On the 4D Variational Data Assimilation with Constraint Conditions

An investigation is carried out on the problem involved in 4D variational data assimilation (VDA) with constraint conditions based on a finite-element shallow-water equation model. In the investigation, the adjoint technology, penalty method and augmented Lagrangian method are used in constraint optimization field to minimize the defined constraint objective functions. The results of the numerical experiments show that the optimal solutions are obtained if the functions reach the minima. VDA with constraint conditions controlling the growth of gravity oscillations is efficient to eliminate perturbation and produces optimal initial field. It seems that this method can also be applied to the problem in numerical weather prediction. Key words Variational data assimilation - Constraint conditions - Penalty methods - finite-element model This research is supported by National Natural Science Foundation of China (Grant No. 49575269) and by National Key Basic Research on the Formation Mechanism and Prediction Theory of Severe Synoptic Disasters (Grant No. G1998040910).

Effective data sampling strategies and boundary condition constraints of physics-informed neural networks for identifying material properties in solid mechanics

Material identification is critical for understanding the relationship between mechanical properties and the associated mechanical functions.However,material identification is a challenging task,especially when the characteristic of the material is highly nonlinear in nature,as is common in biological tissue.In this work,we identify unknown material properties in continuum solid mechanics via physics-informed neural networks(PINNs).To improve the accuracy and efficiency of PINNs,we develop efficient strategies to nonuniformly sample observational data.We also investigate different approaches to enforce Dirichlet-type boundary conditions(BCs)as soft or hard constraints.Finally,we apply the proposed methods to a diverse set of time-dependent and time-independent solid mechanic examples that span linear elastic and hyperelastic material space.The estimated material parameters achieve relative errors of less than 1%.As such,this work is relevant to diverse applications,including optimizing structural integrity and developing novel materials.

Optimization of Generator Based on Gaussian Process Regression Model with Conditional Likelihood Lower Bound Search

The noise that comes from finite element simulation often causes the model to fall into the local optimal solution and over fitting during optimization of generator.Thus,this paper proposes a Gaussian Process Regression(GPR)model based on Conditional Likelihood Lower Bound Search(CLLBS)to optimize the design of the generator,which can filter the noise in the data and search for global optimization by combining the Conditional Likelihood Lower Bound Search method.Taking the efficiency optimization of 15 kW Permanent Magnet Synchronous Motor as an example.Firstly,this method uses the elementary effect analysis to choose the sensitive variables,combining the evolutionary algorithm to design the super Latin cube sampling plan;Then the generator-converter system is simulated by establishing a co-simulation platform to obtain data.A Gaussian process regression model combing the method of the conditional likelihood lower bound search is established,which combined the chi-square test to optimize the accuracy of the model globally.Secondly,after the model reaches the accuracy,the Pareto frontier is obtained through the NSGA-II algorithm by considering the maximum output torque as a constraint.Last,the constrained optimization is transformed into an unconstrained optimizing problem by introducing maximum constrained improvement expectation(CEI)optimization method based on the re-interpolation model,which cross-validated the optimization results of the Gaussian process regression model.The above method increase the efficiency of generator by 0.76%and 0.5%respectively;And this method can be used for rapid modeling and multi-objective optimization of generator systems.

DEDUCTION OF CONSTRAINT CONDITIONS IN THE CALIBRATION OF STEREO-VISION SYSTEN

In the test-field calibration,multi-azimuth stereo image pairs areproduced of the outdoor large control-field by the stereo-vision system under cali-bration.While in the analytical processing,the relationship between image pairsis adopted as a constraint condition,which ensures the stability and quality of thecalibration results.This paper introduces the deduction process of the constraintconditions.

A Note on the Guignard Constraint Qualification and the Guignard Regularity Condition in Vector Optimization

Some remarks are made on the use of the Abadie constraint qualification, the Guignard constraint qualifications and the Guignard regularity condition in obtaining weak and strong Kuhn-Tucker type optimality conditions in differentiable vector optimization problems.

Consistency Conditions and Constraints on Generalized f(R) Gravity with Arbitrary Geometry-Matter Coupling

We study the consistency conditions of the generalized f （ R） gravity by extending f （ R） gravity with non-minimal coupling to the generalized f（R） with arbitrary geometry-matter coupling. Specifically, we discuss the two particular models of generalized f（R） by means of consistency conditions. It is found that the second model is not physically viable so as to be ruled out. Moreover, we further constrain the first model using the Dolgov- Kawasaki stability criterion, and give the value ranges of the parameters in the first model It is worth stressing that our results include the ones in f（R） gravity with non-minimal coupling as the special case of Q（Lm） = Lm.

