scholarly journals Sensitivity analysis and optimization method for the fabrication of one-dimensional beam-splitting phase gratings

2015 ◽  
Vol 23 (9) ◽  
pp. 11771 ◽  
Author(s):  
Shaun Pacheco ◽  
Jonathan F. Brand ◽  
Melissa Zaverton ◽  
Tom Milster ◽  
Rongguang Liang
Keyword(s):  
Sensitivity Analysis ◽  
Optimization Method ◽  
Beam Splitting ◽  
One Dimensional

Time Integration Incorporated Sensitivity Analysis With Generalized-α Method for Multibody Dynamics Systems

2011 ◽  
Author(s):  
Guang Dong ◽  
Zheng-Dong Ma ◽  
Gregory Hulbert ◽  
Noboru Kikuchi
Keyword(s):  
Sensitivity Analysis ◽  
Topology Optimization ◽  
Dynamic Loading ◽  
Multibody Dynamics ◽  
Equations Of Motion ◽  
Time Integration ◽  
Optimization Method ◽  
Sensitivity Analysis Method ◽  
System Equations ◽  
Consecutive Time

The topology optimization method is extended for the optimization of geometrically nonlinear, time-dependent multibody dynamics systems undergoing nonlinear responses. In particular, this paper focuses on sensitivity analysis methods for topology optimization of general multibody dynamics systems, which include large displacements and rotations and dynamic loading. The generalized-α method is employed to solve the multibody dynamics system equations of motion. The developed time integration incorporated sensitivity analysis method is based on a linear approximation of two consecutive time steps, such that the generalized-α method is only applied once in the time integration of the equations of motion. This approach significantly reduces the computational costs associated with sensitivity analysis. To show the effectiveness of the developed procedures, topology optimization of a ground structure embedded in a planar multibody dynamics system under dynamic loading is presented.

scholarly journals Improved Land Evapotranspiration Simulation of the Community Land Model Using a Surrogate-Based Automatic Parameter Optimization Method

Water ◽  
2020 ◽  
Vol 12 (4) ◽  
pp. 943
Author(s):  
Chong Zhang ◽  
Zhenhua Di ◽  
Qingyun Duan ◽  
Zhenghui Xie ◽  
Wei Gong
Keyword(s):  
Sensitivity Analysis ◽  
Parameter Optimization ◽  
Land Surface ◽  
High Efficiency ◽  
Optimization Method ◽  
The Tibetan Plateau ◽  
Optimal Parameters ◽  
Community Land Model ◽  
Optimization Framework ◽  
Sensitivity Analysis Method

Land surface evapotranspiration (ET) is important in land-atmosphere interactions of water and energy cycles. However, regional ET simulation has a great uncertainty. In this study, a highly-efficient parameter optimization framework was applied to improve ET simulations of the Community Land Model version 4.0 (CLM4) in China. The CLM4 is a model at land scale, and therefore, the monthly ET observation was used to evaluate the simulation results. The optimization framework consisted of a parameter sensitivity analysis (also called parameter screening) by the multivariate adaptive regression spline (MARS) method and sensitivity parameter optimization by the adaptive surrogate modeling-based optimization (ASMO) method. The results show that seven sensitive parameters were screened from 38 adjustable parameters in CLM4 using the MARS sensitivity analysis method. Then, using only 133 model runs, the optimal values of the seven parameters were found by the ASMO method, demonstrating the high efficiency of the method. For the optimal parameters, the ET simulations of CLM4 were improved by 7.27%. The most significant improvement occurred in the Tibetan Plateau region. Additional ET simulations from the validation years were also improved by 5.34%, demonstrating the robustness of the optimal parameters. Overall, the ASMO method was found to be efficient for conducting parameter optimization for CLM4, and the optimal parameters effectively improved ET simulation of CLM4 in China.

Design Optimization Method for Composite Components Based on Moment Reliability-Sensitivity Criteria

2017 ◽  
Vol 34 (3) ◽  
Author(s):  
Zhigang Sun ◽  
Changxi Wang ◽  
Xuming Niu ◽  
Yingdong Song
Keyword(s):  
Sensitivity Analysis ◽  
Design Optimization ◽  
Reliability Analysis ◽  
Efficient Method ◽  
Ceramic Matrix Composites ◽  
Optimization Method ◽  
Calculation Model ◽  
Arbitrary Distribution ◽  
Engineering Practice ◽  
Reliability Sensitivity

AbstractIn this paper, a Reliability-Sensitivity Based Design Optimization (RSBDO) methodology for the design of the ceramic matrix composites (CMCs) components has been proposed. A practical and efficient method for reliability analysis and sensitivity analysis of complex components with arbitrary distribution parameters are investigated by using the perturbation method, the respond surface method, the Edgeworth series and the sensitivity analysis approach. The RSBDO methodology is then established by incorporating sensitivity calculation model into RBDO methodology. Finally, the proposed RSBDO methodology is applied to the design of the CMCs components. By comparing with Monte Carlo simulation, the numerical results demonstrate that the proposed methodology provides an accurate, convergent and computationally efficient method for reliability-analysis based finite element modeling engineering practice.

