Comparative Study of Response Surface Designs with Errors-in-Variables Model

This paper investigates the scaled prediction variances in the errors-in-variables model and compares the performance with those in classic model of response surface designs for three factors.The ordinary least squares estimators of regression coefficients are derived from a second-order response surface model with errors in variables.Three performance criteria are proposed.The first is the difference between the empirical mean of maximum value of scaled prediction variance with errors and the maximum value of scaled prediction variance without errors.The second is the mean squared deviation from the mean of simulated maximum scaled prediction variance with errors.The last performance measure is the mean squared scaled prediction variance change with and without errors.In the simulations,1 000 random samples were performed following three factors with 20 experimental runs for central composite designs and 15 for Box-Behnken design.The independent variables are coded variables in these designs.Comparative results show that for the low level errors in variables,central composite face-centered design is optimal;otherwise,Box-Behnken design has a relatively better performance.

Neurodevelopmental disorders:An innovative perspective via the response to intervention model

Neurodevelopmental disorders are a group of conditions classified together by the most recent edition of the Diagnostic and Statistical Manual of Mental Disorders which include intellectual disability,communication disorders,autism spectrum disorder,attention-deficit/hyperactivity disorder,specific learning disorder(SLD),and motor disorders.SLD is present in many students,who exhibit significant difficulties in the acquisition of reading,written expression,and mathematics,mostly due to problems with executive functions(EF).The present study is a review of the current situation of neurodevelopmental disorders and SLD focusing on the benefits of the response to intervention model(RtI),which allows the combination of evaluation and intervention processes.It also addresses the key role of EF.The importance of adapting RtI to new possibilities such as the use of virtual reality is discussed and a theoretical framework for carrying that out is provided.

Dynamic responses of deep underground explosions based on improved Grigorian model

It is important to investigate the dynamic behaviors of deep rocks near explosion cavity to reveal the mechanisms of deformations and fractures. Some improvements are carried out for Grigorian model with focuses on the dilation effects and the relaxation effects of deep rocks, and the high pressure equations of states with Mie-Grüneisen form are also established. Numerical calculations of free field parameters for deep underground explosions are carried out based on the user subroutines which are compiled by means of the secondary development functions of LS-DYNA9703 D software. The histories of radial stress, radial velocity and radial displacement of rock particles are obtained, and the calculation results are compared with those of U.S. Hardhat nuclear test. It is indicated that the dynamic responses of free field for deep underground explosions are well simulated based on improved Grigorian model, and the calculation results are in good agreement with the data of U.S. Hardhat nuclear test. The peak values of particle velocities are consistent with those of test, but the waveform widths and the rising times are obviously greater than those without dilation effects. The attenuation rates of particle velocities are greater than the calculation results with classic plastic model, and they are consistent with the results of Hardhat nuclear test. The attenuation behaviors and the rising times of stress waves are well shown by introducing dilation effects and relaxation effects into the calculation model. Therefore, the defects of Grigorian model are avoided. It is also indicated that the initial stress has obvious influences on the waveforms of radial stress and the radial displacements of rock particles.

Fiscal Policy Effect Analysis Based on Agents Response Equilibrium (ARE) Model

Agents response equilibrium (ARE) model has been taken advantage of to build a multi-agent system for analyzing fiscal policy effect. Through establishing various types of economic entities and endowing them with abilities to react and make decision, the whole system will evolve to new conditions in response to policy change. Compared with different scenarios, it can be concluded that when raising taxation ratio, sectoral scale will shrink to some extent. But supported by government expenditure, certain sectors could be kept in comparatively larger production scale.

Research on the response model of microbolometer

There are certain limitations in the application of uncooled focal plane array （FPA） detector due to the lack of an effective response model which reliably transforms the target temperature to analog output voltage. This paper establishes the response model of microbolometer through researching the detection theory of microbolometer and the heat balance equation under the condition of the pulsed voltage bias. In the establishing process, we simplified the heat balance equation to acquire a simple answer. The experimental data show that, in the temperature dynamic range of 30 K, the biggest tolerance between the model data and the experiment data is 0.2 K; while in the temperature dynamic range of 100 K, it is 1 K. This model can reflect the real response of the microbolometer with only small differences which are acceptable in engineering applications.

Integrated systemic inflammatory response syndrome epidemic model in scale-free networks

Based on the scale-free network, an integrated systemic inflammatory response syndrome model with artificial immunity, a feedback mechanism, crowd density and the moving activities of an individual can be built. The effects of these factors on the spreading process are investigated through the model. The research results show that the artificial immunity can reduce the stable infection ratio and enhance the spreading threshold of the system. The feedback mechanism can only reduce the stable infection ratio of system, but cannot affect the spreading threshold of the system. The bigger the crowd density is, the higher the infection ratio of the system is and the smaller the spreading threshold is. In addition, the simulations show that the individual movement can enhance the stable infection ratio of the system only under the condition that the spreading rate is high, however, individual movement will reduce the stable infection ratio of the system.

