Influences of assembly pressure and flow channel size on performances of proton exchange membrane fuel cells based on a multi-model

In this work, assembly pressure and flow channel size on proton exchange membrane fuel cell performance are optimized by means of a multi-model. Based on stress-strain data of the SGL-22BB GDL obtained from its initial compression experiments, Young's modulus with different ranges of assembly pressure fits well through modeling. A mechanical model is established to analyze influences of assembly pressure on various gas diffusion layer parameters. Moreover, a CFD calculation model with different assembly pressures, channel width, and channel depth are established to calculate PEMFC performances. Furthermore, a BP neural network model is utilized to explore optimal combination of assembly pressure, channel width and channel depth. Finally, the CFD model is used to validate effect of size optimization on PEMFC performance. Results indicate that gap change of GDL below bipolar ribs is more remarkable than that below channels under action of the assembly pressure, making liquid water easily transported under high porosity, which is conducive to liquid water to the channels, reduces the accumulation of liquid water under the ribs, and enhances water removal in the PEMFC. Affected by the assembly force, change of GDL porosity affects its diffusion rate, permeability and other parameters, which is not conducive to mass transfer in GDL. Optimizing the depth and different dimensions through width of the flow field can effectively compensate for this effect. Therefore, the PEMFC performance can be enhanced through the comprehensive optimization of the assembly force, flow channel width and flow channel depth. The optimal parameter is obtained when assembly pressure, channel width and channel depth are set as 0.6 MPa, 0.8 mm, and 0.8 mm, respectively. The parameter optimization enhances the mass transfer, impedance, and electrochemical characteristics of PEMFC. Besides, it effectively enhances the quality transfer efficiency inside GDL, prevents flooding, and reduces concentration loss and ohmic loss.     

Controlling Au electrode patterns for simultaneously monitoring electrical actuation and shape recovery in shape memory polymer

This paper presents an effective approach to achieve efficient electrical actuation and monitoring of shape recovery based on patterned Au electrodes on shape memory polymer (SMP). The electrically responsive shape recovery behavior was characterized and monitored by the evolution change in electrical resistance of patterned Au electrode. Both electrical actuation and temperature distribution in the SMP have been improved by optimizing the Au electrode patterns. The electrically actuated shape recovery behavior and temperature evolution during the actuation were monitored and characterized. The resistance changes could be used to detect beginning/finishing points of the shape recovery. Therefore, the Au electrode not only significantly enhances the electrical actuation performance to achieve a fast electrical actuation, but also enables the resistance signal to detect the free recovery process.     

A knowledge construction methodology to automate case-based learning using clinical documents

The case-based learning (CBL) approach has gained attention in medical education as an alternative to traditional learning methodology. However, current CBL systems do not facilitate and provide computer-based domain knowledge to medical students for solving real-world clinical cases during CBL practice. To automate CBL, clinical documents are beneficial for constructing domain knowledge. In the literature, most systems and methodologies require a knowledge engineer to construct machine-readable knowledge. Keeping in view these facts, we present a knowledge construction methodology (KCM-CD) to construct domain knowledge ontology (i.e., structured declarative knowledge) from unstructured text in a systematic way using artificial intelligence techniques, with minimum intervention from a knowledge engineer. To utilize the strength of humans and computers, and to realize the KCM-CD methodology, an interactive case-based learning system(iCBLS) was developed. Finally, the developed ontological model was evaluated to evaluate the quality of domain knowledge in terms of coherence measure. The results showed that the overall domain model has positive coherence values, indicating that all words in each branch of the domain ontology are correlated with each other and the quality of the developed model is acceptable.     

Mímir: An open-source semantic search framework for interactive information seeking and discovery

Semantic search is gradually establishing itself as the next generation search paradigm, which meets better a wider range of information needs, as compared to traditional full-text search. At the same time, however, expanding search towards document structure and external, formal knowledge sources (e.g. LOD resources) remains challenging, especially with respect to efficiency, usability, and scalability.This paper introduces Mímir—an open-source framework for integrated semantic search over text, document structure, linguistic annotations, and formal semantic knowledge. Mímir supports complex structural queries, as well as basic keyword search.Exploratory search and sense-making are supported through information visualisation interfaces, such as co-occurrence matrices and term clouds. There is also an interactive retrieval interface, where users can save, refine, and analyse the results of a semantic search over time. The more well-studied precision-oriented information seeking searches are also well supported.The generic and extensible nature of the Mímir platform is demonstrated through three different, real-world applications, one of which required indexing and search over tens of millions of documents and fifty to hundred times as many semantic annotations. Scaling up to over 150 million documents was also accomplished, via index federation and cloud-based deployment.     

