Bridging element-free Galerkin and pluri-Gaussian simulation for geological uncertainty estimation in an ensemble smoother data assimilation framework

The facies distribution of a reservoir is one of the biggest concerns for geologists,geophysicists,reservoir modelers,and reservoir engineers due to its high importance in the setting of any reliable decisionmaking/optimization of field development planning.The approach for parameterizing the facies distribution as a random variable comes naturally through using the probability fields.Since the prior probability fields of facies come either from a seismic inversion or from other sources of geologic information,they are not conditioned to the data observed from the cores extracted from the wells.This paper presents a regularized element-free Galerkin(R-EFG)method for conditioning facies probability fields to facies observation.The conditioned probability fields respect all the conditions of the probability theory(i.e.all the values are between 0 and 1,and the sum of all fields is a uniform field of 1).This property achieves by an optimization procedure under equality and inequality constraints with the gradient projection method.The conditioned probability fields are further used as the input in the adaptive pluri-Gaussian simulation(APS)methodology and coupled with the ensemble smoother with multiple data assimilation(ES-MDA)for estimation and uncertainty quantification of the facies distribution.The history-matching of the facies models shows a good estimation and uncertainty quantification of facies distribution,a good data match and prediction capabilities.

Classification and Analysis of Tube Hydroforming Processes with Respect to Adaptive FEM Simulations

Tube hydroforming process is a relative new process f or production of structural parts of low weight and high rigidity. The successfu lness of the process depends largely on the a proper selection of loading path w hich is axial feeding distance as related to the applied internal pressure. Due to the complicated nature of plastic deformation, a optimum loading path which w ill guarantee good hydroformed parts free of winkle and fracture has often to be determined by finite element analysis. In order to save trials and errors, adap tive FEM simulation method has been developed. To effectively apply the adaptive simulation method, we have to know the applicability of the method. In this pap er, a classification of tube hydroforming (THF) processes based on sensitivity to loading parameters has been suggested. Characteristics of the classification have been analyzed in terms of failure mode, dominant loading parameters and th eir working windows. It was discussed that the so called pressure dominant THF p rocess is the most difficult process for both simulation in FEM analysis and pra ctical operation in real manufacturing situation. To effectively find out the op timum loading path for pressure dominant THF process, adaptive FEM simulation st rategies are mostly needed.

PARALLEL ADAPTIVE SIMULATION OF A PLUNGING LIQUID JET

This paper is concerned with three-dimensional numerical simulation of a plunging liquid jet. The transient processes of forming an air cavity around the jet, capturing an initially large air bubble, and the break-up of this large toroidal-shaped bubble into smaller bubbles were analyzed. A stabilized finite element method （FEM） was employed under parallel numerical simulations based on adaptive, unstructured grid and coupled with a level-set method to track the interface between air and liquid. These simulations show that the inertia of the liquid jet initially depresses the pool＇s surface, forming an annular air cavity which surrounds the liquid jet. A toroidal liquid eddy which is subse- quently formed in the liquid pool results in air cavity collapse, and in turn entrains air into the liquid pool from the unstable annular air gap region around the liquid jet.

Fault Diagnosis for Non-linear System Based On Adaptive Fuzzy System

Although lots of valuable results for fault diagnosis based on model have been achieved in linear system, it is difficult to apply these results to non-linear system due to the difficulty of modeling the non-linear system by analysis. Adaptive Fuzzy system provides a way for solving this problem because it can approximate any non-linear system at any accuracy. The key for adaptive Fuzzy system to solve problem is its learning ability, so the authors present a learning algorithm for Adaptive fuzzy system, which can build the system's model by learning from the measurement data as well as experience knowledge with high accuracy. Furthermore, the experiment using the learning algorithm to model a servo-mechanism and to construct the fault diagnosis system based on the model is carried out, the results is very good.

