Regression models for estimating product life cycle cost

Product life cycle cost (LCC) is defined as the cost that is incurred in all stages of the life cycle of a product, including product creation, use and disposal. In recent years, LCC has become as crucial as product quality and functionality in deciding the success of a product in the market. In order to estimate LCC of new products, researchers have employed several (parametric) regression analysis models and artificial neural networks (ANN) on historical life cycle data with known costs. In this article, we conduct an empirical study on performance of five popular non-parametric regression models for estimating LCC under different simulated environments. These environments are set by varying the number of cost drivers (independent variables), the size of sample data, the noise degree of sample data, and the bias degree of sample data. Statistical analysis of the results recommend best LCC estimation models for variable environments in stages of the product life cycle. These findings are validated with real-world data from previous work.     

Algorithms and performance of load-balancing with multiple hash functions in massive content distribution

We consider a two-tier content distribution system for distributing massive content, consisting of an infrastructure content distribution network (CDN) and a large number of ordinary clients. The nodes of the infrastructure network form a structured, distributed-hash-table-based (DHT) peer-to-peer (P2P) network. Each file is first placed in the CDN, and possibly, is replicated among the infrastructure nodes depending on its popularity. In such a system, it is particularly pressing to have proper load-balancing mechanisms to relieve server or network overload. The subject of the paper is on popularity-based file replication techniques within the CDN using multiple hash functions. Our strategy is to set aside a large number of hash functions. When the demand for a file exceeds the overall capacity of the current servers, a previously unused hash function is used to obtain a new node ID where the file will be replicated. The central problems are how to choose an unused hash function when replicating a file and how to choose a used hash function when requesting the file. Our solution to the file replication problem is to choose the unused hash function with the smallest index, and our solution to the file request problem is to choose a used hash function uniformly at random. Our main contribution is that we have developed a set of distributed, robust algorithms to implement the above solutions and we have evaluated their performance. In particular, we have analyzed a random binary search algorithm for file request and a random gap removal algorithm for failure recovery.     

PAMR: Passive aggressive mean reversion strategy for portfolio selection

This article proposes a novel online portfolio selection strategy named “Passive Aggressive Mean Reversion” (PAMR). Unlike traditional trend following approaches, the proposed approach relies upon the mean reversion relation of financial markets. Equipped with online passive aggressive learning technique from machine learning, the proposed portfolio selection strategy can effectively exploit the mean reversion property of markets. By analyzing PAMR’s update scheme, we find that it nicely trades off between portfolio return and volatility risk and reflects the mean reversion trading principle. We also present several variants of PAMR algorithm, including a mixture algorithm which mixes PAMR and other strategies. We conduct extensive numerical experiments to evaluate the empirical performance of the proposed algorithms on various real datasets. The encouraging results show that in most cases the proposed PAMR strategy outperforms all benchmarks and almost all state-of-the-art portfolio selection strategies under various performance metrics. In addition to its superior performance, the proposed PAMR runs extremely fast and thus is very suitable for real-life online trading applications. The experimental testbed including source codes and data sets is available at .     

High corrosion resistant Ti-5%Ta-1.8%Nb alloy for fuel reprocessing application

The conventional low carbon austenitic stainless steels display good corrosion resistance behaviour in nitric acid media. However, they are sensitive to intergranular corrosion in boiling nitric acid media in the presence of oxidizing ions like hexavalent chromium, tetravalent iron and hexavalent plutonium. The Ti-5%Ta-1.8%Nb alloy was evaluated as a candidate material for such applications of nuclear fuel reprocessing. Extensive tests were carried out to establish the superior corrosion properties in comparison to the conventional stainless steel or nitric acid grade stainless steel. The fabricability of this new alloy to various shapes like rod, sheet, wire and its weldability, which is required for making vessels, was found to be good.     

Environmental degradation of materials during wet storage of spent nuclear fuels

Wet storage is the predominant mode of storage of spent nuclear fuels. Due to legislation and other constraints, many countries do not reprocess spent fuels and have to store these for extended periods in spent fuel storage pools (SFSPs). Although the water chemistry of the pool is benign, certain factors such as stagnancy of water, crevices, and galvanic contacts between various materials of the fuel clad and the lining of the pools can result in unexpected localized corrosion. In this study, the susceptibility to localized corrosion of aluminum-1S (Al-1S), Zircaloy-2, and type 304 stainless steel (SS) has been assessed using accelerated tests with crevice bent beam (CBB) assemblies. The pool water constituents have been analyzed and electrochemical potentials (ECPs) measured in water samples drawn from different locations of the pool. The ECP has also been measured in situ, in the pools. It has been demonstrated that under conditions of crevice and galvanic contact, aluminum clad fuels from research reactors are prone to localized corrosion even in the benign environments of a SFSP. The ECP experiments indicate the importance of surface condition of the material and irradiation on degradation of various materials due to corrosion.     

