Traceability of Chemical Measurement Results

Traceability to recognised references, ultimately to the SI units, is an indispensable prerequisite for measurement results to be comparable and trustworthy and hence accepted worldwide. This holds also for chemical measurement results, particularly as these are often used as a basis for important decisions and agreements, for example in health care and environmental protection. The concept of traceability and the special problems associated with its application to chemical analysis as compared to metrology in general are described. Current approaches to establish traceability of chemical measurement results are reported. The most important development in the last two decades was the establishment of the Consultative Committee for Metrology in Chemistry under the Metre Convention, which provided the basis for an international reference framework for chemical measurements. In order to link up laboratory results anywhere in the world with this international reference framework, traceability structures on the national level are required. It is shown, using the demand for traceable chemical measurements in Germany as an example, how such structures can be established and efficiently used

Die Adoption des Electronic Commerce im deutschen Einzelhandel

Electronic Commerce , Einzelhande

Binary search trees: average and worst case behavior

We discuss several simple strategies for constructing binary search trees. Upper and lower bounds for the average and worst case search time in trees constructed according to these strategies are derived. Furthermore, different implementations are discussed and the results are applied to digital searching

Simulation and experiment of gas diffusion in a granular bed

The diffusion of gas through porous material is important to understand the physical processes underlying cometary activity. We study the diffusion of a rarefied gas (Knudsen regime) through a packed bed of monodisperse spheres via experiments and numerical modelling, providing an absolute value of the diffusion coefficient and compare it to published analytical models. The experiments are designed to be directly comparable to numerical simulations, by using precision steel beads, simple geometries, and a trade-off of the sample size between small boundary effects and efficient computation. For direct comparison, the diffusion coefficient is determined in Direct Simulation Monte Carlo (DSMC) simulations, yielding a good match with experiments. This model is further-on used on a microscopic scale, which cannot be studied in experiments, to determine the mean path of gas molecules and its distribution, and compare it against an analytical model. Scaling with sample properties (particle size, porosity) and gas properties (molecular mass, temperature) is consistent with analytical models. As predicted by these, results are very sensitive on sample porosity and we find that a tortuosity $q(\varepsilon)$ depending linearly on the porosity $\varepsilon$ can well reconcile the analytical model with experiments and simulations. Mean paths of molecules are close to those described in the literature, but their distribution deviates from the expectation for small path lengths. The provided diffusion coefficients and scaling laws are directly applicable to thermophysical models of idealised cometary material.Comment: accepted by MNRA

Pattern representation and recognition with accelerated analog neuromorphic systems

Despite being originally inspired by the central nervous system, artificial neural networks have diverged from their biological archetypes as they have been remodeled to fit particular tasks. In this paper, we review several possibilites to reverse map these architectures to biologically more realistic spiking networks with the aim of emulating them on fast, low-power neuromorphic hardware. Since many of these devices employ analog components, which cannot be perfectly controlled, finding ways to compensate for the resulting effects represents a key challenge. Here, we discuss three different strategies to address this problem: the addition of auxiliary network components for stabilizing activity, the utilization of inherently robust architectures and a training method for hardware-emulated networks that functions without perfect knowledge of the system's dynamics and parameters. For all three scenarios, we corroborate our theoretical considerations with experimental results on accelerated analog neuromorphic platforms.Comment: accepted at ISCAS 201

Response of a coriolis gas flow meter to steady and transient wet gas flow conditions

Coriolis devices are continuously evolving to meet the demands of different conditions, such as wet gas flow. However, their application in wet gas flow has not yet been thoroughly explored. The impact of steady flow disturbances on Coriolis flow meters is well-documented, and empirical compensation or correction methods can be implemented accordingly. However, there has been inadequate investigation into the response of Coriolis meters under transient flow conditions and their comparison with steady flow in a wet gas. In this study, a Coriolis device was horizontally installed in a 50 mm pipe diameter. The experimental fluids consisted of air and water, with Lockhart-Martinelli (XLM) values ranging from 0.02 to 0.40. Steady and transient flow conditions at different gas and liquid flow rates were studied. The findings demonstrate the capability of standard deviation (STD) in distinguishing transient flow from steady one. Additionally, a strong correlation was observed between XLM and gas Over-Reading (OR) across various gas flow rates and XLM values. This correlation is particularly evident for XLM < 0.1. At extremely low liquid loading (XLM < 0.05), the average percentage error remains below 7 % even without the utilization of any correction models. Furthermore, the impact of different sensor installations, which had been largely overlooked in previous studies, was investigated