Simulation of gas species and temperature separation in the counter-flow Ranque–Hilsch vortex tube using the large eddy simulation technique

A computational fluid dynamic model is used to predict the species and temperature separation within a counter flow Ranque–Hilsch vortex tube. The large eddy simulation (LES) technique was employed for predicting the gas flow and temperature fields and the species mass fractions (nitrogen and helium) in the vortex tube. A vortex tube with a circumferential inlet stream of nitrogen–helium mixture and an axial (cold) outlet stream and a circumferential (hot) outlet stream was considered. The temporal evolutions of the axial, radial and azimuthal components of the velocity along with the temperature, pressure and mass density and species concentration fields within the vortex tube are simulated. Even though a large temperature separation was observed, only a very minimal gas separation occurred due to diffusion effects. Correlations between the fluctuating components of velocity, temperature and species mass fraction were calculated to understand the separation mechanism. The inner core flow was found to have large values of eddy heat flux and Reynold’s stresses. Simulations were carried out for varying amounts of cold outlet mass flow rates. Performance curves (temperature separation/gas separation versus cold outlet mass fraction) were obtained for a specific vortex tube with a given inlet mass flow rate.     

Berries anthocyanins as potential SARS-CoV–2 inhibitors targeting the viral attachment and replication; molecular docking simulation

The viral respiratory disease, severe acute respiratory syndrome (SARS), has turned into a global health concern. Till now, there is no drug or vaccine has yet been specifically approved for SARS-CoV-2. One of the urgent solutions against the recent COVID-19 disease is the use of dietary molecules, which can be found abundantly in functional food. In the current study, we have conducted a molecular docking approach for eighteen dietary molecules belong to the subclass of anthocyanins, as potential inhibitors of the main protease and spike glycoprotein of SARS-CoV-2. Both selected targets, playing a vital role in attachment and replication of the virus. The results indicated that cyanidin-3-arabinoside exhibited the lowest binding energy and located onto the pocket through a sufficient number of hydrogen bonds with the main protease virus. However, pelargonidin-3-glucoside and pelargonidin 3-rhamnoside display significant binding energy with the spike glycoprotein of SARS-CoV-2. All compounds mentioned above shown high drug-likeness and fulfils the Lipinski’s rule of five, as well as confer favorable toxicity parameters, in addition to ADME values. Considering the obtained results, regular consumption of berry fruits, which are rich in anthocyanin compounds, should be supportive to inhibit viral infectious by reducing of propagation and pathogenicity of SARS-CoV–2.     

Particle swarm optimization algorithm for a vehicle routing problem with heterogeneous fleet, mixed backhauls, and time windows

Today, companies need to collect and to deliver goods from and to their depots and their customers. This problem is described as a Vehicle Routing Problem with Mixed Linehaul and Backhaul customers (VRPMB). The goods delivered from the depot to the customers can be alternated with the goods picked up. Other variants of VRP added to VRPMB are Heterogeneous fleet and Time Windows. This paper studies a complex VRP called HVRPMBTW which concerns a logistic/transport society, a problem rarely studied in literature. In this paper, we propose a Particle Swarm Optimization (PSO) with a local search. This approach has shown its effectiveness on several combinatorial problems. The adaptation of this approach to the problem studied is explained and tested on the benchmarks. The results are compared with our previous methods and they show that in several cases PSO improves the results.     

Miscible blends of styrene–cinnamic acid copolymers with poly(ethyl methacrylate)

Differential scanning calorimetry and inverse gas chromatography have been used to investigate the miscibility behaviour of blends of poly(ethyl methacrylate) (PEMA) with styrene–cinnamic acid statistical copolymers PSCA5, PSCA8, PSCA23 having compositions of, respectively, 5, 8 and 23 mol% of cinnamic acid. Several probes with different chemical nature and polarity have been used to determine the polymer–solute and polymer–polymer interaction parameters. DSC and CPGI measurements indicate that poly(ethyl methacrylate) is miscible with each poly[(styrene)‐co‐(cinnamic acid)] copolymer as established from the observation of a single composition‐dependent glass transition temperature. This deduction is corroborated by the IGC data; comparison of the experimental retention volume of the blend with the algebraic average retention volumes of the pure components, together with negative values of the apparent polymer–polymer interaction parameter, establish the miscibility of the studied systems. Furthermore, the polymer–polymer interaction parameters are found to show marked probe dependence; this is discussed in terms of the Δχ effect. As indicated by the variation of the glass transition temperature with blend composition, the application of the Kwei and the Schneider approaches to the calorimetric results suggests the occurrence of strong specific interactions within the blends; the strength of these intermolecular interactions increases with the cinnamic acid content in the PSCA copolymer. © 2001 Society of Chemical Industry     

