Local mechanical behavior mapping of a biopolymer blend using nanoindentation,finite element computation,and simplex optimization strategy

In this study, we suggest a simple scheme to derive interfacial behavior using combination of nanoindentation and finite element computation. The starting point is the experimental generation of a rectangular grid composed of 32 indentations to measure the exact variation of stiffness across the interface of a bio‐based composite. A finite element simulation of nanoindentation is implemented based on elasto‐plastic material model. An optimization strategy is used to identify the behavior of all phases by matching predicted results to observed mechanical response. Results show that extent of interphase layer has a typical dimension of 8.0 ± 4.9 µm. The optimization strategy based on simplex proves to be efficient to derive the elasto‐plastic behavior of the blend across the interface with a residual value of less than 30 µN. The identification procedure demonstrates that the extent of the interfacial region depends on the measured physical quantity. The contrast across the interface for both Young's and the tangent moduli appear to be more effective than the contrast given by the yield stress. Identified Young's moduli for zein, starch, and interfacial zone are 4.78 ± 0.27, 4.13 ± 0.19, and 3.91 ± 0.17 GPa. Plasticity parameter represented by tangent modulus varies in the same order as 1238 ± 120, 847 ± 108, and 976 ± 94 MPa, respectively. © 2017 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2017 , 134, 44891.     

Cooling enhancement of planar-balanced magnetron cathode

In physical vapor deposition on a magnetron cathode, temperature of sensitive components must be kept under threshold limit, so as to ensure the cathode reliability,the process reproducibility, and the best quality of thin films.This can be achieved by an adequate design to enhance the dissipation of heat generated at the cathode. In this paper,temperature distribution and streamlines velocity of the cathode coolant inside a cathode magnetron are analyzed by using CFD solver ANSYS FLUENT in the single-phase method in combination with k–e standards turbulent model.The results show that the design is appropriate under the calculation parameters, and for high heat densities some improvements are necessary to enhance heat dissipation and keep temperature under the threshold limit.     

Internal melting and coarsening of liquid droplets in an Al–Cu alloy: a 4-D experimental study

In conventional melting experiments of pure monocrystalline metals, the phase transformation starts at the sample surface and progresses inwards according to thermal gradients. In solutionized alloys, traces of internal melting are usually observed after reheating and quenching from the semi-solid state. The formation and development of these liquid pockets are not fully understood despite their significance in semi-solid processing, where the formability is greatly influenced by the distribution of liquid within the feedstock material. In situ X-ray microtomography was performed in this study to shed light on this phenomenon. We report in detail the melting and isothermal holding of a model binary alloy where a remarkable number of liquid droplets were observed to develop and coalesce. Various computational tools have been used to study their statistical evolution as well as the local ripening mechanisms involved. We analysed an interesting case of particle coarsening which differs from classical case studies by the fact that the fast-diffusing liquid phase is entrapped within the slow-diffusing solid medium.     

Fuzzy decision support for tools selection in the core front end activities of new product development

The innovation process may be divided into three main parts: the front end (FE), the new product development (NPD) process, and the commercialization. Every NPD process has a FE in which products and projects are defined. However, companies tend to begin the stages of FE without a clear definition or analysis of the process to go from Opportunity Identification to Concept Generation; as a result, the FE process is often aborted or forced to be restarted. Koen’s Model for the FE is composed of five phases. In each of the phases, several tools can be used by designers/managers in order to improve, structure, and organize their work. However, these tools tend to be selected and used in a heuristic manner. Additionally, some tools are more effective during certain phases of the FE than others. Using tools in the FE has a cost to the company, in terms of time, space needed, people involved, etc. Hence, an economic evaluation of the cost of tool usage is critical, and there is furthermore a need to characterize them in terms of their influence on the FE. This paper focuses on decision support for managers/designers in their process of assessing the cost of choosing/using tools in the core front end (CFE) activities identified by Koen, namely Opportunity Identification and Opportunity Analysis. This is achieved by first analyzing the influencing factors (firm context, industry context, macro-environment) along with data collection from managers followed by the automatic construction of fuzzy decision support models (FDSM) of the discovered relationships. The decision support focuses upon the estimated investment needed for the use of tools during the CFE. The generation of FDSMs is carried out automatically using a specialized genetic algorithm, applied to learning data obtained from five experienced managers, working for five different companies. The automatically constructed FDSMs accurately reproduced the managers’ estimations using the learning data sets and were very robust when validated with hidden data sets. The developed models can be easily used for quick financial assessments of tools by the person responsible for the early stage of product development within a design team. The type of assessment proposed in this paper would better suit product development teams in companies that are cost-focused and where the trade-offs between what (material), who (staff), and how long (time) to involve in CFE activities can vary a lot and hence largely influence their financial performances later on in the NPD process.     

