An axisymmetric model for thread forming in polycarbonate and polypropylene screw and boss fasteners

Plastic boss and screw fasteners are an economical means of securing automotive components, such as instrument or body panels. However, new materials and/or suboptimal design present challenges to the boss/screw effectiveness. Failure of a boss/screw can result is loss of functional performance or increased squeak and rattle. Failure is often controlled by what occurs during the initial thread‐forming process. Thus, the goal of this paper is to develop an FEA model to elucidate the thread‐forming process so that we can facilitate subsequent design and/or process optimization, and understand potential failure modes. The FEA must accommodate nonlinear couplings, such as large strain and heat transfer. Heat generation is present in the forms of interfacial shear heating and plastic work associated with the large deformation of the interface between the boss and screw. Strain rate‐dependent materials are included using the Eyring theory for plastic flow of polymeric materials. Results of the model are presented and compared to experimentally determined torque curves and temperatures. Polym. Eng. Sci. 44:1498–1508, 2004. © 2004 Society of Plastics Engineers.     

Invariant‐set‐based fault diagnosis in Lure systems

In this paper, we present an invariant‐set‐based method for actuator and sensor fault detection and isolation in Lure systems. The Lure plant is controlled by an observer‐based feedback tracking controller, designed for the nominal (fault‐free) system. Suitable residual signals are constructed from measurable system outputs and estimates associated with the nominal observer. Faults are diagnosed by online contrasting the residual signal trajectories against sets of values that the residuals are shown to attain under healthy or faulty operation. These values are obtained via set‐invariance analysis of the system closed‐loop trajectories. Copyright © 2013 John Wiley & Sons, Ltd.     

A study of tailored blank welding between mild steel sheet and zn-coated steel sheet by CO2 laser beam

Research was conducted on tailored blank welding between mild steel sheet and Zn-coated steel sheet using CO₂ laser beam. The materials used in this study were low carbon steel sheets with a thickness of 1.2 mm and Zn-coated steel sheet with the same thickness and 6.3 μm Zn coating. Experiments were conducted by applying the Taguchi method to obtain optimum conditions for the application of this tailored blank laser welding method in practical manufacturing processes. Optical microscopy, XRD, SEM and TEM analysis were performed to observe the microstructures and to determine the structures of welded zone. In addition, mechanical properties were measured by the microhardness test, tensile test and Erichsen test to evaluate the formability of the welded specimen. There was no trapped Zn in the fusion zone, and the phases of this region consisted of polygonal ferrite, quasi-polygonal ferrite, banitic ferrite and martensite. The elongation value of welded specimen was more than 80% of the value in substrate metal, and the LDH value was more than 90% of the value in substrate metal.     

Analysis of Distance Collaboration Modalities: Alternatives to Meeting Face-to-Face

Physical and temporal boundaries are rapidly diminishing in an age of swiftly advancing information communication technologies. Today’s technologically sophisticated business and organizational environments offer a number of distance collaboration modalities (DSMs) that can facilitate efficient and cost-effective meetings that have traditionally required face-to-face meeting venues. Selection of the DCMs that maximize meeting effectiveness is significantly challenging given the wide diversity of available options. Theory and empirical data can be useful as a guide in the selection of the most appropriate DCMs to maximize organizational productivity and success. This article reviews the literature on the behavioral and technical affordances and limitations of the various DCMs. It also provides a theoretical model based on media synchronicity theory to help guide selection of effective DCMs. This theoretical framework emphasizes the primacy of media alignment with core communication processes as well as social and interpersonal factors that influence meeting effectiveness.     

