Thermal and hydraulic performance of a modified two-stage evaporative cooler

The thermal and hydraulic performance of a modified two-stage evaporative cooler is evaluated. Variables considered are the mode of operation, packing thickness, mass flow rate of the water flowing to the precooler, and the mass flux of water flowing over the packing media. The effectiveness of the system increased with the increase of the mass flow rate of water flowing to the precooler, decreasing the mass flux of water flowing to the packing, and with the increase of the packing thickness. The effectiveness of the system with structured packing was higher than that with sheathy leaf base or natural fiber packing.The air-side pressure drop per unit length in the direction of air flow was nearly constant when the structured packing was used. For the sheathy leaf and natural fiber packings, the air pressure drop increased at a uniform rate as the mass flux of water flowing over the packing increased. The air pressure drop was lowest for the setup with the structured packing.     

Measuring the errors of form of industrial surfaces: prediction and optimization

To acquire maximum information on the geometrical errors of industrially made surfaces at a minimum cost, a method for estimating conditional probabilities of a random signal (Bayesian prediction) is applied to three-dimensional metrology. First, a surface is interpolated between data acquired on a coordinate measuring machine (CMM). Then, for a given probability, limit surfaces are computed that bind a region of space containing the known data and the most probable interpolation of the missing data of the surface. These bounds can be treated as the surface; their points can be considered as if they were actual CMM data when fitting a tolerance zone or a datum feature to the data. For Bayesian prediction, the basic hypotheses on the signal are stationarity, ergodicity, and gaussian density. Deviations from these hypotheses and their consequences on the prediction are taken into account and corrections are proposed.     

Urban water demand,climatic variation,and irrigation-water insecurity: interactive stressors and lessons for water governance from the Angat River basin (Philippines)

Climatic variation and intersectoral water competition increasingly challenge the effective provision of irrigation services. This article explores their combined effects on irrigation allocation from the Angat Reservoir (Philippines), where domestic water use in Metro Manila has overtaken regional irrigation as the dominant right-holder. Rules protecting Metro Manila’s large right to water ‘interact’ with dry spells to affect irrigation security in wet and dry seasons. Historically, irrigators were uncompensated because re-allocation’s cause was contested as (1) an unforeseeable climatic event (releasing domestic utilities of liability), or (2) produced by urban demand (requiring compensation). Trade-off rules must be prepared to navigate combinatory effects.     

Synthesis and characterization of saturated and unsaturated copolyesters based on bis-1,4-(dicarboxymethoxy) benzene

Saturated copolyester were prepared by copolyesterification of bis-1,4-(dicarboxymethoxy) benzene and phthalic anhydride with diethylene glycol, triethylene glycol, tetraethylene glycol, 1,4-butane diol, 1,2-propane diol, and 1,6-hexamethylene glycol. Also, unsaturated copolyesters were prepared by copolyesterification of bis-1,4-(dicarboxymethoxy) benzene and maleic anhydride with the same glycols. All the copolyester resins obtained have been characterized and unsaturated copolyesters in the form of films were determined. IR and ¹H-NMR spectroscopy were used for both qualitative and quantitative analysis of the copolyesters resins and their hydrolyzate products, after curing with styrene. © 1992 John Wiley & Sons, Inc.     

The diffraction of Kelvin wave due to a narrow headland normal to an infinite coastline

Summary This paper describes an analytic method to determine the diffraction of an oceanographic Kelvin wave system by a narrow headland with the headland being perpendicular to an infinitely long coastline.A standard shallow water approximation theory is assumed for the oceanographic equations. It is also assumed that the Kelvin wave system propagates uniformly in one direction at infinity.The method used involves the application of source/vortex distributions over the headland together with integral equation techniques. An analytic solution has been found in integral form for the singularity distribution.Numerical solution for the unknown singularity distribution is obtained. Plots of co-amplitude (R), co-tidal (, co-(R cos ) and co-(R sin ) contours for the diffracted wave system are presented.     

Synergistic toughening and electrical functionalization of an epoxy using MWCNTs and silane- /plasma-activated basalt fibers

This work studied the effects of adding short basalt fibers (BFs) and multi-walled carbon nanotubes (MWCNTs), both separately and in combination, on the mechanical properties, fracture toughness, and electrical conductivity of an epoxy polymer. The surfaces of the short BFs were either treated using a silane coupling agent or further functionalized by atmospheric plasma to enhance the adhesion between the BFs and the epoxy. The results of a single fiber fragmentation test demonstrated a significantly improved BF/epoxy adhesion upon applying the plasma treatment to the BFs. This resulted in better mechanical properties and fracture toughness of the composites containing the plasma-activated BFs. The improved BF/epoxy adhesion also affected the hybrid toughening performance of the BFs and MWCNTs. In particular, synergistic toughening effects were observed when the plasma-activated BFs/MWCNTs hybrid modifiers were used, while only additive toughening effects occurred for the silane-sized BFs/MWCNTs hybrid modifiers. This work demonstrated a potential to develop strong, tough, and electrically conductive epoxy composites by adding hybrid BF/MWCNT modifiers.     

Effect of pH and zeta potential of Pickering stabilizing magnetite nanoparticles on the features of magnetized polystyrene microspheres

Styrene as a monomer was emulsified in water using several magnetite nanoparticles concentration and pH values. Emulsified styrene drops were used as templates for polymerization, in presence of water soluble free radical initiator, and formation of composite particles. Styrene template drops stabilization was verified by light as well as scanning electron microscopy imaging, which ensured the participation of the particles in building up a mechanical barrier to stop oil drops coalescence. Furthermore, the produced polystyrene composites were strongly attracted to an external magnet. The difference in particles size as a function of pH was elucidated using zeta potential measurements, which indicated dominance of pH on the hydrophilicity of the particles and consequently the extent of emulsification, which in turn affected the size of the obtained microspheres. Under some circumstances, capsules were formed instead of particles. Thereby, it can be concluded that the magnetic microspheres are optimally formed at pH 2.3 independently of the magnetite content used.     

Intrusion Detection Based on Bidirectional Long Short-Term Memory with Attention Mechanism

With the recent developments in the Internet of Things (IoT), the amount of data collected has expanded tremendously, resulting in a higher demand for data storage, computational capacity, and real-time processing capabilities. Cloud computing has traditionally played an important role in establishing IoT. However, fog computing has recently emerged as a new field complementing cloud computing due to its enhanced mobility, location awareness, heterogeneity, scalability, low latency, and geographic distribution. However, IoT networks are vulnerable to unwanted assaults because of their open and shared nature. As a result, various fog computing-based security models that protect IoT networks have been developed. A distributed architecture based on an intrusion detection system (IDS) ensures that a dynamic, scalable IoT environment with the ability to disperse centralized tasks to local fog nodes and which successfully detects advanced malicious threats is available. In this study, we examined the time-related aspects of network traffic data. We presented an intrusion detection model based on a two-layered bidirectional long short-term memory (Bi-LSTM) with an attention mechanism for traffic data classification verified on the UNSW-NB15 benchmark dataset. We showed that the suggested model outperformed numerous leading-edge Network IDS that used machine learning models in terms of accuracy, precision, recall and F1 score.