On the Second Order Optimality Conditions for Optimization Problems with Inequality Constraints

A nonlinear optimization problem (P) with inequality constraints can be converted into a new optimization problem (PE) with equality constraints only. This is a Valentine method for finite dimensional optimization. We review second order optimality conditions for (PE) in connection with those of (P). A strictly complementary slackness condition can be made to get the property that sufficient optimality conditions for (P) imply the same property for (PE). We give some new results (see Theorems 3.1, 3.2 and 3.3) .Without any assumption, a counterexample is given to show that these conditions are not equivalent.

Connecting Conditions and Constraint Equations in Applied Science

To solve the optimal solution of some issues in applied science, studying of connecting conditions, constraint conditions and constraint equations is made. This paper cites an example in point in vibration mechanics and seeks the connecting conditions and constraint equations of high speed compound rotating system. This paper points out that the selection of the boundary conditions or connection conditions can effect on the optimal solution of the issue as soon as the object function is determined.

Gait Recognition via Cross Walking Condition Constraint

Gait recognition is a biometric technique that captures human walking pattern using gait silhouettes as input and can be used for long-term recognition.Recently proposed video-based methods achieve high performance.However,gait covariates or walking conditions,i.e.,bag carrying and clothing,make the recognition of intra-class gait samples hard.Advanced methods simply use triplet loss for metric learning,which does not take the gait covariates into account.For alleviating the adverse influence of gait covariates,we propose cross walking condition constraint to explicitly consider the gait covariates.Specifically,this approach designs center-based and pair-wise loss functions to decrease discrepancy of intra-class gait samples under different walking conditions and enlarge the distance of inter-class gait samples under the same walking condition.Besides,we also propose a video-based strong baseline model of high performance by applying simple yet effective tricks,which have been validated in other individual recognition fields.With the proposed baseline model and loss functions,our method achieves the state-of-the-art performance.

Energy Conditions and Constraints on the Generalized Non-Local Gravity Model

We study and derive the energy conditions in generalized non-local gravity, which is the modified theory of general relativity obtained by adding a term m2n-2R□-nRto the Einstein-Hilbert action. Moreover, to obtain some insight on the meaning of the energy conditions, we illustrate the evolutions of four energy conditions with the model parameter ε for different n. By analysis we give the constraints on the model parameters ε.

Some Convexificators-Based Optimality Conditions for Nonsmooth Mathematical Program with Vanishing Constraints

In this paper, by using the notion of convexificator, we introduce the generalized standard Abadie constraint qualification and the generalized MPVC Abadie constraint qualification, and define the generalized stationary conditions for the nonsmooth mathematical program with vanishing constraints (MPVC for short). We show that the generalized strong stationary is the first order necessary optimality condition for nonsmooth MPVC under the generalized standard Abadie constraint qualification. Sufficient conditions for global or local optimality for nonsmooth MPVC are also derived under some generalized convexity assumptions.

SECOND-ORDER OPTIMALITY CONDITIONS FOR OPTIMAL CONTROL PROBLEMS GOVERNED BY 3-DIMENSIONAL NEVIER-STOKES EQUATIONS

This article is concerned with second-order necessary and sufficient optimality conditions for optimal control problems governed by 3-dimensional Navier-Stokes equations. The periodic state constraint is considered.

A counterexample of the Euler condition:the Appell-Hamel dynamical system on a horizontally moving plate

As a counterexample of the Euler condition for nonholonomic constraint problems [H. C. Shen, Acta Phys. Sin. 54, 2468 （2005）], we investigate the Apell-Hamel dynamical system on a horizontally moving plate. The inconsistency of the results with Newton mechanics suggests that the Euler condition is not a universal model for nonlinear nonholonomic systems. This is attributed to the fact that the virtual displacements so obtained are not normal to the constraint forces.

