Robust Control Synthesis for Gust Load Alleviation from Large Aeroelastic Models with Relaxation of Spatial Discretisation

This paper introduces a methodology for the design of gust load control systems directly from large aeroelastic models with relaxation of spatial discretisation. A convenient state-space representation of the vortex-panel unsteady aerodynamics suitable for control synthesis is presented. This allows a full understanding of the dynamics of the linearized vortex aeroelastic model and is suitable for control system design. Through the use of robust controllers, large reductions in loading could be achieved. Comparisons are also made between robust and classical control methods. It further demonstrates that controllers synthesized from models of coarse spatial discretizations and of an order of magnitude smaller in size were capable of rejecting disturbances on fully converged models, with performances comparable to expensive higher order controllers developed from full models

Reconstructing the Star Formation History of the Galaxy

The evolution of the star formation rate in the Galaxy is one of the key ingredients quantifying the formation and determining the chemical and luminosity evolution of galaxies. Many complementary methods exist to infer the star formation history of the components of the Galaxy, from indirect methods for analysis of low-precision data, to new exact analytic methods for analysis of sufficiently high quality data. We summarise available general constraints on star formation histories, showing that derived star formation rates are in general comparable to those seen today. We then show how colour-magnitude diagrams of volume- and absolute magnitude-limited samples of the solar neighbourhood observed by Hipparcos may be analysed, using variational calculus techniques, to reconstruct the local star formation history. The remarkable accuracy of the data coupled to our maximum-likelihood variational method allows objective quantification of the local star formation history with a time resolution of ~ 50 Myr. Over the past 3Gyr, the solar neighbourhood star formation rate has varied by a factor of ~ 4, with characteristic timescale about 0.5Gyr, possibly triggered by interactions with spiral arms.Comment: 12 pages, Proc. of the Sept. 20-24, 1999 Vulcano Workshop ``The chemical evolution of the Milky Way: stars vs. clusters'', eds. F. Matteucci & F. Giovanell

Using multiple classifiers for predicting the risk of endovascular aortic aneurysm repair re-intervention through hybrid feature selection.

Feature selection is essential in medical area; however, its process becomes complicated with the presence of censoring which is the unique character of survival analysis. Most survival feature selection methods are based on Cox's proportional hazard model, though machine learning classifiers are preferred. They are less employed in survival analysis due to censoring which prevents them from directly being used to survival data. Among the few work that employed machine learning classifiers, partial logistic artificial neural network with auto-relevance determination is a well-known method that deals with censoring and perform feature selection for survival data. However, it depends on data replication to handle censoring which leads to unbalanced and biased prediction results especially in highly censored data. Other methods cannot deal with high censoring. Therefore, in this article, a new hybrid feature selection method is proposed which presents a solution to high level censoring. It combines support vector machine, neural network, and K-nearest neighbor classifiers using simple majority voting and a new weighted majority voting method based on survival metric to construct a multiple classifier system. The new hybrid feature selection process uses multiple classifier system as a wrapper method and merges it with iterated feature ranking filter method to further reduce features. Two endovascular aortic repair datasets containing 91% censored patients collected from two centers were used to construct a multicenter study to evaluate the performance of the proposed approach. The results showed the proposed technique outperformed individual classifiers and variable selection methods based on Cox's model such as Akaike and Bayesian information criterions and least absolute shrinkage and selector operator in p values of the log-rank test, sensitivity, and concordance index. This indicates that the proposed classifier is more powerful in correctly predicting the risk of re-intervention enabling doctor in selecting patients' future follow-up plan

Identifying which septic patients have increased mortality risk using severity scores:a cohort study

