Computational Fluid Dynamics versus Experiment: An Investigation on Liquid Weeping of Nye Trays

The weeping phenomenon was investigated using some experimental tests and a numerical model. The tests were performed within a 1.22‐m‐diameter pilot‐scale column including two chimney trays and two Nye test trays with an air‐water system. The rates of weeping were measured in the Nye trays with two heights of the weir and a hole area of 5 %. Moreover, the weeping rates in the outlet and inlet halves of the Nye tray and the total weeping rate were calculated. In the next step, an Eulerian‐Eulerian computational fluid dynamics (CFD) technique was used. The results show good agreement between the attained CFD findings and the experimental data.     

A new linearly constrained minimum variance beamformer for reconstructing EEG sparse sources

Brain source imaging based on EEG aims to reconstruct the neural activities producing the scalp potentials. This includes solving the forward and inverse problems. The aim of the inverse problem is to estimate the activity of the brain sources based on the measured data and leadfield matrix computed in the forward step. Spatial filtering, also known as beamforming, is an inverse method that reconstructs the time course of the source at a particular location by weighting and linearly combining the sensor data. In this paper, we considered a temporal assumption related to the time course of the source, namely sparsity, in the Linearly Constrained Minimum Variance (LCMV) beamformer. This assumption sounds reasonable since not all brain sources are active all the time such as epileptic spikes and also some experimental protocols such as electrical stimulations of a peripheral nerve can be sparse in time. Developing the sparse beamformer is done by incorporating L1-norm regularization of the beamformer output in the relevant cost function while obtaining the filter weights. We called this new beamformer SParse LCMV (SP-LCMV). We compared the performance of the SP-LCMV with that of LCMV for both superficial and deep sources with different amplitudes using synthetic EEG signals. Also, we compared them in localization and reconstruction of sources underlying electric median nerve stimulation. Results show that the proposed sparse beamformer can enhance reconstruction of sparse sources especially in the case of sources with high amplitude spikes.     

A Comparative Investigation on Bioactivity and Antibacterial Properties of Sol-Gel Derived 58S Bioactive Glass Substituted by Ag and Zn

Silicon - The bioactive glass systems of xAg2O-SiO2-P2O5-CaO and xZnO-SiO2-P2O5-CaO (x = 2 and 4% mol) were successfully synthesized through sol-gel method. The effect of silver and...     

Experimentelle und analytische Untersuchung des out‐of‐plane‐Verhaltens von unbewehrten Mauerwerkswänden unter Erdbebenbelastung

Experimental and analytical investigation of the seismic out‐of‐plane behavior of unreinforced masonry walls In addition to the vertical and horizontal load‐bearing in‐plane, masonry must also withstand out‐of‐plane loads that occur in earthquake scenarios. The out‐of‐plane behavior of unreinforced masonry walls depends on a variety of parameters and is very complex due to the strong non‐linearity. Current design methods in German codes and various international codes have not been explicitly developed for out‐of‐plane behavior and contain considerable conservatism. In the present work, shaking‐table experiments with heat‐insulating masonry walls have been conducted to investigate the out‐of‐plane behavior of vertical spanning unreinforced masonry walls. As shown in previous numerical investigations, important parameters are neglected in existing design and analysis models and the out‐of‐plane capacity is underestimated significantly. In the conducted experiments the results of these numerical investigations are verified. Furthermore, the development of an analytical design model to determine the force‐displacement relationship and the out‐of‐plane load‐bearing capacity considering all significant parameters is presented.     

In situ measurements of human cough aerosol hygroscopicity

The airborne dynamics of respiratory droplets, and the transmission routes of pathogens embedded within them, are governed primarily by the diameter of the particles. These particles are composed of the fluid which lines the respiratory tract, and is primarily mucins and salts, which will interact with the atmosphere and evaporate to reach an equilibrium diameter. Measuring organic volume fraction (OVF) of cough aerosol has proved challenging due to large variability and low material volume produced after coughing. Here, the diametric hygroscopic growth factors (GF) of the cough aerosol produced by healthy participants were measured in situ using a rotating aerosol suspension chamber and a humidification tandem differential mobility analyser. Using hygroscopicity models, it was estimated that the average OVF in the evaporated cough aerosol was 0.88 ± 0.07 and the average GF at 90% relative humidity (RH) was 1.31 ± 0.03. To reach equilibrium in dry air the droplets will reduce in diameter by a factor of approximately 2.8 with an evaporation factor of 0.36 ± 0.05. Hysteresis was observed in cough aerosol at RH = ∼35% and RH = ∼65% for efflorescence and deliquescence, respectively, and may depend on the OVF. The same behaviour and GF were observed in nebulized bovine bronchoalveolar lavage fluid.     

Uncertain location–allocation decisions for a bi-objective two-stage supply chain network design problem with environmental impacts

In the cases that the historical data of an uncertain event is not available, belief degree-based uncertainty theory is a useful tool to reflect such uncertainty. This study focuses on uncertain bi-objective supply chain network design problem with cost and environmental impacts under uncertainty. As such network may be designed for the first time in a geographical region, this problem is modelled by the concepts of belief degree-based uncertainty theory. This article is almost the first study on belief degree-based uncertain supply chain network design problem with environmental impacts. Two approaches such as expected value model and chance-constrained model are applied to convert the proposed uncertain problem to its crisp form. The obtained crisp forms are solved by some multi-objective optimization approaches of the literature such as TH, Niroomand, MMNV. A deep computational study with several test problems are performed to study the performance of the crisp models and the solution approaches. According to the results, the obtained crisp formulations are highly sensitive to the changes in the value of the cost parameters. On the other hand, Niroomand and MMNV solution approaches perform better than other solution approaches from the solution quality point of view.     

Optimisation of a combined Stirling cycle–organic Rankine cycle using a genetic algorithm

In a Stirling cycle a huge amount of energy is wasted due to the losses. This wasted energy may be utilised as a heat source for the boiler of an organic Rankine cycle (ORC). Combination of these two cycles leads to an increased cycle efficiency compared to a single Stirling cycle and the analysis and optimisation of the integrated system is carried out. Optimisation is performed using the genetic algorithm and considering three decision variables: the temperature of the cold tank of the Stirling cycle, the pressure ratio and the temperature of the ORC condenser. In optimisation, the efficiency is considered as the objective function and the highest value is achieved by adjusting the decision variables. Using this method, the efficiency of the overall combined cycle was improved in which the highest efficiency was obtained to be 41.5%.