Strain rate- and temperature-dependent tensile properties of an epoxy-based, thermosetting, shape memory polymer (Veriflex-E)

In this study, the inelastic deformation behavior of an epoxy-based, thermally triggered shape memory polymer resin, known as Veriflex-E, was investigated. The experimental program was designed to explore the influence of strain rate on monotonic loading at various temperatures which is needed to establish the design space of SMPs in load bearing applications. Thermally actuated shape memory polymers can be thought of as having two phases separated by the glass transition temperature (T _g ). At temperatures below the T _g , Veriflex-E exhibits a high elastic modulus and positive, non-linear strain rate sensitivity in monotonic loading. The Poisson’s ratio at room temperature is independent of the strain rate, but dependent upon the strain magnitude. As the temperature is increased, the strain rate sensitivity in monotonic loading decreases. Well above the T _g , the elastic modulus drops by several orders of magnitude. In this high temperature region, the material achieves strain levels well above 100% and Poisson’s ratio is constant at 0.5 regardless of strain rate or strain magnitude.     

A thermomechanical constitutive model for an epoxy based shape memory polymer and its parameter identifications

This paper presents a three-dimensional (3D) finite deformation thermomechanical model to study the glass transition and shape memory behaviors of an epoxy based shape memory polymer (SMP) (Veriflex E) and a systematic material parameter identification scheme from a set of experiments. The model was described by viscoelastic elements placed in parallel to represent different active relaxation mechanisms around glass transition temperature in the polymer. A set of standard material tests was proposed and conducted to identify the model parameter values, which consequently enable the model to reproduce the experimentally observed shape memory (SM) behaviors. The parameter identification procedure proposed in this paper can be used as an effective tool to assist the construction and application of such 3D multi-branch model for general SMP materials.     

Medium-access control protocols for WDM-based optical access networks with passive-star clusters interconnected by a backbone ring

This paper investigates the performance of medium access control (MAC) protocols in a wavelength-division multiplexing (WDM) based optical access network consisting of a backbone ring interconnecting several passive-star-based clusters of optical networking units (ONUs) at customer premises. Each cluster is connected to the backbone through an access node (AN). A scheduler located in each AN, executes two MAC protocols, one for the intracluster traffic and the other for the intercluster traffic. In order to maintain the quality of service, the scheduler in the AN employs, priority-based queuing for the intercluster traffic on pre-assigned wavelengths. For controlling the intracluster traffic, the scheduler employs pre-transmission coordination with ranging and look-ahead functionalities in the MAC protocol. The performance of MAC protocol for intracluster traffic is evaluated through event-driven simulation, while for intercluster traffic the MAC performance is evaluated through analytical modeling of the queuing system employing two dynamic bandwidth management schemes. Performance of the intracluster MAC protocol is shown to be improved by novel use of subcarrier multiplexing on the wavelength used for the control packet transmission. A comparative study of the two intercluster schemes in terms of end-to-end delay is carried out, to understand the effect of priority queuing on the real-time and non-real-time service packets.     

Machine Learning and Deep Learning powered satellite communications: Enabling technologies,applications, open challenges,and future research directions

The recent wave of creating an interconnected world through satellites has renewed interest in satellite communications. Private and government-funded space agencies are making advancements in the creation of satellite constellations, and the introduction of 5G has brought a new focus to a fully connected world. Satellites are the proposed solutions for establishing high throughput and low latency links to remote, hard-to-reach areas. This has caused the injection of many satellites in Earth's orbit, which has caused many discrepancies. There is a need to establish highly adaptive and flexible satellite systems to overcome this. Machine Learning (ML) and Deep Learning (DL) have gained much popularity when it comes to communication systems. This review extensively provides insight into ML and DL's utilization in satellite communications. This review covers how satellite communication subsystems and other satellite system applications can be implemented through Artificial Intelligence (AI) and the ongoing open challenges and future directions.     

Reduction of Iron-Ore Pellets Using Different Gas Mixtures and Temperatures

Direct reduction of iron ore (DRI) is gaining an increased attention due to the growing need to decarbonize industrial processes. The current industrial DRI processes are performed using reformed natural gas, which results in CO₂ emission, although it is less than carbothermic reduction in the blast furnace. Carbon-free reduction may be realized through the utilization of green H₂ as a reducing agent, in place of natural gas. Herein, the effects of various gas mixtures and temperature on the reduction kinetics of the hematite iron-ore pellets are focused on in this work. Pellets are reduced at 700, 800, 850, and 900 °C in hydrogen and using various gas mixes at 850 °C. Morphology of the pellets is investigated with the help of scanning electron microscopy and mercury intrusion porosimetry. The effects of temperature and gas composition on the reduction kinetics and porosity of the pellets are discussed. A notable effect of reduction rate on the internal structure of the pellets is detected, slower reduction rate yielded bigger pores offsetting the gas composition. Higher temperature results in coarser pores and higher porosity. Increase of CO content in the gas mix also leads to bigger pore size.     

