Littérature scientifique sur le sujet « Sensitivity indices, given data, first order indices »
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Articles de revues sur le sujet "Sensitivity indices, given data, first order indices"
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Melese, Abdisa Shiferaw, Oluwole Daniel Makinde, and Legesse Lemecha Obsu. "Mathematical modelling and analysis of coffee berry disease dynamics on a coffee farm." Mathematical Biosciences and Engineering 19, no. 7 (2022): 7349–73. http://dx.doi.org/10.3934/mbe.2022347.
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<abstract><p>This paper focuses on a mathematical model for coffee berry disease infestation dynamics. This model considers coffee berry and vector populations with the interaction of fungal pathogens. In order to gain an insight into the global dynamics of coffee berry disease transmission and eradication on any given coffee farm, the assumption of logistic growth with a carrying capacity reflects the fact that the amount of coffee plants depends on the limited size of the coffee farm. First, we show that all solutions of the chosen model are bounded and non-negative with positive initial data in a feasible region. Subsequently, endemic and disease-free equilibrium points are calculated. The basic reproduction number with respect to the coffee berry disease-free equilibrium point is derived using a next generation matrix approach. Furthermore, the local stability of the equilibria is established based on the Jacobian matrix and Routh Hurwitz criteria. The global stability of the equilibria is also proved by using the Lyapunov function. Moreover, bifurcation analysis is proved by the center manifold theory. The sensitivity indices for the basic reproduction number with respect to the main parameters are determined. Finally, the numerical simulations show the agreement with the analytical results of the model analysis.</p></abstract>
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Younes, Anis, Jabran Zaouali, François Lehmann, and Marwan Fahs. "Sensitivity and identifiability of hydraulic and geophysical parameters from streaming potential signals in unsaturated porous media." Hydrology and Earth System Sciences 22, no. 7 (2018): 3561–74. http://dx.doi.org/10.5194/hess-22-3561-2018.
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Abstract. Fluid flow in a charged porous medium generates electric potentials called streaming potential (SP). The SP signal is related to both hydraulic and electrical properties of the soil. In this work, global sensitivity analysis (GSA) and parameter estimation procedures are performed to assess the influence of hydraulic and geophysical parameters on the SP signals and to investigate the identifiability of these parameters from SP measurements. Both procedures are applied to a synthetic column experiment involving a falling head infiltration phase followed by a drainage phase. GSA is used through variance-based sensitivity indices, calculated using sparse polynomial chaos expansion (PCE). To allow high PCE orders, we use an efficient sparse PCE algorithm which selects the best sparse PCE from a given data set using the Kashyap information criterion (KIC). Parameter identifiability is performed using two approaches: the Bayesian approach based on the Markov chain Monte Carlo (MCMC) method and the first-order approximation (FOA) approach based on the Levenberg–Marquardt algorithm. The comparison between both approaches allows us to check whether FOA can provide a reliable estimation of parameters and associated uncertainties for the highly nonlinear hydrogeophysical problem investigated. GSA results show that in short time periods, the saturated hydraulic conductivity (Ks) and the voltage coupling coefficient at saturation (Csat) are the most influential parameters, whereas in long time periods, the residual water content (θs), the Mualem–van Genuchten parameter (n) and the Archie saturation exponent (na) become influential, with strong interactions between them. The Mualem–van Genuchten parameter (α) has a very weak influence on the SP signals during the whole experiment. Results of parameter estimation show that although the studied problem is highly nonlinear, when several SP data collected at different altitudes inside the column are used to calibrate the model, all hydraulic (Ks,θs,α,n) and geophysical parameters (na,Csat) can be reasonably estimated from the SP measurements. Further, in this case, the FOA approach provides accurate estimations of both mean parameter values and uncertainty regions. Conversely, when the number of SP measurements used for the calibration is strongly reduced, the FOA approach yields accurate mean parameter values (in agreement with MCMC results) but inaccurate and even unphysical confidence intervals for parameters with large uncertainty regions.
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Van Niekerk, Elna, and Luke Sandham. "Visual interpretation of ASTER satellite data, Part 1: Geologic mapping in the Cradle of Humankind World Heritage Site." Suid-Afrikaanse Tydskrif vir Natuurwetenskap en Tegnologie 26, no. 3 (2007): 177–95. http://dx.doi.org/10.4102/satnt.v26i3.132.