Mechanical properties of graphene films enhanced by homo-telechelic functionalized polymer fillers via π–π stacking interactions

Most researches on graphene/polymer composites are focusing on improving the mechanical and electrical properties of polymers at low graphene content instead of paying attention to constructing graphene’s macroscopic structures. In current study the homo-telechelic functionalized polyethylene glycols (FPEGs) were tailored with π-orbital-rich groups (namely phenyl, pyrene and di-pyrene) via esterification reactions, which enhanced the interaction between polyethylene glycol (PEG) molecules and chemical reduced graphene oxide (RGO) sheets. The π–π stacking interactions between graphene sheets and π-orbital-rich groups endowed the composite films with enhanced tensile strength and tunable electrical conductivity. The formation of graphene network structure mediated by the FPEGs fillers via π–π stacking non-covalent interactions should account for the experimental results. The experimental investigations were also complemented with theoretical calculation using a density functional theory. Atomic force microscope (AFM), scanning electron microscope (SEM), X-ray diffraction (XRD), nuclear magnetic resonance (NMR), thermal gravimetric analysis (TGA), UV–vis and fluorescence spectroscopy were used to monitor the step-wise preparation of graphene composite films.     

Smart control of the assembly process with a fuzzy control system in the context of Industry 4.0

Assembly line balancing is important for the efficiency of the assembly process, however, a wide range of disruptions can break the current workload balance. Some researchers explored the task assignment plan for the assembly line balancing problem with the assumption that the assembly process is smooth with no disruption. Other researchers considered the impacts of disruptions, but they only explored the task re-assignment solutions for the assembly line re-balancing problem with the assumption that the re-balancing decision has been made already. There is limited literature exploring on-line adjustment solutions (layout adjustment and production rate adjustment) for an assembly line in a dynamic environment. This is because real-time monitoring of an assembly process was impossible in the past, and it is difficult to incorporate uncertainty factors into the balancing process because of the randomness and non-linearity of these factors. However, Industry 4.0 breaks the information barriers between different parts of an assembly line, since smart, connected products, which are enabled by advanced information and communication technology, can intelligently interact and communicate with each other and collect, process and produce information. Smart control of an assembly line becomes possible with the large amounts of real-time production data in the era of Industry 4.0, but there is little literature considering this new context. In this study, a fuzzy control system is developed to analyze the real-time information of an assembly line, with two types of fuzzy controllers in the fuzzy system. Type 1 fuzzy controller is used to determine whether the assembly line should be re-balanced to satisfy the demand, and type 2 fuzzy controller is used to adjust the production rate of each workstation in time to eliminate blockage and starvation, and increase the utilization of machines. Compared with three assembly lines without the proposed fuzzy control system, the assembly line with the fuzzy control system performs better, in terms of blockage ratio, starvation ratio and buffer level. Additionally, with the improvement of information transparency, the performance of an assembly line will be better. The research findings shed light on the smart control of the assembly process, and provide insights into the impacts of Industry 4.0 on assembly line balancing.     

Cover Picture: Arresting,Fixing, and Separating Dimers Composed of Uniform Silica Colloidal Spheres (Adv. Funct. Mater. 12/2006)

In colloidal suspensions of silica, particles undergo constant collisions. By controlling various parameters, the repulsive barrier can be reduced, thereby substantially increasing the number of collision‐induced dimerization events. Xia and co‐workers report on p. 1627 that the dimers could be arrested and then permanently fixed by introducing a small amount of fresh tetraethylorthosilicate into the colloidal suspension, with monodisperse dimer yields of up to 50 %. This yield could be increased to 80 % by centrifugation in a density gradient medium. When fresh tetraethylorthosilicate is introduced into a colloidal suspension of silica spheres, it hydrolyzes and condenses in situ to arrest and fix the dimers resulting from constant collisions between the spheres. By optimizing the experimental parameters (including the length of aging time) and the diameter of the silica spheres, as well as the concentrations of counterions, water, and ammonia, it is possible to routinely produce monodisperse dimers with a yield as high as 50 %. When combined with centrifugation using a density gradient medium, the yield of such dimers could be further increased to 80 %. It is believed that this method will provide a simple and versatile approach to the high‐volume production of dimers from spherical colloids composed of different materials. These dimers may find widespread use in a range of applications such as fabrication of photonic crystals and fundamental studies related to colloidal science.     

HART通信协议在汽油机速度测量和监控方面的应用

首先介绍了HART通信协议及他的优点，然后介绍了HART通信协议在汽油机测速方面的软件实现。该软件主要采用目前流行的VB编程语言。可设计出界面友好、功能强大的测量和监控软件。