Computational Parametric Analysis of Cellular Solids with the Miura-Ori Metamaterial Geometry under Quasistatic Compressive Loads

Origami-based metamaterials have widespread application prospects in various industries including aerospace, automotive, flexible electronics, and civil engineering structures. Among the wide range of origami patterns, the fourfold tessellation known as Miura-ori is of particular attraction to engineers and designers. More specifically, researchers have proposed different 3D structures and metamaterials based on the geometric characteristics of this classic origami pattern. Herein, a computational modeling approach for the design and evaluation of 3D cellular solids with the Miura-ori metamaterial geometry which can be of zero or nonzero thicknesses is presented. To this end, first, a range of design alternatives generated based on a numerical parametric model is designed. Next, their mechanical properties and failure behavior under quasistatic axial compressive loads along three perpendicular directions are analyzed. Then, the effects of various geometric parameters on their energy absorption behavior under compression in the most appropriate direction are investigated. The findings of this study provide a basis for future experimental investigations and the potential application of such cellular solids for energy-absorbing purposes.     

Sterilizing tissue-materials using pulsed power plasma

This paper investigates the potential of pulsed power to sterilize hard and soft tissues and its impact on their physico-mechanical properties. It hypothesizes that pulsed plasma can sterilize both vascular and avascular tissues and the transitive layers in between without deleterious effects on their functional characteristics. Cartilage/bone laminate was chosen as a model to demonstrate the concept, treated at low temperature, at atmospheric pressure, in short durations and in buffered environment using a purposed-built pulsed power unit. Input voltage and time of exposure were assigned as controlling parameters in a full factorial design of experiment to determine physical and mechanical alteration pre- and post-treatment. The results demonstrated that, discharges of 11 kV sterilized samples in 45 s, reducing intrinsic elastic modules from 1.4 ± 0.9 to 0.9 ± 0.6 MPa. There was a decrease of 14.1 % in stiffness and 27.8 % in elastic-strain energy for the top quartile. Mechanical impairment was directly proportional to input voltage (P value < 0.05). Bacterial inactivation was proportional to treatment time for input voltages above 32 V (P < 0.001; R _Sq  = 0.98). Thermal analysis revealed that helix-coil transition decelerated with exposure time and collagen fibrils were destabilized as denaturation enthalpy reduced by 200 μV. We concluded by presenting a safe operating threshold for pulsed power plasma as a feasible protocol for effective sterilization of connective tissues with varying level of loss in mechanical robustness which we argue to be acceptable in certain medical and tissue engineering application.     

A Real-Time Power Controller for Grid-Connected Inverters in LV Smart Microgrids

This paper presents a real-time power flow controller for VSIs （voltage source inverters） interfaced to low voltage microgrids. The proposed controller is modular, flexible, intelligent, inexpensive, portable, adaptive and designed to positively contribute in low voltage microgrids in which the lines R/X ratio is greater than the transmission lines. Therefore, the proposed control strategy is developed for operation in distribution lines. The controller strategy is different from the conventional grid-connected inverters which are designed based on transmission line characteristics. This controller, using a Texas Instrument general purpose DSP （digital signal processor）, is programmed and tuned using MATLAB/SIMULINK in order to enhance self-healing, reliability and stability of the grid. This general purpose controller makes proper decisions using its local measurements as the primary source of data. The controller has the capability of communicating with the adjacent controllers and sharing the information if/when needed. The power flow output of the inverter is tested for both islanded and grid-connected modes of operation. The inverter positively contributes to active and reactive power supply while operating in grid-connected mode. The proposed control method has been implemented on a Texas Instrument DSC （digital signal controller） chip and tested on a hardware test bench at the Alternative Energy Laboratory at WVU1T （West Virginia University Institute of Technology）. The system＇s experimental results veri~ the validity and efficiency of the proposed controller.     