Cement-based mixes: Shearing properties and pore pressure

This study presents original results on the rheological measurement of concrete mixes. It focuses on how to determine their mechanical and physical behavior under shearing stress. More specifically, the influence of aggregate content on shearing properties is studied. A vane rheometer was developed to characterize fresh cement-based materials. In addition to the conventional concrete rheometer, a special hydraulic pressure transducer was fitted to the container to monitor the pore water pressure variation while shearing the material. Experiments on cement paste, mortar, and concrete bring a new approach to help us understand the behavior of fresh-state mixes. The results show 1) a correlation between water pore pressure and torque applied on the vane; 2) a critical sand volume fraction, ?_c, as a limit between colloidal interaction behavior and frictional behavior in mortars; beyond this critical fraction, a leap in yield stress and a drop in pore pressure due to granular dilatancy are noticed; 3) the granular content clearly influences the increase in yield stress of the cement mixes: above ?_c, this increase becomes negligible.     

Turbulence modulation of dense two-phase flows: Comment on “Modelling of dense gas-particle flow in a circulating fluidized bed by Distinct Cluster Method (DCM)”

In a recent paper, Liu X. and Xu X. [2009. Modelling of dense gas-particle flow in a circulating fluidized bed by Distinct Cluster Method (DCM). Powder Technology 195, 235-244] reported the results of numerical simulations of a circulating fluidized bed using Discrete Cluster Method (DCM). We comment on the veracity of the use of a one-way turbulence model to predict turbulence in the context of dense and moderately dense two-phase flows.     

Monte Carlo simulation to reveal the copper dissolution kinetics of an ion selective electrode based on copper sulfide

The present work aims at studying copper dissolution of a Cu²⁺ ion-selective electrode based on a CuS thin film. The electrode is prepared using electrochemical deposition of CuS on a silicon substrate. The obtained film exhibits an apparent cohesive granular structure with an average grain size of about 33 μm, a small porosity content (<4%) and a thickness of about 7.48 μm. The Cu²⁺ electrochemical response shows a nearly Nernstian behavior in the range of pCu 6–1. The copper dissolution is experimentally studied in a wide pH range. In order to quantitatively predict copper mass dissolution, an original numerical model is developed based on Monte Carlo simulation. Our main hypothesis is based on dissolution probability that triggers the whole dissolution process through solution/electrode surface exchanges. Several probability forms are suggested accounting for the real observed electrochemical kinetics. The experimental results show that, under a low pH, the dissolution process severely leads to the consumption of large material. Moreover, our predictions suggest a dissolution profile as a two-stage process irrespective of pH. Our numerical model is able to fit correctly the observed kinetics considering an exponential probability form under all pH conditions.     

Heterogeneous reaction induced by the piston effect in supercritical binary mixtures

It is now well established that the large compressibility of supercritical fluids is responsible for the strong enhancement of the thermo-acoustic heating, leading to the speeding up of the heat transport thanks to the piston effect instead of the expected slowing down. We show in this paper, through numerical simulations, that the hydrodynamics behavior of supercritical fluids also couples with the critical behavior of the solubility of solids to cause the release of a heterogeneous reaction at solid surfaces in dilute binary supercritical mixtures.     

Near-room-temperature mid-infrared quantum well photodetector

We demonstrate InGaAs mid-infrared quantum well infrared photodetectors (MIR PV-QWIPs) that enable cost-effective mature GaAs-based detection and imaging technologies, with exceptional material uniformity, reproducibility, and yield, over a large area, with high spectral selectivity, innate polarization sensitivity, radiation hardness, high detectivity, and high speed operation at TEC temperatures without bias.     

Evaluation of wall boundary condition parameters for gas–solids fluidized bed simulations

Wall boundary conditions for the solids phase have significant effects on numerical predictions of various gas–solids fluidized beds. Several models for the granular flow wall boundary condition are available in the open literature for numerical modeling of gas–solids flow. A model for specularity coefficient used in Johnson and Jackson boundary conditions by Li and Benyahia (Li and Benyahia, AIChE J. 2012;58:2058–2068) is implemented in the open‐source CFD code‐MFIX. The variable specularity coefficient model provides a physical way to calculate the specularity coefficient needed by the partial‐slip boundary conditions for the solids phase. Through a series of two‐dimensional numerical simulations of bubbling fluidized bed and circulating fluidized bed riser, the model predicts qualitatively consistent trends to the previous studies. Furthermore, a quantitative comparison is conducted between numerical results of variable and constant specularity coefficients to investigate the effect of spatial and temporal variations in specularity coefficient. Published 2013 American Institute of Chemical Engineers AIChE J, 59: 3624–3632, 2013