High-throughput concentration of rare malignant tumor cells from large-volume effusions by multistage inertial microfluidics

On-chip concentration of rare malignant tumor cells (MTCs) in malignant pleural effusions (MPEs) with a large volume is challenging. Previous microfluidic concentrators suffer from a low concentration factor (CF) and...

Aluminum in Bottom Sediments of the Lower Silesian Rivers Supplying Dam Reservoirs vs. Selected Chemical Parameters

The study was carried out on sediments collected from three rivers: Nysa Szalona, Strzegomka and Bystrzyca flowing in southwestern Poland. The content of Al in sediments and in bottom water was determined in relation to chemical conditions. The study was carried out in a four-year cycle, during spring and autumn. The aim of the study was to determine the level and accumulation of aluminum in sediments of rivers supplying dam reservoirs storing water for consumption. The sediments studied were mineral in nature, with neutral pH and moderate sulfate content. The level of Al and heavy metals in the sediments was the highest in the Nysa Szalona River and the lowest in the Strzegomka River, which was also evident in the concentration factor (CF). In terms of season, higher Al contents were recorded in sediments in autumn than in spring, which was also reflected in the concentration factor (CF). Along the course of the river, a gradual decrease in Al levels was observed in successive tributaries in the Nysa Szalona and Strzegomka Rivers, while there was no apparent regularity for the Bystrzyca. Against this background, a comparison of extreme sites below the springs and at the reservoir outlet shows that values were higher in the Nysa Szalona below the springs, and lower in the Strzegomka and Bystrzyca below the reservoir outlet. The general picture of Al and heavy metal loading of the studied sediments shows the lowest loading for the Strzegomka, only the enrichment factor (EF) was the lowest for the Nysa Szalona: metal pollution index (MPI)—S < B < NS, contamination factor (Cf)—S < B < NS, degree of contamination (DC)—S < NS < B, EF—NS < B < S, geoaccumulation index (Igeo)—S < B < NS, CF—S < NS < B. There was no effect of catchment size and river length on Al levels in sediments.

Surface Roughness Characterization for Stress Concentration Factor Predictions: A Bayesian Learning Approach

The surface roughness has an important influence on the fatigue life of the structures. The fatigue life reduces due to the stress concentration caused by surface roughness. The stress concentration governs the fatigue crack initiation and propagation. The accurate acquisition of the stress concentration factor of rough surfaces is a key issue in determining fatigue life. Nevertheless, semi-empirical models may be biased for various machining processes. Besides, finite element method simulations cannot give explicit expression of the stress concentration factor. Bayesian learning can construct accurate prediction models which offering a number of additional advantages. In this paper, based on several data pairs constructed by finite element method, the correlation expression between the stress concentration factor and statistical roughness parameters of surfaces is established quickly through Bayesian learning. Compared with some other semi-empirical models, the accuracy and stability of the proposed method are certified. This paper provides a simple and effi-cient approach to determine the stress concentration factor for rough surfaces under different processing conditions.

A Series Solution for 2D Scattering of Cylindrical SH-Waves by Surrounding Loose Rock Zone of Underground Tunnel Lining

This paper presents a closed-form series solution of cylindrical SH-wave scattering by the surrounding loose rock zone of underground tunnel lining in a uniform half-space based on the wave function expansion method and the mirror image method. The correctness of the series solution is verified through residual convergence and comparison with the published results. The influence of the frequency of the incident cylindrical SH-wave, the distance between the wave source and the lining, the lining buried depth, and the properties of the surrounding loose rock zone on the dynamic stress concentration of the tunnel lining is investigated. The results show that the incident wave with high frequency always makes the dynamic stress concentration of the tunnel lining obvious. With the increase of the distance between the wave source and the tunnel lining, the stress around the tunnel lining decreases, but the dynamic stress concentration factor around the tunnel lining does not decrease significantly but occasionally increases. The ground surface has a great influence on the stress concentration of the tunnel lining. The amplitude of the stress concentration factor of tunnel lining is highly related to the shear wave velocity of the surrounding loose rock zone. When the property of the surrounding rock (shear wave velocity) changes more, the amplitude of the stress concentration factor is larger, that is, the stress concentration is more significant.