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Since the first earth observing satellite was launched in 1972, remote sensing has become a powerful tool in the arsenal of geoscientists. This satellite became known as Landsat 1 and carried the Multispectral Scanner (MSS) delivering imagery at a spatial resolution of 80, and spectral resolution from blue to near infrared. Ongoing satellite and sensor development to the end of the century produced the Landsat Thematic Mapper (TM) with improved spatial and spectral resolution, as well as the SPOT series of satellites delivering the highest spatial but limited spectral resolution. These developments culminated in the SPOT 4 (1998) and Landsat Enhanced Thematic Mapper (1999) sensors. While Landsat ETM in particular provided much improved spatial and spectral resolutions, on the basis of which a large amount of geoscientific remote sensing was conducted world wide, the data did not provide adequate spectral and spatial sensitivity to be optimally effective for geological mapping at the local scale. On 18 December 1999 the Terra platform was launched, carrying five remote sensing instruments, including ASTER (Advanced Space borne Thermal Emission and Reflection Radiometer). ASTER consists of three separate instrument subsystems, each operating in a different spectral region, and using separate optical systems. These are the Visible and Very Near Infrared (VNIR) subsystem with a 15m-spatial resolution, the Short Wave Infrared (SWIR) subsystem with a 30m-spatial resolution and the Thermal Infrared (TIR) subsystem with a 90m-spatial resolution. ASTER effectively offers an improvement on Landsat MSS, Landsat TM, Landsat ETM+ and SPOT spectral and spatial resolutions. Given the paucity of published research on geological remote sensing at the local scale in South Africa, and particularly on the use of ASTER for geological mapping in South Africa, it is imperative that the value of ASTER be investigated. This article reports on the improved detail and scale achieved in the mapping of litho-stratigraphy, geological structures and mining-related features by the visual interpretation of processed ASTER images. ASTER imagery obtained from the EOS website was subjected to a range of image enhancement and analysis techniques including colour composites, band ratios, normalised difference indices, regression and decorrelation, in order to obtain optimal visual interpretability. Eight images thus obtained could be used for visual analysis, and it became evident that litho-stratigraphy, faults, fracture zones and elements of the regional seam system, as well as remnants of mining activities, were readily identifiable. Some of these were in accordance with the most recent and accurate geological map of the area, but many of them had apparently not been mapped. These features were annotated and were verified by field checks. In all cases the accuracy of detection and location from satellite imagery was confirmed on the ground. The improved detail and accuracy obtained by visual interpretation of processed ASTER satellite data for mapping a section of the Cradle of Humankind World Heritage Site demonstrated the potential value of this data for a variety of other geoscience applications. It appears that the improved accuracy can be ascribed jointly to the higher spatial and spectral resolution provided by ASTER data.
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Jafari, Marzieh, and Khaled Akbari. "Global sensitivity analysis approaches applied to parameter selection for numerical model-updating of structures." Engineering Computations 36, no. 4 (2019): 1282–304. http://dx.doi.org/10.1108/ec-08-2018-0336.
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Purpose This paper aims to measure the sensitivity of the structure’s deformation numerical model (NM) related to the various types of the design parameters, which is a suitable method for parameter selection to increase the time of model-updating. Design/methodology/approach In this research, a variance-based sensitivity analysis (VBSA) approach is proposed to measure the sensitivity of NM of structures. In this way, the contribution of measurements of the structure (such as design parameter values and geometry) on the output of NM is studied using first-order and total-order sensitivity indices developed by Sobol’. In this way the generated data set of parameters by considering different distributions such as Gaussian or uniform distribution and different order as input along with, the resulted deformation variables of NM as output has been submitted to the Sobol’ indices estimation procedure. To the verification of VBSA results, a gradient-based sensitivity analysis (SA), which is developed as a global SA method has been developed to measure the global sensitivity of NM then implemented over the NM’s results of a tunnel. Findings Regarding the estimated indices, it has been concluded that the derived deformation functions from the tunnel’s NM usually are non-additive. Also, some parameters have been determined as most effective on the deformation functions, which can be selected for model-updating to avoid a time-consuming process, so those may better to be considered in the group of updating parameters. In this procedure for SA of the model, also some interactions between the selected parameters with other parameters, which are beneficial to be considered in the model-updating procedure, have been detected. In this study, some parameters approximately (27 per cent of the total) with no effect over the all objective functions have been determined to be excluded from the parameter candidates for model-updating. Also, the resulted indices of implemented VBSA were approved during validation by the gradient-based indices. Practical implications The introduced method has been implemented for a circular lined tunnel’s NM, which has been created by Fast Lagrangian Analysis of Continua software. Originality/value This paper plans to apply a statistical method, which is global on the results of the NM of a soil structure by a complex system for parameter selection to avoid the time-consuming model-updating process.
