Integrated energy system for industrial complexes. Part I: A linear programming approach

A personal-computer based model of an Integrated Energy System for Industrial Estates (IESIE) has been developed as a pre-feasibility tool: it addresses the total energy concept by combining a set of CHP plant(s), boilers, vapor-compression and absorption chillers, national grid and utility transportation system. The core of the general model is the linear programming (LP) model which takes into account the changing demand-pattern of various loads and their tariffs, standby charge of electricity, unit fuel price, equipment costs, land cost, depreciation, O & M expenses, interest rate, taxes, etc. The output of the LP model yields the minimum total operating cost, optimal sizes of the equipment and their respective operational schedules. The hot utility and cold utility transportation model estimates the economic-minimum pipe size, considering installation cost, heat loss/gain cost and pumping cost. The heat balance model finds the thermal cycle equipment sizes as well as the variation of the heat-to-power ratio with load. Finally the economic model does the cash-flow analysis to determing whether the project will yield a required rate-of-return to be economically viable.

Simulations have been done using the model considering a number of sample load patterns with the prevailing cost factors in India. An after tax IRR of 20% was found for sites having load factors greater than 0·6, and up to 10 km utility transportation distance.     

Characteristics of DC magnetron sputtered ternary cobalt-nickel silicide thin films for ultra shallow junction devices

Ternary cobalt-nickel silicide thin films were synthesized by DC magnetron sputtering from an equiatomic cobalt-nickel alloy target. Grazing incidence XRD, Rutherford back scattering, high-resolution cross-sectional TEM analysis and electrical study were carried out to investigate the formation of silicide, stoichiometry, film thickness, depth profile and sheet resistance of as-deposited and post-deposition annealed films. The ternary silicide layer thickness was calculated from RBS simulated data, which was found to vary 20-43 nm for as-deposited and different vacuum annealed films. A minimum value of sheet resistance 2.73 Ω/sq corresponding to a resistivity of ∼8.4 μΩ-cm was obtained for optimized deposition and annealing conditions.     

Self-Sensing Actuation With Adaptive Control in Applications With Switching Trajectory

This paper presents the application of self-sensing actuation (SSA) to facilitate the implementation of piezoelectric actuator in an intelligent mechatronic system. SSA is a technique to employ smart materials, such as piezoelectric materials, simultaneously as a sensor and an actuator; thereby increasing the level of integration of the system. The piezoelectric actuator is equipped with an exclusive adaptive controller amidst its nonlinearities and system's disturbance. The application area to be discussed is a microdispensing system, which is an example of a micromanufacturing process, combining a fluidic system and a positioning system.     

Doping-Dependent Nonlinear Electron Mobility in GaAs|InxGa1 –xAs Coupled Quantum-Well Pseudo-Morphic MODFET Structure

Semiconductors - We analyze the asymmetric delta-doping dependence of nonlinear electron mobility μ of GaAs|InxGa1 –xAs double quantum-well pseudo-morphic modulation doped field-effect...     

High Performance Lithium‐Ion Batteries Using Layered 2H‐MoTe2 as Anode

The major challenges faced by candidate electrode materials in lithium‐ion batteries (LIBs) include their low electronic and ionic conductivities. 2D van der Waals materials with good electronic conductivity and weak interlayer interaction have been intensively studied in the electrochemical processes involving ion migrations. In particular, molybdenum ditelluride (MoTe₂) has emerged as a new material for energy storage applications. Though 2H‐MoTe₂ with hexagonal semiconducting phase is expected to facilitate more efficient ion insertion/deinsertion than the monoclinic semi‐metallic phase, its application as an anode in LIB has been elusive. Here, 2H‐MoTe₂, prepared by a solid‐state synthesis route, has been employed as an efficient anode with remarkable Li⁺ storage capacity. The as‐prepared 2H‐MoTe₂ electrodes exhibit an initial specific capacity of 432 mAh g^?1 and retain a high reversible specific capacity of 291 mAh g^?1 after 260 cycles at 1.0 A g^?1. Further, a full‐cell prototype is demonstrated by using 2H‐MoTe₂ anode with lithium cobalt oxide cathode, showing a high energy density of 454 Wh kg^?1 (based on the MoTe₂ mass) and capacity retention of 80% over 100 cycles. Synchrotron‐based in situ X‐ray absorption near‐edge structures have revealed the unique lithium reaction pathway and storage mechanism, which is supported by density functional theory based calculations.     

Time gap effect on bond strength of 3D-printed concrete

An advancing technology that combines the concrete extrusion with a motion control to create structures with complex geometrical shapes without the need for formwork is known as 3D concrete printing. Since this technique prints layer by layer, the time taken to reach the same position in the subsequent layer is important as it will create an anisotropic property that has a weaker tensile strength at the bond interface of the two printed filaments. Through rheological measurement, which reveals the material deformation and flow behaviour, it is possible to examine the material structural build-up due to time-gap effect by measuring at different time delay. This paper focuses on investigating the time-gap effect on the printed filament with rheological and observation at macroscopic-scale to understand the material behaviour of the initial and subsequent printed layer during its fresh phase. Rheological experiment findings reveal that the tensile strength of the printed specimen is correlated to the material modulus at the initial layer.     

Normalization-Based Task Scheduling Algorithms for Heterogeneous Multi-Cloud Environment

Cloud computing is one of the most successful technologies that offer on-demand services through the Internet. However, datacenters of the clouds may not have unlimited capacity which can fulfill the demanded services in peak hours. Therefore, scheduling workloads across multiple clouds in a federated manner has gained a significant attention in the recent years. In this paper, we present four task scheduling algorithms, called CZSN, CDSN, CDN and CNRSN for heterogeneous multi-cloud environment. The first two algorithms are based on traditional normalization techniques, namely z-score and decimal scaling respectively which are hired from data mining. The next two algorithms are based on two newly proposed normalization techniques, called distribution scaling and nearest radix scaling respectively. All the proposed algorithms are shown to work on-line. We perform rigorous experiments on the proposed algorithms using various synthetic as well as benchmark datasets. Their performances are evaluated through simulation run by measuring two performance metrics, namely makespan and average cloud utilization. The experimental results are compared with that of existing algorithms to show the efficacy of the proposed algorithms.     

Networking and communication challenges for post-exascale systems

With the significant advancement in emerging processor, memory, and networking technologies, exascale systems will become available in the next few years (2020–2022). As the exascale systems begin to be deployed and used, there will be a continuous demand to run next-generation applications with finer granularity, finer time-steps, and increased data sizes. Based on historical trends, next-generation applications will require postexascale systems during 2025–2035. In this study, we focus on the networking and communication challenges for post-exascale systems. Firstly, we present an envisioned architecture for post-exascale systems. Secondly, the challenges are summarized from different perspectives: heterogeneous networking technologies, high-performance communication and synchronization protocols, integrated support with accelerators and field-programmable gate arrays, fault-tolerance and quality-of-service support, energy-aware communication schemes and protocols, softwaredefined networking, and scalable communication protocols with heterogeneous memory and storage. Thirdly, we present the challenges in designing efficient programming model support for high-performance computing, big data, and deep learning on these systems. Finally, we emphasize the critical need for co-designing runtime with upper layers on these systems to achieve the maximum performance and scalability.