The use of freelisting to elicit stakeholder understanding of the benefits sought from healthcare buildings

The process of elicitation and synthesis of the collective understanding of a cultural domain held by a group of stakeholders is challenging. This problem typifies the pre-project activity from which a coherent understanding of the benefits sought from infrastructure investment must emerge to inform the business case rationale. The anthropological freelisting method is evaluated as a solution by determining its ability to be operationalized in a practical form for project application. Using data from the stakeholders of a large NHS Scotland building project, the use of multidimensional scaling for data analysis is compared with participatory pilesorting to determine which freelisting protocol balances insight with practicality. Neither approach is found to offer an ideal method of characterizing sought benefits. The social construction of pilesorting promotes reliability while the analytical rigour of multidimensional scaling remains attractive to auditors. Their distinct insights suggest that both approaches should be combined in future and used alongside further post-elicitation devices from anthropology such as cultural consensus modelling or structured conceptualization.     

Real-time performance models for photovoltaic water pumping systems

This purpose of this paper is to develop and validate a model to accurately predict the cell temperature of a photovoltaic (PV) module that adapts to various mounting configurations, mounting locations, and climates while only requiring readily available data from the module manufacturer. Results from this model are also compared with results from published cell temperature models. The models were used to predict real-time performance from a PV water pumping systems in the desert of Medenine, south of Tunisia using 60-min intervals of measured performance data during one complete year. Statistical analysis of the predicted results and measured data highlights possible sources of errors and the limitations and/or adequacy of existing models, to describe the temperature and efficiency of PV-cells and consequently, the accuracy of performance of PV water pumping systems’ prediction models.     

Formulation and characterization of hybrid polymeric/ZnO nanocomposite coatings with remarkable anti-corrosion and hydrophobic characteristics

In this study, ZnO nanoparticles ranging from 1 to 8% (w/w) were introduced into a hybrid acrylic-silicone polymeric matrix to achieve nanocomposite coating systems with remarkable anti-corrosion and hydrophobic characteristics. The chemical structure of the developed hybrid polymeric matrix was investigated using Fourier transform infrared spectroscopy, whereas the morphology and wettability of the developed surfaces were determined using field emission scanning electron microscopy and contact angle measurements (CA), respectively. Furthermore, the anti-corrosion performance and the barrier properties over 60 days of exposure to a 3.5% NaCl solution were studied by electrochemical impedance spectroscopy. All the obtained results revealed that the presence of ZnO nanoparticles significantly influences the performance of the acrylic-silicone polymeric matrix. A coating system with 3% wt ZnO nanoparticles demonstrated the most pronounced anti-corrosion properties and also achieved the highest CA, with a value of 95.6°.     

CFD and artificial neural network modeling of two-phase flow pressure drop

A large number of experiments in a 2 cm diameter and 6 m length tube were carried out in order to study the two-phase flow regimes and pressure drops in it. The two-phase flow in the experimental tube was modeled using commercial CFD code, Fluent 6.2. An Artificial Neural Network (ANN) with three inputs including gas and liquid velocities and tube slope was designed and trained to predict average pressure drop across the tube. The comparison between CFD and ANN predictions of pressure drops with experimental measurements shows that the CFD results are more accurate than the ANN evaluations for new conditions.     

Photocatalytic degradation of methyl orange dye by NiFe<Subscript>2</Subscript>O<Subscript>4</Subscript> nanoparticles under visible irradiation: effect of varying the synthesis temperature

Nanoparticles of nickel ferrites (NiFe₂O₄) were synthesized at different temperature of synthesis (25, 50 and 80 °C) through the chemical co-precipitation method. The synthesized powders were characterized using X-ray diffraction for crystallite size and lattice parameter calculation. It reveals the presence of cubic spinel structure of ferrites with crystallite size between 29 and 41 nm. Transmission electron microscopy and scanning electron microscopy showed uniform distribution of ferrite particles with some agglomeration. The Fourier-transform infrared spectroscopy showed absorption bonds, which were assigned to the vibration of tetrahedral and octahedral complexes. Raman spectroscopy is used to verify that we have synthesized ferrite spinels and determines their phonon modes. The thermal decomposition of the NiFe₂O₄ was investigated by TGA/DTA. The optical study UV–visible is used to calculate the band gap energy. Magnetic measurements of the samples were carried out by means of vibrating sample magnetometer and these studies reveal that the formed nickel ferrite exhibits ferromagnetic behavior. Photoluminescence showed three bands of luminescence located at 420, 440 and 535 nm. The photocatalytic properties of nickel ferrite (NiFe₂O₄) nanoparticles were evaluated by studying the photodecomposition of methyl orange as organic pollutant models and showed a good photocatalytic activity.     

