Rapid manufacturing techniques in the development of an axial blood pump impeller
Abstract This paper presents a comparison of manufacturing techniques used in the development of an axial blood pump impeller. In this development process the impeller was designed and its performance was evaluated with the aid of computational fluid dynamics (CFD). Prototypes of those designs where the CFD results show promise were needed in sufficient quantities at a low cost for experimental validation of the CFD results. As the impeller is less than 16 mm in diameter with a maximum blade thickness of about 1.5 mm, innovative manufacturing techniques are explored in this paper to determine the best process for quick fabrication of prototypes that are dimensionally accurate, structurally robust and low in cost. Four rapid prototyping techniques were explored. The completed parts were compared on the basis of manufacturing time, quality and strength of parts obtained, manufacturing cost and also in vitro performances. Based on these studies, it was concluded that selective laser sintering (SLS) is the most appropriate method for the quick production of prototype parts for evaluation of pump performance.
Computational fluid dynamics as a development tool for rotary blood pumps.
Computational fluid dynamics (CFD) is beginning to significantly impact the development of biomedical devices, in particular rotary cardiac assist devices. The University of Pittsburgh's McGowan Center for Artificial Organ Development has extensively used CFD as the primary tool to analyze and design a novel axial flow blood pump having a magnetically suspended rotor. The blood-contacting surfaces of the pump were developed using a design strategy based on CFD that involved closely coupling a Navier-Stokes solver to a parameterized geometry modeler and advanced mesh movement techniques. CFD-based blood damage models for shear-induced hemolysis as well as surrogate functions describing thrombosis potential were employed to help guide design improvements. This CFD-based design approach resulted in the timely development of a pump subjected to multiple geometric refinements without building expensive physical prototypes for each design iteration. A physical prototype of the final improved pump was fabricated and experimentally analyzed using particle imaging flow visualization. The CFD predicted results correlated well with the experimental data including pressure-flow (H-Q) performance and specific flow field features. It is estimated that the present CFD-based design approach shortened the overall design time frame from an order of years to months.
Benchmark database for fine-grained image classification of benthic macroinvertebrates
Abstract Managing the water quality of freshwaters is a crucial task worldwide. One of the most used methods to biomonitor water quality is to sample benthic macroinvertebrate communities, in particular to examine the presence and proportion of certain species. This paper presents a benchmark database for automatic visual classification methods to evaluate their ability for distinguishing visually similar categories of aquatic macroinvertebrate taxa. We make publicly available a new database, containing 64 types of freshwater macroinvertebrates, ranging in number of images per category from 7 to 577. The database is divided into three datasets, varying in number of categories (64, 29, and 9 categories). Furthermore, in order to accomplish a baseline evaluation performance, we present the classification results of Convolutional Neural Networks (CNNs) that are widely used for deep learning tasks in large databases. Besides CNNs, we experimented with several other well-known classification methods using deep features extracted from the data.