New initial condition of the new agegraphic dark energy model

The initial condition Ωde（zini）=n^2（1＋zini）^-2/4 at zini = 2000,widely used to solve the differential equation of the density of the new agegraphic dark energy（NADE） Ωde,makes the NADE model a single-parameter dark-energy cosmological model.However,we find that this initial condition is only applicable in a flat universe with only dark energy and pressureless matter.In fact,in order to obtain more information from current observational data,such as the cosmic microwave background（CMB） and the baryon acoustic oscillations（BAO）,we need to consider the contribution of radiation.For this situation,the initial condition mentioned above becomes invalid.To overcome this shortcoming,we investigate the evolutions of dark energy in matter-dominated and radiation-dominated epochs,and obtain a new initial condition de（zini）=n2（1＋zini）-2（1＋F（zini））2/4 at z ini = 2000,where F（z）≡Ωr0（1＋z）/[Ωm0＋Ωr0（1＋z）] with Ωr0 and Ωm0 being the current density parameters of radiation and pressureless matter,respectively.This revised initial condition is applicable for the differential equation of Ωde obtained in the standard Friedmann-Robertson-Walker（FRW） universe with dark energy,pressureless matter,radiation,and even spatial curvature,and can still keep the NADE model as a single-parameter model.With the revised initial condition and the observational data of type Ia supernova（SNIa）,CMB,and BAO,we finally constrain the NADE model.The results show that the single free parameter n of the NADE model can be constrained tightly.

Growing Sandpile Problem with Local and Non-Local Boundaries Conditions

In this paper, we study a class of Prigozhin equation for growing sandpile problem subject to local and a non-local boundary condition. The problem is a generalized model for a growing sandpile problem with Neumann boundary condition (see [1]). By the semi-group theory, we prove the existence and uniqueness of the solution for the model and thanks to a duality method we do the numerical analysis of the problem. We finish our work by doing numerical simulations to validate our theoretical results.

An intelligent automatic correlation method of oilbearing strata based on pattern constraints:An example of accretionary stratigraphy of Shishen 100 block in Shinan Oilfield of Bohai Bay Basin,East China

Aiming at the problem that the data-driven automatic correlation methods which are difficult to adapt to the automatic correlation of oil-bearing strata with large changes in lateral sedimentary facies and strata thickness,an intelligent automatic correlation method of oil-bearing strata based on pattern constraints is formed.We propose to introduce knowledge-driven in automatic correlation of oil-bearing strata,constraining the correlation process by stratigraphic sedimentary patterns and improving the similarity measuring machine and conditional constraint dynamic time warping algorithm to automate the correlation of marker layers and the interfaces of each stratum.The application in Shishen 100 block in the Shinan Oilfield of the Bohai Bay Basin shows that the coincidence rate of the marker layers identified by this method is over 95.00%,and the average coincidence rate of identified oil-bearing strata reaches 90.02% compared to artificial correlation results,which is about 17 percentage points higher than that of the existing automatic correlation methods.The accuracy of the automatic correlation of oil-bearing strata has been effectively improved.

The Double Self—Dual Gravity with Cosmological Term and Constraints Under the Double Constant Conformal Transformation

The double constraint equations in the self-dual gravitational theory containing the cosmological term are derived in gravity. Furthermore, in order to deeply study the Lorentzian and Euclidean reality conditions for this theory, the relations between constraints are discussed by introducing the double constant conformal transformation and the double complex function method.

Constraint Stabilization and One-Step Correction Method for Dynamical Systems

A computational method of constraint stabilization and correction is introduced. The method is based on the Baumgart＇s one-step method. Constraint conditions are addressed to stabilize and correct the solution. Two examples are given to illustrate the results of the method.

Guignard’s Constraint Qualification (GCQ) and Multiobjective Optimisation Problems

Investigation of optimality conditions has been one of the most interesting topics in the theory of multiobjective optimisation problems (MOP). To derive necessary optimality conditions of MOP, we consider assumptions called constraints qualifications. It is recognised that Guignard Constraint Qualification (GCQ) is the most efficient and general assumption for scalar objective optimisation problems;however, GCQ does not ensure Karush-Kuhn Tucker (KKT) necessary conditions for multiobjective optimisation problems. In this paper, we investigate the reasons behind that GCQ are not allowed to derive KKT conditions in multiobjective optimisation problems. Furthermore, we propose additional assumptions that allow one to use GCQ to derive necessary conditions for multiobjective optimisation problems. Finally, we also include sufficient conditions for multiobjective optimisation problems.

On Integrability of Fully Rheonomous Affine Constraints

This paper presents a complete integrability condition for fully rheonomous affine constraints in terms of the rheonomous bracket. We first define fully rheonomous affine constraints and develop geometric representation for them. Next, the rheonomous bracket is explained and some properties of it are derived. We then investigate a necessary and sufficient condition on complete integrability for the fully rheonomous affine constraints based on the rheonomous bracket as an extension of Frobenius’ theorem. The effectiveness and the availability of the new results are also evaluated via an example.