Structural optimisation of diffusion-driven degradation processes

In the field of structural engineering, structures are developed and calculated. The stresses and deformations resulting from mechanical loads are determined, and the structures are dimensioned to ensure load-bearing capacity, usability and durability in accordance with standards. The application of structural optimisation algorithms enables the development of more efficient and economical building structures, whereby maximum permissible stresses can be exhausted. However, standardised calculations take environmental influences, such as chemical impact, only via so-called exposure classes and resulting material properties into account. Detailed calculations on the influence of stresses and deformations of the structures, especially due to the long-term chemical influence and resulting material degradation, are often neglected. For example, specific stress constraints may be exceeded. Within the scope of the present work, a numerical programme is developed, enabling an efficient optimisation of mechanical structures that are additionally burdened by degradation processes due to diffusive concentrations. For this purpose, a mechanicalchemical- degradation coupled model is developed. Within the framework of classical structural mechanics, the developed material behaviour is presented, taking into account modified physical principles of continuum mechanics to describe a mechanical-chemicaldegradation coupled processes. With the help of the fundamentals of the Finite Element Method (FEM), the solution of the non-linear problem is outlined in detail. Furthermore, the developed structural analysis is embedded in a mathematical algorithm of gradient-based structural optimisation. The optimisation allows a deeper analysis and reduction of the harmful effects due to the influence of acting chemical concentrations. A variational approach to structural optimisation provides the simultaneous integration of analytically prepared sensitivity analysis with the structural analysis for embedding the continuum mechanical formulations. Thus, efficient structural optimisation of the introduced mechanical-chemical-degradation model is comprehensively presented. The mathematical model with the required derivations as well as discretisation is documented and implemented in a computer-based model

Structural optimisation of diffusion driven degradation processes

In this article, we propose an optimisation framework that can contribute to the prevention of premature failure or damage to building structures and can thereby strengthen their longevity. We concentrate on structures that are contaminated by chemical substances and that have strong destructive effects on the material. The aim of this contribution is a mathematical algorithm that allows the optimisation of a structure exposed to chemical influences and thus the assurance of the static load capacity. To achieve this, we present a coupled mechanical-diffusion-degradation approach embedded in a finite element (FE) framework. Furthermore, we integrate an optimisation algorithm to reduce material degradation. In this paper, we establish shape optimisation of a structure with a gradient based optimisation algorithm

Computational Modeling in Liver Surgery

The need for extended liver resection is increasing due to the growing incidence of liver tumors in aging societies. Individualized surgical planning is the key for identifying the optimal resection strategy and to minimize the risk of postoperative liver failure and tumor recurrence. Current computational tools provide virtual planning of liver resection by taking into account the spatial relationship between the tumor and the hepatic vascular trees, as well as the size of the future liver remnant. However, size and function of the liver are not necessarily equivalent. Hence, determining the future liver volume might misestimate the future liver function, especially in cases of hepatic comorbidities such as hepatic steatosis. A systems medicine approach could be applied, including biological, medical, and surgical aspects, by integrating all available anatomical and functional information of the individual patient. Such an approach holds promise for better prediction of postoperative liver function and hence improved risk assessment. This review provides an overview of mathematical models related to the liver and its function and explores their potential relevance for computational liver surgery. We first summarize key facts of hepatic anatomy, physiology, and pathology relevant for hepatic surgery, followed by a description of the computational tools currently used in liver surgical planning. Then we present selected state-of-the-art computational liver models potentially useful to support liver surgery. Finally, we discuss the main challenges that will need to be addressed when developing advanced computational planning tools in the context of liver surgery.Peer Reviewe

Structural optimisation of diffusion driven degradation processes

In this article, we propose an optimisation framework that can contribute to the prevention of premature failure or damage to building structures and can thereby strengthen their longevity. We concentrate on structures that are contaminated by chemical substances and that have strong destructive effects on the material. The aim of this contribution is a mathematical algorithm that allows the optimisation of a structure exposed to chemical influences and thus the assurance of the static load capacity. To achieve this, we present a coupled mechanical-diffusion-degradation approach embedded in a finite element (FE) framework. Furthermore, we integrate an optimisation algorithm to reduce material degradation. In this paper, we establish shape optimisation of a structure with a gradient based optimisation algorithm

Computational Modeling in Liver Surgery

The need for extended liver resection is increasing due to the growing incidence of liver tumors in aging societies. Individualized surgical planning is the key for identifying the optimal resection strategy and to minimize the risk of postoperative liver failure and tumor recurrence. Current computational tools provide virtual planning of liver resection by taking into account the spatial relationship between the tumor and the hepatic vascular trees, as well as the size of the future liver remnant. However, size and function of the liver are not necessarily equivalent. Hence, determining the future liver volume might misestimate the future liver function, especially in cases of hepatic comorbidities such as hepatic steatosis. A systems medicine approach could be applied, including biological, medical, and surgical aspects, by integrating all available anatomical and functional information of the individual patient. Such an approach holds promise for better prediction of postoperative liver function and hence improved risk assessment. This review provides an overview of mathematical models related to the liver and its function and explores their potential relevance for computational liver surgery. We first summarize key facts of hepatic anatomy, physiology, and pathology relevant for hepatic surgery, followed by a description of the computational tools currently used in liver surgical planning. Then we present selected state-of-the-art computational liver models potentially useful to support liver surgery. Finally, we discuss the main challenges that will need to be addressed when developing advanced computational planning tools in the context of liver surgery