Faculty Publications

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    Universal Grey Number Systems for Uncertainty Quantification
    (Springer Science and Business Media Deutschland GmbH, 2023) Kumar, A.; Balu, A.S.
    In the recent past, modelling and analysis of structures with uncertain parameters have evoked significant interest.Physical imperfections, model flaws and system complexities can all be sources of uncertainty.In addition, the action loads (live, wind and earthquake) applied to a structure during its lifetime are not deterministic, hence for the proper performance assessment of the structural system, it is essential to properly account for these uncertainties.Uncertainties are usually described by probabilistic and non-probabilistic approaches.The growing interest in the non-probabilistic approach developed due to the incredibility of the probabilistic approach when data is insufficient.For estimating the ranges of the structural system’s response, the interval finite element approach looks to be acceptable, whose input parameters are defined in the ranges.However, the range of values predicted by the interval analysis suffers dependency problem.This can cause the computed findings to be overestimated.Although, the use of numerical truncation technique, parameterization of intervals and subinterval technique suggested by several researchers to avoid the dependency problem caused by general interval arithmetic.The physical rules (distributive law) are not violated by a universal grey numbers are a form of grey number and predict accurate results when compared with the interval approach.The universal grey number system is one such approach where computational efficiency and accuracy can be achieved when the input parameters are available in the ranges/interval. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
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    Uncertainties in predicting impacts of climate change on hydrology in basin scale: a review
    (Springer Science and Business Media Deutschland GmbH info@springer-sbm.com, 2020) Jose, D.M.; Dwarakish, G.S.
    The sensitivity of the hydrological system to climate change and the role of hydrological systems in the environment have motivated researchers to study the impacts of climate change on hydrology. Modelling the hydrological impacts of climate change is generally done in various stages and has uncertainty associated with each of them. These include scenario uncertainty in climate scenario selection, model uncertainty in climate simulation by global climatic models (GCMs), uncertainties while downscaling GCMs, biases in downscaled data, erroneous input to the hydrological model, and uncertainty in the structure and parameterisation of the hydrological model. The present paper aims at reviewing the uncertainties involved at each stage of climate change impact assessment of hydrology. In the near future, climate scenario uncertainties would be smaller than those associated with the choice of GCMs. Multi-model ensemble approach takes better account of uncertainties involved with GCMs. Moreover, considering a range of possible climate scenarios is recommended than using a single best or average case climate scenario. GCMs shall be downscaled by statistical or dynamical methods (regional climatic models (RCMs)) before using them for regional studies. Bias correction methods can considerably improve the RCM simulations. Evaluation of model performance is recommended for regional-scale studies for the preparation of adaptation strategies. Taking into account the uncertainties associated with climate impact studies can help formulate effective adaptation strategies. © 2020, Saudi Society for Geosciences.
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    Fuzzy logic modeling for groundwater level forecasting of west coast region in India
    (2011) Dandagala, D.; Deka, P.C.
    Forecasting the groundwater table in unconfined aquifer is essential for efficient planning of conjunctive use in a basin. In this study, fuzzy logic (FL) models have been developed for groundwater level forecasting in west coast humid region of Karnataka state, India. The FL modeling was carried out to forecast the groundwater table by one week lead time at three different sites over the study area. Mamdani fuzzy inference system was adopted in the present study and finally centroid of area defuzzification method has been applied to obtain crisp output. The results concluded that the FL model performed quite satisfactorily as assessed by various performance indices such as Root mean square error, Coefficient of correlation, and Mean absolute error. © 2011 CAFET-INNOVA TECHNICAL SOCIETY. All rights reserved.
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    Sensitivity of Pushover Curve to Material and Geometric Modelling-An Analytical Investigation
    (Elsevier Ltd, 2015) Panandikar, N.; Babu Narayan, K.S.
    Nonlinear static analysis or pushover analysis developed over the last two decades and became the preferred procedure for design and seismic performance evaluation, as this procedure is relatively simple and considers post-elastic behaviour. It provides information on seismic demands imposed by the design ground motion on the structural system and its components. Generation of pushover curve from analysis for reinforced concrete structure involves tremendous amount of computational efforts as the input data for analysis itself is quite exhaustive. The analysis results are very sensitive to the techniques employed in geometric and material modelling. This paper envisages presenting the sensitivity of pushover analysis results to geometric and material modelling parameters by comparing the analysis results with that of experimental investigations. Attempt has been made to understand the sensitivity of parameters like variation in material properties, inaccuracies in placement of reinforcement, effect of confinement of concrete and modelling techniques for elements and plastic hinges. SAP-2000 has been utilised in the current investigation and results have been highlighted suggesting strategies to enhance pushover analysis capabilities. © 2015 Elsevier B.V.
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    Cumulant-based correlated probabilistic load flow considering photovoltaic generation and electric vehicle charging demand
    (Higher Education Press Limited Company, 2017) Bhat, N.G.; Prusty, B.R.; Jena, D.
    This paper applies a cumulant-based analytical method for probabilistic load flow (PLF) assessment in transmission and distribution systems. The uncertainties pertaining to photovoltaic generations and aggregate bus load powers are probabilistically modeled in the case of transmission systems. In the case of distribution systems, the uncertainties pertaining to plug-in hybrid electric vehicle and battery electric vehicle charging demands in residential community as well as charging stations are probabilistically modeled. The probability distributions of the result variables (bus voltages and branch power flows) pertaining to these inputs are accurately established. The multiple input correlation cases are incorporated. Simultaneously, the performance of the proposed method is demonstrated on a modified Ward-Hale 6-bus system and an IEEE 14-bus transmission system as well as on a modified IEEE 69-bus radial and an IEEE 33-bus mesh distribution system. The results of the proposed method are compared with that of Monte-Carlo simulation. © 2017, Higher Education Press and Springer-Verlag Berlin Heidelberg.
