Experimental Investigations of Machinability in the Turning of Compacted Graphite Iron using Minimum Quantity Lubrication

Unique mechanical properties of the compacted graphite iron (CGI) attracted attention of manufacturers and suppliers mainly in automotive industry in last decades. However due to the low machinability of the CGI material, more efficient machining strategies need to be implemented. Improvement in the cost-effective and environmentally sensitive processing of compacted graphite iron (CGI) is one of the major concerns of the manufacturing world because of the allure of CGI's mechanical properties. This study assesses the efficiency of minimum quantity lubrication (MQL) in CGI turning when compared to the dry-cutting condition. The turning tests were conducted across a wide range of cutting parameters: three different cutting speeds (100, 200, 300 m/min) and three different feed rates (0.1, 0.2, 0.3 mm/rev), all at a constant depth of cut (1 mm). The MQL efficiency is evaluated through cutting force and surface roughness measurements, optical and SEM analyses of chip formation and tool-wear analysis. The results showed that MQL usage provided a reduction in the resultant cutting forces by 2–5%, a reduction in surface roughness by 25%. The SEM analysis also revealed much clearer and smoother cutting edges on tool surfaces used in the MQL tests.     

Modeling river water quality parameters using modified adaptive neuro fuzzy inference system

Water quality is always one of the most important factors in human health. Artificial intelligence models are respected methods for modeling water quality. The evolutionary algorithm(EA) is a new technique for improving the performance of artificial intelligence models such as the adaptive neuro fuzzy inference system(ANFIS) and artificial neural networks(ANN). Attempts have been made to make the models more suitable and accurate with the replacement of other training methods that do not suffer from some shortcomings, including a tendency to being trapped in local optima or voluminous computations. This study investigated the applicability of ANFIS with particle swarm optimization(PSO)and ant colony optimization for continuous domains(ACO_R) in estimating water quality parameters at three stations along the Zayandehrood River, in Iran. The ANFIS-PSO and ANFIS-ACO_R methods were also compared with the classic ANFIS method, which uses least squares and gradient descent as training algorithms. The estimated water quality parameters in this study were electrical conductivity(EC), total dissolved solids(TDS), the sodium adsorption ratio(SAR), carbonate hardness(CH), and total hardness(TH). Correlation analysis was performed using SPSS software to determine the optimal inputs to the models. The analysis showed that ANFIS-PSO was the better model compared with ANFIS-ACO_R. It is noteworthy that EA models can improve ANFIS' performance at all three stations for different water quality parameters.     

大功率二氧化碳压缩机运行效率的实验研究

本文在不同压力和转速工况下,对一台由挪威科技大学与Sintef联合研发的大功率单级活塞式二氧化碳制冷压缩机进行了实验测试,得出压缩机效率、容积效率以及油循环率随压缩比和转速的变化曲线,以及效率最优时各参数的范围。结果表明：当压缩比为2.1、转速为2 500 r/min时,油循环率达到最大值2.84%;当压缩比为1.88,转速为1000 r/min时,容积效率达到最大值85.8%;当压缩比为1.5~2.5,转速约为1 500 r/min时,压缩机效率最优;当转速为1500 r/min,压缩比为2.0时,可达到最大值79.1%。针对压缩机效率的实验数据进行了数学拟合,并与两台同类压缩机的产品效率作对比分析,结果表明：大功率压缩机当压缩比为1.5~3.2时的效率比同类压缩机约高11.5%。     

Novel Nanoencapsulation Technology and its Potential Role in Bile Acid-Based Targeted Gene Delivery to the Inner Ear

Hearing loss impacts a large proportion of the global population. Damage to the inner ear, in particular the sensitive hair cells, can impact individuals for the rest of their lives. There are very limited options for interventions after damage to these cells has occurred. Targeted gene delivery may provide an effective means to trigger appropriate differentiation of progenitor cells for effective replacement of these sensitive hair cells. There are several hurdles that need to be overcome to effectively deliver these genes. Nanoencapsulation technology has previously been used for the delivery of pharmaceuticals, proteins and nucleic acids, and may provide an effective means of delivering genes to trigger appropriate differentiation. This review investigates the background of hearing loss, current advancements and pitfalls of gene delivery, and how nanoencapsulation may be useful.     

Automated design of error-resilient and hardware-efficient deep neural networks

Applying deep neural networks (DNNs) in mobile and safety-critical systems, such as autonomous vehicles, demands a reliable and efficient execution on hardware. The design of the neural architecture has a large influence on the achievable efficiency and bit error resilience of the network on hardware. Since there are numerous design choices for the architecture of DNNs, with partially opposing effects on the preferred characteristics (such as small error rates at low latency), multi-objective optimization strategies are necessary. In this paper, we develop an evolutionary optimization technique for the automated design of hardware-optimized DNN architectures. For this purpose, we derive a set of inexpensively computable objective functions, which enable the fast evaluation of DNN architectures with respect to their hardware efficiency and error resilience. We observe a strong correlation between predicted error resilience and actual measurements obtained from fault injection simulations. Furthermore, we analyze two different quantization schemes for efficient DNN computation and find one providing a significantly higher error resilience compared to the other. Finally, a comparison of the architectures provided by our algorithm with the popular MobileNetV2 and NASNet-A models reveals an up to seven times improved bit error resilience of our models. We are the first to combine error resilience, efficiency, and performance optimization in a neural architecture search framework.

