Academic literature on the topic 'Locally parametric methods'
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Journal articles on the topic "Locally parametric methods"
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Penev, Spiridon, and Kanta Naito. "Locally robust methods and near-parametric asymptotics." Journal of Multivariate Analysis 167 (September 2018): 395–417. http://dx.doi.org/10.1016/j.jmva.2018.06.006.
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Cheng, Ming-Yen, Edwin Choi, Jianqing Fan, and Peter Hall. "Skewing Methods for Two-Parameter Locally Parametric Density Estimation." Bernoulli 6, no. 1 (February 2000): 169. http://dx.doi.org/10.2307/3318637.
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A. Hamad, Sarwar, and Kawa S. Mohamed Ali. "A Comparative Study of Nearest Neighbor Regression and Nadaraya Watson Regression." Academic Journal of Nawroz University 10, no. 2 (May 24, 2021): 180–88. http://dx.doi.org/10.25007/ajnu.v10n2a505.
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Two non-parametric statistical methods are studied in this work. These are the nearest neighbor regression and the Nadaraya Watson kernel smoothing technique. We have proven that under a precise circumstance, the nearest neighborhood estimator and the Nadaraya Watson smoothing produce a smoothed data with a same error level, which means they have the same performance. Another result of the paper is that nearest neighborhood estimator performs better locally, but it graphically shows a weakness point when a large data set is considered on a global scale.
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Bolešová, Mária, Katarína Gajdošová, and Marek Čuhák. "Reconstruction Effectiveness of Locally Supported Flat Slabs to Increase in Shear Resistance." Solid State Phenomena 309 (August 2020): 246–51. http://dx.doi.org/10.4028/www.scientific.net/ssp.309.246.
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The most used horizontal load-bearing systems in concrete buildings are flat slabs. The effective and economic reconstruction of a locally supported flat slab of an existing building creates a complex task. Shear stress arises near the column and it becomes critical in design with increasing slab slenderness and requires a more detailed calculation. Increasing in the shear resistance of the flat slab can be achieved in various ways. Each method brings different effectiveness, advantages and disadvantages. The most widely used methods of the reconstruction are the increase in the size of the column (therein increasing the control perimeter for displaying the shear stress), the increase in the thickness of the flat slab or reinforcing the slab with shear reinforcement. Bolts and screw anchors (using different mounting angles) can be used as shear reinforcement. Each mentioned reconstruction method should be subjected to numerical calculations and verification of its efficiency. The parametric study presented in this paper is focused on the reconstruction techniques and their verification according to various numerical models. The results from Eurocode 2, fib Model Code 2010 and the new generation of Eurocode 2 are compared to show the differences between them. The aim of this paper is to bring a demonstration of the reconstruction methods that will increase in the shear resistance of the locally supported flat slabs and trying to choose the most effective one.
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Yu, Xu, Jun-yu Lin, Feng Jiang, Jun-wei Du, and Ji-zhong Han. "A Cross-Domain Collaborative Filtering Algorithm Based on Feature Construction and Locally Weighted Linear Regression." Computational Intelligence and Neuroscience 2018 (2018): 1–12. http://dx.doi.org/10.1155/2018/1425365.
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Cross-domain collaborative filtering (CDCF) solves the sparsity problem by transferring rating knowledge from auxiliary domains. Obviously, different auxiliary domains have different importance to the target domain. However, previous works cannot evaluate effectively the significance of different auxiliary domains. To overcome this drawback, we propose a cross-domain collaborative filtering algorithm based on Feature Construction and Locally Weighted Linear Regression (FCLWLR). We first construct features in different domains and use these features to represent different auxiliary domains. Thus the weight computation across different domains can be converted as the weight computation across different features. Then we combine the features in the target domain and in the auxiliary domains together and convert the cross-domain recommendation problem into a regression problem. Finally, we employ a Locally Weighted Linear Regression (LWLR) model to solve the regression problem. As LWLR is a nonparametric regression method, it can effectively avoid underfitting or overfitting problem occurring in parametric regression methods. We conduct extensive experiments to show that the proposed FCLWLR algorithm is effective in addressing the data sparsity problem by transferring the useful knowledge from the auxiliary domains, as compared to many state-of-the-art single-domain or cross-domain CF methods.
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Leppink, Jimmie. "Small numbers are an opportunity, not a problem." Scientia Medica 31, no. 1 (June 30, 2021): e40128. http://dx.doi.org/10.15448/1980-6108.2021.1.40128.
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Aims: outcomes of research in education and training are partly a function of the context in which that study takes place, the questions we ask, and what is feasible. Many questions are about learning, which involves repeated measurements in a particular time window, and the practical context is usually such that offering an intervention to some but not to all learners does not make sense or is unethical. For quality assurance and other purposes, education and training centers may have very locally oriented questions that they seek to answer, such as whether an intervention can be considered effective in their context of small numbers of learners. While the rationale behind the design and outcomes of this kind of studies may be of interest to a much wider community, for example to study the transferability of findings to other contexts, people are often discouraged to report on the outcomes of such studies at conferences or in educational research journals. The aim of this paper is to counter that discouragement and instead encourage people to see small numbers as an opportunity instead of as a problem.Method: a worked example of a parametric and a non-parametric method for this type of situation, using simulated data in the zero-cost Open Source statistical program R version 4.0.5.Results: contrary to the non-parametric method, the parametric method can provide estimates of intervention effectiveness for the individual participant, account for trends in different phases of a study. However, the non-parametric method provides a solution in several situations where the parametric method should be used.Conclusion: Given the costs of research, the lessons to be learned from research, and statistical methods available, small numbers should be considered an opportunity, not a problem.
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Escamilla-Rivera, Celia, Jackson Levi Said, and Jurgen Mifsud. "Performance of non-parametric reconstruction techniques in the late-time universe." Journal of Cosmology and Astroparticle Physics 2021, no. 10 (October 1, 2021): 016. http://dx.doi.org/10.1088/1475-7516/2021/10/016.
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Abstract In the context of a Hubble tension problem that is growing in its statistical significance, we reconsider the effectiveness of non-parametric reconstruction techniques which are independent of prescriptive cosmological models. By taking cosmic chronometers, Type Ia Supernovae and baryonic acoustic oscillation data, we compare and contrast two important reconstruction approaches, namely Gaussian processes (GP) and the Locally weighted Scatterplot Smoothing together with Simulation and extrapolation method (LOESS-Simex or LS). In the context of these methods, besides not requiring a cosmological model, they also do not require physical parameters in their approach to their reconstruction of data (but they do depend on statistical hyperparameters). We firstly show how both GP and LOESS-Simex can be used to successively reconstruct various data sets to a high level of precision. We then directly compare both approaches in a quantitative manner by considering several factors, such as how well the reconstructions approximate the data sets themselves to how their respective uncertainties evolve. In light of the puzzling Hubble tension, it is important to consider how the uncertain regions evolve over redshift and the methods compare for estimating cosmological parameters at current times. For cosmic chronometers and baryonic acoustic oscillation compiled data sets, we find that GP generically produce smaller variances for the reconstructed data with a minimum value of σGP-min = 1.1, while the situation for LS is totally different with a minimum of σLS-min = 50.8. Moreover, some of these characteristics can be alleviate at low z, where LS presents less underestimation in comparison to GP.
