On pointwise decay rates of time‐periodic solutions to the Navier–Stokes equation

We study the existence of a time‐periodic solution with pointwise decay properties to the Navier–Stokes equation in the whole space. We show that if the time‐periodic external force is sufficiently small in an appropriate sense, then there exists a time‐periodic solution $\{u,p\}$ of the Navier–Stokes equation such that $|{?}^j{u(t,x)|=O(|x|}^{1?n?j})$ and $|{?}^j{p(t,x)|=O(|x|}^{?n?j})(j=0,1,\dots )$ uniformly in $t\in \mathbb{R}$ as $|x|\to \infty$. Our solution decays faster than the time‐periodic Stokes fundamental solution and the faster decay of its spatial derivatives of higher order is also described.     

An efficient edge based data structure for the compressible Reynolds-averaged Navier–Stokes equations on hybrid unstructured meshes

An efficient edge based data structure has been developed in order to implement an unstructured vertex based finite volume algorithm for the Reynolds-averaged Navier–Stokes equations on hybrid meshes. In the present approach, the data structure is tailored to meet the requirements of the vertex based algorithm by considering data access patterns and cache efficiency. The required data are packed and allocated in a way that they are close to each other in the physical memory. Therefore, the proposed data structure increases cache performance and improves computation time. As a result, the explicit flow solver indicates a significant speed up compared to other open-source solvers in terms of CPU time. A fully implicit version has also been implemented based on the PETSc library in order to improve the robustness of the algorithm. The resulting algebraic equations due to the compressible Navier–Stokes and the one equation Spalart–Allmaras turbulence equations are solved in a monolithic manner using the restricted additive Schwarz preconditioner combined with the FGMRES Krylov subspace algorithm. In order to further improve the computational accuracy, the multiscale metric based anisotropic mesh refinement library PyAMG is used for mesh adaptation. The numerical algorithm is validated for the classical benchmark problems such as the transonic turbulent flow around a supercritical RAE2822 airfoil and DLR-F6 wing-body-nacelle-pylon configuration. The efficiency of the data structure is demonstrated by achieving up to an order of magnitude speed up in CPU times.     

Prediction of the drag reduction effect of pulsating pipe flow based on machine learning

Prediction of drag reduction effect caused by pulsating pipe flows is examined using machine learning. First, a large set of flow field data is obtained experimentally by measuring turbulent pipe flows with various pulsation patterns. Consequently, more than 7000 waveforms are applied, obtaining a maximum drag reduction rate and maximum energy saving rate of 38.6% and 31.4%, respectively. The results indicate that the pulsating flow effect can be characterized by the pulsation period and pressure gradient during acceleration and deceleration. Subsequently, two machine learning models are tested to predict the drag reduction rate. The results confirm that the machine learning model developed for predicting the time variation of the flow velocity and differential pressure with respect to the pump voltage can accurately predict the nonlinearity of pressure gradients. Therefore, using this model, the drag reduction effect can be estimated with high accuracy.     

Sensitive CE-MS method for monitoring of riociguat and desmethylriociguat levels in human serum

Riociguat is novel antihypertensive drug for treatment of pulmonary hypertension. As such, it is still being tested in many clinical and pharmacokinetic trials. Existing methods that determine serum riociguat and desmethylriociguat (DMR) are based solely on liquid chromatography with mass spectrometry. Therefore, we present a novel capillary electrophoresis with mass spectrometry method (CE-MS) for their determination in human serum as alternative method for ongoing trials. Complete resolution of both analytes was achieved by means of pH optimization of ammonium formate background electrolytes that are fully compatible with ESI/MS detection. Simple liquid-liquid extraction was used as sample pretreatment. The calibration dependence of the method was linear (in the range of 10–1000 ng/mL), with adequate accuracy (90.1–114.9%) and precision (13.4%). LOD and LOQ were arbitrarily set at 10 ng/mL for both analytes. Clinical applicability was validated using serum samples from patients treated with riociguat in pharmacokinetic study and the results corresponded with reference HPLC-MS/MS values. Capillary electrophoresis proved to be sensitive and selective tool for the analysis of riociguat and DMR.     

Determination of sulfa antibiotic residues in river and particulate matter by field-amplified sample injection-capillary zone electrophoresis

In the present research, field-amplified sample injection–CZE (FASI–CZE) coupled with a diode array detector was established to determine trace level sulfa antibiotic. Sulfathiazole, sulfadiazine, sulfamethazine, sulfadimethoxine, sulfamethoxazole, and sulfisoxazole were selected as analytes for the experiments. The background electrolyte solution consisted of 70.0 mmol/L borax and 60.0 mmol/L boric acid (including 10% methanol, pH 9.1). The plug was 2.5 mmol/L borax, which was injected into the capillary at a pressure of 0.5 psi for 5 s. Then the sample was injected into the capillary at an injection voltage of –10 kV for 20 s. The electrophoretic separation was carried out under a voltage of +19 kV. The capillary temperature was maintained at 20˚C throughout the analysis, and six sulfonamides were completely separated within 35 min. Compared with pressure injection-CZE, the sensitivity of FASI-CZE was increased by 6.25–10.0 times, and the LODs were reduced from 0.2–0.5 to 0.02–0.05 μg/mL. The method was applied to the determination of sulfonamides in river water and particulate matter samples. The recoveries were 78.59–106.59%. The intraday and interday precisions were 2.89–7.35% and 2.77–7.09%, respectively. This provides a simpler and faster method for the analysis of sulfa antibiotic residues in environmental samples.     

Limitations of the Clausius‐Mossotti function used in dielectrophoresis and electrical impedance studies of biomacromolecules

Dielectrophoresis (DEP) studies have progressed from the microscopic scale of cells and bacteria, through the mesoscale of virions to the molecular scale of DNA and proteins. The Clausius‐Mossotti function, based on macroscopic electrostatics, is invariably employed in the analyses of all these studies. The limitations of this practice are explored, with the conclusion that it should be abandoned for the DEP study of proteins and modified for native DNA. For macromolecular samples in general, a DEP theory that incorporates molecular‐scale interactions and the influence of permanent dipoles is more appropriate. Experimental ways to test these conclusions are proposed.