Interactive hybrid (symbolic-numeric) system approach to near optimal design of mechanical components

A hybrid symbolic-numeric system, referred to as OPTDEX, (Optimal Design Expert) for the optimal design of mechanical components and systems has been developed. The system is written in Golden Common LISP and IBM Professional (Ryan-McFarland) FORTRAN for execution on the IBM PC/AT microcomputer. Graphical output has been implemented using the Graphical Kernal System (GKS) standard. This microcomputer-based implementation makes the system particularly attractive as an easily accessible, low-cost engineering analysis and design tool.Experience with the system indicates that the time required to achieve, at least partially optimized engineering design solutions, is similar to that which may be expected with standard, nonoptimization-based microcomputer computation. Any added computational time may be justified and subsequently offset by increased long-term design efficacy.The OPTDEX protocol (Fig. 1) assumes a modular form, whereby each level can be modified, updated, and enhanced independently of the others to accommodate various design philosophies and the subdivision of large-scale design problems. A design cell approach has been adopted that has the capability of addressing the design of various mechanical components and systems. The current version of the OPTDEX design cell library, which is undergoing revision and expansion, includes speed reducer, bearing, coupling, and shaft design capabilities.This modular structure and generalized design cell approach, which underlies the OPTDEX system, establishes the basis of a formalized methodology for mechanical engineering design, which may be extended to include other design-related disciplines as well. For example, with the addition of appropriate design cells, the system can be configured for VLSI circuit design in electrical engineering, scheduling, and job routing in industrial engineering, and structural design in civil engineering.     

Adaptive control optimization in end milling using neural networks

In this paper, we propose an architecture with two different kinds of neural networks for on-line determination of optimal cutting conditions. A back-propagation network with three inputs and four outputs is used to model the cutting process. A second network, which parallelizes the augmented Lagrange multiplier algorithm, determines the corresponding optimal cutting parameters by maximizing the material removal rate according to appropriate operating constraints. Due to its parallelism, this architecture can greatly reduce processing time and make real-time control possible. Numerical simulations and a series of experiments are conducted on end milling to confirm the feasibility of this architecture.     

Measuring virtual experience in a three-dimensional virtual reality interactive simulator environment: a structural equation modeling approach

With the rapid development of the VR market, virtual experience has increasingly been the object of study in recent years. A growing number of studies have reported the positive effect that virtual experience can have on a user’s mood and loyalty. However, few studies have investigated the influence of the mechanism of virtual experience on users’ mood and loyalty. To compensate for this research gap, this study aims to evaluate consumers’ virtual experience by examining the flow state in a virtual environment. A total of 368 valid questionnaires were collected, and a structural equation modeling approach was employed in the data analysis. The study reveals that forming flow involves many factors: the intrinsic characteristics of the mediated environment, the consumer’s assumptions and perceptions prior to entering the flow state, the stage at which the customer enters the flow state, and the consequences of the flow experience.     

Rapid Microarray System For Passive Batch-Filling and In-Parallel-Printing Protein Solutions

This paper develops a novel microcontact printing system for printing tens of protein solutions into an array with batch filling and parallel printing. This printing system consists of micro filling and micros tamp chips. The micro filling chip can simultaneously transfer numerous protein solutions into the micros tamp chip in seconds by capillary force without cross contamination while preserving the functionality of proteins. Different proteins can be dispensed into the corresponding channels and driven into the tips of the microstamps. The microstamp can then be brought to contact with the substrate to produce bio fluid spot arrays. Teflon patterns are applied on both micro filling and microstamp chips to prevent cross contamination during filling. Thirty-six proteins can be printed in parallel with a spot size variation of less than 5%. This device has a potential to be expanded to a passive and high-throughput system for simultaneously printing hundreds of bio fluid spots to form dense arrays for diagnosing disease or screening for drugs.     

