An analysis of thermal warpage in injection molded flat parts due to unbalanced cooling

To illustrate the potential effect of unbalanced cooling on warpage of flat parts, a simplified two-part analysis is presented. First a computational model for amorphous polymers cooling in an injection molding cavity is presented. The simulation is a finite difference solution of the one-dimensional, transient heat conduction equation with constant material properties. Plastic and mold temperature profiles are calculated through the cooling cycle and the transients from cycle to cycle are included. Temperatures are predicted for both sides of the mold allowing asymmetrical cooling to be analyzed. The model is verified analytically and is in agreement with published data. Secondly, a simplified method of predicting the thermal warpage of a fiat part from calculated temperature profiles is discussed and illustrated. The relative effects on calculated part warpage of asymmetric mold geometry and cooling fluid temperature are predicted with this analysis method. The sensitivity of warpage to these design factors is illustrated for an example part.     

The effect of molecular structure on the gas transmission rates of aromatic polyimides

A series of high-molecular weight condensation polyimides was evaluated to determine the effect of polymer molecular structure on the transmission rate of oxygen, carbon dioxide, and water vapor. The polyimide films were prepared from either 3,3′,4,4′-benzophenone tetracarboxylic dianhydride (BTDA) or pyromellitic dianhydride (PMDA) with various diamines. The study shows that molecular structure had a strong influence on gas transmission rates with results for some films varying three orders of magnitude from that of other polyimide films. In general, the BTDA series of polyimides had overall lower gas transmission rates than the PMDA-derived series. Polymers prepared with meta-oriented diamines characteristically displayed lower gas transmission than those prepared with para-oriented diamines.     

Team cognition in a cyber defense context: focus on social support behaviors

In the face of increasingly prominent cyber security issues, the organization of cyber team analysts has become crucial to thwart cyber threats. Few studies have examined the functioning of the team and the interaction between individuals in a cyber defense context and how the context influences team adaptation. The present study investigates team cognition in a cyber defense context and in particular the nature of task- or team-centered communication among analysts during a cyber defense simulation exercise. Results indicate that markers of situation assessment and shared mental models are both strategically present and linked. Nevertheless, the frequency of these markers varies depending on the quantity and quality of problems encountered; in particular, variations in social support behaviors are observed. Decreasing social support behaviors during high level activities suggests the adaptation of social behaviors depending on the threats and attacks on the system. Theoretical and practical implications are discussed in terms of theories and potential consequences for strategic adaptation and team resilience.

     

Mass transfer in 3D-printed electrolyzers: The importance of inlet effects

This article investigates the effect of inlet shape, entrance length, and turbulence promoters on mass transfer by using 3D-printed electrolyzers. Our results show that the inlet design can promote turbulence and lead to an earlier transition to turbulent flow. The Reynolds number at which the transition occurs can be predicted by the ratio of the cross-sectional area of the inlet to the cross-sectional area of the electrolyzer channel. A longer entrance length results in more laminar behavior and a later transition to turbulent flow. With an entrance length of 550 mm, the inlet design did no longer affect the mass transfer performance significantly. The addition of gyroid type turbulence promoters resulted in a factor of 2 to 4 increase in mass transfer depending on inlet design, entrance length, and the type of promoter. From one configuration to another, there was a minimal variation in pressure drop (<1600 Pa).     

Non-intrusive Coupling: Recent Advances and Scalable Nonlinear Domain Decomposition

This paper provides a detailed review of the global/local non-intrusive coupling algorithm. Such method allows to alter a global finite element model, without actually modifying its corresponding numerical operator. We also look into improvements of the initial algorithm (Quasi-Newton and dynamic relaxation), and provide comparisons based on several relevant test cases. Innovative examples and advanced applications of the non-intrusive coupling algorithm are provided, granting a handy framework for both researchers and engineers willing to make use of such process. Finally, a novel nonlinear domain decomposition method is derived from the global/local non-intrusive coupling strategy, without the need to use a parallel code or software. Such method being intended to large scale analysis, we show its scalability. Jointly, an efficient high level Message Passing Interface coupling framework is also proposed, granting an universal and flexible way for easy software coupling. A sample code is also given.     

A memetic algorithm to solve an unrelated parallel machine scheduling problem with auxiliary resources in semiconductor manufacturing

In this paper, we propose a metaheuristic for solving an original scheduling problem with auxiliary resources in a photolithography workshop of a semiconductor plant. The photolithography workshop is often a bottleneck, and improving scheduling decisions in this workshop can help to improve indicators of the whole plant. Two optimization criteria are separately considered: the weighted flow time (to minimize) and the number of products that are processed (to maximize). After stating the problem and giving some properties on the solution space, we show how these properties help us to efficiently solve the problem with the proposed memetic algorithm, which has been implemented and tested on large generated instances. Numerical experiments show that good solutions are obtained within a reasonable computational time.     

Behaviour based on decision matrices for a coordination between agents in a urban traffic simulation

This paper describes a multi-agent coordination mechanism applied to intersection simulation situations. In a goal of urban traffic simulation, we must consider the dynamic interactions between autonomous vehicles. The field of multi-agent systems provides us some studies for such systems, in particular on the coordination mechanisms. Conflicts between vehicles (i.e. agents) are very frequent in such applications, and they may cause deadlocks, particularly at intersections such as crossroads. Our approach is based on the solving of two player games/decision matrices which characterize three basic situations. An aggregation method generalizes to n-player games for complex crossroads. The objective of this approach consists in searching basic two-player matrices for solving n-agent problems. To explain the principle, we describe our approach for a particular case of crossroad with three agents. Finally, the obtained results have been examined via a tool of road traffic simulation, ARCHISIM. We assume also that the global traffic replicates the behavior of agents in different situations.     

Diagnosability Analysis of a Class of Hierarchical State Machines

This paper addresses the problem of fault detection and isolation for a particular class of discrete event dynamical systems called hierarchical finite state machines (HFSMs). A new version of the property of diagnosability for discrete event systems tailored to HFSMs is introduced. This notion, called L₁-diagnosability, captures the possibility of detecting an unobservable fault event using only high level observations of the behavior of an HFSM. Algorithms for testing L₁-diagnosability are presented. In addition, new methodologies are presented for studying the diagnosability properties of HFSMs that are not L₁-diagnosable. These methodologies avoid the complete expansion of an HFSM into its corresponding flat automaton by focusing the expansion on problematic indeterminate cycles only in the associated extended diagnoser.