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Rodríguez-Guisado, Esteban, Antonio Ángel Serrano-de la Torre, Eroteida Sánchez-García, Marta Domínguez-Alonso, and Ernesto Rodríguez-Camino. "Development of an empirical model for seasonal forecasting over the Mediterranean." Advances in Science and Research 16 (August 26, 2019): 191–99. http://dx.doi.org/10.5194/asr-16-191-2019.
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Abstract. In the frame of MEDSCOPE project, which mainly aims at improving predictability on seasonal timescales over the Mediterranean area, a seasonal forecast empirical model making use of new predictors based on a collection of targeted sensitivity experiments is being developed. Here, a first version of the model is presented. This version is based on multiple linear regression, using global climate indices (mainly global teleconnection patterns and indices based on sea surface temperatures, as well as sea-ice and snow cover) as predictors. The model is implemented in a way that allows easy modifications to include new information from other predictors that will come as result of the ongoing sensitivity experiments within the project. Given the big extension of the region under study, its high complexity (both in terms of orography and land-sea distribution) and its location, different sub regions are affected by different drivers at different times. The empirical model makes use of different sets of predictors for every season and every sub region. Starting from a collection of 25 global climate indices, a few predictors are selected for every season and every sub region, checking linear correlation between predictands (temperature and precipitation) and global indices up to one year in advance and using moving averages from two to six months. Special attention has also been payed to the selection of predictors in order to guaranty smooth transitions between neighbor sub regions and consecutive seasons. The model runs a three-month forecast every month with a one-month lead time.
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Bürger, G., T. Q. Murdock, A. T. Werner, S. R. Sobie, and A. J. Cannon. "Downscaling Extremes—An Intercomparison of Multiple Statistical Methods for Present Climate." Journal of Climate 25, no. 12 (2012): 4366–88. http://dx.doi.org/10.1175/jcli-d-11-00408.1.
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Abstract Five statistical downscaling methods [automated regression-based statistical downscaling (ASD), bias correction spatial disaggregation (BCSD), quantile regression neural networks (QRNN), TreeGen (TG), and expanded downscaling (XDS)] are compared with respect to representing climatic extremes. The tests are conducted at six stations from the coastal, mountainous, and taiga region of British Columbia, Canada, whose climatic extremes are measured using the 27 Climate Indices of Extremes (ClimDEX; http://www.climdex.org/climdex/index.action) indices. All methods are calibrated from data prior to 1991, and tested against the two decades from 1991 to 2010. A three-step testing procedure is used to establish a given method as reliable for any given index. The first step analyzes the sensitivity of a method to actual index anomalies by correlating observed and NCEP-downscaled annual index values; then, whether the distribution of an index corresponds to observations is tested. Finally, this latter test is applied to a downscaled climate simulation. This gives a total of 486 single and 162 combined tests. The temperature-related indices pass about twice as many tests as the precipitation indices, and temporally more complex indices that involve consecutive days pass none of the combined tests. With respect to regions, there is some tendency of better performance at the coastal and mountaintop stations. With respect to methods, XDS performed best, on average, with 19% (48%) of passed combined (single) tests, followed by BCSD and QRNN with 10% (45%) and 10% (31%), respectively, ASD with 6% (23%), and TG with 4% (21%) of passed tests. Limitations of the testing approach and possible consequences for the downscaling of extremes in these regions are discussed.
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Kanwal, S., M. K. Siddiqui, E. Bonyah, T. S. Shaikh, I. Irshad, and S. Khalid. "Ordering Acyclic Connected Structures of Trees Having Greatest Degree-Based Invariants." Complexity 2022 (March 16, 2022): 1–16. http://dx.doi.org/10.1155/2022/3769831.
