Inverse Modelling to Obtain Head Movement Controller Signal

Experimentally obtained dynamics of time-optimal, horizontal head rotations have previously been simulated by a sixth order, nonlinear model driven by rectangular control signals. Electromyography (EMG) recordings have spects which differ in detail from the theoretical rectangular pulsed control signal. Control signals for time-optimal as well as sub-optimal horizontal head rotations were obtained by means of an inverse modelling procedures. With experimentally measured dynamical data serving as the input, this procedure inverts the model to produce the neurological control signals driving muscles and plant. The relationships between these controller signals, and EMG records should contribute to the understanding of the neurological control of movements

Modelling of SFRC using inverse finite element analysis

A method of inverse finite element analysis is used to determine the constitutive relationship of SFRC in tension, using primary experimental data. Based on beam bending test results and results from pull-out tests, an attempt is made to explain the physical processes taking place during the cracking stage. Basic models predicting the behaviour of SFRC in tension are proposed. © RILEM 2006

Feedback methods for inverse simulation of dynamic models for engineering systems applications

Inverse simulation is a form of inverse modelling in which computer simulation methods are used to find the time histories of input variables that, for a given model, match a set of required output responses. Conventional inverse simulation methods for dynamic models are computationally intensive and can present difficulties for high-speed applications. This paper includes a review of established methods of inverse simulation,giving some emphasis to iterative techniques that were first developed for aeronautical applications. It goes on to discuss the application of a different approach which is based on feedback principles. This feedback method is suitable for a wide range of linear and nonlinear dynamic models and involves two distinct stages. The first stage involves design of a feedback loop around the given simulation model and, in the second stage, that closed-loop system is used for inversion of the model. Issues of robustness within closed-loop systems used in inverse simulation are not significant as there are no plant uncertainties or external disturbances. Thus the process is simpler than that required for the development of a control system of equivalent complexity. Engineering applications of this feedback approach to inverse simulation are described through case studies that put particular emphasis on nonlinear and multi-input multi-output models

Recent advances in the modelling of renal function

Differential equation models have become an indispensable tool in the effort towards a complete understanding of hypertonic urine formation. Recent advances in this field include the treatment of a kidney model as an inverse prob lern, the modelling of the three-dimensional Organization of the renal medulla, and dynamic models for the tubuloglomerular feedback mechanism. The latter make use of techniques from bifurcation and chaos theory

Optimal finite element modelling and efficient reconstruction in non-linear 3D electrical resistance tomography

Electrical Impedance Tomography can provide images with well-defined characteristics using a fully non-linear reconstruction process when appropriate constraints are imposed on the solution to allow the ill-posed inverse problem to be solved. Using appropriate finite element discretizations for forward solution and inverse problem offers additional advantages in the image reconstruction process, such as (a) inclusion of prior knowledge, (b) generic model templating to adapt to, for example, individual head shapes, and (c) obtaining accurate results without unnecessary computational overhead. We have developed an efficient 3D non-linear reconstruction algorithm based on a regularized inverse conjugate gradient solver which incorporates (a) local image smoothness constraints, and (b) a number of optimisations which reduce the computing power required to obtain an accurate solution. We show results from applying this to various problems which arise in medical resistivity reconstruction given only surface potential measurements and demonstrate the importance of the FE discretization. Keywords: 3D non-linear electrical impedance tomography, FE template modelling, optimal finite element meshes, 3D visualization, FE discretization

Characterization of mechanical properties in weld metal using inverse modelling

Nowadays, more oil and gas transportation pipelines are constructed in areas with permafrost and/or higher seismic activity. These pipelines can be subjected to longitudinal plastic deformations necessitating a strain based design. Since girth- and seam welds are critical in terms of structural integrity, it is desirable to know their mechanical properties. In a strain based design context, the accurate determination of yield strength and hardening are necessary. A longitudinally extracted (is parallel to the pipe axis) specimen notched at the weld region and loaded in tension, in combination with inverse modelling is assumed to be a valuable tool to determine these properties. This notched cross weld test ensures that the largest deformations will occur at the weld, thereby allowing to fully determine the stress-strain behaviour of the weld metal. Inverse modelling combines experimental full-field strain data with numerical simulations to determine the constitutive parameters. Strains will be measured experimentally and compared with simulated data. By minimizing their difference, i.e. a certain cost function, a correspondence is found and the desired parameters are determined. This paper focuses on one aspect of the inverse modelling framework, the development of the parametric finite element model

Reconstruction of the spatial dependency of dielectric and geometrical properties of adhesively bonded structures

An inverse problem motivated by the nondestructive testing of adhesively bonded structures used in the aircraft industry is studied. Using transmission line theory, a model is developed which, when supplied with electrical and geometrical parameters, accurately predicts the reflection coefficient associated with such structures. Particular attention is paid to modelling the connection between the structures and the equipment used to measure the reflection coefficient. The inverse problem is then studied and an optimization approach employed to recover these electrical and geometrical parameters from experimentally obtained data. In particular the approach focuses on the recovery of spatially varying geometrical parameters as this is paramount to the successful reconstruction of electrical parameters. Reconstructions of structure geometry using this method are found to be in close agreement with experimental observations