantage in quantity of calculation and has strong self-adaptability. Finally, a experimental comparison of the results obtained by this method and by the traditional parametric algorithm is conducted.

Mathematical Analysis of Two Approaches for Optimal Parameter Estimates to Modeling Time Dependent Properties of Viscoelastic Materials

Mathematical models for phenomena in the physical sciences are typically parameter-dependent, and the estimation of parameters that optimally model the trends suggested by experimental observation depends on how model-observation discrepancies are quantified. Commonly used parameter estimation techniques based on least-squares minimization of the model-observation discrepancies assume that the discrepancies are quantified with the L2-norm applied to a discrepancy function. While techniques based on such an assumption work well for many applications, other applications are better suited for least-squared minimization approaches that are based on other norm or inner-product induced topologies. Motivated by an application in the material sciences, the new alternative least-squares approach is defined and an insightful analytical comparison with a baseline least-squares approach is provided.

Extended Application of the Conditional Nonlinear Optimal Parameter Perturbation Method in the Common Land Model

An extension of the conditional nonlinear optimal parameter perturbation （CNOP-P） method is applied to the parameter optimization of the Common Land Model （CoLM） for the North China Plain with the differential evolution （DE） method. Using National Meteorological Center （NMC） Reanalysis 6-hourly surface flux data and National Center for Environmental Prediction/Department of Energy （NCEP/DOE） Atmospheric Model Intercomparison Project II （AMIP-II） 6-hourly Reanalysis Gaussian Grid data, two experiments （I and II） were designed to investigate the impact of the percentages of sand and clay in the shallow soil in CoLM on its ability to simulate shallow soil moisture. A third experiment （III） was designed to study the shallow soil moisture and latent heat flux simultaneously. In all the three experiments, after the optimization stage, the percentages of sand and clay of the shallow soil were used to predict the shallow soil moisture in the following month. The results show that the optimal parameters can enable CoLM to better simulate shallow soil moisture, with the simulation results of CoLM after the double-parameter optimal ex- periment being better than the single-parameter optimal experiment in the optimization slot. Purthermore, the optimal parameters were able to significantly improve the prediction results of CoLM at the prediction stage. In addition, whether or not the atmospheric forcing and observational data are accurate can seriously affect the results of optimization, and the more accurate the data are, the more significant the results of optimization may be.

Optimal Structural Parameters for a Plastic Centrifugal Pump Inducer

The aim of the study is to determine the optimal structural parameters for a plastic centrifugal pump inducer within the framework of an orthogonal experimental method.For this purpose,a numerical study of the related flow field is performed using CFX.The shaft power and the head of the pump are taken as the evaluation indicators.Accordingly,the examined variables are the thickness(S),the blade cascade degree(t),the blade rim angle(β1),the blade hub angle(β2)and the hub length(L).The impact of each structural parameter on each evaluation index is examined and special attention is paid to the following combinations:S2 mm,t 2,β1235°,β2360°and L 140 mm(corresponding to a maximum head of 98.15 m);S 5 mm,t 1.6,β1252°,β2350°and L 140 mm(corresponding to a minimum shaft power of 63.06 KW).Moreover,using least squares and fish swarm algorithms,the pump shaft power and head are further optimized,yielding the following optimal combination:S 5 mm,t 1.9,β1252°,β2360°and L 145 mm(corresponding to the maximum head of 91.90 m,and a minimum shaft power of 64.83 KW).

Phase-Based Optical Flow Method with Optimized Parameter Settings for Enhancing Displacement Measurement Adaptability

To enhance the applicability and measurement accuracy of phase-based optical flow method using complex steerable pyramids in structural displacement measurement engineering applications, an improved method of optimizing parameter settings is proposed. The optimized parameters include the best measurement points of the Region of Interest (ROI) and the levels of pyramid filters. Additionally, to address the issue of updating reference frames in practical applications due to the difficulty in estimating the maximum effective measurement value, a mechanism for dynamically updating reference frames is introduced. Experimental results demonstrate that compared to representative image gradient-based displacement measurement methods, the proposed method exhibits higher measurement accuracy in engineering applications. This provides reliable data support for structural damage identification research based on vibration signals and is expected to broaden the engineering application prospects for structural health monitoring.

An Improved Cyclostationary Feature Detection Based on the Selection of Optimal Parameter in Cognitive Radios

Spectrum sensing is an important part of cognitive radio systems to find spectrum hole for transmission which enables cognitive radio systems coexist with the authorized radio systems without harmful interference.In this paper,an improved cyclostationary feature detection method is proposed to reduce computational complexity without loss of good performance based on the optimal parameter selection strategy for choosing detection parameters of cyclic frequency and lag.Taking binary phase shift keying (BPSK) and quadrature phase shift keying (QPSK) signals as examples,the theoretical analyses are presented for choosing the optimal parameters.Simulation results are given to certify the correctness of the proposed parameter selection strategy and show the performance of the proposed method.

