Excitation Function Calculations of Neutron-Induced Reactions of Some Zirconium Target Isotopes

Nuclear structures with high performance materials will be critical for the success of future fusion energy. Zirconium alloys are extensively used for nuclear reactor core materials as fuel cladding and guide tubes due to excellent radiation and corrosion resistant properties. In this paper, the excitation functions of ⁹⁰Zr(n,2n)⁸⁹Zr, ⁹⁰Zr(n,α)⁸⁷Sr, ⁹¹Zr(n,p)⁹¹Y and ⁹²Zr(n,p)⁹²Y nuclear reactions were calculated for energies up to 25 MeV. Besides, ALICE/ASH and TALYS 1.6 codes were used for the cross section calculations. The obtained calculations were compared with the experimental data in the literature.     

RAFALE: Rethinking the provisioning of virtuAl network services using a Fast and scAlable machine LEarning approach

Network Function Virtualization (NFV) has been identified to revamp the provisioning of next-generation network services. This new paradigm allows cloud and network/service providers to compose their network services, also known as service function chains (SFCs), in an agile way since the software of the network function is decoupled from the legacy hardware. To reap the benefits of this new technology, there is a need for novel mechanisms that help cloud and network/service providers deploy the increasingly complex virtual network services seamlessly, efficiently, and in a time-efficient way. Existing state-of-the-art techniques often rely on the Integer Linear Programming framework, heuristics/metaheuristics, and greedy methods to deploy the services function chains. However, these techniques although reasonable and acceptable, still suffer from several key limitations: convergence time and scalability. To this end, we propose RAFALE, a suite of solution techniques, to tame this complexity by leveraging the concept of similarity from machine learning and skip-gram modeling framework. To the best of our knowledge, we are the first to tackle these key limitations and propose a suite of solutions to them. RAFALE, a novel approach proposed to find the similarity between the new incoming virtual network service request and all the already-deployed services to learn from the previous experience of deploying techniques and use the same or close similar provisioning techniques. RAFALE is the first and the only method that develops the idea of detecting the similarity between virtual network services. Experimental results show that RAFALE reduces greatly the convergence time needed for provisioning virtual network services and can scale to 100 virtual network functions per virtual network service compared to the state-of-the-art. The Experimental results prove that RAFALE accomplished the NFV promises; decreasing the time and complexity of managing and deploying the virtual services, and providing a solution that is agile, faster, and scalable to deploy the new service requests by skipping one or more service provisioning steps (i.e., detecting and resolving the conflicts among policies, placement, and chaining) while satisfying the validated NFV policies.

     

Use of Eddy Current Conductivity and Hardness Testing to Evaluate Heat Damage in Aluminum Alloys

Aluminum alloys are heat treated to provide optimal material properties for use in a variety of applications. However, when exposed to abnormally high temperatures, an evaluation must be performed to determine if the aluminum component has been compromised. Nondestructive evaluation of aluminum alloys, by means of electrical conductivity and hardness tests, can assist in determining the condition of the part. These techniques require experience and engineering judgment to properly interpret the data produced in order to determine whether a part needs to be replaced. This article will elaborate on issues with these nondestructive techniques to help diagnose the condition of aluminum alloys exposed to high temperatures.     

Silicene Nanoribbons on an Insulating Thin Film

Silicene, a new 2D material has attracted intense research because of the ubiquitous use of silicon in modern technology. However, producing free-standing silicene has proved to be a huge challenge. Until now, silicene could be synthesized only on metal surfaces where it naturally forms strong interactions with the metal substrate that modify its electronic properties. Here, the authors report the first experimental evidence of silicene nanoribbons on an insulating NaCl thin film. This work represents a major breakthrough, for the study of the intrinsic properties of silicene, and by extension to other 2D materials that have so far only been grown on metal surfaces.     

Implementation of Hydraulic Modelling for Water-Loss Reduction Through Pressure Management

This study was conducted in the Konyaalti Water Distribution Network in Antalya, Turkey. The study area was divided into 18 district metered areas (DMAs) for better management of water losses. Water levels in reservoirs, flow rates, and water pressures were monitored on-line by the SCADA data system. A hydraulic model was calibrated and verified for each DMA using data provided by SCADA. The model results revealed that a number of DMAs exhibited high pressures, greater than 3.5 bars, and high minimum night flow (MNF) throughout the year. Also, the Infrastructure Leakage Index (ILI) for the study area was greater than 20, indicating high water losses. As a result of these findings, a pressure reducing valve (PRV) was installed at DMA No. 2 as an example and set at 3.0 bars resulting in considerable reduction in water losses. The optimum pressure level for setting the PRV was chosen using the hydraulic model. The same model was used to predict water savings due to pressure reduction. The predicted water savings were verified using long periods of flow rates and water pressure profiles. The predicted and measured water savings showed good agreement. The study concluded that hydraulic modelling is essential for applying appropriate pressure management strategies.     

Tribological Behavior of TiAlN,AlTiN, and AlCrN Coatings at Boundary Lubricating Condition

In this study, ~?3.5 µm thick multilayer titanium alumina nitride (TiAlN), alumina titanium nitride (AlTiN), and alumina chromium nitride (AlCrN) coatings were deposited on the H13 steel surface by cathodic arc physical vapor deposition (CAPVD) method. The tribological performance of the coatings was evaluated by a tribometer at boundary lubrication condition. Then, coating surfaces were observed by optical microscope, optical profilometer, and atomic force microscope to evaluate the morphological changes, wear volumes, and tribofilm thickness. Also, scanning electron microscopy (energy dispersive X-ray) and X-ray photoelectron spectrometry analyses were applied to coating surfaces for the tribochemical evolution of the tribofilm. Results showed that AlCrN coating performed the best tribological behavior at boundary lubricated condition, when compared to TiAlN and AlTiN coatings and it can be used as a wear resistant cam tappet coating in internal combustion engines.     

Effect of Deep Cryogenic Treatment on Wear Resistance of AISI 52100 Bearing Steel

In this study, the effects of deep cryogenic treatment (DCT) on the wear resistance of AISI 52100 bearing steel were investigated. For this purpose, a number of bearing steel samples were held for different times (12, 24, 36, 48, 60 h) at deep cryogenic temperatures (?145 °C). The wear experiments were carried out in a ball–disk arrangement, by applying loads of 10 and 20 N and a sliding velocity of 0.15 m/s. After conducting the experimental studies, 36 h was found to be the optimal holding time. At this holding time, the wear rate and friction coefficient were decreased, while the hardness reached to maximum values. It was observed that DCT led to significant microstructural changes, which resulted in improved tribological properties.