Weighted Likelihood Estimation Method Based on the Multidimensional Nominal Response Model

The Monte Carlo study evaluates the relative accuracy of Warm＇s （1989） weighted likelihood estimate （WLE） compared to the maximum likelihood estimate （MLE） using the nominal response model. And the results indicate that WLE was more accurate than MLE.

A model for the response of wave directions in slowly turning wind fields

On the basis of the wave energy balance equation, the response model of mean directions of locally wind-generated waves in slowly turning wind fields has been derived. The results show that in a homogeneous field, the time scale of the response is not only related to the rate of wave growth, but also to the directional energy distribution and the angle between the wind direction and the mean wave direction. Furthermore, the law of change in the mean wave direction has been derived. The numerical computations show that the response of wave directions to slowly turning wind directions can be treated as the superposition of the responses of wave directions to a series of sudden small-angle changes of wind directions and the turning rate of the mean wave direction depends on the turning rate and the total turning angles of the wind direction. The response of wave directions is in agreement with the response for a sudden change of wind directions if the change in wind directions is very fast. Based on the normalized rates of wave growth under local winds presented by Wen et al. (1989), a quantitative estimate of the time scale of the response shows that the relationships between the dimensionless time scale and both the dimensionless total wave energy and the dimensionless peak frequency agree fairly well with the observations in comparison with other models.

Design optimization of transonic compressor stage using CFD and response surface model

In order to shorten the design period, the paper describes a new optimization strategy for computationally expensive design optimization of turbomachinery, combined with design of experiment (DOE), response surface models (RSM), genetic algorithm (GA) and a 3-D Navier-Stokes solver(Numeca Fine). Data points for response evaluations were selected by improved distributed hypercube sampling (IHS) and the 3-D Navier-Stokes analysis was carried out at these sample points. The quadratic response surface model was used to approximate the relationships between the design variables and flow parameters. To maximize the adiabatic efficiency, the genetic algorithm was applied to the response surface model to perform global optimization to achieve the optimum design of NASA Stage 35. An optimum leading edge line was found, which produced a new 3-D rotor blade combined with sweep and lean, and a new stator one with skew. It is concluded that the proposed strategy can provide a reliable method for design optimization of turbomachinery blades at reasonable computing cost.

Elastic strain response in the modified phase-field-crystal model

To understand and develop new nanostructure materials with specific mechanical properties, a good knowledge of the elastic strain response is mandatory. Here we investigate the linear elasticity response in the modified phase-field-crystal（MPFC） model. The results show that two different propagation modes control the elastic interaction length and time, which determine whether the density waves can propagate or not. By quantitatively calculating the strain field, we find that the strain distribution is indeed extremely uniform in case of elasticity. Further, we present a detailed theoretical analysis for the orientation dependence and temperature dependence of shear modulus. The simulation results show that the shear modulus reveals strong anisotropy and the one-mode analysis provides a good guideline for determining elastic shear constants until the system temperature falls below a certain value.

Dynamic finite element model updating using meta-model and genetic algorithm

Current dynamic finite element model updating methods are not efficient or restricted to the problem of local optima. To circumvent these, a novel updating method which integrates the meta-model and the genetic algorithm is proposed. Experimental design technique is used to determine the best sampling points for the estimation of polynomial coefficients given the order and the number of independent variables. Finite element analyses are performed to generate the sampling data. Regression analysis is then used to estimate the response surface model to approximate the functional relationship between response features and design parameters on the entire design space. In the fitness evaluation of the genetic algorithm, the response surface model is used to substitute the finite element model to output features with given design parameters for the computation of fitness for the individual. Finally, the global optima that corresponds to the updated design parameter is acquired after several generations of evolution. In the application example, finite element analysis and modal testing are performed on a real chassis model. The finite element model is updated using the proposed method. After updating, root-mean-square error of modal frequencies is smaller than 2%. Furthermore, prediction ability of the updated model is validated using the testing results of the modified structure. The root-mean-square error of the prediction errors is smaller than 2%.

