On modeling the deformations and tool-workpiece interactions during machining metal matrix composites

Significance of application of metal matrix composites (MMCs) in various industries has already been demonstrated. In order to address the challenges faced during machining MMCs, development of novel modeling techniques for understanding the mechanics of the process is crucial. This paper presents a new approach towards finite element modeling of MMC machining process to facilitate the analysis of plastic deformations. Transient Lagrangian modeling is used with adaptive remeshing control in order to reduce the effects of mesh distortions on accurate estimation of plastic deformation during machining. The thorough understanding of MMC plastic deformations, which is achieved using the developed model, is an asset in analysis of MMC behavior during the process.     

Analysis of the hazards for the molten cuprous chloride pouring operation in an industrial hydrogen production facility

An analysis is reported of a design for a local exhaust ventilation system for the molten cuprous chloride pouring station in an industrial plant. Heat recovery from molten cuprous chloride is a key process within the copper–chlorine (Cu–Cl) cycle of thermochemical water splitting for hydrogen production. Because of particulate matter, dust, and vapors emitted by the molten salt, an effective and safe design is crucial. The design process involves calculating duct diameters to provide the desired duct air velocity through the system. The static pressure is evaluated so that the fan size can be determined. An adequate supply of makeup air must be provided to replace the air exhausted through the ventilation system. The economics of the ventilation system and ways to protect employee health, as well as minimize the costs associated with exhaust ventilation, are also described. Copyright © 2011 John Wiley & Sons, Ltd.     

Comparison of molten salt heat recovery options in the Cu-Cl cycle of hydrogen production

This paper presents a comparative review of different options for recovering heat from molten CuCl in the Cu-Cl cycle of hydrogen production. Various technologies exist for recovering heat from the molten CuCl in the cycle, but each has its advantages and challenges. In this paper, different parameters such as heat transfer rate, additional materials in the cycle, energy efficiency, temperature retention, economics, material issues, and design feasibility are considered in the evaluation of methods. It is shown that casting/extrusion, atomization methods, with a separate vessel using water as a coolant and rotary/spinning atomization using air as a coolant, can be considered as the most efficient and reliable methods for heat recovery from molten CuCl.     

Pinch analysis for recycling thermal energy in the Cu–Cl cycle

Due to lower temperature requirements than other thermochemical cycles, the copper-chlorine (Cu–Cl) cycle is one of the most promising cycles for hydrogen production. The cycle consists of a number of endothermic and exothermic processes. The overall efficiency of the cycle can be improved by recovering as much heat as possible from the exothermic processes within the cycle and minimizing the net heat input to the cycle. In this paper, a pinch methodology is used to determine the minimum energy requirement for the overall Cu–Cl cycle, if heat recovery within the cycle is optimized. All heating and cooling flows (actual or potential) are presented as temperature-energy flow profiles and combined into composite curves for the entire cycle. Additional equipment and the overall thermal layout of the cycle are also investigated.     

A bi-objective possibilistic programming model for open shop scheduling problems with sequence-dependent setup times, fuzzy processing times, and fuzzy due dates

We are concerned with an open shop scheduling problem having sequence-dependent setup times. A novel bi-objective possibilistic mixed-integer linear programming model is presented. Sequence-dependent setup times, fuzzy processing times and fuzzy due dates with triangular possibility distributions are the main constraints of this model. An open shop scheduling problem with these considerations is close to the real production scheduling conditions. The objective functions are to minimize total weighted tardiness and total weighted completion times. To solve small-sized instances for Pareto-optimal solutions, an interactive fuzzy multi-objective decision making (FMODM) approach, called TH method proposed by Torabi and Hassini, is applied. Using this method, an equivalent auxiliary single-objective crisp model is obtained and solved optimally by the Lingo software. For medium to large size examples, a multi-objective particle swarm optimization (MOPSO) algorithm is proposed. This algorithm consists of a decoding procedure using a permutation list to reduce the search area in the solution space. Also, a local search algorithm is applied to generate good initial particle positions. Finally, to evaluate the effectiveness of the MOPSO algorithm, the results are compared with the ones obtained by the well-known SPEA-II, using design of experiments (DOE) based on some performance metrics.     

