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Profile measurement with boundary information plays a vital role in the detection of quality in the assembly of aviation parts. The purpose of this paper is to improve the evaluation accuracy of the aerodynamic shapes of airplanes, the profiles of large-sized parts need to be measured accurately.

In this paper, an accurate profile measurement method based on boundary reference points is proposed for the industrial stereo-vision system. Based on the boundary-reference points, the authors established a priori constraint for extracting the boundary of the measured part. Combining with the image features of background and the measured part, an image-edge compensation model is established to extract the boundary of the measured part. The critical point of a laser stripe on the edge of the measured part is extracted corresponding to the boundary constraint. Finally, as per the principle of binocular vision, the profile of the measured part is reconstructed.

Laboratory experiments validate the measurement accuracy of the proposed method which is 0.33 mm. In the analysis of results between the measured data and the theoretical model, the measuring accuracy of the proposed method was found to be significantly higher than that of the other traditional methods.

An aviation part was measured in the part-assembly shop by the proposed method, which verified the feasibility and effectiveness of this method. The research can realize the measurement of smooth surface boundary which can solve existing profile reconstruction problems for aviation parts.

According to the two-dimensional contour constraint, critical points of the laser strip sequence at the edge of measured part are extracted and the accurate profile reconstruction with the boundary is realized.

Gives a bibliographical review of the finite element meshing and remeshing from the theoretical as well as practical points of view. Topics such as adaptive techniques for meshing and remeshing, parallel processing in the finite element modelling, etc. are also included. The bibliography at the end of this paper contains 1,727 references to papers, conference proceedings and theses/dissertations dealing with presented subjects that were published between 1990 and 2001.

Investigates errors of the reconstruction temperatures at boundaries caused by variation of the locations of two temperature sensors in a one‐dimensional inverse heat conduction problem (IHCP) by using a time marching implicit finite difference inverse solver. Numerical simulation results of selected functions indicate that errors of the reconstruction temperature at each boundary can be presented by a simple relation. Each relation contains an unknown coefficient which can be determined by using one numerical simulation through the inverse solver of a pair specified sensor locations. This relation can then be used for estimating the other recovery errors at the boundary without using the inverse solver.

The purpose of this paper is to propose a numerical procedure for discrete identification of the missing part of the domain boundary in a heat conduction problem. A new approach to sensitivity analysis is intended to give a better understanding of the influence of measurement error on boundary reconstruction.

The solution of Laplace’s equation is obtained using the Trefftz method, and then each of the sought boundary points can be derived numerically from a nonlinear equation. The sensitivity analysis comes down to the analytical evaluation of a sensitivity factor.

The proposed method very accurately recovers the unknown boundary, including irregular shapes. Even a very large number of the boundary points can be determined without causing computational problems. The sensitivity factor provides quantitative assessment of the relationship between the temperature measurement errors and boundary identification errors. The numerical examples show that some boundary reconstruction problems are error-sensitive by nature but such problems can be recognized with the use of a sensitive factor.

The present approach based on the Trefftz method separates, in terms of computation, specification of the coefficients appearing in the Trefftz method and missing coordinates of the sought boundary points. Due to introducing a sensitivity factor, a more profound sensitivity analysis was successfully conducted.

The purpose of this paper is to provide the current state of the art in the development of a computer code combining an immersed boundary method with a conjugate heat transfer (CHT) approach, including some new findings. In particular, various treatments of the fluid-solid-interface conditions are compared in order to determine the most accurate one. Most importantly, the method is capable of computing a challenging three dimensional compressible turbulent flow past an air cooled turbine vane.

The unsteady Reynolds-averaged Navier–Stokes (URANS) equations are solved within the fluid domain, whereas the heat conduction equation is solved within the solid one, using the same spatial discretization and time-marching scheme. At the interface boundary, the temperatures and heat fluxes within the fluid and the solid are set to be equal using three different approximations.

