Ahmet DEMIRTAS

Abstract Powder compaction is a complex manufacturing process, even though the procedural description is simple. While different methods are used in the literature, it is still challenging to understand the governing principles. It is especially challenging for empirical studies to investigate particle-level interactions. Thus, computational analyses are required for particle-level understanding. A wide range of computational methods has been developed, such as the discrete element method (DEM) and the multi-particle finite element method (MPFEM), to characterize powder compaction at the particle level. However, a limited number of studies in the literature have analyzed powder compaction using the 3D multi-particle finite element method. Historically, these studies focus only on solid particles. The compaction behavior of hollow spheres, common to pharmaceutical spray drying, was investigated both computationally and experimentally. In the computational analysis, two different particle sizes with different shell-thicknesses were examined using the 3D multi-particle finite element method. In the experimental study, polymer hydroxypropyl methylcellulose acetate succinate (HPMCAS) particles spray-dried at two different outlet temperatures (45 °C and 80 °C) were used. The results showed that particle diameter/shell-thickness (d/w) plays an essential role in powder compaction behavior. Regardless of the particle size, reducing shell-thickness reduced the required global axial stress to reach equivalent levels of relative density. However, with a constant ratio of d/w, changes to particle size (d) did not significantly influence the global compaction behavior. Similar results were observed in experimental studies. Simulation results showed that thinner-shell particles yield early in the compaction stage. Additionally, both experimentally and computationally, a spherical hollow particle buckling effect was observed. In summary, this study provides new information on how powder compaction behavior was influenced by particle size and particle shell-thickness.

The recent studies have shown that long-term bisphosphonate use may result in a number of mechanical alterations in the bone tissue including a reduction in compositional heterogeneity and an increase in microcrack density. There are limited number of experimental and computational studies in the literature that evaluated how these modifications affect crack initiation and propagation in cortical bone. Therefore, in this study, the entire crack growth process including initiation and propagation was simulated at the microscale by using the cohesive extended finite element method. Models with homogeneous and heterogeneous material properties (represented at the microscale capturing the variability in material property values and their distribution) as well as different microcrack density and microstructure were compared. The results showed that initiation fracture resistance was higher in models with homogeneous material properties compared to heterogeneous ones, whereas an opposite ...

Recent studies demonstrated an association between atypical femoral fracture (AFF) and long-term bisphosphonate (BP) use for osteoporosis treatment. Due to BP treatment, bone undergoes alterations including increased microcrack density and reduced tissue compositional heterogeneity. However, the effect of these changes on the fracture response of bone is not well understood. As a result, the goal of the current study is to evaluate the individual and combined effects of microcracks and tissue compositional heterogeneity on fracture resistance of cortical bone using finite element modeling (FEM) of compact tension (CT) specimen tests with varying microcrack density, location, and clustering, and material heterogeneity in three different bone samples. The simulation results showed that an increase in microcrack density improved the fracture resistance irrespective of the local material property heterogeneity and microcrack distribution. A reduction in material property heterogeneity a...

Each protein has different duties based on its shape and motion. The protein molecules get their shapes based on the amino acids sequence and interaction with each other (protein folding). Computing the protein folding is extremely expensive even for a small protein structure. In this work rigid and flexible regions of protein molecules has been studied which can result in reducing computational cost of protein molecules mobility analysis. Abstract Motivation The most important aspect for this project is helping the future of human beings by creating new drugs, designing protein based nano-robots, and improving the protein structural analysis.

Intrinsic flexibility of protein molecules enables them to change their 3D structure and perform their specific task. Therefore, identifying rigid regions and consequently flexible regions of proteins has a significant role in studying protein molecules' function. In this study, we developed a kinematic model of protein molecules considering all covalent and hydrogen bonds in protein structure. Then, we used this model and developed two independent rigidity analysis methods to calculate degrees of freedom (DOF) and identify flexible and rigid regions of the proteins. The first method searches for closed loops inside the protein structure and uses Grübler–Kutzbach (GK) criterion. The second method is based on a modified 3D pebble game. Both methods are implemented in a matlab program and the step by step algorithms for both are discussed. We applied both methods on simple 3D structures to verify the methods. Also, we applied them on several protein molecules. The results show that both methods are calculating the same DOF and rigid and flexible regions. The main difference between two methods is the run time. It's shown that the first method (GK approach) is slower than the second method. The second method takes 0.29 s per amino acid versus 0.83 s for the first method to perform this rigidity analysis.