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Bhardwaj, Divya, Archya Dasgupta, Daniel DiCenzo, Stephen Brade, Kashuf Fatima, Karina Quiaoit, Maureen Trudeau, et al. "Early Changes in Quantitative Ultrasound Imaging Parameters during Neoadjuvant Chemotherapy to Predict Recurrence in Patients with Locally Advanced Breast Cancer." Cancers 14, no. 5 (February 28, 2022): 1247. http://dx.doi.org/10.3390/cancers14051247.
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Background: This study was conducted to explore the use of quantitative ultrasound (QUS) in predicting recurrence for patients with locally advanced breast cancer (LABC) early during neoadjuvant chemotherapy (NAC). Methods: Eighty-three patients with LABC were scanned with 7 MHz ultrasound before starting NAC (week 0) and during treatment (week 4). Spectral parametric maps were generated corresponding to tumor volume. Twenty-four textural features (QUS-Tex1) were determined from parametric maps acquired using grey-level co-occurrence matrices (GLCM) for each patient, which were further processed to generate 64 texture derivatives (QUS-Tex1-Tex2), leading to a total of 95 features from each time point. Analysis was carried out on week 4 data and compared to baseline (week 0) data. ∆Week 4 data was obtained from the difference in QUS parameters, texture features (QUS-Tex1), and texture derivatives (QUS-Tex1-Tex2) of week 4 data and week 0 data. Patients were divided into two groups: recurrence and non-recurrence. Machine learning algorithms using k-nearest neighbor (k-NN) and support vector machines (SVMs) were used to generate radiomic models. Internal validation was undertaken using leave-one patient out cross-validation method. Results: With a median follow up of 69 months (range 7–118 months), 28 patients had disease recurrence. The k-NN classifier was the best performing algorithm at week 4 with sensitivity, specificity, accuracy, and area under curve (AUC) of 87%, 75%, 81%, and 0.83, respectively. The inclusion of texture derivatives (QUS-Tex1-Tex2) in week 4 QUS data analysis led to the improvement of the classifier performances. The AUC increased from 0.70 (0.59 to 0.79, 95% confidence interval) without texture derivatives to 0.83 (0.73 to 0.92) with texture derivatives. The most relevant features separating the two groups were higher-order texture derivatives obtained from scatterer diameter and acoustic concentration-related parametric images. Conclusions: This is the first study highlighting the utility of QUS radiomics in the prediction of recurrence during the treatment of LABC. It reflects that the ongoing treatment-related changes can predict clinical outcomes with higher accuracy as compared to pretreatment features alone.
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Noh, Yung-Kyun, Masashi Sugiyama, Song Liu, Marthinus C. du Plessis, Frank Chongwoo Park, and Daniel D. Lee. "Bias Reduction and Metric Learning for Nearest-Neighbor Estimation of Kullback-Leibler Divergence." Neural Computation 30, no. 7 (July 2018): 1930–60. http://dx.doi.org/10.1162/neco_a_01092.
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Nearest-neighbor estimators for the Kullback-Leiber (KL) divergence that are asymptotically unbiased have recently been proposed and demonstrated in a number of applications. However, with a small number of samples, nonparametric methods typically suffer from large estimation bias due to the nonlocality of information derived from nearest-neighbor statistics. In this letter, we show that this estimation bias can be mitigated by modifying the metric function, and we propose a novel method for learning a locally optimal Mahalanobis distance function from parametric generative models of the underlying density distributions. Using both simulations and experiments on a variety of data sets, we demonstrate that this interplay between approximate generative models and nonparametric techniques can significantly improve the accuracy of nearest-neighbor-based estimation of the KL divergence.
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Feldmann, Kira, Michael Scheuerer, and Thordis L. Thorarinsdottir. "Spatial Postprocessing of Ensemble Forecasts for Temperature Using Nonhomogeneous Gaussian Regression." Monthly Weather Review 143, no. 3 (February 27, 2015): 955–71. http://dx.doi.org/10.1175/mwr-d-14-00210.1.
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Abstract Statistical postprocessing techniques are commonly used to improve the skill of ensembles from numerical weather forecasts. This paper considers spatial extensions of the well-established nonhomogeneous Gaussian regression (NGR) postprocessing technique for surface temperature and a recent modification thereof in which the local climatology is included in the regression model to permit locally adaptive postprocessing. In a comparative study employing 21-h forecasts from the Consortium for Small Scale Modelling ensemble predictive system over Germany (COSMO-DE), two approaches for modeling spatial forecast error correlations are considered: a parametric Gaussian random field model and the ensemble copula coupling (ECC) approach, which utilizes the spatial rank correlation structure of the raw ensemble. Additionally, the NGR methods are compared to both univariate and spatial versions of the ensemble Bayesian model averaging (BMA) postprocessing technique.
Dissertations / Theses on the topic "Locally parametric methods"
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Rau, Christian, and rau@maths anu edu au. "Curve Estimation and Signal Discrimination in Spatial Problems." The Australian National University. School of Mathematical Sciences, 2003. http://thesis.anu.edu.au./public/adt-ANU20031215.163519.
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In many instances arising prominently, but not exclusively, in imaging problems, it is important to condense the salient information so as to obtain a low-dimensional approximant of the data. This thesis is concerned with two basic situations which call for such a dimension reduction. The first of these is the statistical recovery of smooth edges in regression and density surfaces. The edges are understood to be contiguous curves, although they are allowed to meander almost arbitrarily through the plane, and may even split at a finite number of points to yield an edge graph. A novel locally-parametric nonparametric method is proposed which enjoys the benefit of being relatively easy to implement via a `tracking' approach. These topics are discussed in Chapters 2 and 3, with pertaining background material being given in the Appendix. In Chapter 4 we construct concomitant confidence bands for this estimator, which have asymptotically correct coverage probability. The construction can be
likened to only a few existing approaches, and may thus be considered as our main contribution.
¶
Chapter 5 discusses numerical issues pertaining to the edge and confidence band estimators of Chapters 2-4. Connections are drawn to popular topics which originated in the fields of computer vision and signal processing, and which surround edge detection. These connections are exploited so as to obtain greater robustness of the likelihood estimator, such as with the presence of sharp corners.
¶
Chapter 6 addresses a dimension reduction problem for spatial data where the ultimate objective of the analysis is the discrimination of these data into one of a few pre-specified groups. In the dimension reduction step, an instrumental role is played by the recently
developed methodology of functional data analysis. Relatively standar non-linear image processing techniques, as well as wavelet shrinkage, are used prior to this step. A case study for remotely-sensed navigation radar data exemplifies the methodology of Chapter 6.
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Yee, Irene Mei Ling. "Local parametric poisson models for fisheries data." Thesis, University of British Columbia, 1988. http://hdl.handle.net/2429/28360.