Optimal Rational Parameterization of Quadratic Curves Based on the Geographic Information of Both Ends

In this paper, we rewrote the equation of algebraic curve segmentswith the geometric informationonboth ends. The optimal or nearly optimal rationalparametric equation is determinedbythe principle that parametricspeedsat both endsareequal. Comparing withotherliteratures, the methodofthis paper has advantage in efficiency andiseasy to realize. The equation of optimal rational parameterization can be obtained directly by the information of both ends. Large numbers ofexperimental data show that our method hasbeen given withmore self-adaptability and accuracy than that ofotherliteratures, and if the parametricspeedat any end reaches its maximum or minimum value, the parameterization is optimal; otherwise itis close tooptimal rational parameterization.

Optimal Microwave Radiation Field Parameters for Mercury Ion Microwave Frequency Standards

We propose a method to determine the optimal power of the microwave resonance transition that simultaneously improves the signal-to-noise ratio and reduces line width based on saturation broadening theory and experiment. Saturation broadening spectra of the ground state hyperfine transition of trapped 199Hg＋ ions are measured and analyzed. The value of the optimal microwave power is obtained by using the proposed method and is verified. Rabi oscillations decay spectra of trapped 199Hg＋ ions are observed and the optimal microwave irradiation time for the maximum transition signal intensity is determined. This work will help to improve the short-term frequency stability of the mercury ion microwave frequency standard.

Application of MPSO technique to find optimal location and parameter setting of TCSC

A new mothod was presented to find the optimal location and parameter setting of Thyristor Controlled Series Compensator (TCSC) to maxmize the transfer capability.Firstly the sensitivity of the transfer capability with respect was described to the line's reactance was described to find the more sensitive lines for installing TCSC,however,the line which has the most sesitivity value is always not the best line for installing TCSC.For solving this problem,the more sensitive m lines were selected as the alternative line group of installing TCSC,and then modified particle swarm optimization (MPSO) was used to find out the optimal location and the optimal parameter settings of TCSC.Particle swarm optimization (PSO) algorithm can results premature convergence.For solving this problem,population entropy and cellular automata were introduced to it.Simulation results of IEEE 30-bus system proved the effectiveness of the method and its application values.

The Optimal Matching Parameter of Half Discrete Hilbert Type Multiple Integral Inequalities with Non-Homogeneous Kernels and Applications

By using the weight function method,the matching parameters of the half discrete Hilbert type multiple integral inequality with a non-homogeneous kernel K(n,||x||ρ,m)=G(nλ1||x||ρmλ,2)are discussed,some equivalent conditions of the optimal matching parameter are established,and the expression of the optimal constant factor is obtained.Finally,their applications in operator theory are considered.

Nonlinear Algebraic Equations Solved by an Optimal Splitting-Linearizing Iterative Method

How to accelerate the convergence speed and avoid computing the inversion of a Jacobian matrix is important in the solution of nonlinear algebraic equations(NAEs).This paper develops an approach with a splitting-linearizing technique based on the nonlinear term to reduce the effect of the nonlinear terms.We decompose the nonlinear terms in the NAEs through a splitting parameter and then linearize the NAEs around the values at the previous step to a linear system.Through the maximal orthogonal projection concept,to minimize a merit function within a selected interval of splitting parameters,the optimal parameters can be quickly determined.In each step,a linear system is solved by the Gaussian elimination method,and the whole iteration procedure is convergent very fast.Several numerical tests show the high performance of the optimal split-linearization iterative method(OSLIM).

Interpretable machine learning optimization(InterOpt)for operational parameters:A case study of highly-efficient shale gas development

An algorithm named InterOpt for optimizing operational parameters is proposed based on interpretable machine learning,and is demonstrated via optimization of shale gas development.InterOpt consists of three parts:a neural network is used to construct an emulator of the actual drilling and hydraulic fracturing process in the vector space(i.e.,virtual environment);:the Sharpley value method in inter-pretable machine learning is applied to analyzing the impact of geological and operational parameters in each well(i.e.,single well feature impact analysis):and ensemble randomized maximum likelihood(EnRML)is conducted to optimize the operational parameters to comprehensively improve the efficiency of shale gas development and reduce the average cost.In the experiment,InterOpt provides different drilling and fracturing plans for each well according to its specific geological conditions,and finally achieves an average cost reduction of 9.7%for a case study with 104 wells.