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Being building block of data sciences, link prediction plays a vital role in revealing the hidden mechanisms that lead the networking dynamics. Since many techniques depending in vertex similarity and edge features were put forward to rule out many well-known link prediction challenges, many problems are still there just because of unique formulation characteristics of sparse networks. In this study, we applied some graph transformations and several inequalities to determine the greatest value of first and second Zagreb invariant, S K and S K 1 invariants, for acyclic connected structures of given order, diameter, and pendant vertices. Also, we determined the corresponding extremal acyclic connected structures for these topological indices and provide an ordering (with 5 members) giving a sequence of acyclic connected structures having these indices from greatest in decreasing order.
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Upadhyaya, Shruti, and R. Ramsankaran. "Multi-Index Rain Detection: A New Approach for Regional Rain Area Detection from Remotely Sensed Data." Journal of Hydrometeorology 15, no. 6 (2014): 2314–30. http://dx.doi.org/10.1175/jhm-d-14-0006.1.
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Abstract In this article, a new approach called Multi-Index Rain Detection (MIRD) is suggested for regional rain area detection and was tested for India using Kalpana-1 satellite data. The approach was developed based on the following hypothesis: better results should be obtained for combined indices than an individual index. Different combinations (scenarios) were developed by combining six commonly used rain detection indices using AND and OR logical connectives. For the study region, an optimal rain area detection scenario and optimal threshold values of the indices were found through a statistical multi-decision-making technique called the Technique for Order Preference by Similarity Ideal Solution (TOPSIS). The TOPSIS analysis was carried out based on independent categorical statistics like probability of detection, probability of no detection, and Heidke skill score. It is noteworthy that for the first time in literature, an attempt has been made (through sensitivity analysis) to understand the influence of the proportion of rain/no-rain pixels in the calibration/validation dataset on a few commonly used statistics. Thus, the obtained results have been used to identify the above-mentioned independent categorical statistics. Based on the results obtained and the validation carried out with different independent datasets, scenario 8 (TIRt &lt; 260 K and TIRt − WVt &lt; 19 K, where TIRt and WVt are the brightness temperatures from thermal IR and water vapor, respectively) is found to be an optimal rain detection index. The obtained results also indicate that the texture-based indices [standard deviation and mean of 5 × 5 pixels at time t (mean5)] did not perform well, perhaps because of the coarse resolution of Kalpana-1 data. It is also to be noted that scenario 8 performs much better than the Roca method used in the Indian National Satellite (INSAT) Multispectral Rainfall Algorithm (IMSRA) developed for India.
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Razmyan, S., and F. Hosseinzadeh Lotfi. "An Application of Monte-Carlo-Based Sensitivity Analysis on the Overlap in Discriminant Analysis." Journal of Applied Mathematics 2012 (2012): 1–14. http://dx.doi.org/10.1155/2012/315868.
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Discriminant analysis (DA) is used for the measurement of estimates of a discriminant function by minimizing their group misclassifications to predict group membership of newly sampled data. A major source of misclassification in DA is due to the overlapping of groups. The uncertainty in the input variables and model parameters needs to be properly characterized in decision making. This study combines DEA-DA with a sensitivity analysis approach to an assessment of the influence of banks’ variables on the overall variance in overlap in a DA in order to determine which variables are most significant. A Monte-Carlo-based sensitivity analysis is considered for computing the set of first-order sensitivity indices of the variables to estimate the contribution of each uncertain variable. The results show that the uncertainties in the loans granted and different deposit variables are more significant than uncertainties in other banks’ variables in decision making.
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Del Corso, Giulio, Roberto Verzicco, and Francesco Viola. "Sensitivity analysis of an electrophysiology model for the left ventricle." Journal of The Royal Society Interface 17, no. 171 (2020): 20200532. http://dx.doi.org/10.1098/rsif.2020.0532.
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Modelling the cardiac electrophysiology entails dealing with the uncertainties related to the input parameters such as the heart geometry and the electrical conductivities of the tissues, thus calling for an uncertainty quantification (UQ) of the results. Since the chambers of the heart have different shapes and tissues, in order to make the problem affordable, here we focus on the left ventricle with the aim of identifying which of the uncertain inputs mostly affect its electrophysiology. In a first phase, the uncertainty of the input parameters is evaluated using data available from the literature and the output quantities of interest (QoIs) of the problem are defined. According to the polynomial chaos expansion, a training dataset is then created by sampling the parameter space using a quasi-Monte Carlo method whereas a smaller independent dataset is used for the validation of the resulting metamodel. The latter is exploited to run a global sensitivity analysis with nonlinear variance-based indices and thus reduce the input parameter space accordingly. Thereafter, the uncertainty probability distribution of the QoIs are evaluated using a direct UQ strategy on a larger dataset and the results discussed in the light of the medical knowledge.