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    Preprocessing of Multi-Time Instant PV Generation Data
    (Institute of Electrical and Electronics Engineers Inc., 2018) Prusty, B.; Jena, D.
    For the evaluation of system overlimit risk indices in a PV-integrated power system, PV generation data at specific instants of time (in each day for several years) are required to be collected. Such data have inherent annual periodic variations, which are different at various places. These variations are skewed and/or multimodal, which contributes significantly toward the overall variance of data and is primarily attributable to the Sun's position. This letter proposes a regression model that assumes the observed data as a function of few influencing factors related to the Sun's position and trend in data. Finally, the estimated variations using the developed model are removed from the data to characterize the unpredictable components. © 1969-2012 IEEE.
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    Analysis of structural systems with imprecise uncertainties using high dimensional model representation
    (World Scientific, 2021) Spoorthi, S.K.; Balu, A.S.
    Uncertainties present in any structural system inherently affect the performance and design of the system. The sources of uncertainties serve the basis for delineating the types as aleatory or epistemic. The probabilistic models can be considered as the most valuable strategies to deal with aleatory uncertainties, while convex models, possibility theory, evidence theory and Bayesian probability theory can be used to deal with epistemic uncertainty. However, when only scarce datasets are available and knowledge is incomplete, a more general framework, such as probability-box, is more appropriate to describe the uncertainty. Furthermore, analysis of complex and multi-dimensional structures is expensive and time consuming when numerical techniques are used. Therefore, simulation of such structures for many realisation of uncertain input becomes a challenging task in the uncertainty analysis. In this paper, complex structural systems with imprecise uncertain input are studied and evaluated efficiently by High Dimensional Model Representation based uncertainty analysis. © 2021 World Scientific Publishing Company.
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    Battery Storage-Based Novel Hybrid Islanding Detection Technique Using Lissajous Pattern Estimation
    (Institute of Electrical and Electronics Engineers Inc., 2022) Mondal, S.; Gayen, P.K.; Gaonkar, D.N.
    The reliability, uncertainty, and sensitivity of local islanding detection method for distributed generation (DG) system under diversified real-time scenarios and nonlinear loading conditions are not greatly explored. In this article, a new type hybrid islanding detection technique (IDT) is suggested, which reduces uncertainty and simultaneously improves reliability and sensitivity under different situations. In the technique, one detection parameter is defined, which is calculated from estimation of major and minor axes of Lissajous pattern (LP). Here, the evaluation of the parameter is done in two stages to avoid erroneous detection. In the first stage, the initiation of voltage transient is detected by LP. In the second stage, the active control via battery energy storage system (BESS) distinguishes nuisance tripping case from the islanding state. The extra active power injection/absorption via BESS also helps to identify islanding state at very near to zero power condition, i.e., sensitivity is enhanced. The detection time is found within 160 ms for different test cases, which is well below that of the acceptable upper value (2 s) specified in standard. The uncertainties in detection and threshold setting due to variations of harmonics and other operating conditions are removed in the proposed case, which is a distinct advantage. The Typhoon-HIL tool is used to carry out various case studies in real-time. Here, superior performances of proposed approach are observed in comparison with other state of the arts reported in the literature. © 1963-2012 IEEE.
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    Impact of increased particle concentration on magnetorheological fluid properties and their damping performance
    (Korean Society of Rheology, Australian Society of Rheology, 2022) Kariganaur, A.K.; Kumar, H.; Arun, M.
    Magnetorheological (MR) fluid properties are essential in analyzing the performance of any MR fluid system. The fluid properties are dependent on shape, size, and magnetic saturation of the magnetic particles. Preliminary characteristics with SEM, particle size analysis (PSA), and vibration sample magnetometer (VSM) on carbonyl iron particles were performed to verify the particle’s feasibility to synthesize the MR fluid in a laboratory. Synthesis and characterization of MR fluids with particle concentrations (PC) of 10% (PC10), 15% (PC15), 20% (PC20), 30% (PC30), and 35% (PC35) by volume are carried out. To show the inherent nonlinearity of the MR fluid, Herschel–Bulkley model is used. The relationship between sedimentation velocity, yield stress, and thermal conductivity is established as a function of particle concentration with experimental uncertainty of 6.15, 5, and 8.96%, respectively. Functional testing of PC15 and PC30 was carried out on an MR damper fabricated on dimensions obtained from the literature for the required size. The results indicate that damping force is 42% more in PC30 than PC15 at higher loading parameters. Finally, the saturation magnetization of the MR fluid depends not only on applied current but also on loading parameters when operating in the system. © 2022, Korean Society of Rheology.
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    Effective configuration of perforated baffle plate for efficient slosh damping in liquid retaining tanks under lateral excitation
    (Elsevier Ltd, 2022) Nimisha, P.; Jayalekshmi, B.R.; Venkataramana, K.
    Perforated baffle plates are used as an anti-slosh mechanism in various fields owing to the need for slosh suppression and weight reduction. However, there is an uncertainty in the selection of configuration of perforated baffle plate due to the several influencing parameters for slosh damping efficiency. Therefore, the present study focuses on the development of an efficient slosh damping configuration for the perforated baffle plate. For this, nonlinear dynamic analysis under seismic ground motions with different PGA/PGV ratios has been carried out in the time domain using the concepts of Computational Fluid Dynamics (CFD) in the numerical models of liquid tanks with perforated baffle plates of different configurations. The response of the system under impulsive and convective modes is analysed by observing the free surface elevation, hydrodynamic pressure, turbulence kinetic energy and turbulence eddy dissipation as the response parameters. The study developed an effective baffle configuration for efficient slosh damping, considering the various response parameters. © 2022 Elsevier Ltd