Simulation of an aircraft thermal management system based on vapor cycle response surface model

The modern aircraft Thermal Management System(TMS)faces significant challenges due to increasing thermal loads and limited heat dissipation pathways.To optimize TMS during the conceptual design stage,the development of a modeling and simulation tool is crucial.In this study,a TMS simulation model library was created using MATLAB/SIMULINK.To simplify the complexity of the Vapor Cycle System(VCS)model,a Response Surface Model(RSM)was constructed using the Monte Carlo method and validated through simulation experiments.Taking the F-22 fighter TMS as an example,a thermal dynamic simulation model was constructed to analyze the variation of thermal response parameters in key subsystems and elucidate their coupling relationships.Furthermore,the impact of total fuel flow and ram air flow on the TMS was investigated.The findings demonstrate the existence of an optimal total fuel flow that achieves a balance between maximizing fuel heat sink utilization and minimizing bleed air demand.The adaptive distribution of fuel and ram air flow was found to enhance aircraft thermal management performance.This study contributes to improving modeling efficiency and enhancing the understanding of the thermal dynamic characteristics of TMS,thereby facilitating further optimization in aircraft TMS design.

Study on the Photosynthetic Characteristics of Six Varieties(Strains)in Chinese Chestnut

[Objectives]This study was conducted to investigate the differences of photosynthetic physiological characteristics of different varieties(strains),which will provide a theoretical basis for high photosynthesis efficiency breeding and application in Chinese chestnut.[Methods]Six Chinese chestnut varieties of Castanea mollissima‘Yanbao’,C.mollissima‘Yanqiu’,C.mollissima‘Yanchang’,C.mollissima‘Yanjia’,C.mollissima‘Qianxi 37’,and C.mollissima‘Hybrid 22’were used as the materials.Using the portable photosynthesis system Li-6400,we measured the photosynthetic characteristics and diurnal variation of leaf samples of six different chestnut varieties or strains.We fitted the light response curves and photosynthetic parameters using the leaf floating model.Additionally,we determined the chlorophyll content in the leaves using a UV-visible spectrophotometer.[Results]Among the six chestnut varieties or strains,‘Yanqiu’exhibited a significantly higher photosynthetic light saturation point(P LSP)compared to other five varieties,and‘Hybrid 22’ranked second,indicating that these two varieties had the strongest adaptation to high light intensity.The photosynthetic light compensation point(P LCP)of‘Yanchang’was significantly higher than other five varieties,and"Qianxi 37"ranked second,indicating that these two varieties had the strongest adaptation to low light intensity.Additionally,they exhibited higher chlorophyll content and maintained good photosynthetic characteristics even in shaded environments with weak light stress.Varieties‘Yanbao’and‘Yanjia’showed higher P LSP and lower P LCP,indicating that these two varieties have a wider range of adaptation to light intensity.They were capable of efficiently utilizing light across a broader spectrum of intensities.‘Yanqiu’had the highest maximum net photosynthetic rate(P n,max)and the lowest dark respiration rate(R d),along with the highest chlorophyll content.It indicated that‘Yanqiu’has strong photosynthetic capacity and organic matter accumulation ability.It also had the highest P LSP,enabling it to fully utilize the high light environment of the Yanshan Mountains and possessed high light efficiency characteristics.The P n,max of‘Yanqiu’was significantly higher than other varieties.‘Hybrid 22’and‘Yanbao’also exhibited significantly higher P n,max compared with‘Yanjia’and‘Qianxi 37’.‘Yanchang’had the lowest P n,max.The order of P n,max among the six chestnut varieties or strains was as follows:‘Yanqiu’>‘Hybrid 22’>‘Yanbao’>‘Yanjia’>‘Qianxi 37’>‘Yanchang’.[Conclusions]

Modeling of Ship Maneuvering Motion Using Neural Networks

In this paper, Neural Networks （NNs） are used in the modeling of ship maneuvering motion. A nonlinear response model and a linear hydrodynamic model of ship maneuvering motion are also investigated. The maneuverability indices and linear non-dimensional hydrodynamic derivatives in the models are identified by using two-layer feed forward NNs. The stability of parametric estimation is confirmed. Then, the ship maneuvering motion is predicted based on the obtained models. A comparison between the predicted results and the model test results demonstrates the validity of the proposed modeling method.

Response of Biomass Spatial Pattern of Alpine Vegetation to Climate Change in Permafrost Region of the Qinghai-Tibet Plateau,China

