Development, simulation validation, and wind tunnel testing of a digital controller system for flutter suppression

Flutter suppression (FS) is one of the active control concepts being investigated by the AFW program. The design goal for FS control laws was to increase the passive flutter dynamic pressure by 30 percent. In order to meet this goal, the FS control laws had to be capable of suppressing both symmetric and antisymmetric flutter instabilities simultaneously. In addition, the FS control laws had to be practical and low-order, robust and capable of real time execution within the 200 hz. sampling time. The purpose here is to present an overview of the development, simulation validation, and wind tunnel testing of a digital controller system for flutter suppression

Joint and individual analysis of breast cancer histologic images and genomic covariates

A key challenge in modern data analysis is understanding connections between complex and differing modalities of data. For example, two of the main approaches to the study of breast cancer are histopathology (analyzing visual characteristics of tumors) and genetics. While histopathology is the gold standard for diagnostics and there have been many recent breakthroughs in genetics, there is little overlap between these two fields. We aim to bridge this gap by developing methods based on Angle-based Joint and Individual Variation Explained (AJIVE) to directly explore similarities and differences between these two modalities. Our approach exploits Convolutional Neural Networks (CNNs) as a powerful, automatic method for image feature extraction to address some of the challenges presented by statistical analysis of histopathology image data. CNNs raise issues of interpretability that we address by developing novel methods to explore visual modes of variation captured by statistical algorithms (e.g. PCA or AJIVE) applied to CNN features. Our results provide many interpretable connections and contrasts between histopathology and genetics

Digital-flutter-suppression-system investigations for the active flexible wing wind-tunnel model

Active flutter suppression control laws were designed, implemented, and tested on an aeroelastically-scaled wind tunnel model in the NASA Langley Transonic Dynamics Tunnel. One of the control laws was successful in stabilizing the model while the dynamic pressure was increased to 24 percent greater than the measured open-loop flutter boundary. Other accomplishments included the design, implementation, and successful operation of a one-of-a-kind digital controller, the design and use of two simulation methods to support the project, and the development and successful use of a methodology for on-line controller performance evaluation

Using Key Performance Indicators for multi-criteria traffic management strategic decisions

In recent research work (FP7 CONDUITS) a performance evaluation framework for traffic management and Intelligent Transport Systems was developed. The new framework consists of a set of Key Performance Indicators (KPIs) for the strategic themes of traffic efficiency, safety, pollution reduction and social inclusion, and the last stages of the project saw its validation through its application to four case studies. Following up from this work, this paper presents the extension of the framework for use as a prediction tool enabling urban transport authorities to assess the impacts of relevant policies and technologies before implementing them. The first stage of the extension focused on pollution reduction, and a novel decision support tool (CONDUITS_DST) integrating the respective KPI with micro-simulation modelling was developed. Case studies executed in Brussels and Zurich demonstrated the usability and viability of the tool. This paper takes the development one step further and reports on the extension of the approach, which moves from single-criterion to a multi-criteria decision support tool through the inclusion of the KPI on traffic efficiency, again based onmicro-simulation modelling outputs

Using Key Performance Indicators for traffic management and Intelligent Transport Systems as a prediction tool

In recent research work (FP7 CONDUITS) a performance evaluation framework for traffic management and Intelligent Transport Systems was developed. The new framework consists of a set of Key Performance Indicators (KPIs) for the strategic themes of traffic efficiency, safety, pollution reduction and social inclusion, and the last stages of the project saw its validation through its application to four case studies. Following up from this work, this paper presents the extension of the framework for use as a prediction tool enabling urban transport authorities to assess the impacts of relevant policies and technologies before implementing them. Focussing on pollution reduction, a tool (CONDUITS-DST) integrating the respective KPIs with microsimulation modelling is developed. The paper describes the integration process, including the model chosen for calculating the emissions levels of a number of scenarios, presents the results of the application to a case study in the city of Brussels, and outlines future developments targeted at broadening the integration of the KPIs into decision-makin

Development and testing of a predictive traffic safety evaluation tool for road traffic management and ITS impact assessment

In recent research the CONDUITS performance evaluation framework for traffic management and Intelligent Transport Systems (ITS) was developed, consisting of a set of Key Performance Indicators (KPIs) for the strategic themes of traffic efficiency, safety, pollution reduction and social inclusion. Follow-up work has concentrated on integrating the developed CONDUITS KPIs with microscopic traffic simulation. The outcome has been a predictive evaluation tool for traffic management and ITS, called CONDUITS_DST, in which two of the four KPI categories have been integrated to date: pollution and traffic efficiency. The objective of the present study is to further extend the predictive evaluation framework to include the theme of traffic safety. Contributing to the development of the CONDUITS_DST traffic safety module, the paper identifies and proposes relevant models and metrics linking traffic characteristics with road safety impacts. In doing so, it enables the extraction of the necessary input data for each of the three CONDUITS KPIs for traffic safety (accidents, direct impacts, and indirect impacts) directly from microscopic traffic simulation models. The proposed models and metrics are tested in conjunction with the relevant CONDUITS KPIs for safety using data from simulation models before and after the implementation of a bus priority signalling system in Brussels. Testing takes place both at the network level, but also at the level of individual links, and the results show that the framework is able to capture the expected safety impacts adequately well, paving the way towards its implementation is the traffic safety module of CONDUITS_DST

Inelastic Scattering Time for Conductance Fluctuations

We revisit the problem of inelastic times governing the temperature behavior of the weak localization correction and mesoscopic fluctuations in one- and two-dimensional systems. It is shown that, for dephasing by the electron electron interaction, not only are those times identical but the scaling functions are also the same.Comment: 10 pages Revtex; 5 eps files include