Rapid and accurate profiling of infection-causing pathogens remains a significant challenge in modern health care. Despite advances in molecular diagnostic techniques, blood culture analysis remains the gold standard for diagnosing sepsis. However, this method is too slow and cumbersome to significantly influence the initial management of patients. The swift initiation of precise and targeted antibiotic therapies depends on the ability of a sepsis diagnostic test to capture clinically relevant organisms along with antimicrobial resistance within 1 to 3 h. The administration of appropriate, narrow-spectrum antibiotics demands that such a test be extremely sensitive with a high negative predictive value. In addition, it should utilize small sample volumes and detect polymicrobial infections and contaminants. All of this must be accomplished with a platform that is easily integrated into the clinical workflow. In this review, we outline the limitations of routine blood culture testing and discuss how emerging sepsis technologies are converging on the characteristics of the ideal sepsis diagnostic test. We include seven molecular technologies that have been validated on clinical blood specimens or mock samples using human blood. In addition, we discuss advances in machine learning technologies that use electronic medical record data to provide contextual evaluation support for clinical decision-making.

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Particle Image Velocimetry (PIV) and pressure fluctuation measurements are used for investigating the onset and development of rotating stall within a centrifugal pump having a vaned diffuser. The experiments are performed in a facility that enables measurements between the diffuser vanes, within part of the impeller, in the gap between them and in the volute. The diffuser is also instrumented with pressure transducers that track the circumferential motion of rotating stall in the stator. The timing of low-pass-filtered pressure signals are also used for triggering the acquisition of PIV images. The data include detailed velocity distributions, instantaneous and phase-averaged, at different blade orientations and stall phases, as well as auto-and cross-spectra of pressure fluctuations measured simultaneously in neighboring vane passages. The cross-spectra show that the stall propagation rate is 0.93 Hz, 6.2 percent of the impeller speed, and that the stall travels from the passages located on the exit side of the volute toward the beginning side, crossing the tongue region in the same direction as the impeller, where it diminishes. Under stall conditions the flow in the diffuser passage alternates between outward jetting, when the low-pass-filtered pressure is high, to a reverse flow, when the filtered pressure is low. Being below design conditions, there is a consistent high-speed leakage flow in the gap between the impeller and the diffuser from the exit side to the beginning of the volute. Separation of this leakage flow from the diffuser vane causes the onset of the stall. The magnitude of the leakage and the velocity distribution in the gap depend on the orientation of the impeller blade. Conversely, the flow in a stalled diffuser passage and the occurrence of stall do not vary significantly with blade orientation. With decreasing flow-rate the magnitudes of leakage and reverse flow within a stalled diffuser passage increase, and the stall-cell size extends from one to two diffuser passages.

The present paper addresses two basic modeling problems of the flow in turbomachines. For simulation of flows within multistage turbomachinery, unsteady Reynolds-averaged Navier–Stokes (RANS) of an entire series of blade rows is typically impractical. On the other hand, when performing RANS of each blade row separately one is faced with major difficulties in matching boundary conditions. A popular remedy is the “passage-averaged” approach. Unsteady effects caused by neighboring rows are averaged out over all blade orientations, but are accounted for through “deterministic” stresses, which must be modeled. To experimentally study modeling issues for deterministic stresses we use particle image velocimetry data of the flow in a centrifugal pump with a vaned diffuser that includes the flow in the impeller, the gap between the impeller and diffuser, between the diffuser vanes and within the volute downstream. The data have been presented in part A of this paper (Sinha and Katz, 1998, “Flow Structure and Turbulence of a Centrifugal Pump with a Vaned Diffuser,” Proceedings of the ASME Fluids Engineering Division, Washington, DC). Deterministic stresses are obtained from the difference between the phase-averaged and passage-averaged data, whereas the Reynolds stresses are determined from the difference between the instantaneous and phase averaged data. In agreement with previous findings, the deterministic stresses are larger than the Reynolds stresses in regions close to the interface between blade rows, and thus must be carefully accounted for in passage-averaged simulations. The Reynolds stresses are larger in regions located far from the transition region. The second series of issues involves modeling for large-eddy simulation. The measured subgrid stresses determined by spatially filtering the data are compared to eddy viscosity models and show significant discrepancies, especially in regions with separating shear layers. Backscatter of energy that persists during phase averaging is also observed. [S0098-2202(00)00901-9]

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