Influence of Aging Parameters on the Tensile Properties and Quality Index of Al-9?Pct Si-1.8?Pct Cu-0.5?Pct Mg 354-Type Casting Alloys

The current study was carried out with a view to investigating the influence of age-hardening parameters, aging temperature and time, on the tensile properties and quality indices of a high-strength Al-9 pct Si casting alloy, namely, 354-Al-9 pct Si-1.8 pct Cu-0.5 pct Mg. Quality charts were used as an evaluation tool for selecting the optimum conditions to be applied, in practice, in order to develop high strength and optimum quality in 354 casting alloy. Aging at a low temperature of 428 K (155 °C) was observed to produce the greatest strength and optimum quality in the 354-type castings compared to aging at higher temperatures. The peak strength observed for 354 alloy may be attained after shorter aging times on the condition that the aging temperature is increased. The aging times required for reaching peak strength in 354 alloys are 72 hours, 40 hours, 8 hours, 1 hour, and 15 minutes at aging temperatures of 428 K, 443 K, 468 K, 493 K, and 518 K (155 °C, 170 °C, 195 °C, 220 °C, and 245 °C), respectively. Aging treatment at higher temperatures is accompanied by a reduction in the tensile properties and quality index values of the castings; however, it also introduces the possibility of a significant economical strategy for minimizing the time and the cost of this same treatment. Aging treatment at a lower temperature of 428 K (155 °C) produces fine and dense precipitates displaying smaller interparticle spacing, while at higher aging temperatures, such as 518 K (245 °C), the precipitates are coarser in size, less dense, and more widely dispersed. The quality charts developed in the course of the current research facilitate the interpretation and evaluation of the tensile properties of the 354 alloy. Such charts provide a logical evaluation tool, from the metallurgical point of view, for an accurate prediction of the influence of aging parameters studied on the properties of the alloys. Depending on the required level of tensile properties and based on the quality charts developed, it is possible to make a rigorous selection as to the most suitable aging parameters to be applied to the 354 alloy so as to obtain the best possible cost-effective compromise between alloy strength and quality.     

Uniform Stabilization of an Axially Moving Kirchhoff String by a Boundary Control of Memory Type

In this paper, we study the stabilization of solutions of an axially moving string of kirchhoff type by a viscoelastic boundary control. We prove that the dissipation produced by the viscoelastic term is sufficient to suppress the transversal vibrations that occur during the axial motion of the string, and we also show that the string displacement decays in an arbitrary rate. When comparing with immobile strings, we conclude that the movement of the string itself produces enough extra damping ensuring the stabilization.     

Electric load forecasting by using dynamic neural network

Electrical energy is fundamental for the wellbeing and for the economic development of any country. However, all countries must ensure access to essential resources and ensure the continuity of its supply. Due to the non-storable nature of electrical energy, the amount of consumed active power should always be equal the produced active power just to avoid power system frequency deviation problem. In order to keep the relationship production–consumption relation in compliance with different standards and to secure profitable operations of power system, electric load consumption must be predicted and controlled instantaneously. Several statistical and classical techniques are proposed in the literature but unfortunately all these methods are not accurate in a satisfactory manner. In this paper, a dynamic neural network is used for the prediction of daily power consumption. The suitability and the performance of the proposed approach is illustrated and verified with simulations on load data collected from French Transmission System Operator (RTE) website. The obtained results show that the accuracy and the efficiency are improved comparatively to conventional methods widely used in this field of research.     

CFD Modeling of Micromixing and Velocity Distribution in a 1.7‐MHz Tubular Sonoreactor

The effect of high‐frequency (1.7 MHz) ultrasound waves on the mixing rate in a new continuous tubular sonoreactor was investigated by CFD modeling. Modeling of piezoelectric transducer (PZT) vibrations was done based on the dynamic mesh model. Results indicate that the acoustic streams were in the direction of wave propagation and their maximum velocity near the PZT surface agreed well with experimental measurements. The micromixing efficiency of the sonoreactor was studied by adopting the Villermaux/Dushman reaction in the modeling. Comparison of the calculated relative segregation index from modeling results with experimental data revealed reasonable accordance.