Rietveld_l 1995 Rietveld Software For Mac

Rietveld refinement is a technique described by Hugo Rietveld for use in the characterisation of crystalline materials. The neutron and X-ray diffraction of powder samples results in a pattern characterised by reflections (peaks in intensity) at certain positions. The height, width and position of these reflections can be used to determine many aspects of the material's structure.
Information, the reader is referred to The Rietveld Method edited by R. Young (1993) and the mono-graph Modern Powder Diffraction edited by Bish & Post (1989). Guidelines for the publication of the results of Rietveld analyses can be found in the paper by Young et al. It has been assumed that the Rietveld reﬁnement software used is.

Rietveld refinement of Sr 5(AsO 4) 3Cl from high-resolution synchrotron data Anthony M. Henderson,b Richard F. Wendlandtc and Wendy J. Harrisonc aSynchrotron Radiation Source, STFC Daresbury Laboratory, Daresbury, Warrington.

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record nr. 455357

Refereed Article in a scientific journal
Record number	455357
Title	A fully adaptive forecasting model for short-term drinking water demand
Author(s)	Bakker, M.; Vreeburg, J.H.G.; Schagen, K.M. van; Rietveld, L.C.
Source	Environmental Modelling & Software 48 (2013). - ISSN 1364-8152 - p. 141 - 151.
DOI	https://doi.org/10.1016/j.envsoft.2013.06.012
Department(s)	Environmental Technology WIMEK
2013
Keyword(s)	distribution network - consumption - prediction - operation - systems
For the optimal control of a water supply system, a short-term water demand forecast is necessary. We developed a model that forecasts the water demand for the next 48 h with 15-min time steps. The model uses measured water demands and static calendar data as single input. Based on this input, the model fully adaptively derives day factors and daily demand patterns for the seven days of the week, and for a configurable number of deviant day types. Although not using weather data as input, the model is able to identify occasional extra water demand in the evening during fair weather periods, and to adjust the forecast accordingly. The model was tested on datasets containing six years of water demand data in six different areas in the central and Southern part of Netherlands. The areas have all the same moderate weather conditions, and vary in size from very large (950,000 inhabitants) to small (2400 inhabitants). The mean absolute percentage error (MAPE) for the 24-h forecasts varied between 1.44 and 5.12%, and for the 15-min time step forecasts between 3.35 and 10.44%. The model is easy to implement, fully adaptive and accurate, which makes it suitable for application in real time control. (C) 2013 Elsevier Ltd. All rights reserved.
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[Submitted on 2 Jun 2010 (v1), last revised 3 Jun 2010 (this version, v2)]

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Abstract: SrRietveld is a highly automated software toolkit for Rietveld refinement.Compared to traditional refinement programs, it is more efficient to use andeasier to learn. It is designed for modern high throughput diffractometers andcapable of processing large numbers of>Loading...

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