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Poisson process is a common model for count data. However, a global Poisson model is inadequate for sparse data such as the marked salmon recovery data that have huge extraneous variations and noise. An empirical Bayes model, which enables information to be aggregated to overcome the lack of information from data in individual cells, is thus developed to handle these data. The method fits a local parametric Poisson model to describe the variation at each sampling period and incorporates this approach with a conventional local smoothing technique to remove noise. Finally, the overdispersion relative to the Poisson model is modelled by mixing these locally smoothed, Poisson models in an appropriate way. This method is then applied to the marked salmon data to obtain the overall patterns and the corresponding credibility intervals for the underlying trend in the data.Science, Faculty of
Statistics, Department of
Graduate
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Mays, James Edward. "Model robust regression: combining parametric, nonparametric, and semiparametric methods." Diss., Virginia Polytechnic Institute and State University, 1995. http://hdl.handle.net/10919/49937.
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In obtaining a regression fit to a set of data, ordinary least squares regression depends directly on the parametric model formulated by the researcher. If this model is incorrect, a least squares analysis may be misleading. Alternatively, nonparametric regression (kernel or local polynomial regression, for example) has no dependence on an underlying parametric model, but instead depends entirely on the distances between regressor coordinates and the prediction point of interest. This procedure avoids the necessity of a reliable model, but in using no information from the researcher, may fit to irregular patterns in the data. The proper combination of these two regression procedures can overcome their respective problems. Considered is the situation where the researcher has an idea of which model should explain the behavior of the data, but this model is not adequate throughout the entire range of the data. An extension of partial linear regression and two methods of model robust regression are developed and compared in this context. These methods involve parametric fits to the data and nonparametric fits to either the data or residuals. The two fits are then combined in the most efficient proportions via a mixing parameter. Performance is based on bias and variance considerations.Ph. D.
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Žiemelis, Audrius. "Morfologinio daugiareikšminimo statistiniais metodais parametrų tyrimas." Master's thesis, Lithuanian Academic Libraries Network (LABT), 2010. http://vddb.laba.lt/obj/LT-eLABa-0001:E.02~2010~D_20100615_084959-97619.
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Šiame darbe kuriamas įrankis, kuris padėtų nustatyti, kurios morfologinės žymos savybės yra svarbios sprendžiant lietuvių kalbos morfologinio daugiareikšmiškumo problemą. Morfologinio daugiareikšmiškumo problema išsprendžiama tuomet, kai pagal kontekstą vienam žodžiui priskiriama viena morfologinė žyma. Darbe naudojamas tekstynas, kurį sudaro daugiau nei 1.200.000 žodžių. Tekstyne žodžiams morfologines žymas nustatė ekspertas, o visos galimos žodžio morfologinės žymos buvo sugeneruotos su pagalbiniu įrankiu. Morfologinio daugiareikšmiškumo problemoms spręsti suprogramuotas ir taikytas Viterbi algoritmas, randantis tikėtiniausią sakinį atitinkančią kalbos dalių seką pagal sukurtus bigramų ar trigramų kalbos modelius. Atlikus testavimą naudojant dešimt kartų kryžminį patikrinimą, pasiekti toki rezultatai: • 90,10% – tikslumas, kuris parodo ar teisingai priskirta morfologinė žyma daugiareikšmiams žodžiams; • 96,39% – bendras tikslumas, kuris skaičiuojamas įtraukiant ir tuos žodžius, kurie turėjo tik vieną morfologinę žymą.In this research was developed tool, which helps to determine, which morphological mark attributes are important when solving problem of morphological ambiguity in Lithuanian language. Morphological ambiguity problem is solved, when one word is matched with one morphological mark. Research uses corpus, which contains over than 1.200.000 words. Morphological marks in the corpus were assigned by expert and list of all possible morphological marks was generated with other utility. There was developed and applied Viterbi algorithm to solve morphological ambiguity problem, which finds the most expected path of part of speeches by created bigram or trigram speech models. Testing was implemented using cross validation with 10 folds. There was achieved these results: • 90,10% – accuracy, which shows if morphological mark was correctly match with ambiguous word; • 96,39% – total accuracy, which calculated when included non-ambiguous words.
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Weining, Wang. "Adaptive methods for risk calibration." Doctoral thesis, Humboldt-Universität zu Berlin, Wirtschaftswissenschaftliche Fakultät, 2012. http://dx.doi.org/10.18452/16585.
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Dieser Artikel enthält vier Kapitel. Das erste Kapitel ist berechtigt, '''' lokalen Quantil Regression"und seine Zusammenfassung: Quantil Regression ist eine Technik, bedingte Quantil Kurven zu schätzen. Es bietet ein umfassendes Bild über ein Antwort-Kontingent auf erklärenden Variablen. In einem Rahmen flexible Modellierung ist eine besondere Form der bedingten Quantil-Kurve nicht von vornherein festgelegt. Dies motiviert eine lokale parametrische anstatt einer globalen feste Modell passend Ansatz. Eine nichtparametrische Glättung Schätzung der bedingte Quantil Kurve erfordert, zwischen lokalen Krümmung und stochastische auszugleichen Variabilität. In den ersten Essay empfehlen wir eine lokale Modellauswahl Technik, die eine adaptive Schätzung der bedingte bietet Quantil-Regression-Kurve bei jedem Entwurf-Punkt. Theoretische Ergebnisse behaupten, dass das vorgeschlagene adaptive Verfahren als führt gut als Orakel die würde das Risiko der lokalen Abschätzung für die Aufgabenstellung minimieren. Wir veranschaulichen die Leistung der Trolle.This article includes four chapters. The first chapter is entitled ``Local Quantile Regression", and its summary: Quantile regression is a technique to estimate conditional quantile curves. It provides a comprehensive picture of a response contingent on explanatory variables. In a flexible modeling framework, a specific form of the conditional quantile curve is not a priori fixed. This motivates a local parametric rather than a global fixed model fitting approach. A nonparametric smoothing estimate of the conditional quantile curve requires to balance between local curvature and stochastic variability. In the first essay, we suggest a local model selection technique that provides an adaptive estimate of the conditional quantile regression curve at each design point. Theoretical results claim that the proposed adaptive procedure performs as good as an oracle which would minimize the local estimation risk for the problem at hand. We illustrate the performance of the procedure by an extensive simulation study and consider a couple of applications: to tail dependence analysis for the Hong Kong stock market and to analysis of the distributions of the risk factors of temperature dynamics.
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Chen, Ying. "Adaptive risk management." Doctoral thesis, Humboldt-Universität zu Berlin, Wirtschaftswissenschaftliche Fakultät, 2007. http://dx.doi.org/10.18452/15581.