Adaptive Simulated Annealing Based Protein Loop Modeling of Neurotoxins

A loop modeling method, adaptive simulated annealing, for ab initio prediction of protein loop structures, as an optimization problem of searching the global minimum of a given energy function, is proposed. An interface-friendly toolbox—LoopModeller in Windows and Linux systems, VC++ and OpenGL environments is developed for analysis and visualization. Simulation results of three short-chain neurotoxins modeled by LoopModeller show that the method proposed is fast and efficient.

Reliability assessment for serviceability limit states of stiffened deep cement mixing column-supported embankments

The reliability and deterministic analyses of wood-cored stiffened deep cement mixing and deep cement mixing column-supported embankments(referred to as WSCSE and DCSE,respectively)considering serviceability limit state requirements are presented in this paper.Random field theory was used to simulate the spatial variability of soil
cement mixing(SCM)material in which the adaptive Kriging Monte Carlo simulation was adopted to estimate the failure probability of a column
supported embankment(CSE)system.A new method for stochastically generating random values of unconfined compressive strength(qu)and the ratio(Ru)between the undrained elastic modulus and qu of SCM material based on statistical correlation data is proposed.Reliability performance of CSEs concerning changes in the mean(μ),coefficient of variation(CoV),and vertical spatial correlation length(θv)of qu and Ru are presented and discussed.The obtained results indicate that WSCSE can provide a significantly higher reliability level and can tolerate more SCM material spatial variability than DCSE.Some performance of DCSE and WSCSE,which can be considered satisfactory in a deterministic framework,cannot guarantee an acceptable reliability level from a probabilistic viewpoint.This highlights the importance and necessity of employing reliability analyses for the design of CSEs.Moreover,consideration of only μ and CoV of qu seems to be sufficient for reliability analysis of WSCSE while for DCSE,uncertainties regarding the Ru(i.e.both μ and CoV)and θv of qu cannot be ignored.

Scale adaptive simulation of vortex structures past a square cylinder

The scale adaptive simulation（SAS） turbulence model is evaluated on a turbulent flow past a square cylinder using the open-source CFD package OpenF OAM 2.3.0. Two and three-dimensional simulations are performed to determine global quantities like drag and lift coefficients and Strouhal number in addition to mean and fluctuating velocity profiles in the recirculation and wake regions. SAS model is evaluated against the Shear Stress Transport k-ω（SST） model and also compared with previously reported results based on DES, LES and DNS turbulence approaches. Results show that global quantities along with mean velocity profiles are well-captured by 2-D SAS model. The 3-D SAS model also succeeded in providing comparable results with recently published DES study on Reynolds shear stress and velocity fluctuation components using about 12 times lower computational cost. It is shown that large values of the SAS model constant result in too dissipative behavior, so that proper calibration of the SAS model constant for different turbulent flows is vital.

Adaptive Fuzzy Torque Control of Passive Torque Servo Systems Based on Small Gain Theorem and Input-to-state Stability

Passive torque servo system （PTSS） simulates aerodynamic load and exerts the load on actuation system, but PTSS endures position coupling disturbance from active motion of actuation system, and this inherent disturbance is called extra torque. The most important issue for PTSS controller design is how to eliminate the influence of extra torque. Using backstepping technique, adaptive fuzzy torque control （AFTC） algorithm is proposed for PTSS in this paper, which reflects the essential characteristics of PTSS and guarantees transient tracking performance as well as final tracking accuracy. Takagi-Sugeno （T-S） fuzzy logic system is utilized to compensate parametric uncertainties and unstructured uncertainties. The output velocity of actuator identified model is introduced into AFTC aiming to eliminate extra torque. The closed-loop stability is studied using small gain theorem and the control system is proved to be semiglobally uniformly ultimately bounded. The proposed AFTC algorithm is applied to an electric load simulator （ELS）, and the comparative experimental results indicate that AFTC controller is effective for PTSS.

