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De Santis A.,INSA | Asner G.P.,Carnegie Institution | Vaughan P.J.,Laboratorio Of Espectro Radiometria Y Teledeteccion Ambiental Cchs Csic | Knapp D.E.,Carnegie Institution
Remote Sensing of Environment | Year: 2010

Uncertainties in burning efficiency (BE) estimates can lead to large errors in fire emission quantification (from 23% to 46%). One of the main causes of these errors is the spatial variability of fuel consumption within burned areas. This paper studies whether burn severity (BS) maps can be used to improve BE assessment. A burn severity map of two large fires in California was obtained by inverting a simulation model constrained by post-fire observations from Landsat TM imagery. Model output values of BS were validated against field measurements, obtaining a high correlation (R2 = 0.85) and low errors (Root Mean Square Error, RMSE = 0.14) throughout a wide range of BS levels. The BS map obtained was then used to adjust BE reference values per vegetation type found in the area before the fire. The adjusted burning efficiency (BEadj) was compared to the burned biomass, which was estimated by subtracting vegetation indices from pre- and post-fire images. Results showed a high correlation for conifers (R2 = 0.75) and hardwoods (R2 = 0.73), and a moderate correlation (R2 ∼ 0.5) for shrubs and grasslands. In general, for all vegetation types BEadj performed better (R2 = 0.4-0.75) than literature-based BE (R2 < 0.0001). This study demonstrates: (i) the consistency of the simulation model inversion for BS estimation in temperate ecosystems, and (ii) the improvement of BE estimation when the spatial variability of the combustion was quantified in terms of BS. © 2010 Elsevier Inc. All rights reserved. Source


Valcarce A.,TriaGnoSys GmbH | Wagen J.-F.,BME | Gorce J.-M.,INSA
IEEE Vehicular Technology Magazine | Year: 2011

Owing to its direct applicability in solving problems of the telecommunications industry, propagation prediction for a long time has been an important area of research and development. Because of the increasing complexity of wireless networks, growing number of smaller cells, and higher intercell interference, software tools that aid in network optimization are necessary. Therefore, in the study of particular environments, where wireless networks are deployed, deterministic propagation models play an important role. © 2011 IEEE. Source


Seguy S.,INSA | Insperger T.,Budapest University of Technology and Economics | Arnaud L.,National Engineering School of Tarbes | Dessein G.,National Engineering School of Tarbes | Peigne G.,Ecole Centrale Nantes
International Journal of Advanced Manufacturing Technology | Year: 2010

Spindle speed variation is a well-known technique to suppress regenerative machine tool vibrations, but it is usually considered to be effective only for low spindle speeds. In this paper, the effect of spindle speed variation is analyzed in the high-speed domain for spindle speeds corresponding to the first flip (period doubling) and to the first Hopf lobes. The optimal amplitudes and frequencies of the speed modulations are computed using the semidiscretization method. It is shown that period doubling chatter can effectively be suppressed by spindle speed variation, although, the technique is not effective for the quasiperiodic chatter above the Hopf lobe. The results are verified by cutting tests. Some special cases are also discussed where the practical behavior of the system differs from the predicted one in some ways. For these cases, it is pointed out that the concept of stability is understood on the scale of the principal period of the system-that is, the speed modulation period for variable spindle speed machining and the tooth passing period for constant spindle speed machining. © 2009 Springer-Verlag London Limited. Source


Boryczko K.,Rzeszow University of Technology | Piegdon I.,Rzeszow University of Technology | Eid M.,INSA
Safety, Reliability and Risk Analysis: Beyond the Horizon - Proceedings of the European Safety and Reliability Conference, ESREL 2013 | Year: 2014

At present, many types of software based on high performing models are available in the field of risk analysis. RENO software tool is a powerful and friendly-user platform for building and running complex risk analysis. It can handle a large set of probabilistic and deterministic scenarios using an intuitive flowchart modeling approach and simulation. The paper proposes a method to perform probabilistic risk analysis for Collective Water Supply System (CWSS), using RENO software. Examples are illustrated with flowcharting models. Simulations are used to estimate the reliability of the CWSS. The examples are academic so that they could be verified analytically and demonstrate the simulation capabilities of RENO software. © 2014 Taylor & Francis Group, London. Source


Veras R.P.,Federal University of Campina Grande | Laime E.M.O.,Federal University of Campina Grande | Fernandes P.D.,INSA | Soares F.A.L.,Federal University of Campina Grande | Freire E.A.,Federal University of Campina Grande
Revista Brasileira de Engenharia Agricola e Ambiental | Year: 2011

The jatropha (Jatropha curcas L.) is an oleaginous plant, adapted to the brazilian semiarid conditions, with potentialities to produce biodiesel. Aiming to evaluate its growth and production parameters, an experiment was carried out in drainage lysimeters, between January/2009 and January/2010, in the experimental area of the Academic Unit of Agricultural Engineering of CTRN/UFCG. The effects of the saline irrigation water were studied on the growth and seed yield of jatropha. The treatments consisted of five levels of electrical conductivity of irrigation water (ECw: 0.6; 1.8; 3.0; 4.2 and 5.4 dS m-1), distributed in a completely randomized block design with four replications, being the plot constituted by one plant grown in each lysimeter. The study started on the 210 day up to 360 days after transplanting; at the end of the period, plant height and stem diameter were not significantly affected by salinity of irrigation treatments. On the other hand, the seed production was significantly affected, with the largest quantity produced by plants that received irrigation water with the electrical conductivity of 2.28 dS m-1. Source

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