Characterization of composite materials based on LDPE loaded with agricultural tunisian waste

This study investigated the use of an available agricultural Tunisian vine stem waste as a filler material. Composites of green materials were prepared using vine stems as filler and low density polyethylene (LDPE) as a matrix. A series of composite films was prepared by different loadings of the vine stem waste with 10–50% of the filler in 10% intervals. The ensuing materials were characterized by several techniques. The morphology of the composites was investigated using scanning electron microscopy (SEM). The thermal and mechanical properties were studied using differential scanning calorimetry (DSC) and dynamic mechanical analysis (DMA), respectively. The results indicated that vine‐stem based particles enhanced the thermo‐mechanical properties of the thermoplastic matrix and demonstrated that this available lignocellulosic biomass of vine stems can be considered to be a promising filler material. However, the obtained result of water absorption indicated that the maximum limit of the filler content should not exceed 30% of vine stems. POLYM. COMPOS., 36:817–824, 2015. © 2014 Society of Plastics Engineers     

Open shop scheduling problem with a multi-skills resource constraint: a genetic algorithm and an ant colony optimisation approach

The continuous evolution of manufacturing environments leads to a more efficient production process that controls an increasing number of parameters. Production resources usually represent an important constraint in a manufacturing activity, specially talking about the management of human resources and their skills. In order to study the impact of this subject, this paper considers an open shop scheduling problem based on a mechanical production workshop to minimise the total flow time including a multi-skill resource constraint. Then, we count with a number of workers that have a versatility to carry out different tasks, and according to their assignment a schedule is generated. In that way, we have formulated the problem as a linear as and a non-linear mathematical model which applies the classic scheduling constraints, adding some different resources constraints related to personnel staff competences and their availability to execute one task. In addition, we introduce a genetic algorithm and an ant colony optimisation (ACO) method to solve large size problems. Finally, the best method (ACO) has been used to solve a real industrial case that is presented at the end.     

Reliability optimization of a redundant system with failure dependencies

In a multi-component system, the failure of one component can reduce the system reliability in two aspects: loss of the reliability contribution of this failed component, and the reconfiguration of the system, e.g., the redistribution of the system loading. The system reconfiguration can be triggered by the component failures as well as by adding redundancies. Hence, dependency is essential for the design of a multi-component system.In this paper, we study the design of a redundant system with the consideration of a specific kind of failure dependency, i.e., the redundant dependency. The dependence function is introduced to quantify the redundant dependency. With the dependence function, the redundant dependencies are further classified as independence, weak, linear, and strong dependencies. In addition, this classification is useful in that it facilitates the optimization resolution of the system design. Finally, an example is presented to illustrate the concept of redundant dependency and its application in system design. This paper thus conveys the significance of failure dependencies in the reliability optimization of systems.     

Stepanov-Like Pseudo Almost Periodic Solution of Quaternion-Valued for Fuzzy Recurrent Neural Networks with Mixed Delays

Neural Processing Letters - Real-valued neural networks or complex-valued neural networks are sometimes inappropriate for some engineering and research problems for instance where the data is...     

Work-conserving dynamic time-division multiplexing for multi-criticality systems

Real-Time Systems - Multi-core architectures pose many challenges in real-time systems, which arise from contention between concurrent accesses to shared memory. Among the available memory...     

A comparison of a fluoroscopy-free mechanical targeting system and a free-hand technic for the placement of distal interlocking screws of tibial nails

Recently, radiation-independent aiming devices for the tibia which compensate for insertion-related implant deformation have been developed, but the benefits of such systems have not been determined. This study prospectively evaluated the duration of the nailing procedure, the length of radiation time, and the accuracy of interlocking screw placement with a radiation-independent distal aiming system and the free-hand technique. In an oblique cadaveric tibial fracture, a surgeon inexperienced with either technique performed a statically locked intramedullary nailing. For the aiming system and free-hand technique respectively, the total operation time was 25.4 +/- 11.3 vs 30.9 +/- 14.3 min (P = 0.029), the distal locking time was 16.7 +/- 8.6 vs 21.9 +/- 10.5 min (P = 0.004), the total fluoroscopy time was 9 +/- 5 vs 93 +/- 34 s (P < 0.0001), the distal locking fluoroscopy time was 0 versus 88 +/- 33 s (P < 0.0001), and the screw destruction was -0.7 +/- 5.2 vs 26.8 +/- 31.6 microns (P = 0.001). The failure rate was 1.6% (1 of 60 screws) in both groups. These results suggest that aiming devices can eliminate the need for radiation during distal interlocking screw placement.