Numerical study of the hydrodynamics and heat transfer characteristics of liquid–liquid Taylor flow in microchannel

A numerical study of an oil–water Taylor flow is presented in this paper to explore its flow and heat transfer characteristics. Due to the large surface area to volume ratio in narrow channels, using slug flows, high heat and mass transfer rates could be achieved. Sound knowledge of the underlying physics of slug flow is required for the practical design of microfluidic devices. In this study, hydrodynamics and heat transfer characteristics of dispersed oil droplets flowing inside a vertically upward circular microchannel (D = 0.1 mm) with water being the carrier phase have been explored numerically. ANSYS Fluent was employed to capture the liquid–liquid interface using volume of fluid method. Two different boundary conditions were considered in the present study. First, an isothermal wall of 373 K and later a constant wall heat flux (420 kW/m²) were, respectively, prescribed over the wall of the microchannel. The numerical code was validated against the results available in the literature, and the significant results in the form of pressure drop and heat transfer rates have been discussed. A considerable increase in Nusselt number, up to 180% and 210%, was observed with the oil–water slug flow in contrast to the liquid‐only single‐phase flow inside the microchannel for isothermal and constant wall heat flux conditions, respectively.     

Band‐Edge Engineered Hybrid Structures for Dye‐Sensitized Solar Cells Based on SnO2 Nanowires

In this report, we show for the first time that SnO₂ nanowire based dye sensitized solar cells exhibit an open circuit voltage of 560 mV, which is 200 mV higher than that using SnO₂ nanoparticle based cells. This is attributed to the more negative flat band potential of nanowires compared to the nanoparticles as determined by open circuit photo voltage measurements made at high light intensities. The nanowires were employed in hybrid structures consisting of highly interconnected SnO₂ nanowire matrix coated with TiO₂ nanoparticles, which showed an open circuit voltage of 720 mV and an efficiency of 4.1% compared to 2.1% obtained with pure SnO₂ nanowire matrix. The electron transport time constants for SnO₂ nanowire matrix were an order of magnitude lower and the recombination time constants are about 100 times higher than that of TiO₂ nanoparticles. The higher efficiency observed for DSSCs based on hybrid structure is attributed to the band edge positions of SnO₂ relative to that of TiO₂ and faster electron transport in SnO₂ nanowires.     

Synthesis of magnetite by coprecipitation and sintering and its characterization

Magnetite powder was synthesized via chemical co-precipitation method using FeCl₃?·?6H₂O and FeCl₂?·?4H₂O as salts and ammonium hydroxide (25% NH₄OH) solution as precipitating agent. The phases, composition and morphology of the magnetite was characterized by X-ray diffraction (XRD), micro laser Raman spectroscopy and scanning electron microscopy–energy dispersive X-ray spectroscopy. The XRD and Raman studies confirmed the formation of magnetite phase only. The results showed that the particles were properly crystallized with no other impurity. Very fine and non-uniform powder sizes were observed even after sieving operation. The magnetite particles were also characterized after sintering the powder at 1100°C, grinding and sieving. The resultant powder size in the range of 105–125?µm was obtained. After sintering, magnetite peaks got sharpened due to increase in the crystallite size. Raman peaks even at a higher laser power were observed for magnetite that were absent before sintering. Hematite peaks observed for the un-sintered powder at higher laser power was attributed to oxidation by laser radiation/heat. Efficiency of the co-precipitation process (before sintering) was established to be ～85%.     

Effect of amorphous content on dissolution characteristics of rifampicin

Rifampicin, one of the main first line anti-TB drugs, shows variable bioavailability in different marketed preparations and reasons cited include physiological, degradation, manufacturing/ processing, solid state, and bioavailability assessment procedure. Although the amorphous form of a drug is expected to exhibit higher solubility, the amorphous rifampicin has been reported to have a solubility disadvantage as compared to crystalline form II, which is used in marketed preparations. Amorphous form was generated and characterized by solid-state characterization techniques. Physical powder mixtures of form II with varying amounts of amorphous form were prepared, which were then subjected to solid-state characterization techniques and further evaluated for their dissolution behavior. Differential scanning calorimetry (DSC) scans show that area enclosed by integral of melting endotherm can be used for quantification of crystalline component, which can then be used to estimate amorphous content. No definite trend was evident in powder dissolution of mixtures that could implicate solubility difference of amorphous form. Intrinsic dissolution rate (IDR) results indicate that amorphous content has no effect on dissolution profiles of crystalline rifampicin.     

Sulfur compounds in the fuel range fractions from different crude oils

A gas chromatograph coupled with sulfur chemiluminscence detector (GC-SCD) has been used for the speciation of individual sulfur compounds in fractions of different crude oils. The crude oil fractions characterized were light naphtha (C5-90°C), heavy naphtha (90–140°C), kerosene (140–240°C), and gas oil (240–370°C) fractions obtained from true boiling point distillation process. Low boiling fractions (up to 140°C) were analyzed by existing ASTM D5623 (American Society for Testing and Materials, 2009a) method for sulfur compound speciation. As there is no standard method for the distribution of sulfur compounds in high boiling samples (up to 370°C), therefore, a methodology has been developed for the diesel range samples. The identification of individual sulfur compounds were carried out by using reference sulfur compounds. The results show that type of sulfur compounds depends upon the boiling range of the fraction and source of crude oil. The major changes in the sulfur compounds profiles of different fractions are discussed. The results of this study can be used to predict the suitability of crude oil for the production of Euro-IV and V gasoline and diesel fuels.