Evaluation of machinability and economic performance in cryogenic-assisted hard turning of α-β titanium: a step towards sustainable manufacturing

Abstract

Titanium, a difficult-to-cut material, consumes higher time and cost in removing material by machining to produce parts. Machining of Ti alloys has got serious attention owing to its reactive nature with tool materials at elevated temperature that aggravates tool wear. Reportedly, effective and efficient cooling and lubrication at the tool–work interface can ameliorate the machinability of Ti-alloys. In this perspective, this article interrogates the underlying mechanism of critical responses such as surface roughness, temperature, tool life and machining cost under dry, minimum quantity lubrication (MQL) and cryogenic liquid nitrogen (LN2) modes. The effect of cutting speeds and feed rates on such responses have been considered as a function of cooling strategy to standardize the cooling technique as the best alternative for machining. Cryogenic cooling seems to be preponderant regarding machining cost, temperature, surface roughness and tool life in hard turning of a–b titanium alloy. The feasibility of cryogenic cooling was investigated using the iso-response technique in comparison with dry and MQL-assisted hard turning. Experimental results revealed longer tool life and lower machining cost under cryogenic condition followed by MQL and dry machining. Moreover, cryogenic LN2 has been identified as an appropriate alternative to reduce the temperature and surface roughness. On contrary, dry turning evoked a high-temperature and rapid tool wear. In a nutshell, cryogenic assisted hard turning has acceded as a sustainable strategy from an environmental and economic perspective.     

pH Responsive Abelmoschus esculentus Mucilage and Administration of Methotrexate: In-Vitro Antitumor and In-Vivo Toxicity Evaluation

The rapid progression in biomaterial nanotechnology apprehends the potential of non-toxic and potent polysaccharide delivery modules to overcome oral chemotherapeutic challenges. The present study is aimed to design, fabricate and characterize polysaccharide nanoparticles for methotrexate (MTX) delivery. The nanoparticles (NPs) were prepared by Abelmoschus esculentus mucilage (AEM) and chitosan (CS) by the modified coacervation method, followed by ultra-sonification. The NPs showed much better pharmaceutical properties with a spherical shape and smooth surface of 213.4–254.2 nm with PDI ranging between 0.279–0.485 size with entrapment efficiency varying from 42.08 ± 1.2 to 72.23 ± 2.0. The results revealed NPs to possess positive zeta potential and a low polydispersity index (PDI). The in-vitro drug release showed a sustained release of the drug up to 32 h with pH-dependence. Blank AEM -CS NPs showed no in-vivo toxicity for a time duration of 14 days, accompanied by high cytotoxic effects of optimized MTX loaded NPs against MCF-7 and MD-MBA231 cells by MTT assay. In conclusion, the findings advocated the therapeutic potential of AEM/CS NPs as an efficacious tool, offering a new perspective for pH-responsive routing of anticancer drugs with tumor cells as a target.     

Use of basalt in asphalt concrete mixes

One of the main reasons behind the appearance of early distresses in Jordan roads and the low surface skid resistance is the use of marginal quality limestone aggregate. Large quantities of good quality basalt are available in the Northeastern parts of Jordan. In this research, the possibility of improving the properties of local asphalt concrete mixes by replacing different portions of the normally used limestone aggregate by basalt was investigated. The replacement included total replacement of the limestone by basalt, replacing the coarse aggregate, and replacing the fine aggregate. Results showed that the optimal mix was the mix that had basalt coarse aggregate and limestone fine aggregate. In order to overcome the stripping potential of the optimal mix, 20% of the filler portion of the aggregate, material smaller than 0.075 mm, was replaced by lime. The optimal mix showed superiority, over the tested mixes, in all the evaluated properties, which were Marshall Stability, indirect tensile strength, stripping resistance, resilient modulus, dynamic creep, fatigue, and rutting.     

Impact of load profile and collector technology on the fractional savings of solar domestic water heaters under various climatic conditions

This paper investigates the influence of the domestic hot water load profiles and the collector's technology (Flat Plate FPC, Evacuated Tube ETC and Compound Parabolic CPC) on the performance of forced circulation solar water heaters operating under various climatic conditions. For this end, a typical single family house composed of five occupants located in Morocco was considered. It is found that, the solar fraction can reach annual average values of 80% especially in areas with high solar energy potential. For a fixed consumption profile, the simulations showed that the installations with FPC, ETC and CPC can consume about 1644, 1199 and 1481 kWh/year of auxiliary energy, respectively. Moreover, it is found that, adapting the consumption profile, can save approximately 43 kWh/year for FPC, 13 kWh/year for ETC and about 29 kWh/year for CPC of energy.     

Bottom-Up Association Rule Mining in Relational Databases

Although knowledge discovery from large relational databases has gained popularity and its significance is well recognized, the prohibitive nature of the cost associated with extracting such knowledge, as well as the lack of suitable declarative query language support act as limiting factors. Surprisingly, little or no relational technology has yet been significantly exploited in data mining even though data often reside in relational tables. Consequently, no relational optimization has yet been possible for data mining. We exploit the transitive nature of large item sets and the so called anti-monotonicity property of support thresholds of large item sets to develop a natural least fixpoint operator for set oriented data mining from relational databases. The operator proposed has several advantages including optimization opportunities, and traditional candidate set free large item set generation. We present an SQL3 expression for association rule mining and discuss its mapping to the least fixpoint operator developed in this paper.     