     

Achieving IT‐based synergies through regulation‐oriented and consensus‐oriented IT governance capabilities

This study aims at exploring the IT governance capabilities that enable organizations to achieve IT‐based synergies. Following existing work on the contextualization of theories and drawing on the resource‐based view of the firm (RBV), we develop an RBV of IT‐based synergies in two steps. First, we adopt existing context‐specific constructs and relationships from prior work on IT governance capabilities, IT relatedness, and synergies to develop a preliminary contextualization of the RBV. Second, to further refine our theoretical framework, we conduct an exploratory field study that includes interviews with 26 CIOs and other IT executives from 21 multibusiness firms. Our findings suggest that IT governance capabilities lead to IT‐based synergies through IT relatedness and business process relatedness. We found regulation‐oriented IT governance capabilities (IT roles and IT processes) to increase IT relatedness, while consensus‐oriented IT governance capabilities (IT groups and relational capabilities) had a positive effect on business process relatedness. Our results suggest that, in isolation, IT and business process relatedness lead to IT cost synergies, while collectively enabling IT‐induced business synergies. Our study is among the first to treat IT relatedness as an endogenous construct and to explicitly integrate business process relatedness into the IT governance domain. Our context‐specific decomposition of IT governance capabilities helps to better explain their links to IT and business process relatedness. These findings contribute to a better understanding of the tension between IT‐based synergies and business‐IT alignment. Decision‐makers are guided in developing IT governance capabilities to achieve IT‐based synergies.     

A mortar formulation for frictionless line-to-line beam contact

Multibody System Dynamics - This paper describes the quasi-static formulation of frictionless line contact between flexible beams by employing the mortar finite element approach. Contact...     

Synthesis and Characterization of Anti-fungus,Anti-corrosion and Self-cleaning Hybrid Nanocomposite Coatings Based on Sol–Gel Process

Anti-corrosion, anti-fungus, and self-cleaning properties of coatings containing ZnO–TiO₂, SiO₂–TiO₂ and SiO₂/TiO₂/ZnO nanoparticles synthesized based on sol–gel precursors using tetra methoxysilane, 3-glycidoxypropyl trimethoxysilane, tetra (n-butyl orthotitanate) and zinc acetate dihydrate were investigated by FESEM, EDAX and TEM analyses. Results indicated uniform dispersion of inorganic nanoparticles in the range of 20–40 nm in size. Anti-corrosion property of the hybrid coating was characterized by EIS measurements and parametrically analyzed in an equivalent circuit when the coating was exposed to salt solution. Results showed that, ZnO and TiO₂ nanoparticles enhance anti-corrosion property of the hybrid coatings. Anti-fungus and anti-bacterial properties of the coatings were determined by diameter of inhibition zone and inhabitation of bacterial growth, respectively. The coating containing ZnO and TiO₂ nanoparticles showed anti-fungus and anti-bacterial properties which were related to their photocatalytic properties. Degradation of methylene blue in aqueous solution was determined by UV–Visible tests which indicated self-cleaning property of the coatings containing ZnO and TiO₂ nanoparticles.     

Experimental research on photocatalytic oxidation air purification technology applied to aircraft cabins

The experiment presented in this report was performed in a simulated aircraft cabin to evaluate the air cleaning effects of two air purification devices that used photocatalytic oxidation (PCO) technology. Objective physical, chemical and physiological measurements and subjective human assessments were used for the evaluation. Comparisons were made between conditions with and without the PCO units installed in the re-circulated air system. Four groups of 17 subjects were exposed for 7 h to each test condition. Chemical analysis indicates that ethanol, isoprene and toluene were decomposed by oxidation in the PCO units tested. However, some intermediate products, such as formaldehyde and acetaldehyde, were detected. Physiological measurements did not show any significant effects of the two PCO units except that skin dryness was reduced by operating PCO unit 2. Both positive and negative effects of using PCO units on subjective assessments were observed after the first 3 1/4 hours of exposure. After 6 h of exposure, a positive effect of using either PCO unit on symptoms of dizziness and claustrophobia was observed.     

Hyphenation of gas chromatography to microcoil 1H nuclear magnetic resonance spectroscopy

Whereas the hyphenation of gas chromatography (GC) with mass spectrometry is of great importance, little is known about the coupling to nuclear magnetic resonance spectroscopy (NMR). The investigation of this technique is an attractive proposition because of the valuable information given by NMR on molecular structure. The experiments shown here are to our knowledge the first hyphenating capillary GC to microcoil NMR. In contrast to liquids, gases have rarely been investigated by NMR, mainly due to the experimental difficulties in handling gases and the low signal-to-noise-ratio (SNR) of the NMR signal obtained at atmospheric pressure. With advances in NMR sensitivity (higher magnetic fields and solenoidal microprobes), this limitation can be largely overcome. In this paper, we describe the use of a custom-built solenoidal NMR microprobe with an active volume of 2 microL for the NMR detection of several compounds at 400 MHz, first in a mixture, and then with full coupling to capillary GC to identify them separately. The injected amounts of each analyte in the hyphenated experiments are in the range of 15-50 micromol, resulting in reasonable SNR for sample masses of 1-2 microg.