Assessment of falsework performance using fuzzy set concepts

Human-based uncertainties which are abundant in falsework construction are seldom included in the assessment of falsework performance. The classical probability concept is impractical and fails to treat the uncertainties which are commonly expressed in linguistic variables. A method of assessing falsework adequacy has been developed based on a fuzzy set concept. This concept interpretes in mathematical terms the linguistic variables of subjective appraisals of the falsework enabling and triggering events and their consequences. Graphical display were constructed from the final assessment and presented as a guide to determine the overall falsework performance. This method can be used as a tool for quality control processes in which reduction of the enabling and triggering events can be conducted to achieve a desired level of overall falsework performance.     

Registration-based compensation using sparse representation in conformal-array STAP

Space-time adaptive processing (STAP) is a well-known technique in detecting slow-moving targets in the clutter-spreading environment. When considering the STAP system with conformal radar array (CFA), the training data are range-dependent, which results in poor detection performance of traditional statistical-based algorithms. Current registration-based compensation (RBC) is implemented based on a sub-snapshot spectrum using temporal smoothing. In this case, the estimation accuracy of the configuration parameters and the clutter power distribution is limited. In this paper, the technique of sparse representation is introduced into the spectral estimation, and a new compensation method is proposed, namely RBC with sparse representation (SR-RBC). This method first establishes the relationship between the clutter covariance matrix (CCM) and the clutter spectral distribution. Based on this, it avoids the problem of lacking stationary training data and converts the CCM estimation into the solving of the underdetermined equation only with the test cell. Then sparse representation method, like iterative reweighted least square (IRLS) is used to guide the solution of the underdetermined equation towards the actual clutter distribution. Finally, the transform matrix is designed using the CCM estimation so that the processed training data behaves nearly stationary with the test cell. Because the configuration parameters and the clutter spectral response are obtained with full-snapshot using sparse representation, SR-RBC provides more accurate clutter spectral estimation, and the transformed training data are more stationary so that better signal-clutter-ratio (SCR) improvement is achieved.     

Highly efficient Cu(In,Ga)Se2 solar cells grown on flexible polymer films

Solar cells based on polycrystalline Cu(In,Ga)Se(2) absorber layers have yielded the highest conversion efficiency among all thin-film technologies, and the use of flexible polymer films as substrates offers several advantages in lowering manufacturing costs. However, given that conversion efficiency is crucial for cost-competitiveness, it is necessary to develop devices on flexible substrates that perform as well as those obtained on rigid substrates. Such comparable performance has not previously been achieved, primarily because polymer films require much lower substrate temperatures during absorber deposition, generally resulting in much lower efficiencies. Here we identify a strong composition gradient in the absorber layer as the main reason for inferior performance and show that, by adjusting it appropriately, very high efficiencies can be obtained. This implies that future manufacturing of highly efficient flexible solar cells could lower the cost of solar electricity and thus become a significant branch of the photovoltaic industry.     

Deep Anomaly Detection on Tennessee Eastman Process Data

This paper provides the first comprehensive evaluation and analysis of modern (deep-learning-based) unsupervised anomaly detection methods for chemical process data. We focus on the Tennessee Eastman process dataset, a standard litmus test to benchmark anomaly detection methods for nearly three decades. Our extensive study will facilitate choosing appropriate anomaly detection methods in industrial applications. From the benchmark, we conclude that reconstruction-based methods are the methods of choice, followed by generative and forecasting-based methods.     

Using synchroton radiation-based micro-computer tomography (SR μ-CT) for the measurement of fibre orientations in cellulose fibre-reinforced polylactide (PLA) composites

The present work deals with the measurement of fibre orientation angles in composites. A study by Bax and Müssig [1] investigated the mechanical properties (tensile and impact characteristics) of injection-moulded flax and Cordenka-reinforced polylactide (PLA) composites with fibre mass fractions between 10 and 30 %. Raising the fibre content from 10 to 30 % resulted in an increase in tensile characteristics, but it was noted that a reinforcement with 10 % flax fibres led to poorer tensile strength as compared to the neat PLA matrix. This behaviour was not expected and needs clarification. Therefore, test specimens with a fibre content of 10 and 30 mass % were examined for their fibre orientations and void content. For the investigations, microcomputer tomography images were created by monochromatic synchrotron radiation. Fibre orientation angles of these micrographs were determined with an adapted measuring mask of the Fibreshape software. It could be shown that the fibre orientation in the composite is dependent on the fibre mass fraction and the type of fibre. No voids were found in all the investigated composites. The average fibre orientation angle of 10 % flax/PLA showed a larger deviation from the longitudinal axis of the test specimen than the other samples, and is made primarily responsible for the lower tensile strength of this composite.     

Organic Junction Field‐Effect Transistor

The realization and performance of a novel organic field‐effect transistor—the organic junction field‐effect transistor (JFET)—is discussed. The transistors are based on the modulation of the thickness of a depletion layer in an organic pin junction with varying gate potential. Based on numerical modeling, suitable layer thicknesses and doping concentrations are identified. Experimentally, organic JFETs are realized and it is shown that the devices clearly exhibit amplification. Changes in the electrical characteristics due to a variation of the intrinsic and the p‐doped layer thickness are rationalized by the numerical model, giving further proof to the proposed operational mechanism.     

核-壳结构有机硅弹性体技术对环氧树脂体系性能的影响

介绍了在双组分环氧树脂体系中采用的核-壳结构有机硅弹性体技术,以及其对涂层机械性能的影响。结果表明,通过采用该技术能明显改善涂层的性能,涂层的抗冲击强度、耐候性、附着力和耐腐蚀性显著提高,滑动阻力明显降低。     

Regional knowledge production in nanomaterials: a spatial filtering approach

Nanomaterials are seen as a key technology for the twenty-first century, and much is expected of them in terms of innovation and economic growth. They could open the way to many radically new applications, which would form the basis of innovative products. As nanomaterials are still in their infancy, universities, public research institutes and private businesses seem to play a vital role in the innovation process. Existing literature points to the importance of knowledge spillovers between these actors and suggests that the opportunities for these depend on proximity, with increasing distance being detrimental to the extent that spillovers can be realised. Due to the technological complexity, however, proximity could also be less important as relevant nanomaterials research is globally dispersed. Hence in this paper, we analyse the effects of co-location of R&D activities on nanomaterial patenting. Based on European Patent Office data at the German district level (NUTS-3), we estimate two negative binomial models in a knowledge production function framework and include a spatial filtering approach to adjust for spatial autocorrelation. Our results indicate that there is a significant positive effect of both public and private R&D on the production of nanomaterial patents. Moreover, we find a positive interaction between them which hints at the importance of their co-location for realising the full potential of an emerging technology like nanomaterials.