Kinetic Monte Carlo simulation for homogeneous nucleation of metal nanoparticles during vapor phase synthesis

We present a free‐energy driven kinetic Monte Carlo model to simulate homogeneous nucleation of metal nanoparticles (NPs) from vapor phase. The model accounts for monomer‐cluster condensations, cluster–cluster collisions, and cluster evaporations simultaneously. Specifically, we investigate the homogeneous nucleation of Al NPs starting with different initial background temperatures. Our results indicate good agreement with earlier phenomenological studies using the Gibbs# free energy formulation from Classical Nucleation Theory (CNT). Furthermore, nucleation rates for various clusters are calculated through direct cluster observations. The steady‐state nucleation rate estimated using two different approaches namely, the Yasuoka‐Matsumoto (YM) and mean first passage time (MFPT) methods indicate excellent agreement with each other. Finally, our simulation results depict the expected increase in the entropy of mixing as clusters approach the nucleation barrier, followed by its subsequent drastic loss after the critical cluster formation resulting from first‐order phase transitions. © 2017 American Institute of Chemical Engineers AIChE J, 63: 18–28, 2018     

Type II robotic assembly line balancing problem: An evolution strategies algorithm for a multi-objective model

In this paper a different type II robotic assembly line balancing problem (RALB-II) is considered. One of the two main differences with the existing literature is objective function which is a multi-objective one. The aim is to minimize the cycle time, robot setup costs and robot costs. The second difference is on the procedure proposed to solve the problem. In addition, a new mixed-integer linear programming model is developed. Since the problem is NP-hard, three versions of multi-objective evolution strategies (MOES) are employed. Numerical results show that the proposed hybrid MOES is more efficient.     

Optimized Hemolysin Type 1 Secretion System in Escherichia coli by Directed Evolution of the Hly Enhancer Fragment and Including a Terminator Region

Type 1 secretion systems (T1SS) have a relatively simple architecture compared to other classes of secretion systems and therefore, are attractive to be optimized by protein engineering. Here, we report a KnowVolution campaign for the hemolysin (Hly) enhancer fragment, an untranslated region upstream of the hlyA gene, of the hemolysin T1SS of Escherichia coli to enhance its secretion efficiency. The best performing variant of the Hly enhancer fragment contained five nucleotide mutations at five positions (A30U, A36U, A54G, A81U, and A116U) resulted in a 2-fold increase in the secretion level of a model lipase fused to the secretion carrier HlyA1. Computational analysis suggested that altered affinity to the generated enhancer fragment towards the S1 ribosomal protein contributes to the enhanced secretion levels. Furthermore, we demonstrate that involving a native terminator region along with the generated Hly enhancer fragment increased the secretion levels of the Hly system up to 5-fold.     

Indium channel implant for improved short-channel behavior ofsubmicrometer NMOSFETs

Indium has been used as an alternative channel implant in submicrometer-channel Si MOSFETs in order to obtain highly nonuniform channel doping. Superior device characteristics have been obtained down to 0.17-μm channel length. The device characteristics have been compared to those of uniform boron-implanted short-channel MOSFETs used in a 0.25-μm CMOS technology. Results indicate that NMOSFETs with nonuniform channel doping obtained with indium have superior short-channel effect (SCE) when compared to NMOSFETs with uniformly (boron) doped channel     

Smart production systems: automating decision-making in manufacturing environment

Smart production systems (SPS) are manufacturing systems capable of autonomously diagnosing their health and autonomously designing continuous improvement projects, leading to the desired productivity improvement. The main component of SPS, developed in this paper, is the Programmable Manufacturing Advisor (PMA), which evaluates the system's health and calculates optimal steps for continuous improvement. The analytics of PMA are based on the theory of Production Systems Engineering (PSE); the numerics of PMA are based on PSE Toolbox, which implements the PSE methods. In this paper, the PMA-based SPS architecture with manager-in-the-loop is described, theoretical/analytical foundations of PMA are outlined, its software/hardware implementations are commented upon, and demonstrations of PMA-based SPS operation are provided using two production systems: automotive underbody assembly (large volume manufacturing) and hot-dip galvanisation plant (small manufacturing organisation).     

Prediction of the effectiveness of rolling dynamic compaction using artificial neural networks and cone penetration test data

Rolling Dynamic Compaction(RDC),which is a ground improvement technique involving non-circular modules drawn behind a tractor,has provided the construction industry with an improved ground compaction capability,especially with respect to a greater influence depth and a higher speed of compaction,resulting in increased productivity. However,to date,there is no reliable method to predict the effectiveness of RDC in a range of ground conditions. This paper presents a new and unique predictive tool developed by means of artificial neural networks(ANNs) that permits a priori prediction of density improvement resulting from a range of ground improvement projects that employed 4-sided RDC modules;commercially known as"impact rollers". The strong coefficient of correlation(i.e. R0.86) and the parametric behavior achieved in this study indicate that the model is successful in providing reliable predictions of the effectiveness of RDC in various ground conditions.