Test selection and optimization for PHM based on failure evolution mechanism model

The test selection and optimization （TSO） can improve the abilities of fault diagnosis, prognosis and health-state evalua- tion for prognostics and health management （PHM） systems. Traditionally, TSO mainly focuses on fault detection and isolation, but they cannot provide an effective guide for the design for testability （DFT） to improve the PHM performance level. To solve the problem, a model of TSO for PHM systems is proposed. Firstly, through integrating the characteristics of fault severity and propa- gation time, and analyzing the test timing and sensitivity, a testability model based on failure evolution mechanism model （FEMM） for PHM systems is built up. This model describes the fault evolution- test dependency using the fault-symptom parameter matrix and symptom parameter-test matrix. Secondly, a novel method of in- herent testability analysis for PHM systems is developed based on the above information. Having completed the analysis, a TSO model, whose objective is to maximize fault trackability and mini- mize the test cost, is proposed through inherent testability analysis results, and an adaptive simulated annealing genetic algorithm （ASAGA） is introduced to solve the TSO problem. Finally, a case of a centrifugal pump system is used to verify the feasibility and effectiveness of the proposed models and methods. The results show that the proposed technology is important for PHM systems to select and optimize the test set in order to improve their performance level.

Reliability analysis on civil engineering project based on integrated adaptive simulation annealing and gray correlation method

Dynamic reliability is a very important issue in reliability research. The dynamic reliability analysis for the project is still in search of domestic and international research in the exploration stage. By now, dynamic reliability research mainly concentrates on the reliability assessment; the methods mainly include dynamic fault tree, extension of event sequence diagram and Monte Carlo simulation, and et al. The paper aims to research the dynamic reliability optimization. On the basis of analysis of the four quality influence factors in the construction engineering, a method based on gray correlation degree is employed to calculate the weights of factors affecting construction process quality. Then the weights are added into the reliability improvement feasible index （RIFI）. Furthermore, a novel nonlinear programming mathematic optimization model is established. In the Insight software environment, the Adaptive Simulated Annealing （ASA） algorithm is used to get a more accurate construction subsystem optimal reliability under different RIFI conditions. In addition, the relationship between construction quality and construction system reliability is analyzed, the proposed methods and detailed processing can offer a useful reference for improving the construction system quality level.

Design of Water Network with Multiple Contaminants and Zero Discharge

The paper presents a procedure to design water network. First of all, water reuse system, water regeneration reuse system (including regeneration recycle) and wastewater treatment system are designed separately. But the interaction between different parts demands that each part is designed iteratively to optimize the whole water network. Therefore, on the basis of the separated design a water netvrork superstructure including reuse, regeneration and wastewater treatment is established from the system engineering point of view. And a multi-objective adaptive simulated annealing genetic algorithm is adopted to simultaneously integrate the overall water netvrork to balance the economic and environmental effects. The algorithm overcomes the defect of local optimum of simulated annealing (SA), avoids the pre-maturation of genetic algorithm (GA) and finds a set of solutions (pareto front) in acceptable computer time. Prom the pareto front, a point with minimum fresh water consumption will be extended to zero discharge as our ultimate goal.

Numerical simulation of three-dimensional breaking waves and its interaction with a vertical circular cylinder

Wave breaking plays an important role in wave-structure interaction. A novel control volume finite element method with adaptive unstructured meshes is employed here to study 3-D breaking waves. The numerical framework consists of a ＂volume of fluid＂ type method for the interface capturing and adaptive unstructured meshes to improve computational efficiency. The numerical model is validated against experimental measurements of breaking wave over a sloping beach and is then used to study the breaking wave impact on a vertical circular cylinder on a slope. Detailed complex interfacial structures during wave impact, such as plunging jet formation and splash-up are captured in the simulation, demonstrating the capability of the present method.

