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The purpose of this paper is to develop a transform method and a deep learning model to identify the inner surface shape based on the measurement temperature at the outer boundary of the pipe.

The training process is assisted by the finite element method (FEM) simulation which solves the direct problem for the data preparation. To avoid re-meshing the domain when the inner surface shape varies, a new transform method is proposed to transform the shape identification problem into the effective thermal conductivity identification problem. The deep learning model is established to set up the relationship between the measurement temperature and the effective thermal conductivity. Then the unknown geometry shape is acquired by the mapping between the inner shape and the effective thermal conductivity through the inverse transform method.

The new method is successfully applied to identify the internal boundary of a pipe with eccentric circle, ellipse and nephroid inner geometries. The results show that as the measurement points increased and the measurement error decreased, the results became more accurate. The position of the measurement point and mesh density of the FEM model have less effect on the results.

The deep learning model and the transform method are developed to identify the pipe inner surface shape. There is no need to re-mesh the domain during the computation progress. The results show that the proposed method is a fast and an accurate tool for identifying the pipe inner surface.

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.

In this paper, Sensitivity Method (SM) was used to the identification of boundary conditions. Particular attention in this paper was paid to the Levenberg‐Marquardt (L‐M) regularization method, because the inverse problems of the electromagnetic field are not well conditioned in typical cases. It was proved that using some information about the expected solution, the L‐M regularization method gives satisfactory results even in such cases where the singular value analysis (SVA) fails. The identified boundary conditions were compared with the results obtained by using the direct least squares (LS) method.

The magnetic field was applied for identification of a shape of an inaccessible boundary between substances of different magnetic properties. Taking advantage of the conception of substitute field sources a mathematical model of the problem was described by means of the potential theory and integral equations. Numerical processing of Fredholm integral equations of the first kind appearing in the above model leads to a system of ill‐posed and non‐linear algebraic equations. This results in numerical instability. The problem was solved by the use of the fixed‐point technique based on Brouwer’s theorem. A few numerical examples were illustrated for the selected shape of the investigated boundary.

A mathematical description of temperature-dependent boundary conditions is crucial in manifold model-based control or prototyping applications, where accurate thermal simulation results are required. Estimation of boundary condition coefficients for complex geometries in complicated or unknown environments is a challenging task and often does not fulfill given accuracy limits without multiple manual adaptions and experiments. This paper aims to describe an efficient method to identify thermal boundary conditions from measurement data using model order reduction.

An optimization problem is formulated to minimize temperature deviation over time between simulation data and available temperature sensors. Convection and radiation effects are expressed as a combined heat flux per surface, resulting in multiple temperature-dependent film coefficient functions. These functions are approximated by a polynomial function or splines, to generate identifiable parameters. A formulated reduced order system description preserves these parameters to perform an identification. Experiments are conducted with a test-bench to verify identification results with radiation, natural and forced convection.

The generated model can approximate a nonlinear transient finite element analysis (FEA) simulation with a maximum deviation of 0.3 K. For the simulation of a 500 min cyclic cooling and heating process, FEA takes a computation time of up to 13 h whereas the reduced model takes only 7-11 s, using time steps of 2 s. These low computation times allow for an identification, which is verified with an error below 3 K. When film coefficient estimation from literature is difficult due to complex geometries or turbulent air flows, identification is a promising approach to still achieve accurate results.

A well parametrized model can be further used for model-based control approaches or in observer structures. To the knowledge of the authors, no other methodology enables model-based identification of thermal parameters by physically preserving them through model order reduction and therefore derive it from a FEA description. This method can be applied to much more complex geometries and has been used in an industrial environment to increase product quality, due to accurate monitoring of cooling processes.

The purpose of this study is to simultaneously determine the constitutive parameters and boundary conditions by solving inverse mechanical problems of power hardening elastoplastic materials in three-dimensional geometries.

The power hardening elastoplastic problem is solved by the complex variable finite element method in software ABAQUS, based on a three-dimensional complex stress element using user-defined element subroutine. The complex-variable-differentiation method is introduced and used to accurately calculate the sensitivity coefficients in the multiple parameters identification method, and the Levenberg–Marquardt algorithm is applied to carry out the inversion.

Numerical results indicate that the complex variable finite element method has good performance for solving elastoplastic problems of three-dimensional geometries. The inversion method is effective and accurate for simultaneously identifying multi-parameters of power hardening elastoplastic problems in three-dimensional geometries, which could be employed for solving inverse elastoplastic problems in engineering applications.

The constitutive parameters and boundary conditions are simultaneously identified for power hardening elastoplastic problems in three-dimensional geometries, which is much challenging in practical applications. The numerical results show that the inversion method has high accuracy, good stability, and fast convergence speed.

Through an inductive approach, I examine the process in which autonomy is exercised in the board-executive director relationship. A further contribution of the current study is the exploration of the antecedents of the delegation process.

Utilizing the benefits of semi-structured critical incident interviews, and analysis of organizational documentation, I study the process in which autonomy is exercised in the board-executive director relationship.

Evidence is found within organizations of times when it is clear that board members understand that there are boundaries to their role, respecting this autonomy, and times when board members overstep their role. Next, in the current study, I explore the antecedents of the delegation process, including identification of role boundaries, role clarity, clear expectations, trust in the executive director, and trust in the governance control systems.

Autonomy has historically been examined within seemingly paradoxical frameworks; this has included investigating autonomy as part of the definition of laissez faire leadership, as a key feature of transformational leadership and as one component of the jobs characteristics model, while others have characterized it as a stream of shared leadership. In the current project, the process of providing autonomy takes on characteristics consistent with both vertical leadership and distributed leadership. The executive director similarly plays a role in maintaining previously defined role boundaries, which is evidence of bidirectional influence. However, the board plays a disproportionately larger role in delineating and maintaining role boundaries – characteristics I demonstrate as being consistent with transformational leadership.

In this chapter, I provide a refreshing divergence from typical board prescriptions, in that I examine the board-executive director relationship through a behavioural lens. A clear understanding of the mutual influence and antecedents of autonomy are important to practitioners seeking to enhance performance through the delineation of roles.

This paper aims to put forth a model that accounts for the effect of servant leadership on employee creativity from a social identity perspective. Specifically, this paper aims to examine team identification as the mediating mechanism by which servant leadership influence employee creativity. This paper also intends to investigate the moderating influences of horizontal and vertical collectivism on the effectiveness of servant leadership on follower team identification.

Servant leadership, team identification, collectivism (consisted of horizontal and vertical collectivism) and employee creativity were assessed in an empirical study based on a sample of 451 employees from 11 banks in China.

Drawing on social identity theory, this study found that follower team identification partially mediates the relationship between servant leadership and employee creativity. In addition, results showed that horizontal collectivism moderates the relationship between servant leadership and follower team identification; the relationship was more positive when horizontal collectivism was high, rather than low; vertical collectivism also moderates the relationship between servant leadership and follower team identification; the relationship was more positive when vertical collectivism was low, rather than high. However, results of this study indicated that the moderated mediation effects of team identification on the relationship between servant leadership and employee creativity are nonsignificant.

First, this research affirmed the need to promote servant leadership in employment settings. Second, managers’ understandings of the instrumental role of servant leadership in showing interpersonal acceptance, offering encouragement and support and expressing trust would prove to be valuable because it could enhance employee creativity. Finally, the findings from this study should help managers gain a better understanding of the contextual factors.

The first contribution of the current study was to identify team identification as an important psychological process that can link servant leadership to employee creativity. Another important contribution of the current research was the identification of the boundary conditions (e.g. horizontal and vertical collectivism).

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.

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.