The effect of handle friction and inward or outward torque on maximum axial push force

OBJECTIVE: To investigate the relationship among friction, applied torque, and axial push force on cylindrical handles. BACKGROUND: We have earlier demonstrated that participants can exert greater contact force and torque in an "inward" movement of the hand about the long axis of a gripped cylinder (wrist flexion/forearm supination) than they can in an "outward" hand movement. METHOD: Twelve healthy participants exerted anteriorly directed maximum push forces along the long axis of aluminum and rubber handles while applying deliberate inward or outward torques, no torque (straight), and an unspecified (preferred) torque. RESULTS: Axial push force was 12% greater for the rubber handle than for the aluminum handle. Participants exerted mean torques of 1.1, 0.3, 2.5, and -2.0 Nm and axial push forces of 94, 85, 75, and 65 N for the preferred, straight, inward, and outward trials, respectively. Left to decide for themselves, participants tended to apply inward torques, which were associated with increased axial push forces. CONCLUSION: Axial push force was limited by hand-handle coupling--not the whole body's push strength. Participants appeared to intuitively know that the application of an inward torque would improve their maximum axial push force. Axial push forces were least when a deliberate torque was requested, probably because high levels of torque exertions interfered with the push. APPLICATION: A low-friction handle decreases maximum axial push force. It should be anticipated that people will apply inward torque during maximum axial push.     

Inferring the capacity of the vector Poisson channel with a Bernoulli model

The capacity defines the ultimate fidelity limits of information transmission by any system. We derive the capacity of parallel Poisson process channels to judge the relative effectiveness of neural population structures. Because the Poisson process is equivalent to a Bernoulli process having small event probabilities, we infer the capacity of multi-channel Poisson models from their Bernoulli surrogates. For neural populations wherein each neuron has individual innervation, inter-neuron dependencies increase capacity, the opposite behavior of populations that share a single input. We use Shannon's rate-distortion theory to show that for Gaussian stimuli, the mean-squared error of the decoded stimulus decreases exponentially in both the population size and the maximal discharge rate. Detailed analysis shows that population coding is essential for accurate stimulus reconstruction. By modeling multi-neuron recordings as a sum of a neural population, we show that the resulting capacity is much less than the population's, reducing it to a level that can be less than provided with two separated neural responses. This result suggests that attempting neural control without spike sorting greatly reduces the achievable fidelity. In contrast, single-electrode neural stimulation does not incur any capacity deficit in comparison to stimulating individual neurons.     

Auditory system plasticity in children after long periods of complete deafness

Separation and identification of proteins by two-dimensional (2-D) electrophoresis can be used for protein-based gene expression analysis. In this report single protein spots, from polyvinylidene difluoride blots of micropreparative E. coli 2-D gels, were rapidly and economically identified by matching their amino acid composition, estimated pI and molecular weight against all E. coli entries in the SWISS-PROT database. Thirty proteins from an E. coli 2-D map were analyzed and identities assigned. Three of the proteins were unknown. By protein sequencing analysis, 20 of the 27 proteins were correctly identified. Importantly, correct identifications showed unambiguous "correct" score patterns. While incorrect protein identifications also showed distinctive score patterns, indicating that protein must be identified by other means. These techniques allow large-scale screening of the protein complement of simple organisms, or tissues in normal and disease states. The computer program described here is accessible via the World Wide Web at URL address (http:@expasy.hcuge.ch/).     

Hidden Markov models for the stimulus-response relationships of multistate neural systems

Given recent experimental results suggesting that neural circuits may evolve through multiple firing states, we develop a framework for estimating state-dependent neural response properties from spike train data. We modify the traditional hidden Markov model (HMM) framework to incorporate stimulus-driven, non-Poisson point-process observations. For maximal flexibility, we allow external, time-varying stimuli and the neurons' own spike histories to drive both the spiking behavior in each state and the transitioning behavior between states. We employ an appropriately modified expectation-maximization algorithm to estimate the model parameters. The expectation step is solved by the standard forward-backward algorithm for HMMs. The maximization step reduces to a set of separable concave optimization problems if the model is restricted slightly. We first test our algorithm on simulated data and are able to fully recover the parameters used to generate the data and accurately recapitulate the sequence of hidden states. We then apply our algorithm to a recently published data set in which the observed neuronal ensembles displayed multistate behavior and show that inclusion of spike history information significantly improves the fit of the model. Additionally, we show that a simple reformulation of the state space of the underlying Markov chain allows us to implement a hybrid half-multistate, half-histogram model that may be more appropriate for capturing the complexity of certain data sets than either a simple HMM or a simple peristimulus time histogram model alone.