Response of a spherical cavity in a fully-coupled thermo-poro-elastodynamic medium by cell-adaptive second-order central high resolution schemes

In this study,fully coupled thermo-poroelastic saturated media are simulated by a grid/cell adaptive central high resolution scheme.The central method corresponds to the second order Kurganov-Tadmor(KT)scheme working on adapted cells with the total variation diminishing(TVD)stability condition.The coupled equations include motion,fluid flow,heat flow,continuity condition,and a constitutive equation.The grid/cell adaptation is performed by the interpolating wavelet transform in the multiresolution framework to capture fine scale responses and to obtain a computationally effective solver.With respect to the use of central schemes,the coupled equations should be re-expressed as a system of coupled first-order hyperbolic-parabolic partial differential equations(PDEs)with possible source(load)terms.The system is initially derived in the Cartesian coordinate system,and it is subsequently modified to consider a spherical cavity in isotropic,symmetric,and saturated media in the spherical coordinate system.It is assumed that the cavity boundary is subjected to sudden time-dependent thermal/mechanical sources.Discontinuous propagating fronts develop in the media due to the aforementioned loading.It is challenging to handle these solutions with numerical methods,and special attention is required to prevent/control numerical dispersion and dissipation.Hence,as previously mentioned,adaptive central high resolution schemes are employed in the present study.

An approach for shape optimization of stratosphere airships based on multidisciplinary design optimization

Airship shape is crucial to the design of stratosphere airships. In this paper, multidisciplinary design optimization (MDO) technology is introduced into the design of airship shape. We devise a composite objective function, based on this technology, which takes account of various factors which influence airship performance, including aerodynamics, structures, energy and weight to determine the optimal airship shape. A shape generation algorithm is proposed and appropriate mathematical models are constructed. Simulation results show that the optimized shape gives an improvement in the value of the composite objective function compared with a reference shape.

Numerical investigation of drag force on flow through circular array of cylinders

A 2-D model for flow through a circular patch with an array of vertical circular cylinders in a channel is established using the Navier-Stokes equations with a hybrid RANS/LES turbulence model-the Scale Adaptive Simulation （SAS） model. The applica- bility of the model is first validated by test cases where experimental data are available for comparison with the computed results. It is verified that the present model can predict well the average velocity and turbulence structure. The drag force and drag coefficient are then calculated using the present model for a number of cases with different solid volume fractions, cylinder Reynolds numbers and patch diameters. It is shown that the drag coefficient increases with increasing solid volume fraction, but decreases with increa- sing Reynolds number. However, the drag coefficient is independent of the diameter of circular batch when the solid volume fraction and Reynolds number are kept constant.

Lattice Boltzmann method for simulating particle-fluid interactions

The lattice Boltzmann method （LBM） has gained increasing popularity in the last two decades as an alternative numerical approach for solving fluid flow problems. One of the most active research areas in the LBM is its application in particle-fluid systems, where the advantage of the LBM in efficiency and parallel scalability has made it superior to many other direct numerical simulation （DNS） techniques. This article intends to provide a brief review of the application of the LBM in particle-fluid systems. The numerical techniques in the LBM pertaining to simulations of particles are discussed, with emphasis on the advanced treatment for boundary conditions on the particle-fluid interface. Other numerical issues, such as the effect of the internal fluid, are also briefly described. Additionally, recent efforts in using the LBM to obtain closures for particle-fluid drag force are also reviewed.

An analysis on possibility of intelligent speed adaptation in terms of drivers' consciousness

Intelligent speed adaptation （ISA） is considered as an effective measure to reduce number of traffic accidents in the field of intelligent transportation systems （ITS）. On the other hand, its effects for traffic safety are still doubted by many people. To make the possibility analysis, an experiment is conducted by using driving simulator. Regarding ISA ap- proaches, there are three modes： mandatory, voluntary and advisory. Among them, the advisory type seems to be the easiest one to introduce. Therefore, we focus on the advisory mode in this study by considering ISA just at the beginning stage in Japan. The experiment consists of four steps： without ISA, ISA using pictures, ISA using voices and again without ISA. The outputs obtained from the driving simulator are analyzed combined with the consciousness of the participants. The experiment shows that the ISA can improve recognition of speed limitation especially for people who have random rambling or looking aside tendency. Furthermore, the ISA especially when using voices can contribute in changing the consciousness of people who are aggressive in driving. Their driving speeds can reduce so that positive effects on traffic safety can be concluded.