Role of Grafting on Particle and Film Morphology and Film Properties of Zero VOC Polyurethane/Poly(meth)acrylate Hybrid Dispersions

Hybrid waterborne dispersions of polyurethane (PU)/poly(meth)acrylic are widely applied in coating and adhesive products, as well as in many other applications. The synergetic performance of the two component polymers is highly dependent on the ability to control the PU and (meth)acrylic network structure. In this work, the effect of grafting and the impact of macromolecular architecture on the particle and film morphology as well as on the properties of PU/(meth)acrylic hybrid films is investigated. It is shown that with grafting, the absolute molar mass distribution (MMD) is shifted toward higher values as the low molar mass PU chains become incorporated in the (meth)acrylic polymer network. Furthermore, by using different types of functional monomers, the nature of the MMD can be altered. Using transmission electron microscopy (TEM) analysis, it is demonstrated that more homogeneous particle and film morphologies are obtained in the case of grafted hybrids. Finally, the impact of network structure on tensile strength is outlined highlighting that grafted polymer films have higher Young's modulus and strain hardening than the non‐grafted ones.     

Real-time PH-based interpolation algorithm for high speed CNC machining

Various methods for parametric interpolation of non-uniform rational B-spline (NURBS) curves have been proposed in the past. However, the errors caused by the approximate nature of the NURBS interpolator were rarely taken into account. This paper proposes an integrated look-ahead algorithm for parametric interpolation along NURBS curves. The algorithm interpolates the sharp corners on the curve with the Pythagorean-hodograph (PH) interpolation. This will minimize the geometric and interpolator approximation errors simultaneously. The algorithm consists of four different modules: a sharp corner detection module, a PH construction module, a feedrate planning module, and a dynamics module. Simulations are performed to show correctness of the proposed algorithm. Experiments on an X?CY table confirm that the developed method improves tracking and contour accuracies significantly compared to previously proposed algorithms.     

Study of Reaction Between Slag and Carbonaceous Materials

The chemical interaction of a typical slag of EAF with three different carbon sources, coke, rubber-derived carbon (RDC), coke-RDC blend, was studied in atmospheric pressure at 1823 K (1550 °C). Using an IR-gas analyzer, off-gases evolved from the sample were monitored. While the coke-RDC blend exhibited the best reducing performance in reaction with molten slag, the RDC sample showed poor interaction with the molten slag. The gasification of the coke, RDC, and coke-RDC blend was also carried out under oxidizing conditions using a gas mixture of CO₂ (4 wt pct) and Ar (96 wt pct) and it was shown that the RDC sample had the highest rate of gasification step \( C_{0} \mathop{\longrightarrow}\limits{{k_{3} }}{\text{CO}} + nC_{\text{f}} \) (11.6 site/g s (×6.023 × 10²³/2.24 × 10⁴)). This may be attributed to its disordered structure confirmed by Raman spectra and its nano-particle morphology observed by FE-SEM. The high reactivity of RDC with CO₂ provided evidence that the Boudouard reaction was fast during the interaction with molten slag. However, low reduction rate of iron oxide from slag with RDC can be attributed to the initial weak contact between RDC and molten slag implying that the contact between carbonaceous matter and slag plays significant roles in the reduction of iron oxide from slag.     

Link State Routing Based on Compressed Sensing

In table routing protocols such as link state routing, every node in the network periodically broadcasts its link state and the state of its neighbors. These routing updates result in the transmission of a large number of packets. Some of these packets contain correlated or even redundant data which could be compressed if there is central management in the network. However, in autonomous networks, each node acts as a router, in which case central coordination is not possible. In this paper, compressed sensing is used to reduce routing traffic overhead. This can be done at nodes which have greater processing capabilities and no power consumption limitations such as backbone nodes in wireless mesh networks. A method is proposed to select a subset of nodes and thus a subset of links to probe their state. The sensed states are encoded to generate a low dimension sampled vector. This compressed link state vector is broadcast to the entire network. Nodes can then reconstruct link states from this vector using side information. Performance results are presented which demonstrate accurate anomaly detection while adapting to topology changes. Further, it is shown that a proper choice of weighting coefficients in the sampling process can improve detection performance.