Thèses sur le sujet "Sensitivity indices, given data, first order indices"
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GIOIA, PAOLA. "Towards more accurate measures of global sensitivity analysis. Investigation of first and total order indices." Doctoral thesis, Università degli Studi di Milano-Bicocca, 2013. http://hdl.handle.net/10281/45695.
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A new technique for estimating variance–based total sensitivity indices from given data is developed. It is also develped a new approach for the estimation of the first order effects given a specific sample design. This method adopts the RBD approach published by Tarantola et al., (2007) for the computation of first order sensitivity indices in association to Quasi–Random numbers.
Chapitres de livres sur le sujet "Sensitivity indices, given data, first order indices"
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Ahamer, Gilbert, and Karl A. Kumpfmüller. "Education and Literature for Development in Responsibility." In Handbook of Research on Transnational Higher Education. IGI Global, 2014. http://dx.doi.org/10.4018/978-1-4666-4458-8.ch027.
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In order to propose quality assurance for cutting-edge transnational higher education management, this chapter first analyzes data on academic developmental journals while making use of the three widely known literature databases ISI Thomson, Scopus, and Google Scholar; the latter analyzed by the software Publish or Perish (PoP). Time series of data for documents and their citations provide indices; this chapter provides as most helpful indices the ISI impact factor, Scopus SNIP, and PoP AW index. A dozen of the most influential developmental journals are heuristically ranked by taking into account all available indices from all three literature databases. The series of historic bibliometric data since the 1950s shows the dynamics of the global emergence of developmental journals and developmental thought. Secondly, and as a possible template for similar initiatives in global higher education management, this chapter presents the recently established “Global Studies” (GS) Master’s curriculum at Graz University, Austria. Details on this novel curriculum’s targets, modules, courses, and practicals are given. GS embraces six modules and courses from different schools at university. Emphasis is placed on dialogic interdisciplinary understanding and interparadigmatic integration of multiple disciplines and perspectives, when managing education for the purpose of responsibly hedging and managing globalization and socio-economic global change in responsible partnership.
Actes de conférences sur le sujet "Sensitivity indices, given data, first order indices"
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Osborn, Mark, and LiJie Yu. "Decision Support for Remote Monitoring and Diagnostics of Aircraft Engine Using Influence Diagrams." In ASME Turbo Expo 2007: Power for Land, Sea, and Air. ASMEDC, 2007. http://dx.doi.org/10.1115/gt2007-28331.
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FAA regulations require the monitoring of all commercial aircraft engines to ensure airworthiness. In doing so, it provides economic advantages to engine owners to monitor engine performance and resolve identified issues in a timely manner to reduce operational costs or avoid secondary damage. Various remote monitoring and diagnostics service providers exist in the marketplace. However, a common understanding among most of them is that given limited time and information, it is an extremely difficult task to make quick and optimized decisions. Difficulties arise from the fact that an aircraft engine is a complex system and demands considerable expertise to diagnose, but also due to the uncertainty in estimating an engine’s true physical state because of measurement and process noise. Therefore, it is often difficult to decide what action to take in order to achieve the most desirable outcome. In this paper, a cost sensitive engine diagnostic and decision making methodology is described. Diagnostic tool performance at various decision thresholds is estimated over a large set of validated historical cases to evaluate sensitivity, specificity and other quality indices. These quality indices and a set of cost functions are utilized in influence diagrams to derive the optimized decision model in order to minimize costs given the uncertain engine condition and noisy parametric data.
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Jayaraman, Buvana, Manas Khurana, Andrew Wissink, and Rohit Jain. "Uncertainty Quantification Approach for Rotorcraft Simulations." In Vertical Flight Society 78th Annual Forum & Technology Display. The Vertical Flight Society, 2022. http://dx.doi.org/10.4050/f-0078-2022-17462.