Ellipsoidal Optical Cavities for Enhanced Thermophotovoltaics

Herein we present an optical cavity in the form of a prolate ellipsoid that can greatly enhance the performance of solar thermophotovoltaic (STPV) systems. The geometrical parameters of the cavity can be designed to control the degree of photon recycling, the temperature of the emitter within the STPV system, gap distance and effective view factor between the PV cell and the emitter, and to minimize the emission losses. Numerical analysis shows the ellipsoidal optical cavity can be designed to achieve an effective view factor of 88.7% between the emitter and PV cell within a STPV system. Results show an efficiency of 5.62% in a STPV system with a GaSb PV cell and a black-body emitter under solar radiation at a concentration factor of 350X. Further, assuming the surface of the ellipsoidal optical cavity is capable of reflecting 99% of the radiation incident onto its surface, efficiencies of 15.54% can be attained when the solar concentration factor is 1400X. These results are attained for STPV systems without using selective absorbers, emitters or filters. The ellipsoidal optical cavity can be integrated into the design of advanced TPV systems and bring them closer to the high theoretical efficiencies TPV systems are capable of.

Ellipsoidal Optical Cavities for Enhanced Thermophotovoltaics

Herein we present an optical cavity in the form of a prolate ellipsoid that can greatly enhance the performance of solar thermophotovoltaic (STPV) systems. The geometrical parameters of the cavity can be designed to control the degree of photon recycling, the temperature of the emitter within the STPV system, gap distance and effective view factor between the PV cell and the emitter, and to minimize the emission losses. Numerical analysis shows the ellipsoidal optical cavity can be designed to achieve an effective view factor of 88.7% between the emitter and PV cell within a STPV system. Results show an efficiency of 5.62% in a STPV system with a GaSb PV cell and a black-body emitter under solar radiation at a concentration factor of 350X. Further, assuming the surface of the ellipsoidal optical cavity is capable of reflecting 99% of the radiation incident onto its surface, efficiencies of 15.54% can be attained when the solar concentration factor is 1400X. These results are attained for STPV systems without using selective absorbers, emitters or filters. The ellipsoidal optical cavity can be integrated into the design of advanced TPV systems and bring them closer to the high theoretical efficiencies TPV systems are capable of.

Fatigue Evaluation of Offshore Steel Structures Considering Stress Concentration Factor

The installation of offshore structures and facilities in the marine environment, usually for the production and transmission of oil, gas exploration, electricity, and other natural resources is referred to as offshore construction. Since offshore structures are subjected to changing threats to the environment year-round. Fatigue behavior prediction noticed on these structures should be considered during the design stage. Fatigue is one of the failure mechanisms of offshore steel structures, and it must be investigated properly during system design. The fatigue analysis of offshore structures under drag wave force, total wave force, total moment about the sea bed, and other variables are reviewed thoroughly. The structure's dynamic response becomes a critical aspect in the whole design process. The fatigue analysis was carried out using MATLAB software, material properties of the offshore structure, and wave spectrum characteristics in this study. This study shows the JONSWAP spectrum and stress concentration analysis prediction. The offshore support structure that is predicted during the design phase will help to keep the stress concentration factor below the fatigue threshold and anticipate safe life design, according to the results of the fatigue study. The fatigue performances of tripod and jacket steel support structures in intermediate waters depth are compared in this project (20-50 m). The North Atlantic Ocean is used as a reference site, with a sea depth of 45 meters. The tripod and jacket support structures will be designed by using current industry standards. Keywords: [Fatigue evaluation, North Atlantic Ocean and Failure].