Sensitivity Analysis of the Wall Shear Model to the Correlations for Frequency and Slug Holdup in the Gas-Liquid Slug Flow in Pipes

2015 ◽  
Vol 1104 ◽  
pp. 61-67
Author(s):  
Luiz Eduardo Melo Lima ◽  
Eugênio Spanó Rosa
Keyword(s):  
Sensitivity Analysis ◽  
Mixture Model ◽  
Liquid Mixture ◽  
Shear Model ◽  
One Dimensional ◽  
Intermittent Behavior ◽  
Wall Shear ◽  
The One ◽  
Isothermal Gas ◽  
Liquid Flows

The one-dimensional mixture model efficiently predicts gas-liquid flows dominated by gravity force. The advantages of the mixture model are the absence of interfacial terms and the reduced number of transport equations, but its weakness lies on the constitutive laws to predict the wall shear force of a gas-liquid mixture. The objective of this work is to realize a sensitivity analysis of the wall shear model (based on the intermittent behavior of the gas and liquid structures) to the correlations for frequency and slug holdup in the one-dimensional, steady state mixture model applied to an isothermal gas-liquid mixture flowing in the slug regime. The numerical results for the pressure gradient obtained here are compared against experimental data from previous work.

scholarly journals A novel method of sensitivity analysis testing by applying drastic method and fuzzy optimization method to assess Groundwater vulnerability to pollution, case of Senegal River basin in Mali

2017 ◽  
Author(s):  
Keita Souleymane ◽  
Tang Zhonghua
Keyword(s):  
Sensitivity Analysis ◽  
Fuzzy Optimization ◽  
Groundwater Vulnerability ◽  
Optimization Method ◽  
Integrated Analysis ◽  
Fuzzy Method ◽  
Senegal River ◽  
Drastic Method ◽  
Senegal River Basin ◽  
Nitrate Distribution

Abstract. Vulnerability to groundwater pollution from Senegal basin was studied by two different but complementary methods: the DRASTIC method (which evaluates the intrinsic vulnerability) and the fuzzy method (which assesses the specific vulnerability taking into account continuity of the parameters). The validation of this application has been tested by comparing the membership in groundwater and distribution of different classes of vulnerabilities established as well as the nitrate distribution in the study area. Three vulnerability classes (low, medium and high) have been identified by both the DRASTIC method and by fuzzy method (passing by normalized model). An integrated analysis reveals that high class with 14.64 % (for the DRASTIC method), 21.68 % (for normalized DRASTIC method) and the very high grade 18.92 % (for that of fuzzy) are not the most dominant. In addition, a new method for sensitivity analysis was used to identify (and confirm) the main parameters which impact de vulnerability to pollution with fuzzy membership. And the results showed that vadose is the main parameter which impacts groundwater vulnerability to pollution while net recharge has the least contribution to pollution in the study area. It was found also that Fuzzy method better assesses the vulnerability to pollution with a coincidence rate of 81.13 % against 77.35 % for the DRASTIC method. These results are a guide for policy makers on protection areas sensitive to pollution and identification of the sites before later hosting the socio-economic infrastructures.

Optimization and sensitivity analysis of seismic depth migrations from Hibernia Field

Geophysics ◽  
1998 ◽  
Vol 63 (6) ◽  
pp. 2054-2062 ◽  
Author(s):  
Irene Kelly ◽  
Larry R. Lines
Keyword(s):  
Sensitivity Analysis ◽  
Least Squares ◽  
Real Data ◽  
Optimization Method ◽  
Velocity Estimation ◽  
Inversion Method ◽  
Depth Migration ◽  
Velocity Models ◽  
Sensitivity Analysis Method ◽  
Seismic Reflectors

Accurate imaging of seismic reflectors with depth migration requires accurate velocity models. In frontier areas with few well constraints, velocity estimation generally involves the use of methods such as normal moveout analysis, seismic traveltime tomography, or iterative prestack depth migration. These techniques can be effective, but may also be expensive or time‐consuming. In situations where we have information on formation tops from a series of wells which intersect seismic reflectors, we use a least‐squares optimization method to estimate velocity models. This method produces velocity models that optimize depth migrations in terms of well constraints by using least‐squares inversion to match the depth migration images to formation tops. The well log information is used to optimize poststack migration, thereby eliminating some of the time and expense of velocity analysis. In addition to applying an inversion method which optimizes depth migration in terms of formation tops, we can use a sensitivity analysis method of “most‐squares inversion” to explore a range of velocity models which provide mathematically acceptable solutions. This sensitivity analysis quantifies the expected result that our velocity estimates are generally less reliable for thin beds than for thick beds. The proposed optimization method is shown to be successful on synthetic and real data cases from the Hibernia Field of offshore Newfoundland.

Sensitivity Analysis of One-Dimensional Heat Transfer in Tissue With Temperature-Dependent Perfusion

1997 ◽  
Vol 119 (1) ◽  
pp. 77-80 ◽  
Author(s):  
C. R. Davies ◽  
G. M. Saidel ◽  
H. Harasaki
Keyword(s):  
Heat Transfer ◽  
Sensitivity Analysis ◽  
Heated Surface ◽  
Experimental Studies ◽  
Total Artificial Heart ◽  
Tissue Temperature ◽  
Model Parameters ◽  
Temperature Dependent ◽  
One Dimensional

Design criteria for implantable, heat-generating devices such as the total artificial heart require the determination of safe thresholds for chronic heating. This involves in-vivo experiments in which tissue temperature distributions are obtained in response to known heat sources. Prior to experimental studies, simulation using a mathematical model can help optimize the design of experiments. In this paper, a theoretical analysis of heat transfer is presented that describes the dynamic, one-dimensional distribution of temperature from a heated surface. Loss of heat by perfusion is represented by temperature-independent and temperature-dependent terms that can reflect changes in local control of blood flow. Model simulations using physiologically appropriate parameter values indicate that the temperature elevation profile caused by a heated surface adjacent to tissue may extend several centimeters into the tissue. Furthermore, sensitivity analysis indicates the conditions under which temperature profiles are sensitive to changes in thermal diffusivity and perfusion parameters. This information provides the basis for estimation of model parameters in different tissues and for prediction of the thermal responses of these tissues.

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