Background: Early aggressive therapy can reduce the mortality associated with severe sepsis but this relies on prompt recognition, which is hindered by variation among published severity criteria. Our aim was to test the performance of different severity scores in predicting mortality among a cohort of hospital inpatients with sepsis. Methods: We anonymously linked routine outcome data to a cohort of prospectively identified adult hospital inpatients with sepsis, and used logistic regression to identify associations between mortality and demographic variables, clinical factors including blood culture results, and six sets of severity criteria. We calculated performance characteristics, including area under receiver operating characteristic curves (AUROC), of each set of severity criteria in predicting mortality. Results: Overall mortality was 19.4% (124/640) at 30 days after sepsis onset. In adjusted analysis, older age (odds ratio 5.79 (95% CI 2.87-11.70) for ≥80y versus <60y), having been admitted as an emergency (OR 3.91 (1.31-11.70) versus electively), and longer inpatient stay prior to sepsis onset (OR 2.90 (1.41-5.94) for >21d versus <4d), were associated with increased 30 day mortality. Being in a surgical or orthopaedic, versus medical, ward was associated with lower mortality (OR 0.47 (0.27-0.81) and 0.26 (0.11-0.63), respectively). Blood culture results (positive vs. negative) were not significantly association with mortality. All severity scores predicted mortality but performance varied. The CURB65 community-acquired pneumonia severity score had the best performance characteristics (sensitivity 81%, specificity 52%, positive predictive value 29%, negative predictive value 92%, for 30 day mortality), including having the largest AUROC curve (0.72, 95% CI 0.67-0.77). Conclusions: The CURB65 pneumonia severity score outperformed five other severity scores in predicting risk of death among a cohort of hospital inpatients with sepsis. The utility of the CURB65 score for risk-stratifying patients with sepsis in clinical practice will depend on replicating these findings in a validation cohort including patients with sepsis on admission to hospital

Aquatic food security:insights into challenges and solutions from an analysis of interactions between fisheries, aquaculture, food safety, human health, fish and human welfare, economy and environment

Fisheries and aquaculture production, imports, exports and equitability of distribution determine the supply of aquatic food to people. Aquatic food security is achieved when a food supply is sufficient, safe, sustainable, shockproof and sound: sufficient, to meet needs and preferences of people; safe, to provide nutritional benefit while posing minimal health risks; sustainable, to provide food now and for future generations; shock-proof, to provide resilience to shocks in production systems and supply chains; and sound, to meet legal and ethical standards for welfare of animals, people and environment. Here, we present an integrated assessment of these elements of the aquatic food system in the United Kingdom, a system linked to dynamic global networks of producers, processors and markets. Our assessment addresses sufficiency of supply from aquaculture, fisheries and trade; safety of supply given biological, chemical and radiation hazards; social, economic and environmental sustainability of production systems and supply chains; system resilience to social, economic and environmental shocks; welfare of fish, people and environment; and the authenticity of food. Conventionally, these aspects of the food system are not assessed collectively, so information supporting our assessment is widely dispersed. Our assessment reveals trade-offs and challenges in the food system that are easily overlooked in sectoral analyses of fisheries, aquaculture, health, medicine, human and fish welfare, safety and environment. We highlight potential benefits of an integrated, systematic and ongoing process to assess security of the aquatic food system and to predict impacts of social, economic and environmental change on food supply and demand

Charged particle environment of Titan during the T9 flyby

The ion measurements of the Cassini Plasma Spectrometer are presented which were acquired on 26 December 2005, during the T9 flyby at Titan. The plasma flow and magnetic field directions in the distant plasma environment of the moon were distinctly different from the other flybys. The near-Titan environment, dominated by ions of Titan origin, had a split signature, each with different ion composition; the first region was dominated by dense, slow, and cold ions in the 16-19 and 28-40 amu mass range, the second region contained only ions with mass 1 and 2, much less dense and less slow. Magnetospheric ions penetrate marginally into region 1, whereas the region-2 ion population is mixed. A detailed analysis has led us to conclude that the first event was due to the crossing of the mantle of Titan, whereas the second one very likely was a wake crossing. The split indicates the non-convexity of the ion-dominated volume around Titan. Both ion distributions are analysed in detail

Distant X-ray Galaxies: Insights from the Local Population

A full understanding of the origin of the hard X-ray background requires a complete and accurate census of the distant galaxies that produce it. Unfortunately, distant X-ray galaxies tend to be very faint at all wavelengths, which hinders efforts to perform this census. This chapter discusses the insights that can be obtained through comparison of the distant population to local X-ray galaxies, whose properties are well characterized. Such comparisons will ultimately aid investigations into the cosmic evolution of supermassive black holes and their environments.Comment: 19 pages, 10 figures, to appear as Chapter 7 in "Supermassive Black Holes in the Distant Universe" (2004), ed. A. J. Barger, Kluwer Academic Publishers, in pres

Aeroservoelastic modelling and active control of very large wind turbine blades for gust load alleviation.