Review of Design of Process Parameters for Squeeze Casting

Squeeze casting(SC)is an advanced net manufacturing process with many advantages for which the quality and properties of the manufactured parts depend strongly on the process parameters.Unfortunately,a universal efficient method for the determination of optimal process parameters is still unavailable.In view of the shortcomings and development needs of the current research methods for the setting of SC process parameters,by consulting and analyzing the recent research literature on SC process parameters and using the CiteSpace literature analysis software,manual reading and statistical analysis,the current state and characteristics of the research methods used for the determination of SC process parameters are summarized.The literature data show that the number of pub-lications in the literature related to the design of SC process parameters generally trends upward albeit with signifi-cant fluctuations.Analysis of the research focus shows that both“mechanical properties”and“microstructure”are the two main subjects in the studies of SC process parameters.With regard to materials,aluminum alloys have been extensively studied.Five methods have been used to obtain SC process parameters:Physical experiments,numeri-cal simulation,modeling optimization,formula calculation,and the use of empirical values.Physical experiments are the main research methods.The main methods for designing SC process parameters are divided into three categories:Fully experimental methods,optimization methods that involve modeling based on experimental data,and theoreti-cal calculation methods that involve establishing an analytical formula.The research characteristics and shortcomings of each method were analyzed.Numerical simulations and model-based optimization have become the new required methods.Considering the development needs and data-driven trends of the SC process,suggestions for the develop-ment of SC process parameter research have been proposed.

Pulsed gas–liquid discharge plasma catalytic degradation of bisphenol A over graphene/Cd S:process parameters optimization and O_(3)activation mechanism analysis

In the present work,pulsed gas–liquid hybrid discharge plasma coupled with graphene/Cd S catalyst was evaluated to eliminate bisphenol A(BPA)in wastewater.The optimization of a series of process parameters was performed in terms of BPA degradation performance.The experimental results demonstrated that nearly 90%of BPA(20 mg l^(-1))in the synthetic wastewater(p H=7.5,σ=10μS m^(-1))was degraded by the plasma catalytic system over 0.2 g l^(-1)graphene/Cd S at 19k V with a 4 l min^(-1)air flow rate and 10 mm electrode gap within 60 min.The BPA removal rate increased with increasing the discharge voltage and decreasing the initial BPA concentration or solution conductivity.Nevertheless,either too high or too low an air flow rate,electrode gap,catalyst dosage or initial solution p H would lead to a decrease in BPA degradation.Moreover,optical emission spectroscopy was used to gain information on short-lived reactive species formed from the pulsed gas–liquid hybrid discharge plasma system.The results indicated the existence of several highly oxidative free radicals such as·O and·OH.Finally,the activation pathway of O_(3)on the catalyst surface was analyzed by density functional theory.

Hot-deformation kinetics analysis and extrusion parameter optimization of a dilute rare-earth free magnesium alloy

The fundamental research on thermo-mechanical conditions provides an experimental basis for high-performance Mg-Al-Ca-Mn alloys.However, there is a lack of systematical investigation for this series alloys on the hot-deformation kinetics and extrusion parameter optimization. Here, the flow behavior, constitutive model, dynamic recrystallization(DRX) kinetic model and processing map of a dilute rare-earth free Mg-1.3Al-0.4Ca-0.4Mn(AXM100, wt.%) alloy were studied under different hot-compressive conditions. In addition, the extrusion parameter optimization of this alloy was performed based on the hot-processing map. The results showed that the conventional Arrhenius-type strain-related constitutive model only worked well for the flow curves at high temperatures and low strain rates. In comparison, using the machine learning assisted model(support vector regression, SVR) could effectively improve the accuracy between the predicted and experimental values. The DRX kinetic model was established, and a typical necklace-shaped structure preferentially occurred at the original grain boundaries and the second phases. The DRX nucleation weakened the texture intensity, and the further growth caused the more scattered basal texture. The hot-processing maps at different strains were also measured and the optimal hot-processing range could be confirmed at the deformation temperatures of 600~723 K and the strain rates of 0.018~0.563 s^(-1). Based on the optimum hot-processing range, a suitable extrusion parameter was considered as 603 K and 0.1 mm/s and the as-extruded alloy in this parameter exhibited a good strength-ductility synergy(yield strength of ~ 232.1 MPa, ultimate strength of ~ 278.2 MPa and elongation-to-failure of ~ 20.1%). Finally, the strengthening-plasticizing mechanisms and the relationships between the DRXed grain size, yield strength and extrusion parameters were analyzed.

