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The aim of this work was to assess the numerous approaches to structural and material modeling of brain tissue under dynamic loading conditions. The current technological improvements in material modeling have led to various approaches described in the literature. However, the methods used for the determination of the brain’s characteristics have not always been stated or clearly defined and material data are even more scattered. Thus, the research described in this paper explicitly underlines directions for the development of numerical brain models. An important element of this research is the development of a numerical model of the brain based on medical imaging methods. This approach allowed the authors to assess the changes in the mechanical and geometrical parameters of brain tissue caused by the impact of mechanical loads. The developed model was verified through comparison with experimental studies on post-mortem human subjects described in the literature, as well as through numerical tests. Based on the current research, the authors identified important aspects of the modeling of brain tissue that influence the assessment of the actual biomechanical response of the brain for dynamic analyses.

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This article describes an innovative method for eliminating deformation in large crankshafts during measurement of their geometric condition. The currently available techniques for measuring crankshaft geometry are introduced and classified according to their applicability and the method of measurement. The drawbacks of the methods have been identified and a solution to these problems has been proposed. The influence of the rigid support of a shaft on its deformation, and thus on the reduction in the accuracy of crankshaft geometry measurements, has also been investigated. The concept and main versions of the proposed measuring system with active compensation for shaft deflection, by means of actuators cooperating with force transducers monitoring the deflection of individual crank journals of a crankshaft being measured, have been presented and the flexible support control system has also been described. The problems relating to the operation of the control system have been furnished along with a way to solve them, including the issue of noise reduction in the signal from the force transducer and the influence of the controller parameters on the operation of the flexible support. The computer system that controls the flexible supports has been briefly characterized, and the performance of the prototype system and the model reference system has been compared. The results have shown that the system is able to effectively eliminate the deflection and elastic deformation of the crankshaft under the influence of its own weight.

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