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In den vergangenen Jahren ist die Untersuchung des Risikomanagements vom Baselkomitee angeregt, um die Kredit- und Bankwesen regelmäßig zu aufsichten. Für viele multivariate Risikomanagementmethoden gibt es jedoch Beschränkungen von: 1) verlässt sich die Kovarianzschätzung auf eine zeitunabhängige Form, 2) die Modelle beruhen auf eine unrealistischen Verteilungsannahme und 3) numerische Problem, die bei hochdimensionalen Daten auftreten. Es ist das primäre Ziel dieser Doktorarbeit, präzise und schnelle Methoden vorzuschlagen, die diesen Beschränkungen überwinden. Die Grundidee besteht darin, zuerst aus einer hochdimensionalen Zeitreihe die stochastisch unabhängigen Komponenten (IC) zu extrahieren und dann die Verteilungsparameter der resultierenden IC beruhend auf eindimensionale Heavy-Tailed Verteilungsannahme zu identifizieren. Genauer gesagt werden zwei lokale parametrische Methoden verwendet, um den Varianzprozess jeder IC zu schätzen, das lokale Moving Window Average (MVA) Methode und das lokale Exponential Smoothing (ES) Methode. Diese Schätzungen beruhen auf der realistischen Annahme, dass die IC Generalized Hyperbolic (GH) verteilt sind. Die Berechnung ist schneller und erreicht eine höhere Genauigkeit als viele bekannte Risikomanagementmethoden.Over recent years, study on risk management has been prompted by the Basel committee for the requirement of regular banking supervisory. There are however limitations of many risk management methods: 1) covariance estimation relies on a time-invariant form, 2) models are based on unrealistic distributional assumption and 3) numerical problems appear when applied to high-dimensional portfolios. The primary aim of this dissertation is to propose adaptive methods that overcome these limitations and can accurately and fast measure risk exposures of multivariate portfolios. The basic idea is to first retrieve out of high-dimensional time series stochastically independent components (ICs) and then identify the distributional behavior of every resulting IC in univariate space. To be more specific, two local parametric approaches, local moving window average (MWA) method and local exponential smoothing (ES) method, are used to estimate the volatility process of every IC under the heavy-tailed distributional assumption, namely ICs are generalized hyperbolic (GH) distributed. By doing so, it speeds up the computation of risk measures and achieves much better accuracy than many popular risk management methods.
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Pulgar, Germán Mauricio Ibacache. "Modelos mistos aditivos semiparamétricos de contornos elípticos." Universidade de São Paulo, 2009. http://www.teses.usp.br/teses/disponiveis/45/45133/tde-13102009-110415/.
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Neste trabalho estendemos os modelos mistos semiparamétricos propostos por Zhang et al. (1998) para uma classe mais geral de modelos, a qual denominamos modelos mistos aditivos semiparamétricos com erros de contornos elípticos. Com essa nova abordagem, flexibilizamos a curtose da distribuição dos erros possibilitando a escolha de distribuições com caudas mais leves ou mais pesadas do que as caudas da distribuição normal padrão. Funções de verossimilhança penalizadas são aplicadas para a obtenção das estimativas de máxima verossimilhança com os respectivos erros padrão aproximados. Essas estimativas, sob erros de caudas pesadas, são robustas no sentido da distância de Mahalanobis contra observações aberrantes. Curvaturas de influência local são obtidas segundo alguns esquemas de perturbação e gráficos de diagnóstico são propostos. Exemplos ilustrativos são apresentados em que ajustes sob erros normais são comparados, através das metodologias de sensibilidade desenvolvidas no trabalho, com ajustes sob erros de contornos elípticos.In this work we extend the models proposed by Zhang et al. (1998) to a more general class of models, know as semiparametric additive mixed models with elliptical errors in order to allow distributions with heavier or lighter tails than the normal ones. Penalized likelihood equations are applied to derive the maximum likelihood estimates which appear to be robust against outlying observations in the sense of the Mahalanobis distance. In order to study the sensitivity of the penalized estimates under some usual perturbation schemes in the model or data, the local influence curvatures are derived and some diagnostic graphics are proposed. Motivating examples preliminary analyzed under normal errors are reanalyzed under some appropriate elliptical errors. The local influence approach is used to compare the sensitivity of the model estimates.
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Ciomber, Isabelle, and Roland Jakel. "Systematic Analysis and Comparison of Stress Minimizing Notch Shapes : Obtaining a stress concentration factor of Kt=1 without FEM-Code." Universitätsbibliothek Chemnitz, 2014. http://nbn-resolving.de/urn:nbn:de:bsz:ch1-qucosa-141533.
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Als Stand der Technik sind einfache, kreisförmige Verrundungen zur Reduktion von Kerbspannungen an Querschnittsübergängen bekannt, für die aus Tabellenwerken / Diagrammen in der Literatur die Formzahl einfach abgelesen werden kann. Die Effizienz der Spannungsreduktion solcher Lösungen ist jedoch sehr begrenzt. Ziel der Arbeit ist es daher, dem Konstrukteur bzw. Berechnungsingenieur ein Verfahren in die Hand zu geben, mit dem er für Standardquerschnittsübergänge und Standardlastfälle "Nicht-Kreiskerben" ohne teure und zeitaufwendige FEM-Analyse einfach durch Nutzung geeigneter Formzahldiagramme auslegen kann. Dabei sind sogar Formzahlen von nahezu eins möglich, d.h., in der "Kerbe" bleibt praktisch nur noch die Nennspannung übrig. Die Präsentation ist zweitgeteilt: Im ersten Teil werden die Arbeitsmethoden bzw. Softwarefunktionen und verwendeten Softwarewerkzeuge vorgestellt: Dies sind die Programme Creo Parametric als vollparametrisches CAD-Werkzeug und Creo Simulate als p-FEM-Programm der Parametric Technology Coprporation (PTC). Der zweite Teil der Präsentation beschreibt den Gültigkeitsbereich sowie die untersuchten Kerbgeometrien: Die einfache kreisförmige Verrundung als Stand der Technik, die Zwei-Radien-Kerbe, die Baud-Kurve, die Methode der Zugdreiecke nach Claus Mattheck, die elliptische Kerbe sowie die konische Rundung als generalisierte elliptische Kerbe. Es wird kurz eine Bibliothek vorgestellt, mit der solche Kerben einfach ausgelegt werden können, d.h. Ihre exakte Geometrie festgelegt sowie die zugehörige Formzahl αk bestimmt werden kannCircular (one-radius) fillets are known as state-of-the-art for reducing notch stresses at cross section transitions. The stress concentration factor Kt of such geometries can be read out from diagrams/tables given in the literature. However, the efficiency of stress reduction of circular notches is very limited. The goal of the work therefor is to present a method for the designer/analyst how to design non-circular notches/fillets just by using suitable Kt-diagrams without time-consuming and expensive FEM analyses. Kt-numbers of nearly one are possible, that means in the "notch" just the nominal stress appears and no stress concentration takes place. The presentation has two parts: Part one describes the working methods and software functions as well as software tools: Creo Parametric as fully-parametric CAD program and Creo Simulate as embedded p-FEM-tool from Parametric Technology Corporation (PTC) have been used. The second part describes the range of validity and the examined notch geometries: The one-radius fillet as state-of-the-art, the two-radii filet, the Baud-curve, the method of tensile triangles from Claus Mattheck, the standard elliptical fillet and the conical round as generalized elliptical fillet. A notch layout library is shortly presented that allows to design such fillets, that means exactly determine the notch geometry and the related stress concentration factor Kt
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Rau, Christian. "Curve Estimation and Signal Discrimination in Spatial Problems." Phd thesis, 2003. http://hdl.handle.net/1885/48023.