Investigation of influence factors on CO_(2) flowback characteristics and optimization of flowback parameters during CO_(2) dry fracturing in tight gas reservoirs

CO_(2) dry fracturing is a promising alternative method to water fracturing in tight gas reservoirs,especially in water-scarce areas such as the Loess Plateau.The CO_(2) flowback efficiency is a critical factor that affects the final gas production effect.However,there have been few studies focusing on the flowback characteristics after CO_(2) dry fracturing.In this study,an extensive core-to-field scale study was conducted to investigate CO_(2) flowback characteristics and CH_(4) production behavior.Firstly,to investigate the impact of core properties and production conditions on CO_(2) flowback,a series of laboratory experiments at the core scale were conducted.Then,the key factors affecting the flowback were analyzed using the grey correlation method based on field data.Finally,taking the construction parameters of Well S60 as an example,a dual-permeability model was used to characterize the different seepage fields in the matrix and fracture for tight gas reservoirs.The production parameters after CO_(2) dry fracturing were then optimized.Experimental results demonstrate that CO_(2) dry fracturing is more effective than slickwater fracturing,with a 9.2%increase in CH_(4) recovery.The increase in core permeability plays a positive role in improving CH_(4) production and CO_(2) flowback.The soaking process is mainly affected by CO_(2) diffusion,and the soaking time should be controlled within 12 h.Increasing the flowback pressure gradient results in a significant increase in both CH_(4) recovery and CO_(2) flowback efficiency.While,an increase in CO_(2) injection is not conducive to CH_(4) production and CO_(2) flowback.Based on the experimental and field data,the important factors affecting flowback and production were comprehensively and effectively discussed.The results show that permeability is the most important factor,followed by porosity and effective thickness.Considering flowback efficiency and the influence of proppant reflux,the injection volume should be the minimum volume that meets the requirements for generating fractures.The soaking time should be short which is 1 day in this study,and the optimal bottom hole flowback pressure should be set at 10 MPa.This study aims to improve the understanding of CO_(2) dry fracturing in tight gas reservoirs and provide valuable insights for optimizing the process parameters.

Fracture propagation,proppant transport and parameter optimization of multi-well pad fracturing treatment

This paper establishes a 3D multi-well pad fracturing numerical model coupled with fracture propagation and proppant migration based on the displacement discontinuity method and Eulerian-Eulerian frameworks,and the fracture propagation and proppant distribution during multi-well fracturing are investigated by taking the actual multi-well pad parameters as an example.Fracture initiation and propagation during multi-well pad fracturing are jointly affected by a variety of stress interference mechanisms such as inter-cluster,inter-stage,and inter-well,and the fracture extension is unbalanced among clusters,asymmetric on both wings,and dipping at heels.Due to the significant influence of fracture morphology and width on the migration capacity of proppant in the fracture,proppant is mainly placed in the area near the wellbore with large fracture width,while a high-concentration sandwash may easily occur in the area with narrow fracture width as a result of quick bridging.On the whole,the proppant placement range is limited.Increasing the well-spacing can reduce the stress interference of adjacent wells and promote the uniform distribution of fractures and proppant on both wings.The maximum stimulated reservoir volume or multi-fracture uniform propagation can be achieved by optimizing the well spacing.Although reducing the perforation-cluster spacing also can improve the stimulated reservoir area,a too low cluster spacing is not conducive to effectively increasing the propped fracture area.Since increasing the stage time lag is beneficial to reduce inter-stage stress interference,zipper fracturing produces more uniform fracture propagation and proppant distribution.

Analysis of Additional Damping Control Strategy and Parameter Optimization for Improving Small Signal Stability of VSC-HVDC System

The voltage source converter based high voltage direct current(VSC-HVDC)system is based on voltage source converter,and its control system is more complex.Also affected by the fast control of power electronics,oscillation phenomenon in wide frequency domain may occur.To address the problem of small signal stability of the VSCHVDC system,a converter control strategy is designed to improve its small signal stability,and the risk of system oscillation is reduced by attaching a damping controller and optimizing the control parameters.Based on the modeling of the VSC-HVDC system,the general architecture of the inner and outer loop control of the VSCHVDC converter is established;and the damping controllers for DC control and AC control are designed in the phase-locked loop and the inner and outer loop control parts respectively;the state-space statemodel of the control system is established to analyze its performance.And the electromagnetic transient simulation model is built on the PSCAD/EMTDC simulation platform to verify the accuracy of the small signal model.The influence of the parameters of each control part on the stability of the system is summarized.The main control parts affecting stability are optimized for the phenomenon of oscillation due to changes in operation mode occurring on the AC side due to faults and other reasons,which effectively eliminates system oscillation and improves system small signal stability,providing a certain reference for engineering design.