This work provides an accurate and efficient code for solving three dimensional CHT problems, such as the flow through an air cooled gas turbine cascade, using a coupled immersed boundary (IB) CHT methodology. A one-to-one comparison of three different interface-condition approximations has shown that the two multidimensional ones are slightly superior to the early treatment based on a single direction and that the one based on a least square reconstruction of the solution near the IB minimizes the oscillations caused by the Cartesian grid. This last reconstruction is then used to compute a compressible turbulent flow of industrial interest, namely, that through an air cooled gas turbine cascade. Another interesting finding is that the very promising approach based on wall functions does not combine favourably with the interface conditions for the temperature and the heat flux. Therefore, current and future work aims at developing and testing appropriate temperature wall functions, in order to further improve the accuracy – for a given grid – or the efficiency – for a given accuracy – of the proposed methodology.

An accurate and efficient IB CHT method, using a state of the art URANS parallel solver, has been developed and tested. In particular, a detailed study has elucidated the influence of different interface treatments of the fluid-solid boundary upon the accuracy of the computations. Last but not least, the method has been applied with success to solve the well-known CHT problem of compressible turbulent flow past the C3X turbine guide vane.

Electrical impedance tomography (EIT) is a technique for reconstructing the conductivity distribution by injecting currents at the boundary of a subject and measuring the resulting changes in voltage. Image reconstruction for EIT is a nonlinear problem. A generalized inverse operator is usually ill-posed and ill-conditioned. Therefore, the solutions for EIT are not unique and highly sensitive to the measurement noise.

This paper develops a novel image reconstruction algorithm for EIT based on patch-based sparse representation. The sparsifying dictionary optimization and image reconstruction are performed alternately. Two patch-based sparsity, namely, square-patch sparsity and column-patch sparsity, are discussed and compared with the global sparsity.

Both simulation and experimental results indicate that the patch based sparsity method can improve the quality of image reconstruction and tolerate a relatively high level of noise in the measured voltages.

EIT image is reconstructed based on patch-based sparse representation. Square-patch sparsity and column-patch sparsity are proposed and compared. Sparse dictionary optimization and image reconstruction are performed alternately. The new method tolerates a relatively high level of noise in measured voltages.

The identification of plasma parameters from different sets of measurements is a key topic in the thermonuclear fusion research. Most of the information relevant to the plasma shape and position control is usually gained via external magnetic measurements, but information related to internal distribution of current density is not accessible in this way. Other possible measurements are available. In this paper a performance analysis is done with respect to the adoption of polarimetric measurements.

This paper sets out to give an overview about state‐of‐the‐art optical tomographic image reconstruction algorithms that are based on the equation of radiative transfer (ERT).

An objective function, which describes the discrepancy between measured and numerically predicted light intensity data on the tissue surface, is iteratively minimized to find the unknown spatial distribution of the optical parameters or sources. At each iteration step, the predicted partial current is calculated by a forward model for light propagation based on the ERT. The equation of radiative is solved with either finite difference or finite volume methods.

Tomographic reconstruction algorithms based on the ERT accurately recover the spatial distribution of optical tissue properties and light sources in biological tissue. These tissues either can have small geometries/large absorption coefficients, or can contain void‐like inclusions.

These image reconstruction methods can be employed in small animal imaging for monitoring blood oxygenation, in imaging of tumor growth, in molecular imaging of fluorescent and bioluminescent probes, in imaging of human finger joints for early diagnosis of rheumatoid arthritis, and in functional brain imaging.

The applied research in the thermonuclear fusion area is directed towards the design of a commercial reactor. In such a reactor, the room required for the probes deputised to measure the magnetic field for the identification step of the control system must be kept to a minimum, and the number and position of probes must be optimised. A possible approach to the optimal choice of a set of magnetic probes for the reconstruction of a magnetostatic field, based on a statistical approach, is presented and discussed.

This paper deals with the inverse scattering problem of reconstructing the material properties of perfectly conducting or dielectric cylindrical objects. The material properties are reconstructed from measured far‐field scattering data provided by the Electromagnetics Technology Division, AFRL/SNH, 31 Grenier Street, Hanscom AFB, MA 01731‐3010. The measured data have to be calibrated for use in our reconstruction algorithm. The inverse scattering problem formulated as unconstrained nonlinear optimization problem is numerically solved using an iterative scheme with a variable calibration factor which will be determined during the optimization process. Numerical examples show the successful application of the method to the measured data.