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The goal of this work is to quantify the uncertainty and sensitivity of freestream velocity and wind direction on wing download and rotor thrust predictions for the Joint Vertical Experiment (JVX) tiltrotor configuration in hover. Even light winds can have a significant impact on hover performance. Accordingly, an accurate representation of hover performance with uncertainties due to variability in atmospheric wind conditions needs to be understood. To support this effort, mid-fidelity simulations with a Reduced Order Aerodynamic Model in CREATETM-AV Helios is used to generate training and testing data for constructing the surrogate models. Uncertainty propagation is facilitated using a surrogate-based approach which integrates stochastic expansions based non-intrusive polynomial chaos method in the Dakota�environment. The first test case considers wind velocity and directions treated as epistemic uncertain variables. Post uncertainty analysis, parameter sensitivities are established using Sobol indices to rank the relative contribution of input parameters to the total uncertainty in download and thrust. Sensitivity analysis showed that the interaction of wind velocity and direction has the largest influence on download predictions. The second case includes collective as an uncertain input and additionally carries out a sensitivity analysis. Computed Sobol indices identified collective as the major contributor of uncertainty. Ultimately, uncertainty quantification procedure laid out in this work can facilitate informed design decisions based on quantifiable data that is formed using validated computational approaches integrated with established data science principles with statistical metrics.
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Davis, Brad, Gregory Langone, and Nicholas Reisweber. "Sensitivity Analysis and Bayesian Calibration of a Holmquist-Johnson-Cook Material Model for Cellular Concrete Subjected to Impact Loading." In ASME 2022 Verification, Validation, and Uncertainty Quantification Symposium. American Society of Mechanical Engineers, 2022. http://dx.doi.org/10.1115/vvs2022-86800.
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Abstract Periodic updates to small caliber weapon systems and projectiles used in military and law enforcement have resulted in consistently increasing material penetration capabilities. With each new generation, ballistics technology outpaces the lifecycle replacement of live-fire training facilities. For this reason, it is necessary to develop and maintain constitutive material models for use in analyzing the effects new threats will have on existing facilities and for designing new training facilities using numerical methods. This project utilizes material testing data to characterize cellular concretes used in the construction of live-fire training facilities with a 13-parameter Holmquist-Johnson-Cook (HJC) concrete constitutive model. Various statistical tools are used in this analysis to successfully describe the importance of each model parameter and quantify their uncertainty. First, Bayesian linear regression was used to calibrate the parameters in the strength and pressure components of the HJC material model given testing data of cellular concrete. These uncertain parameters were then used to construct computer simulations of penetration and perforation experiments that were previously conducted by Collard and Lanham. Then, Latin Hypercube Sampling of the parameter space was used to generate training data for a Gaussian Process surrogate model of the computer simulation. Using the surrogate model, a global variance-based sensitivity analysis of the material model was completed by computing main and total effect Sobol indices. Finally, a Bayesian calibration of the computer simulation based on the physical experiments was conducted to fully characterize the stochastic behavior of the material subjected to perforation impacts. These approaches can be used to inform decision makers about the potential risk associated with existing facilities and by designers of future live fire training facilities.
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Chen, Ray T., William Phillips, Thomasz Jannson, and David Pelka. "Integration of Polymer Waveguides with HOE On GaAs, LiNbO3, Glass And Aluminum Substrates to Provide massive Fan Out (104/node) Optical Interconnects for Computing." In Optical Computing. Optica Publishing Group, 1989. http://dx.doi.org/10.1364/optcomp.1989.pd1.
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In this paper, we report good quality waveguides (loss<ldb/cm) formed from pure gelatin, i.e., gelatin without ammonium dichromate. Pure gelatin solutions with various water to gelatin ratios were spun on top of soda-lime glass (N=1.512 at 632.8nm). When gelatin first goes into aqueous solution the molecules exist as single chains encircled by water molecules. Upon standing at temperatures below 30 °C, solutions containing more than 1% gelatin become rigid through cross linking and exhibit rubber-like mechanical properties. In this work optical waveguides were thus formed. The waveguiding properties were examined through the prism coupling method. The measured effective indices for TE and TM guided waves were the same for each sample. This implies that no birefringence exists in the gelatin layer. The guiding layer index profiles of multi-mode gelatin waveguides were determined by the inverse WKB method commonly used in integrated optics[l]. Graded index profile of a multi-mode waveguide can be accurately determined by IWKB method. Step indices can also be determined through this method with a small deviation at the turning point [2]. The calculated index profile of sample #D1, composed of 15 grams of gelatin, 100 CC water and spun at 100 rpm, is given in Fig.1, curve A. The measured surface index of various samples with different water-gelatin ratios is shown in Fig.2. Surface index variation from 1.522 to 1.543 was observed. Each data point of Fig.2 was determined by the 0th order mode of the corresponding multimode waveguide (total number of modes >10). Since the guiding layer has a step index, the 0th order mode effective index is almost equal to the surface index. The plotted index profiles of the various gelatin waveguides before wet processing demonstrates that the gelatin layer forms a step index layer and the index refraction increases as the gelatin ratio increases.