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In many instances arising prominently, but not exclusively, in imaging problems, it is important to condense the salient information so as to obtain a low-dimensional approximant of the data. This thesis is concerned with two basic situations which call for such a dimension reduction. The first of these is the statistical recovery of smooth edges in regression and density surfaces. The edges are understood to be contiguous curves, although they are allowed to meander almost arbitrarily through the plane, and may even split at a finite number of points to yield an edge graph. A novel locally-parametric nonparametric method is proposed which enjoys the benefit of being relatively easy to implement via a `tracking' approach. These topics are discussed in Chapters 2 and 3, with pertaining background material being given in the Appendix. In Chapter 4 we construct concomitant confidence bands for this estimator, which have asymptotically correct coverage probability. The construction can be likened to only a few existing approaches, and may thus be considered as our main contribution. ¶ Chapter 5 discusses numerical issues pertaining to the edge and confidence band estimators of Chapters 2-4. Connections are drawn to popular topics which originated in the fields of computer vision and signal processing, and which surround edge detection. These connections are exploited so as to obtain greater robustness of the likelihood estimator, such as with the presence of sharp corners. ¶ Chapter 6 addresses a dimension reduction problem for spatial data where the ultimate objective of the analysis is the discrimination of these data into one of a few pre-specified groups. In the dimension reduction step, an instrumental role is played by the recently developed methodology of functional data analysis. Relatively standar non-linear image processing techniques, as well as wavelet shrinkage, are used prior to this step. A case study for remotely-sensed navigation radar data exemplifies the methodology of Chapter 6.
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Shen, Jhih-Rong, and 沈智榮. "Parametric Optimization of a Fuzzy System Based on CombinedGlobal and Local Search Methods With Application to Illuminant Estimation." Thesis, 2014. http://ndltd.ncl.edu.tw/handle/73396563076243659404.
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碩士國立中興大學
電機工程學系所
102
Color balance algorithm has become an important part of image processing pipeline. Many high-class digital cameras have built-in sensors which can measure illuminant in real-time and make correction to the captured images. Before color balanced, images will appear to have been shifted towards one color or another, i.e., have color cast. A color balance algorithm is a class of image processing developed to remove color cast. Human eyes are sensitive to the neutral colors of the image. Most color balance algorithm is mainly aimed at these colors to adjust image. Color balance algorithms aiming at white color are known as white balance algorithms. Before doing color balance, one step which is very important and necessary is the color temperature estimation of the image. Doing estimation well, and the system can does color balance more correctly. In this thesis, we propose a color temperature algorithm based on fuzzy inference rules by basic concept of color and the experimental results. In this algorithm, we form color sample database with the images are captured in different illuminants at first. Second, we use clustering results of color sample database to form fuzzy inference system and optimize the system. Third, we use global optimization and local optimization to adjust the parameters of the fuzzy system.
Books on the topic "Locally parametric methods"
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Kesoretskikh, Ivan, and Sergey Zotov. Landscape vulnerability: concept and assessment. ru: INFRA-M Academic Publishing LLC., 2019. http://dx.doi.org/10.12737/1045820.
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The monograph presents a methodology for assessing the vulnerability of landscapes to external influences. A comparative analysis of the concepts of "stability", "sensitivity", "vulnerability" in relation to natural complexes. An overview of existing methods for assessing the vulnerability of natural complexes is presented. The author's method of assessing the vulnerability of landscapes to anthropogenic impacts is described. The methodology is based on: selection and justification of criteria for assessing the vulnerability of landscapes; preparation of a parametric matrix and gradation of assessment criteria in accordance with the developed vulnerability classes; calculation of weighting factors of vulnerability assessment parameters; selection of optimal territorial operational unit for landscape vulnerability assessment. The method is implemented in the GIS environment "Assessment of vulnerability of landscapes of the Kaliningrad region to anthropogenic impacts", created by the authors using modern geoinformation products. The specificity of spatial differentiation of different landscapes in terms of vulnerability to anthropogenic impacts at the regional and local levels is revealed. It is stated that the use of the methodology for assessing the vulnerability of landscapes to anthropogenic impacts and its integration into the system of nature management will ensure a balanced account of geoecological features and environmental priorities in territorial planning.
It is of interest to specialists in the field of rational nature management, environmental protection, spatial planning.
Book chapters on the topic "Locally parametric methods"
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Basu, Sanjib, Sreenivasa Rao Jammalamadaka, and Wei Liu. "Local Posterior Robustness with Parametric Priors: Maximum and Average Sensitivity." In Maximum Entropy and Bayesian Methods, 97–106. Dordrecht: Springer Netherlands, 1996. http://dx.doi.org/10.1007/978-94-015-8729-7_6.
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Starke, Ludger, Karsten Tabelow, Thoralf Niendorf, and Andreas Pohlmann. "Denoising for Improved Parametric MRI of the Kidney: Protocol for Nonlocal Means Filtering." In Methods in Molecular Biology, 565–76. New York, NY: Springer US, 2021. http://dx.doi.org/10.1007/978-1-0716-0978-1_34.
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AbstractIn order to tackle the challenges caused by the variability in estimated MRI parameters (e.g., T2* and T2) due to low SNR a number of strategies can be followed. One approach is postprocessing of the acquired data with a filter. The basic idea is that MR images possess a local spatial structure that is characterized by equal, or at least similar, noise-free signal values in vicinities of a location. Then, local averaging of the signal reduces the noise component of the signal. In contrast, nonlocal means filtering defines the weights for averaging not only within the local vicinity, bur it compares the image intensities between all voxels to define “nonlocal” weights. Furthermore, it generally compares not only single-voxel intensities but small spatial patches of the data to better account for extended similar patterns. Here we describe how to use an open source NLM filter tool to denoise 2D MR image series of the kidney used for parametric mapping of the relaxation times T2* and T2.This chapter is based upon work from the COST Action PARENCHIMA, a community-driven network funded by the European Cooperation in Science and Technology (COST) program of the European Union, which aims to improve the reproducibility and standardization of renal MRI biomarkers.
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Levada, Alexandre L. M., and Michel F. C. Haddad. "A Kullback-Leibler Divergence-Based Locally Linear Embedding Method: A Novel Parametric Approach for Cluster Analysis." In Intelligent Systems, 406–20. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-91702-9_27.
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Ma, Hongbin, Liping Yan, Yuanqing Xia, and Mengyin Fu. "Comparison of Several Filtering Methods for Linear Multi-agent Systems with Local Unknown Parametric Couplings." In Kalman Filtering and Information Fusion, 273–91. Singapore: Springer Singapore, 2019. http://dx.doi.org/10.1007/978-981-15-0806-6_13.
