人工神经网络方法辨识岩体力学参数的可辨识性及其稳定性探讨

探讨了以巷道围岩变形观测为依据 ,用神经网络反推岩体物理力学性质和初始地应力环境参数时各参数的可辨识性 ,以及参数辨识的稳定性。找出了待辨识参数个数与所需最少巷道变形观测项目数之间的关系 ,并给出了巷道围岩变形观测项目选择的建议     

中国海洋石油总部办公楼

从中国海洋石油总部办公楼的象征性建筑形态入手,对城市建筑形象与城市空间、建筑内外空间景观、传统建筑空间形态与现代建筑手法以及新材料、新技术在现代化办公建筑中的应用进行了探讨。     

A user perspective on errors-in-variables methods in system identification

The paper starts with a brief survey of errors-in-variables methods in system identification. Background and motivation are given, and it is illustrated why the identification problem can be difficult. Under general weak assumptions, the system is not identifiable, but can be parameterized using one degree of freedom. Examples where identifiability is achieved under additional assumptions are also provided. A number of approaches for parameter estimation of errors-in-variables models are reviewed. The underlying assumptions and principles for each approach are highlighted. The paper then continues by discussing from a user’s perspective on how to proceed when practical problems are handled.     

Assessing and ensuring parameter identifiability for a physically-based strain hardening model for twinning-induced plasticity

Physically-based strain hardening models have become important ingredients in metal forming simulations over the last years, since they allow for the modeling of multi-stage forming processes based on the evolution of physically meaningful internal variables. Although these models are physically-based, there are still many fitting parameters involved which have to be identified from experiments. As a matter of fact, for each physical effect that is included in the model, a separate equation with new fitting parameters is introduced, such that physically-based models tend to contain a large number of fitting parameters. Parameter estimation is often based on the macroscopic response of a specimen which is tested in compression, tension or shear at various strain rates and temperatures. It is not guaranteed that this macroscopic information suffices to estimate parameters in model equations that describe (sub-) microscopic phenomena, since the effect of one parameter on the course of strain hardening can be compensated by other parameters. Since such parameter correlations are hard to detect from the model equations alone, the parameter estimation process may be ill-conditioned, i.e. numerous parameter sets can be found for such models that deliver almost the same minimum value of the error function in the parameter identification process. Given that parameter estimation involves a series of costly experiments, methods are needed that allow for analyzing the identifiability of the model parameters before costly experiments are performed. In this paper, an approach is presented that analyzes model parameter dependencies and quantifies the identifiability of the model parameters. The model considered in this study calculates the flow stress based on the evolution of three dislocation densities and the evolution of deformation twins. The analysis shows that correlations between the model parameters exist and that it is not possible to determine all model parameters based on an experimental set of flow curves in a single curve fitting procedure. An adapted fitting strategy is presented in which fitting is performed step-wise so that in each fitting step, only identifiable parameters are estimated, allowing for successful parameter identification.     

Extensions to modeling aerobic carbon degradation using combined respirometric-titrimetric measurements in view of activated sludge model calibration

Recently a model was introduced to interpret the respirometric (OUR) -titrimetric (Hp) data obtained from aerobic oxidation of different carbon sources in view of calibration of Activated Sludge Model No.1 (ASM1). The model requires, among others, the carbon dioxide transfer rate (CTR) to be relatively constant during aerobic experiments. As CTR is an inherently nonlinear process, this assumption may not hold for certain experimental conditions. Hence, we extended the model to describe the nonlinear CTR behavior. A simple calibration procedure of the CO2 model was developed only using titrimetric data. The identifiable parameter subset of this model when using titrimetric data only contained the first equilibrium constant of the CO2 dissociation, pK1, the initial aqueous CO2 concentration, C(Tinit) and the nitrogen content of biomass, i(NBM). The extended model was then successfully applied to interpret typical data obtained from respirometric-titrimetric measurements with a nonlinear CO2 stripping process. The parameter estimation results using titrimetric data were consistent with the results estimated using respirometric data (OUR) alone or combined OUR and Hp data, thereby supporting the validity of the dynamic CO2 model and its calibration approach. The increased range of applicability and accurate utilization of the titrimetric data are expected to contribute particularly to the improvement of calibration of ASM models using batch experiments.     

Identification of dynamic models in complex networks with prediction error methods—Basic methods for consistent module estimates

The problem of identifying dynamical models on the basis of measurement data is usually considered in a classical open-loop or closed-loop setting. In this paper, this problem is generalized to dynamical systems that operate in a complex interconnection structure and the objective is to consistently identify the dynamics of a particular module in the network. For a known interconnection structure it is shown that the classical prediction error methods for closed-loop identification can be generalized to provide consistent model estimates, under specified experimental circumstances. Two classes of methods considered in this paper are the direct method and the joint-IO method that rely on consistent noise models, and indirect methods that rely on external excitation signals like two-stage and IV methods. Graph theoretical tools are presented to verify the topological conditions under which the several methods lead to consistent module estimates.     

Identification of variable coefficients for vibrating systems by boundary control and observation

We consider the identification problem of coefficients for vibrating systems described by a Euler-Bernoulli beam equation or a string equation, with one end clamped and with an input exerted on the other end. For the beam equation, the observations are the velocity and the angle velocity at the free end, while for the string equation, the observation is the velocity at the free end. In the framework of well-posed linear system theory, we show that both the density and the flexural rigidity of the beam, and the tension of the string, can be uniquely determined by the observations for all positive times. Moreover, a general constructive method is developed to show that the mass density and the elastic modulus of the string are not determined by the observation.     

Estimation of HIV/AIDS parameters

This paper shows how well-established control system techniques can be introduced to formulate guidelines for clinical testing and monitoring of HIV/AIDS disease and the estimation of HIV/AIDS parameters. It is assumed that the viral load and healthy CD4+T cell in plasma are measured. The objective is to estimate all parameters in the basic three-dimensional HIV/AIDS model. For this purpose, through an analysis of basic system properties, the minimal number of measurement samples for the CD4+T cell and the viral load counts is first obtained. The paper determines then the HIV progression stages when an estimation of all parameters is impossible. Outside these stages, the paper proposes two on-line estimation algorithms for all HIV parameters based on the well-known techniques of adaptive identifiers and adaptive observers. Conditions for parameter convergence are discussed. Simulation results are demonstrated for the parameter estimation using adaptive observers.     

Identifiability of errors in variables dynamic systems

There has been substantial research carried out on the errors in variables (EIV) identifiability problem for dynamic systems. These results are spread across a significant volume of literature. Here, we present a single theorem which compactly summarizes many of the known results. The theorem also covers several cases which we believe to be novel. We analyze single input single output systems using second order properties. We also extend the results to a class of multivariable systems.     

Endowment heterogeneity and identifiability in the information-exchange dilemma

In a laboratory experiment providing an information-exchange dilemma we obtained evidence that people in an asymmetric dilemma situation apply a general cooperation norm as well as a norm of proportionality. The results showed that for privileged people the significance of the norm of proportionality is reduced. This egocentric bias allows them to justify that their privilege does not obligate them to contribute more than others. However, this bias is not strong enough to totally invalidate the norm of proportionality. Even with this bias privileged people contributed more than unprivileged. In addition, we found people to be more cooperative if their behavior in the information exchange is identifiable, whereas identifiability does not influence people’s general cooperation norm nor their fairness concept.