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Fuglem, Mark, Martin Richard, and Jan Thijssen. "Challenges Implementing ISO 19906 for Probabilistic Assessment of Multi-year Sea Ice Loads on Sloping Structures." In SNAME 11th International Conference and Exhibition on Performance of Ships and Structures in Ice. SNAME, 2014. http://dx.doi.org/10.5957/icetech-2014-154.
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The ISO standard ISO 19906:2010 provides guidance for determining design loads for offshore structures in arctic and sub-arctic regions, using both deterministic and probabilistic approaches. References are provided for models of both first and multi-year ice loads on both vertically-faced and sloping structures. ISO 19906 indicates that consideration should be given to limit stresses at the ice structure interface based on the dominating ice failure mechanisms, limit forces associated with the available driving force that can act on the interacting ice floe due to wind, currents and surrounding ice, and the kinetic energy of the impacting feature. Analyses show that the kinetic energy of an impacting multi-year floe driven by surrounding ice will result in larger loads than those from driving forces alone. In order to determine penetrations and maximum loads, it is then necessary to consider the variation in load with penetration during an impact. In the case of multi-year ice loads on sloping structures, full-scale data to properly validate models is lacking. Several models are available that estimate maximum loads for level ice interactions with sloping structures. These models can partially account for rubble forming on the structure during the interaction thereby increasing loads, though the ability to estimate rubble heights for different structure shapes and ice conditions at present is limited. In the case of multi-year ridges, several models are available that estimate the maximum load during the interaction of a prismatic beam shaped ridge contacting a conical structure. Data and model for loads from more realistic multi-year ridge shapes are lacking. Additionally, the influence of rubble existing on the structure at the time the ridge impacts is not explicitly considered. This paper examines issues in determining probabilistic design loads for multi-year interactions with sloping structures and presents sensitivity results for key assumptions and parameters. The analyses were carried out using the Sea Ice Loads Software (SILS) developed by C-CORE as part of a Joint Industry Project (JIP) to implement ice load models referenced in ISO 19906 within a probabilistic framework for the purpose of determining design loads. Interpretation was required where ISO 19906 does not provide explicit details on the models and probabilistic implementation. Monte-Carlo simulation was selected for carrying out probabilistic calculations of design loads as this approach is robust.
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Parunov, Josˇko, Paulo Mage, and C. Guedes Soares. "Hull-Girder Reliability of an Aged Oil Tanker." In ASME 2008 27th International Conference on Offshore Mechanics and Arctic Engineering. ASMEDC, 2008. http://dx.doi.org/10.1115/omae2008-57183.
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The aim of the paper is to assess the hull-girder reliability of an existing single-hull oil tanker after 25 years of service using a reliability method and assumptions very similar to those proposed recently by International Maritime Organization (IMO). The evaluation of the wave-induced load effects that occur during long-term operation of the ship in the seaway is carried out in accordance with the International Association of Classification Societies (IACS)-recommended procedure, while transfer functions are calculated using the linear strip theory. The still-water loads are defined on the basis of statistical analysis of data recorded on single-hull oil tankers. The ultimate collapse bending moment of the midship cross section, which is used as the basis for the reliability formulation, is evaluated by progressive collapse analysis and by a single-step procedure according to Common Structural Rules (CSR). The reliability analysis is performed for three states of the hull: as built ship with scantlings of the new ship, CSR corroded state with net thicknesses of the structural members according to the corrosion deduction thickness proposed by CSR and survey state with scantlings according to the thickness measurements after 25 years of service. The yearly probability of structural failure is calculated using the first-order reliability method, while sensitivity analysis and a parametric study are performed to investigate the variability of the results with changes of the random variables within their plausible ranges. Results of the analysis are compared with recommended target reliability indices proposed by IMO and also with the results of the reliability assessment of the new double-hull tanker. Such comparison is possible since similar reliability methods and uncertainty models are employed. Results of the analysis may have several useful applications related to the decision-making aspects of the future of an aged oil tanker.