Optimal expansion of competence sets with multilevel skills

The purpose of competence set expansion is to find an optimal expansion process at the minimal cost and then obtain the required competence set from the acquired competence set to solve a problem. Several models have been proposed to address the competence set expansion problem of only a single decision maker or multiple decision makers without considering multilevel skills. However, a practical competence set expansion model should involve multiple decision makers and multilevel skills. This study discusses an optimal expansion model of incorporating competence sets of group decision makers with multilevel skills. The proposed method not only obtains the optimal competence set expansion of all decision makers with the maximal total benefit but finds all optimal alternatives of the competence set expansion model. A cooperative alliance problem is solved to illustrate the usefulness of the proposed method.     

Wireless link prediction and triggering using modified Ornstein–Uhlenbeck jump diffusion process

Through time domain observation, typical wireless signal strength values seems to exhibit some forms of mean-reverting and discontinuous “jumps” behaviour. Motivated by this fact, we propose a wireless link prediction and triggering (LPT) technique using a modified mean-reverting Ornstein–Uhlenbeck (OU) jump diffusion process. The proposed technique which we refer as OU-LPT is an integral component of wireless mesh network monitoring system developed by ICT FP7 CARrier grade wireless MEsh Network project. In particular, we demonstrate how this technique can be applied in the context of wireless mesh networks to support link switching or handover in the event of predicted link degradation or failure. The proposed technique has also been implemented and evaluated in a real-time experimental testbed. The results show that OU-LPT technique can significantly enhance the reliability of wireless links by reducing the rate of false triggers compared to a conventional linear prediction technique and therefore offers a new direction on how wireless link prediction, triggering and switching process can be conducted in the future.     

Formation of microporous polymeric materials by microemulsion polymerization of methyl methacrylate and 2-hydroxyethyl methacrylate

The investigated microemulsion system consisted of methyl methacrylate, 2-hydroxyethyl methacrylate and water using sodium dodecyl sulphate as surfactant. Ethylene glycol dimethacrylate acting as a cross-linker was also incorporated to enhance the mechanical strengths of the microporous polymeric materials. The polymerization was carried out at room temperature using a reactive redox initiator comprising ammonium persulphate and N,N,N′,N′-tetramethylethylene diamine. The conductivities of the microemulsion samples were monitored during the course of polymerization. The conductivities for a bicontinuous microemulsion before and after polymerization were found to be very similar. In addition, the transformation of microstructures was also examined using a transmission as well as a field emission scanning electron microscope. It is evidenced from the micrographs that microporous polymeric materials prepared from bicontinuous microemulsion polymerization are attributed to numerous coagulations of spherical particles. A possible mechanism for the microstructural transformation is discussed based on the information of conductivity measurements and electron micrographs. © 1996 John Wiley & Sons, Inc.     

Reinforcement of graphene nanoplatelets on plasticized poly(lactic acid) nanocomposites: Mechanical,thermal, morphology,and antibacterial properties

Plasticized poly(lactic acid) (PLA)‐based nanocomposites filled with graphene nanoplatelets (xGnP) and containing poly(ethylene glycol) (PEG) and epoxidized palm oil (EPO) with ratio 2 : 1 (2P : 1E) as hybrid plasticizer were prepared by melt blending method. The key objective is to take advantage of plasticization to increase the material ductility while preserving valuable stiffness, strength, and toughness via addition of xGnP. The tensile modulus of PLA/2P : 1E/0.1 wt % xGnP was substantially improved (30%) with strength and elasticity maintained, as compared to plasticized PLA. TGA analysis revealed that the xGnP was capable of acting as barrier to reduce thermal diffusion across the plasticized PLA matrix, and thus enhanced thermal stability of the plasticized PLA. Incorporation of xGnP also enhanced antimicrobial activity of nanocomposites toward Escherichia coli, Salmonella typhimurium, Staphylococcus aureus, and Listeria monocytogenes. © 2014 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2015 , 132, 41652.