Structural breaks and energy efficiency in Fiji

This paper examines how energy-output ratios (EYRs) in Fiji have responded to the major energy crises and in particular if these ratios have declined after the energy shocks. The expectation is that energy efficiency should improve after an energy crisis. For this purpose we have used at first a few simpler procedures and then a recently developed more powerful tests for structural breaks by Bai and Perron [Bai, J., Perron, P., 1998. Estimating and testing linear models with multiple structural changes. Econometrica 66, 47–78; Bai, J., Perron, P., 2003a. Computation and analysis of multiple structural change models. Journal of Applied Econometrics 18, 1–22; Bai, J., Perron, P., 2003b. Critical values for multiple structural change tests. Econometrics Journal 6, 72–78]. Policy implications of our results are discussed.     

A novel nano-nonwoven fabric with three-dimensionally dispersed nanofibers: entrapment of carbon nanofibers within nonwovens using the wet-lay process

This study demonstrates, for the first time, the manufacturing of novel nano-nonwovens that are comprised of three-dimensionally distributed carbon nanofibers within the matrices of traditional wet-laid nonwovens. The preparation of these nano-nonwovens involves dispersing and flocking carbon nanofibers, and optimizing colloidal chemistry during wet-lay formation. The distribution of nanofibers within the nano-nonwoven was verified using polydispersed aerosol filtration testing, air permeability, low surface tension liquid capillary porometry, SEM and cyclic voltammetry. All these characterization techniques indicated that nanofiber flocks did not behave as large solid clumps, but retained the 'nanoporous' structure expected from nanofibers. These nano-nonwovens showed significant enhancements in aerosol filtration performance. The reduction-oxidation reactions of the functional groups on nanofibers and the linear variation of electric double-layer capacitance with nanofiber loading were measured using cyclic voltammetry. More than 65 m2 (700 ft2) of the composite were made during the demonstration of process scalability using a Fourdrinier-type continuous pilot papermaking machine. The scalability of the process with the control over pore size distribution makes these composites very promising for filtration and other nonwoven applications.     

Interaction of oxidation and damage in high temperature polymeric matrix composites

Polymeric matrix composites with long term durability requirements at high temperatures must be designed to resist degradation due to physical aging, chemical changes and thermo-oxidation. This paper describes the interaction between oxidation and damage during high temperature aging of polymeric matrix composites. The oxidation layer growth in neat resins depends upon the relative dominance of the oxygen diffusion rate in oxidized region and the reaction rate in the un-oxidized region. Oxidation in fiber-reinforced composites is seen to be orthotropic with axial direction of fiber being the preferred oxidation growth direction. Transverse oxidation growth correlates with growth rates in neat resins after accounting for the fiber microstructure effects and attributing additional diffusivity to the fibers and fiber–matrix interphase. However, the oxidation growth in areas where discrete cracking is observed is substantially higher. Close coupling is observed between discrete crack growth rates and oxidation layer growth rates in axial direction. Damage evolution and the interaction of damage and oxygen diffusivity are critical factors and must be considered for oxidation growth prediction in composite materials. In this paper, a model-based analysis of oxidation in composites is presented using a systematic methodology that determines the relative effects of the matrix oxidation, role of fiber and interface effects and that of the damage growth. Carbon fiber-reinforced PMR-15 composites are used for both experimental characterization and simulations.     

A new state estimation method for high-mix semiconductor manufacturing processes

In semiconductor manufacturing upstream processes may affect the wafer substrate in a manner that alters performance in downstream operations, and the context within which a process is run may fundamentally change the way the process behaves. Incorporating these influences into a control method ultimately leads to better predictability and improved control performance, because one lot of a specific product may take a very different processing path through the fabrication facility than the next lot of that same product. This paper provides a new method for state estimation in a high-mix manufacturing scenario, based on a random walk model. This model, combined with a moving window approach and least squares solution, provides better estimates for simulated processes with a high-mix of tools and products with many low-runners as compared to alternative methods. An approach combining the Kalman filter and the least squares solution is also developed, with improved results in some cases. In the case of manufacturing data, we modify the model parameters and the weights on processing contexts to get better results.