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Song, Jinghua, and Sirui Sun. "Research on Architectural Form Optimization Method Based on Environmental Performance-Driven Design." In Proceedings of the 2020 DigitalFUTURES, 217–28. Singapore: Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-33-4400-6_21.
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AbstractIn the context of contemporary environment and society, the architectural form optimization based on Environmental performance-driven design is a method by using environmental performance data to optimize the architectural form. Its value lies in dealing with the interaction between architecture and environment, and developing architecture with environmental sustainability. This thesis summarizes the similarities and differences between performance-driven form design and traditional bionic form design. The traditional bionic design separates the bionic object from its complex living environment, and its simple imitation tends to fall into the local rather than the global optimum. However, performance-driven design is different from bionic design. It advocates environmental factors as a driving factor rather than a confrontational factor. It is a systematic global optimal method for studying architectural form. This paper puts forward the specific architectural form optimization simulation process based on the performance-driven thought. Taking the multilayer parking building design of the riparian zone on the south bank of Chongqing as an example, the parametric design method is used to obtain architectural optimization form adapted to the environment.
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"2. The locally adapted parametric finite element method for interface problems on triangular meshes." In Fluid-Structure Interaction, 41–68. De Gruyter, 2017. http://dx.doi.org/10.1515/9783110494259-002.
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Ziemianski, Leonard, Bartosz Miller, and Grzegorz Piatkowski. "Application of Neurocomputing to Parametric Identification Using Dynamic Responses." In Intelligent Computational Paradigms in Earthquake Engineering, 362–92. IGI Global, 2007. http://dx.doi.org/10.4018/978-1-59904-099-8.ch015.
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The chapter focuses on the applications of neurocomputing to the analysis of identification problems in structural dynamics, the main attention is paid to back-propagation neural networks. The analysed problems relate to (a) application of dynamic response to parameter identification of structural elements with defects modelled as a local change of stiffness or material loss; (b) updating of FEM models of beams, including the identification of material parameters and parameters describing possible defect; (c) identification of circular void or supplementary mass in vibrating plates; (d) identification of a damage in frame structures using both eigenfrequencies and elements of eigenvectors as input data. In the examples involving the experimental measurements the application of a random noise to increase the not sufficient number of data is proposed. The presented results have proved the proposed method capable of carrying out the appointed task and indicated good prospects of neurocomputing application to dynamics of structures.
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Ghaderi, Abdolsalam. "Investigating of Hybrid Meta-Heuristics to Solve the Large-Scale Multi-Source Weber Problems and Performance Measuring of them with Statistical Tests." In Meta-Heuristics Optimization Algorithms in Engineering, Business, Economics, and Finance, 171–97. IGI Global, 2013. http://dx.doi.org/10.4018/978-1-4666-2086-5.ch006.
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The location–allocation problems are a class of complicated optimization problems that requires finding sites for m facilities and to simultaneously allocate n customers to those facilities to minimize the total transportation costs. Indeed, these problems, belonging to the class NP-hard, have a lot of local optima solutions. In this chapter, three hybrid meta-heuristics: genetic algorithm, variable neighborhood search and particle swarm optimization, and a hybrid local search approach. These are investigated to solve the uncapacitated continuous location-allocation problem (multi-source Weber problem). In this regard, alternate location allocation and exchange heuristics are used to find the local optima of the problem within the framework of hybrid algorithms. In addition, some large-scale problems are employed to measure the effectiveness and efficiency of hybrid algorithms. Obtained results from these heuristics are compared with local search methods and with each other. The experimental results show that the hybrid meta-heuristics produce much better solutions to solve large-scale problems. Moreover, the results of two non-parametric statistical tests detected a significant difference in hybrid algorithms such that the hybrid variable neighborhood search and particle swarm optimization algorithm outperform the others.
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Gomes, Daiana C. S., and Ginalber L. O. Serra. "Methodology for Model-Based Fuzzy Kalman Filter Design via Singular Spectral Analysis of Experimental Data." In Applications of Artificial Intelligence in Electrical Engineering, 51–79. IGI Global, 2020. http://dx.doi.org/10.4018/978-1-7998-2718-4.ch003.
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This chapter presents a methodology for designing of fuzzy Kalman filter (FKF) via spectral decomposition of the experimental data. The adopted methodology consists in the parametric estimation of local state-space linear submodels of a fuzzy model of the dynamic system, by means of a fuzzy algorithm based on least squares, as well as in the estimation of FKF gains from the fuzzy model, using the parallel and distributed compensation (PDC) method. The partitioning of experimental data is performed by the fuzzy C-Means (FCM) clustering algorithm, for the definition of the rule base as well as the nonlinear FKF characteristic. Considering the PDC method, the Kalman gains in the consequent of each FKF rule are updated as a function of the unobservable components resulting from the spectral decomposition of noisy experimental data. Computational and experimental results illustrate the good performance of the methodology presented when compared to relevant approaches from the literature.
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"Sensor Models." In Simultaneous Localization and Mapping for Mobile Robots, 174–202. IGI Global, 2013. http://dx.doi.org/10.4018/978-1-4666-2104-6.ch006.
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This is the second chapter of the second section. Analogously to chapter 5, here the authors study probabilistic models of sensors, which is the second fundamental component of the general Bayesian framework for localization. In this chapter, they explain common mathematical models of sensors, stressing their differences and effects in further estimation techniques, in particular whether they are parametrical or not. The chapter also points out the existence of the association problem between observations and known elements of maps for some kinds of sensors, and presents solutions to that problem. Finally, some methods for matching local maps provided by particular kinds of sensors are also included.
Conference papers on the topic "Locally parametric methods"
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Wang, Charlie C. L., Shiang-Fong Chen, Jin Fan, and Matthew M. F. Yuen. "Two-Dimensional Trimmed Surface Development Using a Physics-Based Model." In ASME 1999 Design Engineering Technical Conferences. American Society of Mechanical Engineers, 1999. http://dx.doi.org/10.1115/detc99/dac-8634.
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Abstract This paper presents a general method for parametric trimmed surface development. Parametric trimmed surface development is primarily used for flattening a 3D surface into a corresponding 2D pattern or surface. This method can be applied in computer aided design, texture mapping, ship building, etc. First, the surface is triangulated and mapped onto a plane. This initial planar mapping has the same topology as its original surface. Then, a spring-mass system is applied to deform the plane. The surface elastic deformation energy distribution is indicated by a color graph, which determines a surface cutting line. The method presented here can efficiently solve development problems for complex trimmed surfaces. Accuracy of a developed surface can easily be controlled locally. Thus, compared to earlier methods, this method provides more flexibility for solving CAD and CAM surfacing problems.
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Toman, Rastislav, and Jan Macek. "Evaluation Study of a Multi-Mode HEV with a Dedicated Hybrid Transmission." In FISITA World Congress 2021. FISITA, 2021. http://dx.doi.org/10.46720/f2020-adm-108.
