Incipient plasticity in tungsten during nanoindentation: Dependence on surface roughness, probe radius and crystal orientation

The influence of crystallographic orientation, contact size and surface roughness effects on incipient plasticity in tungsten were investigated by nanoindentation with indenters with a range of end radius (150, 350, 720 and 2800 nm) in single crystal samples with the (100) and (111) orientations. Results for the single crystals were compared to those for a reference polycrystalline tungsten sample tested under the same conditions. Surface roughness measurements showed that the Ra surface roughness was around 2, 4, and 6 nm for the (100), (111) and polycrystalline samples respectively. A strong size effect was observed, with the stress for incipient plasticity increasing as the indenter radius decreased. The maximum shear stress approached the theoretical shear strength when W(100) was indented using the tip with the smallest radius. The higher roughness and greater dislocation density on the W(111) and polycrystalline samples contributed to yield occurring at lower stresses

Beneficiation of Bababudan Low Grade Magnetite ores - A Technical Appraisal

The horse-shoe shaped Bababudan range of low grade magnetite ore deposits in the western part of Karnataka State, India, is distributed over a length of about 25 kms. The deposits have for convenience, been divided into three continuous blocks viz., Rudragiri, Attigundi and Mahal. The huge ore reserves, proximity to the Manglore Port for possible export of iron ore and connection with Bangalore and Manglore cities through national highways, make these deposits prospective for exploration

Microstructure, Precipitation and Micro-segregation in Inconel 825 Weldments: A Comparative study between GTAW and EBW

Inconel 825 is a Ni-Fe-Cr alloy which is widely used in engineering due to its exceptional corrosion resistance and high-temperature strength. Welding (joining) of Inconel 825 has attracted strong research attention over the past few years. In this work, the effects of heat input leading to precipitation and micro segregation of Inconel 825 weldments were examined in light of comparing them while using two popular welding techniques namely, Gas tungsten arc welding (GTAW) and Electron beam welding (EBW). It was discovered that excessive heat input during GTAW can lead to root cracking and solidification cracking; while EBW demonstrated better control over undercut and maintains consistent weld quality even for higher heat inputs. Both GTAW and EBW samples exhibit dendritic grain morphologies with distinctive grain boundaries. Precipitates, such as Al4C3 and TiN were observed in both processes, contributing to improved mechanical properties. While GTAW weldments show some degree of segregation for Mo, Cu, Ti, and Al, EBW weldments demonstrate negligible segregation for major alloying elements but micro-segregation of Ti and Al. In general, the mechanical properties of EBW weldments was better as the average hardness, tensile strength, and ductility was much better compared to the GTAW weldments. This can be attributed to lower heat input, faster cooling rates, and a reduced rate of elemental segregation during EBW. Finally, the fractographic analysis revealed the presence of voids and micro-voids, indicating a ductile mode of failure for both GTAW and EBW samples. These findings offer invaluable insights for selecting the appropriate environment and welding method to join Inconel 825 for critical safety applications

First exit times and residence times for discrete random walks on finite lattices

In this paper, we derive explicit formulas for the surface averaged first exit time of a discrete random walk on a finite lattice. We consider a wide class of random walks and lattices, including random walks in a non-trivial potential landscape. We also compute quantities of interest for modelling surface reactions and other dynamic processes, such as the residence time in a subvolume, the joint residence time of several particles and the number of hits on a reflecting surface.Comment: 19 pages, 2 figure

Real Time Net Zero Energy Building Energy Manager with Heterogeneous Wireless Ad hoc Network Adaptable To IoT Architectures

Significant energy consumption by buildings from utility grid has made researchers revisit existing Building Energy Management Systems (BEMS). Most of the developing countries have taken a green initiative of Net Zero Energy Buildings (NZEB) to reduce carbon foot print and fast depletion of conventional energy sources. Though the integration of solar and wind based systems to grid is successful in recent years, residential building energy management systems with renewable energy sources is still an evolving research area. Monitoring, control and actuation systems should be tightly coupled with the help of any to any device communication namely Internet of Things (IoT) to realize an efficient NZEB. In this paper a real time NZEB is proposed and developed with bi-directional wireless sensor and actuation system. Proposed NZEB central server collects and maintains a database of on site solar generation, battery state of charge and load power consumption data of a building with help of IEEE 802.15.4 and IEEE 802.11 wireless networks. Proposed system was deployed as a test bed with sensing, control, actuation and server modules and connecting them with a bi-directional wireless network architecture similar to IoT. Data observed at experimental test bed confirm that developed system can estimate on site solar power generation, state of charge on battery bank and load power consumption with negligible error. A simulation study with experimental data collected at NZEB test bed shows that NZEB can optimally schedule loads between local generation and utility grid thereby minimizing peak demand on the grid