Power Law Velocity Profile in Fully Developed Turbulent Pipe and Channel Flows

The power law velocity profile has been analyzed in terms of the envelope of the friction factor which gives the friction factor log law. The power law index α and prefactor C are shown as the function of the friction Reynolds number, as well as the function of the alternate variable the nondimensional friction velocity. The fully developed turbulent superpipe flow data of McKeon et al. and fully developed channel flow data of Zanoun et al. have been analyzed and the power law index α and prefactor C data have been estimated, first as a function of the friction Reynolds number and second as function of the nondimensional friction velocity. Based on analysis, several correlations have been proposed that have been supported by the data.     

Fusion of remotely sensed data for soil moisture estimation using relevance vector and support vector machines

A data assimilation (DA) methodology that uses two state-of-the-art techniques, relevance vector machines (RVMs) and support vector machines (SVMs), is applied to retrieve surface (0–6 cm) soil moisture content (SMC) and SMC at a depth of 30 cm. RVMs and SVMs are known for their robustness, efficiency and sparseness and provide a statistically sound approach to solve inverse problems and thus to build statistical models. Here, we build a statistical model that produces acceptable estimations of SMC by using inexpensive and readily available data. The study area for this research is the Walnut Creek watershed in Ames, south-central Iowa, USA. The data were obtained from Soil Moisture Experiments 2002 (SMEX02) conducted at Ames, Iowa. The DA methodology combines remotely sensed inputs with field measurements, crop physiological characteristics, soil temperature, soil water-holding capacity and meteorological data to build a two-step model to estimate SMC using both techniques, i.e. RVMs and SVMs. First, the RVM is used to build a model that retrieves surface (0–6 cm) SMC. This information serves as a boundary condition for the second step of this model, which estimates SMC at a depth of 30 cm. An exactly similar routine is followed with an SVM for estimation of surface (0–6 cm) SMC and SMC at a depth of 30 cm. The results from the RVM and SVM models are compared and statistics show that RVMs perform better (root mean square error (RMSE)?= 0.014 m³ m^?3) when compared with SVMs (RMSE?= 0.017 m³ m^?3) with a reduced computational complexity and more suitable real-time implementation. Cross-validation techniques are used to optimize the model. Bootstrapping is used to check over/under-fitting and uncertainty in model estimates. Computations show good agreement with the actual SMC measurements with coefficients of determination (R ²) for RVM equal to 0.92 and for SVM equal to 0.88. Statistics indicate a good model generalization capability with indexes of agreement (IoAs) for RVM equal to 0.97 and for SVM equal to 0.96.     

Cache memories

A computer has three logical systems. The central processing unit (CPU) that processes data according to instructions. The memory and storage system that stores instructions and data (it can be a volatile temporary memory or a permanent storage system like hard disks). Lastly, the input/output system that is responsible for communication between the computer and external entities. The memory and storage system is the primary concern of this article, specifically cache memory. It stores frequently accessed instructions and data for the CPU. Cache is from the French word “cachet” which means “to hide.” This is a reference to early cache implementations where the cache was invisible to the user and CPU. Cache memory is important; it bridges the gap in capabilities between the CPU and main memory. CPUs have been rapidly getting faster. Cache memory has advanced considerably since Wilkes in 1965 proposed a two-level main store: one conventional and the other unconventional “slave” memory. It has now become a conventional component of high speed computing, with increasing sophistication and size. The performance of cache is critical to overall system processing ability and the ongoing research in this area is attempting to reduce as much as possible the speed gap between the CPU and the memory     

The relationship between electricity consumption,electricity prices and GDP in Pakistan

This study analyzes the relationship among electricity consumption, its price and real GDP at the aggregate and sectoral level in Pakistan. Using annual data for the period 1960–2008, the study finds the presence of unidirectional causality from real economic activity to electricity consumption. In particular, growth in output in commercial, manufacturing and agricultural sectors tend to increase electricity consumption, while in residential sector, growth in private expenditures is the cause of rising electricity consumption. The study concludes that electricity production and management needs to be better integrated with overall economic planning exercises. This is essential to avoid electricity shortfalls and unplanned load shedding.     

Solar radiation models—A review

Solar radiation models for predicting the average daily and hourly global radiation, beam radiation and diffuse radiation on horizontal surface are reviewed in this article. Estimations of monthly average hourly global radiation from daily summations are discussed. It was observed that Collares‐Pereira and Rabl model as modified by Gueymard (CPRG) yielded the best performance for estimating mean hourly global radiation incident on a horizontal surface for Indian regions. Estimations of monthly average hourly beam and diffuse radiation are discussed. It was observed that Singh‐Tiwari and Jamil‐Tiwari both models generally give better results for climatic conditions of Indian regions. Therefore, their use is recommended for composite climate of Indian regions. Empirical correlations developed to establish a relationship between the hourly diffuse fraction and the hourly clearness index using hourly global and diffuse irradiation measurements on a horizontal surface are discussed. Fifty models using the Angstrom–Prescott equation to predict the average daily global radiation with hours of sunshine are considered. It was reported that Ertekin and Yaldiz model showed the best performance against measured data of Konya, Turkey. Copyright © 2010 John Wiley & Sons, Ltd.