Overview of methods to analyse dynamic data

This book gives an overview of existing data analysis methods to analyse the dynamic data obtained from full scale testing, with their advantages and drawbacks. The overview of full scale testing and dynamic data analysis is limited to energy performance characterization of either building components or whole buildings. The methods range from averaging and regression methods to dynamic approaches based on system identification techniques. These methods are discussed in relation to their application in following in situ measurements: -measurement of thermal transmittance of building components based on heat flux meters; -measurement of thermal and solar transmittance of building components tested in outdoor calorimetric test cells; -measurement of heat transfer coefficient and solar aperture of whole buildings based on co-heating or transient heating tests; -characterisation of the energy performance of whole buildings based on energy use monitoring

Political, social and economic determinants of corporate social disclosure by multi-national firms in environmentally sensitive industries

Using examples from environmentally sensitive industries, the paper examines the determinants of corporate social disclosure (CSD). The paper moves beyond the traditional literature in two respects. First it is international in scope, examining the accounting disclosure responses of multi-national companies to the pressures implied by the nature and scope of their operations. Second, variables measuring political risk and social development are developed so that these pressures can be measured, thereby introducing new dimensions to the literature. In common with previous studies, financial risk, size and other control variables are included. The relationships are tested econometrically utilising regression techniques not previously applied in the CSD literature but nonetheless more generally appropriate when using count dependent variables. Results suggest that managers feel an unequal sense of responsibility to different constituencies and their disclosure priorities are determined by stock market accountability, lobbying power of their domestic audience and the political risk of their activities rather than the impact of their activities in countries of operation

The space physics environment data analysis system (SPEDAS)

With the advent of the Heliophysics/Geospace System Observatory (H/GSO), a complement of multi-spacecraft missions and ground-based observatories to study the space environment, data retrieval, analysis, and visualization of space physics data can be daunting. The Space Physics Environment Data Analysis System (SPEDAS), a grass-roots software development platform (www.spedas.org), is now officially supported by NASA Heliophysics as part of its data environment infrastructure. It serves more than a dozen space missions and ground observatories and can integrate the full complement of past and upcoming space physics missions with minimal resources, following clear, simple, and well-proven guidelines. Free, modular and configurable to the needs of individual missions, it works in both command-line (ideal for experienced users) and Graphical User Interface (GUI) mode (reducing the learning curve for first-time users). Both options have “crib-sheets,” user-command sequences in ASCII format that can facilitate record-and-repeat actions, especially for complex operations and plotting. Crib-sheets enhance scientific interactions, as users can move rapidly and accurately from exchanges of technical information on data processing to efficient discussions regarding data interpretation and science. SPEDAS can readily query and ingest all International Solar Terrestrial Physics (ISTP)-compatible products from the Space Physics Data Facility (SPDF), enabling access to a vast collection of historic and current mission data. The planned incorporation of Heliophysics Application Programmer’s Interface (HAPI) standards will facilitate data ingestion from distributed datasets that adhere to these standards. Although SPEDAS is currently Interactive Data Language (IDL)-based (and interfaces to Java-based tools such as Autoplot), efforts are under-way to expand it further to work with python (first as an interface tool and potentially even receiving an under-the-hood replacement). We review the SPEDAS development history, goals, and current implementation. We explain its “modes of use” with examples geared for users and outline its technical implementation and requirements with software developers in mind. We also describe SPEDAS personnel and software management, interfaces with other organizations, resources and support structure available to the community, and future development plans.Published versio

Computer-Aided System for Wind Turbine Data Analysis

Context: The current work on wind turbine failure detection focuses on researching suitable signal processing algorithms and developing efficient diagnosis algorithms. The laboratory research would involve large and complex data, and it can be a daunting task. Aims: To develop a Computer-Aided system for assisting experts to conduct an efficient laboratory research on wind turbine data analysis. System is expected to provide data visualization, data manipulation, massive data processing and wind turbine failure detection. Method: 50G off-line SCADA data and 4 confident diagnosis algorithms were used in this project. Apart from the instructions from supervisor, this project also gained help from two experts from Engineering Department. Java and Microsoft SQL database were used to develop the system. Results: Data visualization provided 6 different charting solutions and together with robust user interactions. 4 failure diagnosis solutions and data manipulations were provided in the system. In addition, dedicated database server and Matlab API with Java RMI were used to resolve the massive data processing problem. Conclusions: Almost all of the deliverables were completed. Friendly GUI and useful functionalities make user feel more comfortable. The final product does enable experts to conduct an efficient laboratory research. The end of this project also gave some potential extensions of the system