Surface Defect incorporated Diamond Machining of Silicon

This paper reports the performance enhancement benefits in diamond turning of the silicon wafer by incorporation of the Surface Defect Machining (SDM) method. The hybrid micromachining methods usually require additional hardware to leverage the added advantage of hybrid technologies such as laser heating, cryogenic cooling, electric pulse or ultrasonic elliptical vibration. The SDM method tested in this paper does not require any such additional baggage and is easy to implement in a sequential micro-machining mode. This paper made use of Raman spectroscopy data, average surface roughness data and imaging data of the cutting chips of silicon for drawing a comparison between conventional Single Point Diamond Turning (SPDT) and SDM while incorporating surface defects in the (i) circumferential and (ii) radial directions. Complimentary 3D Finite Element Analysis (FEA) was performed to analyse the cutting forces and the evolution of residual stress on the machined wafer. It was found that the surface defects generated in the circumferential direction with an interspacing of 1 mm revealed the lowest average surface roughness (Ra) of 3.2 nm as opposed to 8 nm Ra obtained through conventional SPDT using the same cutting parameters. The observation of the Raman spectroscopy performed on the cutting chips showed remnants of phase transformation during the micromachining process in all cases. FEA was used to extract quantifiable information about the residual stress as well as the sub-surface integrity and it was discovered that the grooves made in the circumferential direction gave the best machining performance. The information being reported here is expected to provide an avalanche of opportunities in the SPDT area for low-cost machining solution for a range of other nominal hard, brittle materials such as SiC, ZnSe and GaAs as well as hard steels

Why We Read Wikipedia

Wikipedia is one of the most popular sites on the Web, with millions of users relying on it to satisfy a broad range of information needs every day. Although it is crucial to understand what exactly these needs are in order to be able to meet them, little is currently known about why users visit Wikipedia. The goal of this paper is to fill this gap by combining a survey of Wikipedia readers with a log-based analysis of user activity. Based on an initial series of user surveys, we build a taxonomy of Wikipedia use cases along several dimensions, capturing users' motivations to visit Wikipedia, the depth of knowledge they are seeking, and their knowledge of the topic of interest prior to visiting Wikipedia. Then, we quantify the prevalence of these use cases via a large-scale user survey conducted on live Wikipedia with almost 30,000 responses. Our analyses highlight the variety of factors driving users to Wikipedia, such as current events, media coverage of a topic, personal curiosity, work or school assignments, or boredom. Finally, we match survey responses to the respondents' digital traces in Wikipedia's server logs, enabling the discovery of behavioral patterns associated with specific use cases. For instance, we observe long and fast-paced page sequences across topics for users who are bored or exploring randomly, whereas those using Wikipedia for work or school spend more time on individual articles focused on topics such as science. Our findings advance our understanding of reader motivations and behavior on Wikipedia and can have implications for developers aiming to improve Wikipedia's user experience, editors striving to cater to their readers' needs, third-party services (such as search engines) providing access to Wikipedia content, and researchers aiming to build tools such as recommendation engines.Comment: Published in WWW'17; v2 fixes caption of Table

Using Synchronization for Prediction of High-Dimensional Chaotic Dynamics

We experimentally observe the nonlinear dynamics of an optoelectronic time-delayed feedback loop designed for chaotic communication using commercial fiber optic links, and we simulate the system using delay differential equations. We show that synchronization of a numerical model to experimental measurements provides a new way to assimilate data and forecast the future of this time-delayed high-dimensional system. For this system, which has a feedback time delay of 22 ns, we show that one can predict the time series for up to several delay periods, when the dynamics is about 15 dimensional.Comment: 10 pages, 4 figure

Fairness Beyond Disparate Treatment & Disparate Impact: Learning Classification without Disparate Mistreatment

Automated data-driven decision making systems are increasingly being used to assist, or even replace humans in many settings. These systems function by learning from historical decisions, often taken by humans. In order to maximize the utility of these systems (or, classifiers), their training involves minimizing the errors (or, misclassifications) over the given historical data. However, it is quite possible that the optimally trained classifier makes decisions for people belonging to different social groups with different misclassification rates (e.g., misclassification rates for females are higher than for males), thereby placing these groups at an unfair disadvantage. To account for and avoid such unfairness, in this paper, we introduce a new notion of unfairness, disparate mistreatment, which is defined in terms of misclassification rates. We then propose intuitive measures of disparate mistreatment for decision boundary-based classifiers, which can be easily incorporated into their formulation as convex-concave constraints. Experiments on synthetic as well as real world datasets show that our methodology is effective at avoiding disparate mistreatment, often at a small cost in terms of accuracy.Comment: To appear in Proceedings of the 26th International World Wide Web Conference (WWW), 2017. Code available at: https://github.com/mbilalzafar/fair-classificatio