The increased flexibility of wind turbine blades necessitates not only accurate predictions of the aeroelastic effects, but also requires active control techniques to overcome potentially damaging loadings and oscillations. An aeroservoelastic model, capturing the structural response and the unsteady aerodynamics of very large rotors, will be used to demonstrate the potential of closed-loop load alleviation using aerodynamic control surfaces. The structural model is a geometrically-nonlinear composite beam, which is linearised around equilibrium rotating conditions and coupled with a linearised 3D Unsteady Vortex Lattice Method (UVLM) with prescribed helicoidal wake. This provides a direct higher fidelity solution to BEM for the dynamics of deforming rotors in attached flow conditions. The resulting aeroelastic model is in a state-space formulation suitable for control synthesis. Flaps are modeled directly in the UVLM formulation and LQG controllers are finally designed to reduce fatigue by about 26% in the presence of continuous turbulence. Trade-offs between reducing root-bending moments (RBM) and suppressing the negative impacts on torsion due to flap deployment will also be investigated

An artificial neural network-based rainfall runoff model for improved drainage network modelling

This Presentation is brought to you for free and open access by the City College of New York at CUNY Academic Works. It has been accepted for inclusion in International Conference on Hydroinformatics by an authorized administrator of CUNY Academic Works. For more information, please contact [email protected] th International Conference on Hydroinformatics HIC 2014, New York City, USAModelling rainfall-runoff processes enables hydrologists to plan their response to flooding events. Urban drainage catchment modelling requires rainfall-runoff models as a prerequisite. In the UK, one of the main software tools used for drainage modelling is InfoWorks CS, based on relatively simple methods which are relatively robust in predicting runoff. This paper presents an alternative approach to modelling runoff that will allow for the complex inter-relation of runoff that occurs from impermeable areas, permeable areas, local surface storage and variation in rainfall induced infiltration. Apart from the uncertainties associated with the measurement of connected surfaces to the drainage system, the physical processes involved in runoff are nonlinear, making artificial neural networks (ANNs) an ideal candidate for modelling them. ANNs have been used for runoff prediction in natural catchments, and recently on a study for predicting the performance of urban drainage systems. This study seeks to determine an input set that predicts sewerage flow in urban catchments where the runoff is dominated by infiltration, a major issue for the water industry. A framework is proposed in which an ANN is trained by an evolutionary algorithm, which optimises ANN weights; results are assessed using the Nash-Sutcliffe Efficiency Coefficient. The model is demonstrated on a real-world case study site for which rainfall, flow, air temperature and groundwater levels in three boreholes have been measured. Various combinations of these data are used as model inputs, examining a mixture of daily and sub-daily timesteps. The best predictions are generated from daily linearly combined antecedent rainfall and air temperature, although sub-daily information improves the worst-case performance of the model. Although infiltration is affected by groundwater levels, incorporating groundwater into the model does not improve predictions. The proposed ANN model is capable of producing acceptable predictions, thus avoiding many of the uncertainties involved in traditional infiltration modelling

Biodegradable and compostable alternatives to conventional plastics

This article is available open access through the publisher’s website at the link below. Copyright @ 2009 The Royal Society.Packaging waste forms a significant part of municipal solid waste and has caused increasing environmental concerns, resulting in a strengthening of various regulations aimed at reducing the amounts generated. Among other materials, a wide range of oil-based polymers is currently used in packaging applications. These are virtually all non-biodegradable, and some are difficult to recycle or reuse due to being complex composites having varying levels of contamination. Recently, significant progress has been made in the development of biodegradable plastics, largely from renewable natural resources, to produce biodegradable materials with similar functionality to that of oil-based polymers. The expansion in these bio-based materials has several potential benefits for greenhouse gas balances and other environmental impacts over whole life cycles and in the use of renewable, rather than finite resources. It is intended that use of biodegradable materials will contribute to sustainability and reduction in the environmental impact associated with disposal of oil-based polymers. The diversity of biodegradable materials and their varying properties makes it difficult to make simple, generic assessments such as biodegradable products are all ‘good’ or petrochemical-based products are all ‘bad’. This paper discusses the potential impacts of biodegradable packaging materials and their waste management, particularly via composting. It presents the key issues that inform judgements of the benefits these materials have in relation to conventional, petrochemical-based counterparts. Specific examples are given from new research on biodegradability in simulated ‘home’ composting systems. It is the view of the authors that biodegradable packaging materials are most suitable for single-use disposable applications where the post-consumer waste can be locally composted.EPSR