No abstract

Successfully simulating tissue evolution in bone is of significant importance in predicting various biological processes such as bone remodeling, fracture healing and osseointegration of implants. Each of these processes involves in different ways the permanent or transient formation of different tissue types, namely bone, cartilage and fibrous tissues. The tissue evolution in specific circumstances such as bone remodeling and fracturing healing is currently able to be modeled. Nevertheless, it remains challenging to predict which tissue types and organization can develop without any a priori assumptions. In particular, the role of mechanobiological coupling in this selective tissue evolution has not been clearly elucidated. In this work, a multi-tissue model has been created which simultaneously describes the evolution of bone, cartilage and fibrous tissues. The coupling of the biological and mechanical factors involved in tissue formation has been modeled by defining two different tissue states: an immature state corresponding to the early stages of tissue growth and representing cell clusters in a weakly neo-formed Extra Cellular Matrix (ECM), and a mature state corresponding to wellformed connective tissues. This has allowed for the cellular processes of migration, proliferation and apoptosis to be described simultaneously with the changing ECM properties through strain driven diffusion, growth, maturation and resorption terms. A series of finite element simulations were carried out on idealized cantilever bending geometries. Starting from a tissue composition replicating a mid-diaphysis section of a long bone, a steady-state tissue formation was reached over a statically loaded period of 10,000 h (60 weeks). The results demonstrated that bone formation occurred in regions which are optimally physiologically strained. In two additional 1000 h bending simulations both cartilaginous and fibrous tissues were shown to form under specific geometrical and loading cases and cartilage was shown to lead to the formation of bone in a beam replicating a fracture healing initial tissue distribution. This finding is encouraging in that it is corroborated by similar experimental observations of cartilage leading bone formation during the fracture healing process. The results of this work demonstrate that a multi-tissue mechano-biological model of tissue evolution has the potential for predictive analysis in the design and implementations of implants, describing fracture healing and bone remodeling processes. Keywords Mechano-biological coupling • Tissue differentiation • Finite element • Bone remodeling • Bone healing • Osseointegration Communicated by Francesco dell'Isola.

This paper presents prediction of residual stress evolution for end-to-end process chain of laser powder bed fusion (L-PBF) for an aero-casing component made of IN718. The end-to-end process chain includes the simulation of the L-PBF build process, removal of support structures, heat treatment cycle for stress relief, and application of surface-hardening processes such as shot peening and laser shock peening. The simulation of the end-to-end process chain was performed using validated process models for IN718. Validation of the L-PBF process model was carried out for the aero-casing component, where predicted and measured distortions were found to be in good agreement. The predicted residual stresses after each process of the chain were used to develop theoretical fatigue S-N curves using the endurance limit approach. This approach requires knowledge for the surface roughness, as well as the ultimate strength and relative density of the material (defect level). Understanding the evolution of stresses in manufacturing process chains as well as prediction of material properties for functional performance is essential to reduce iterations during the process and product development of L-PBF parts. The advantage of this approach is that S-N curves can be determined very rapidly at every location of the aero-casing or any other component without conducting any fatigue tests physically, which saves considerable cost and time. The S-N curves after the L-PBF build process, heat treatment, and surface hardening were determined and discussed. It was concluded that the proposed S-N curve predictive methodology can be employed in design workflows for estimation of high cycle fatigue in L-PBF process chains very early in the design stage. This would enable designers to mitigate fatigue problems by designing parts more proactively for L-PBF process constraints such as surface roughness, ultimate strength, residual stresses, and relative density or defect level in the given material.

Bone is a tissue with the remarkable capacity to adapt its structure to an optimized microstructural form depending on variations in the loading conditions. The remodeling process in bone produces distinct tissue distributions such as cortical and trabecular bone but also fibrous and cartilage tissues. Although it has been demonstrated that mechanical factors play a decisive role in the architectural optimization, it may also follow that biological factors have an influence. This interplay between loading and physiology has not been previously reported but is paramount for a proper assessment of bone remodeling outcomes. In this work we present a mechanostat model for bone remodeling which is shown to predict the mechanically driven homeostasis. It is further demonstrated that the steady-state reached is innately dependent upon the loading magnitudes and directions. The model was then adjusted to demonstrate the influence of specific biological factors such as cell proliferation, migration and resorption. Furthermore, two scenarios were created to replicate the physiological conditions of two bone disorders -osteoporosis and osteopetrosis -where the results show that there is a significant distinction between the homeostatic structures reached in each case and that the tissue adaptations follow similar trends to those observed in clinical studies.