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The current legislation requires the increasing levels of vehicle powertrain electrification or hybridization to fulfill the limits of green-house gas emissions. Parallel hybrid electric vehicle (HEV) powertrain topologies are among the frequently used layouts, because of their easy applicability on an existing conventional powertrain by the addition of hybrid modules with mild, full, or plug-in capability. A more “HEV-tailored” approach merges a dedicated hybrid transmission (DHT), an ICE, a gearbox, and one or more electric motors more closely together, reducing HEV powertrain’s mechanical complexity and costs. The current paper investigates a multi-mode HEV with a DHT and two electric machines in optional electric serial or parallel operating modes. Great challenge for the multi-mode HEV topology with DHT is the component sizing: ICE, electric machines, and battery with optimized capacity, and yet fulfilling several roles. On one hand, satisfactory responsiveness on a dynamic driving demands (vehicle acceleration capabilities, top speed etc.). On the other hand, energy consumption achieving better levels than standard parallel HEV topologies. The other challenge for a multi-mode HEV powertrain – similarly as for all HEV powertrains – is a development and optimization of a powertrain supervisory control, based on energy management strategy. These challenges – overall DHT layout, component sizing, and energy management – closely interact and, therefore, must be optimized together. The paper addresses all these challenges using multi-parametric optimization toolchain, that combines a parametric HEV model, energy management strategy, and optimization software. The optimization software includes various optimization strategies: genetic algorithms, gradient based methods, or their combinations. The parametric HEV model is built in GT-Suite 0D/1D/3D multi-physics CAE system simulation software, that also includes different energy management strategies, either locally or globally optimal, considering the whole driving cycle. The toolchain is then used to evaluate the optimal component sizing for two different vehicle classes and fuel economy in a homologation driving cycle and in some real-world driving scenarios. All results are compared to in-house benchmark method.
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Tabssum, Tahera, Priya Charles, and A. V. Patil. "Evaluation of disparity map computed using local stereo parametric and Non-Parametric methods." In 2016 International Conference on Automatic Control and Dynamic Optimization Techniques (ICACDOT). IEEE, 2016. http://dx.doi.org/10.1109/icacdot.2016.7877560.
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Kropotov, Y. A., and V. A. Ermolaev. "Algorithms for processing acoustic signals in telecommunication systems by local parametric methods of analysis." In 2015 International Siberian Conference on Control and Communications (SIBCON). IEEE, 2015. http://dx.doi.org/10.1109/sibcon.2015.7147109.
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Czarniewska, Martyna, Grzegorz Fotyga, and Michal Mrozowski. "Local Mesh Deformation for accelerated parametric studies based on the Finite Element Method." In 2017 IEEE MTT-S International Conference on Numerical Electromagnetic and Multiphysics Modeling and Optimization for RF, Microwave, and Terahertz Applications (NEMO). IEEE, 2017. http://dx.doi.org/10.1109/nemo.2017.7964261.
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Bhange, Ashish, Abhishek Gulia, Anirudh Punnakal, Anil Kumar Anand, Anil Kumar Bansal, Ch Kartikeshwar Patro, and Naveen Kumawat. "Role of interstitial brachytherpy using template (mupit) in locally advanced carcinoma cervix." In 16th Annual International Conference RGCON. Thieme Medical and Scientific Publishers Private Ltd., 2016. http://dx.doi.org/10.1055/s-0039-1685257.
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Introduction: Locally advanced carcinoma cervix includes stages IIB, IIIA, IIIB and IVA. Interstitial brachytherapy has the potential to deliver adequate dose to lateral parametrium and to vagina. Hence, it is preferable in cases with distorted anatomy, extensive (lower) vaginal wall involvement, bulky residual disease post EBRT and parametrium involvement upto lateral pelvic wall. Aim and Objective: To determine clinical outcome and complications (acute and chronic) in locally advanced carcinoma cervix, treated with interstitial brachytherapy using template (MUPIT - Martinez universal perineal interstitial template). Materials and Methods: This study is a retrospective analysis of 37 cases of locally advanced carcinoma cervix (stage IIB-2, IIIB-30, IVA-5), treated with EBRT (dose-median 45Gy/25#) ± concurrent chemotherapy (CCT) - Inj. Cisplatin/Inj Carboplatin, followed by interstitial brachytherapy using MUPIT from December 2009 to June 2015. Initial treatment with EBRT ± CCT was followed by intertstitial brachytherapy. Under spinal anaesthesia and epidural analgesia, MUPIT application was done. Straight and divergent needles (median 26, range 19-29) were inserted to cover parametrium adequately. Needle position was verified with planning CT scan and Brachytherapy planning was done. Dose was normalized to 5 mm box surface from outermost needle with optimization of dose to OAR (Bladder, Rectum and Sigmoid colon). Prescription dose –25Gy in 5#. Treatment was delivered by Microselectron HDR using Ir192 source. Treatment fractions were delivered twice daily with min 6 Hrs. gap in-between fractions. Results: The median duration of follow-up was 25 months. Local control was achieved in 28 patients with residual disease in 7 patients and local recurrence in 2 patients. 10 patients had acute lower GI toxicity {Grade1 (n=6), Grade 2 (n=4)}, 2 patients had acute Grade 1 bladder toxicity. 1 patient had grade 3 and 1 patient had grade 4 chronic bladder toxicity. Chronic rectal toxicity was seen in 10 patients {Grade 2 (n=4), Grade 3 (n=4), Grade 4 (n=2)}. Conclusion: Local control was achieved in 28/37 patients (75.6%) and overall survival rate of 81.1% at median follow up of 25 months in patients with locally advanced carcinoma cervix and unfavorable prognostic factors.
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Young, Timothy J. "Parametric Analysis of Laminar Forced Convective Cooling of Heated Obstacle Arrays." In ASME 1997 International Mechanical Engineering Congress and Exposition. American Society of Mechanical Engineers, 1997. http://dx.doi.org/10.1115/imece1997-0969.
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Abstract An extensive parametric analysis has been performed to fully investigate the fundamental aspects of laminar convective cooling of an array of heated obstacles within a channel. The analysis employs the finite element method to solve the Navier-Stokes equations for the fluid flow and fully accounts for conjugate conduction within the solid obstacles. The influences of parametric changes in the obstacle thermal conductivity, fluid coolant flow rate, and input heating method are examined to establish important fundamental effects and provide practical results. The dependence of the streamlines, isotherms, and local Nusselt numbers on the governing parameters is documented. It was found that increases in the obstacle thermal conductivity improve the internal obstacle heat flow through reduced temperature gradients with large values of the solid thermal conductivity (ksolid/kfluid ≥ 100) effectively isothermalizing the obstacles. Differences between two methods typically used to model the waste heat production in electronic devices, surface flux and volumetric heating, were found to only manifest themselves within the obstacle with only small changes in Nusselt numbers.
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Bu, Fanping, and Bin Yao. "Performance Improvement of Proportional Directional Control Valves: Methods and Experiments." In ASME 2000 International Mechanical Engineering Congress and Exposition. American Society of Mechanical Engineers, 2000. http://dx.doi.org/10.1115/imece2000-2315.