Alpine ecosystems in permafrost region are extremely sensitive to climate changes.To determine spatial pattern variations in alpine meadow and alpine steppe biomass dynamics in the permafrost region of the Qinghai-Tibet Plateau,China,calibrated with historical datasets of above-ground biomass production within the permafrost region's two main ecosystems,an ecosystem-biomass model was developed by employing empirical spatialdistribution models of the study region's precipitation,air temperature and soil temperature.This model was then successfully used to simulate the spatio-temporal variations in annual alpine ecosystem biomass production under climate change.For a 0.44°C decade-1 rise in air temperature,the model predicted that the biomasses of alpine meadow and alpine steppe remained roughly the same if annual precipitation increased by 8 mm per decade-1,but the biomasses were decreased by 2.7% and 2.4%,respectively if precipitation was constant.For a 2.2°C decade-1 rise in air temperature coupled with a 12 mm decade-1 rise in precipitation,the model predicted that the biomass of alpine meadow was unchanged or slightly increased,while that of alpine steppe was increased by 5.2%.However,in the absence of any rise in precipitation,the model predicted 6.8% and 4.6% declines in alpine meadow and alpine steppe biomasses,respectively.The response of alpine steppe biomass to the rising air temperatures and precipitation was significantly lesser and greater,respectively than that of alpine meadow biomass.A better understanding of the difference in alpine ecosystem biomass production under climate change is greatly significant with respect to the influence of climate change on the carbon and water cycles in the permafrost regions of the Qinghai-Tibet Plateau.

Parameter identification and global sensitivity analysis of Xin'anjiang model using meta-modeling approach

Parameter identification, model calibration, and uncertainty quantification are important steps in the model-building process, and are necessary for obtaining credible results and valuable information. Sensitivity analysis of hydrological model is a key step in model uncertainty quantification, which can identify the dominant parameters, reduce the model calibration uncertainty, and enhance the model optimization efficiency. There are, however, some shortcomings in classical approaches, including the long duration of time and high computation cost required to quantitatively assess the sensitivity of a multiple-parameter hydrological model. For this reason, a two-step statistical evaluation framework using global techniques is presented. It is based on （1） a screening method （Morris） for qualitative ranking of parameters, and （2） a variance-based method integrated with a meta-model for quantitative sensitivity analysis, i.e., the Sobol method integrated with the response surface model （RSMSobol）. First, the Morris screening method was used to qualitatively identify the parameters＇ sensitivity, and then ten parameters were selected to quantify the sensitivity indices. Subsequently, the RSMSobol method was used to quantify the sensitivity, i.e., the first-order and total sensitivity indices based on the response surface model （RSM） were calculated. The RSMSobol method can not only quantify the sensitivity, but also reduce the computational cost, with good accuracy compared to the classical approaches. This approach will be effective and reliable in the global sensitivity analysis of a complex large-scale distributed hydrological model.

A Microscale Model for Air Pollutant Dispersion Simulation in Urban Areas： Presentation of the Model and Performance over a Single Building

A microscale air pollutant dispersion model system is developed for emergency response purposes. The model includes a diagnostic wind field model to simulate the wind field and a random-walk air pollutant dispersion model to simulate the pollutant concentration through consideration of the influence of urban buildings. Numerical experiments are designed to evaluate the model＇s performance, using CEDVAL （Compilation of Experimental Data for Validation of Microscale Disper- sion Models） wind tunnel experiment data, including wind fields and air pollutant dispersion around a single building. The results show that the wind model can reproduce the vortexes triggered by urban buildings and the dispersion model simulates the pollutant concentration around buildings well. Typically, the simulation errors come from the determination of the key zones around a building or building cluster. This model has the potential for multiple applications; for example, the prediction of air pollutant dispersion and the evaluation of environmental impacts in emergency situations; urban planning scenarios; and the assessment of microscale air quality in urban areas.

Prediction Model for Vortex-Induced Vibration of Circular Cylinder with Data of Forced Vibration

A model based on the data from forced vibration experiments is developed for predicting the vortex-induced vibra- tions （VIV） of elastically mounted circular cylinders in flow. The assumptions for free and forced vibration tests are explored briefly. Energy equilibrium is taken into account to set up the relationship between the dynamic response of selfexcited oscillations and the force coemcients from forced vibration experiments. The gap between these two cases is bridged straightforwardly with careful treatment of key parameters. Given reduced mass m^# and material damping ratio of an elastically mounted circular cylinder in flow, the response characteristics such as amplitude, frequency, lock-in range, added mass coefficient, cross-flow fluid force and the corresponding phase angle can be predicted all at once. In- stances with different combination of reduced mass and material damping ratio are compared to investigate their effects on VIV. The hysteresis phenomenon can be interpreted reasonably. The predictions and the results from recent experiments carried out by Wifliamson＇ s group are in rather good agreement.

Statistical Modeling Studies of Iron Recovery from Red Mud Using Thermal Plasma

Optimization studies of plasma smelting of red mud were carried out. Reduction of the dried red mud fines was done in an extended arc plasma reactor to recover the pig iron. Lime grit and low ash metallurgical （LAM） coke were used as the flux and reductant, respectively. 2level factorial design was used to study the influence of all parameters on the responses. Response surface modeling was done with the data obtained from statistically designed experiments. Metal recovery at optimum parameters was found to be 79.52%.