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Abstract This paper studies local valve control of the electro-hydraulic system. The sluggish response of hydraulic control valve usually becomes the bottleneck of whole system performance. Although fast valves (e.g. high-bandwidth servo-valves) are available, they are far more expensive than slow valves (e.g. proportional directional control valves). To improve the performance of proportional directional control valves, three different types of controllers are synthesized. Firstly, based on the pole zero cancellation technique, an open loop compensator is designed which requires the accurate valve dynamic model information; Secondly, a full state feedback adaptive robust controller (ARC) is synthesized, which effectively takes into account the effect of parametric uncertainties and uncertain nonlinearities such as friction force and flow force. Finally, an output feedback ARC controller is synthesized to address the problem of unmeasurable states. Theoretically, the proposed ARC controllers guarantee a prescribed output tracking transient performance and final tracking accuracy while achieving asymptotic output tracking in the presence of parametric uncertainties. Comparative experimental results are obtained to show the advantages and limitations of each method.
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Aquelet, N., and M. Souli. "Explicit Coupling Methods in Hydrodynamic Impacts." In ASME 2005 Pressure Vessels and Piping Conference. ASMEDC, 2005. http://dx.doi.org/10.1115/pvp2005-71656.
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The purpose of this paper is to study and compare two finite element coupling methods to simulate the problem of a body penetrating a free surface. The hydrodynamic impact problem concerns industrial designers in shipbuilding domain. In rough seas, sometimes ships suffer local damages from large water impact loads called slamming impacts. In the framework of a collaboration with a french research company in shipbuilding (Principia Marine) a numerical prediction of the local impulse load on a wedge striking a free surface is investigated by using two methods: penalty and Lagrange multiplier formulations. These methods of coupling, which makes it possible to transmit the efforts in pressure from the Eulerian formulation to the Lagrangian formulation and conversely are relatively recent algorithmic developments. The Euler/Lagrange penalty method was successfully used in many scientific and industrial applications: the modeling of the attack of birds on the fuselage of a Jet for the Boeing Corporation, the underwater explosion shaking the oil platforms, the airbag simulation... The explicit coupling based on multiplier approach is a new development, which is compared to the penalty method. For both methods, a parametric study of the local pressure peak is investigated for impact angles from 0 to 30 degrees.
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Nadarajah, Chithranjan, and Tom Schachinger. "Buckling of Local Thin Areas Under External Pressure." In ASME 2008 Pressure Vessels and Piping Conference. ASMEDC, 2008. http://dx.doi.org/10.1115/pvp2008-61049.
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A parametric study of square local thin areas on cylindrical shells under external pressure was conducted using finite element method. The study concentrated on both elastic and as well as plastic buckling of the local thin areas. From the study, conservative screening curves were developed to address the structural integrity of the local thin area under external pressure.
Reports on the topic "Locally parametric methods"
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PARAMETRIC STUDIES ON THE MOMENT RESISTANT BEAMCOLUMN CONNECTION BEHAVIOR OF CONCRETE FILLED DOUBLE STEEL TUBULAR COLUMNS AND I STEEL BEAMS. The Hong Kong Institute of Steel Construction, August 2022. http://dx.doi.org/10.18057/icass2020.p.284.
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The configuration of Concrete filled double steel tubular cross-section (CFDST) has the potential to overcome the beam-column connection difficulties found in steel tubular cross-sections. Since experimental parametric studies are expensive, numerical methods are adopted in this study to understand the behavior of beam-CFDST column connection under monotonic and cyclic loading conditions. The connection type is observed to be as semi-rigid as per EN1993-1-8. Parametric study includes design parameters like, concrete infill strength, yield strength of inner steel tube and outer steel tube, hollowness ratio, width to thickness ratio of inner steel tube and outer steel tube, end plate thickness and provision of stiffeners for end plate. Thickening the inner steel tube locally at the bolt location and providing stiffener plate or bracket at the compression zone of the extended end plate improves the rotational capacity of the connection as high as 0.06 rad for full plastic moment capacity of the beam. Recommendations are given for proportioning the connection components like end plates, bolts, inner steel tube and stiffeners for an optimal semi-rigid connection design.
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HYSTERETIC PERFORMANCE OF WEAK-AXIS CONNECTION WITH I-SHAPED PLATES IN STEEL FRAME. The Hong Kong Institute of Steel Construction, September 2021. http://dx.doi.org/10.18057/ijasc.2021.17.3.1.
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This paper elucidates numerically the behavior of weak-axis moment connections proposed by welding I-shaped plates in the H-section column to increase connection strength and ductility in steel frame. After validating the numerical methods through comparing the results of numerical analysis and experiments, the effectiveness of the proposed weak-axis connection were examined through comparing to the traditional weak-axis connection. The proposed weak-axis connection could move the highest stresses away from the start-stop points of a weld, and thus preventing the premature brittle fracture of the beam flange welds. The plastic hinge formed away from the beam-column interface, while the local buckling occurred in the weld access holes region in the traditional weak-axis connection. The proposed weak-axis connections can be classified as rigid in a strong-bracing system, and be classified as semi-rigid in weak-supported or unsupported system. And then a series of parametric studies was conducted to better understand the behavior of proposed weak-axis moment connections. The force-displacement relationships, location of the plastic hinge, Mises index (MI), triaxiality index (TI) and rupture index (RI) distributions at the beam flange welds were reported in detail. According to the numerical analysis, the design variables of I-shaped plates and widened flange plate are suggested, along with a design procedure.
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BUCKLING BEHAVIOUR OF THE STEEL PLATE IN STEEL – CONCRETE – STEEL SANDWICH COMPOSITE TOWER FOR WIND TURBINE. The Hong Kong Institute of Steel Construction, September 2022. http://dx.doi.org/10.18057/ijasc.2022.18.3.7.
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To solve the problem of collapses caused by local buckling of steel plates under compression in traditional steel towers, a novel steel-concrete-steel (SCS) sandwich composite tower for a wind turbine is proposed in this paper. To study the buckling behaviour of steel plates in SCS sandwich composite towers, six specimens were designed and tested under axial compression. The specimens were designed considering the key parameters of curvature radius, thickness of the steel plate, and the spacing-to-thickness ratio (the ratio of stud spacing to the thickness of steel plate). The failure modes, normalised average stress-strain curves and load-strain curves of the specimens were assessed, and the effects of the curvature radius and the spacing-to-thickness ratio of the steel plate were analysed. The experimental results showed that the buckling strength of the steel plate increased with a decrease in the ratio of the curvature radius to the thickness of the steel plate. The finite element (FE) model of the elastic buckling stress of the steel plate of the SCS sandwich composite tower was employed and validated against the test results. In parametric study, the effects of governing parameters including the curvature radius of the steel plate, thickness of the steel plate and spacing of the studs, on the effective length factors of the inner and outer steel plates were analysed. Subsequently, the design rules of the effective length factor of the inner and outer steel plates, and the design methods of spacing of studs to prevent local instability of the inner and outer steel plates before yielding were proposed.