A study on response analysis of submerged floating tunnel with linear and nonlinear cables

Yarramsetty, Poorna Chandra Rao,Domala, Vamshikrishna,Poluraju, P.,Sharma, R. Techno-Press 2019 Ocean systems engineering Vol.9 No.3

This paper presents the comparison between SFT response with linear and nonlinear cables. The dynamic response analysis of submerged floating tunnel (SFT) is presented computationally with linear and nonlinear tension legs cables. The analysis is performed computationally for two wave directions one at 90 degrees (perpendicular) to tunnel and other at 45 degrees to the tunnel. The tension legs or cables are assumed as linear and non- linear and the analysis is also performed by assuming one tension leg or cable is failed. The Response Amplitude Operators (RAO's) are computed for first order waves, second order waves for both failure and non-failure case of cables. For first order waves- the SFT response is higher for sway and heave degree of freedom with nonlinear cables as compared with linear cables. For second order waves the SFT response in sway degree of freedom is bit higher response with linear cables as compared with nonlinear cables and the SFT in heave degree of freedom has higher response at low time periods with nonlinear cables as compared with linear cables. For irregular waves the power spectral densities (PSD's) has been computed for sway and heave degrees of freedom, at $45^0$ wave direction PSD's are higher with linear cables as compared with nonlinear cables and at $90^0$ wave direction the PSD's are higher with non-linear cables. The mooring force responses are also computed in y and z directions for linear and nonlinear cables.

Quasi-oppositional-based Rao algorithms for multi-objective design optimization of selected heat sinks

R. V. Rao,R. B. Pawar 한국CDE학회 2020 Journal of computational design and engineering Vol.7 No.6

In this paper, an endeavor is made to enhance the convergence speed of the recently proposed Rao algorithms. The new upgraded versions of Rao algorithms named as “quasi-oppositional-based Rao algorithms” are proposed in this paper. The quasi-oppositional-based learning is incorporated in the basic Rao algorithms to diversify the searching process of the algorithms. The performance of the proposed algorithms is tested on 51 unconstrained benchmark functions. Also, three multi-objective optimization case studies of different heat sinks such as a single-layered microchannel heat sink (SL-MCHS), a double-layered microchannel heat sink (DL-MCHS), and a plate-fin heat sink (PFHS) are attempted to investigate the effectiveness of the proposed algorithms in solving real-world complex engineering optimization problems. The results obtained using the proposed algorithms are compared with the results obtained using the well-known advanced optimization algorithms such as genetic algorithm (GA), artificial bee colony (ABC), differential evolution (DE), particle swarm optimization (PSO), teaching-learning-based algorithm (TLBO), Jaya algorithm, multi-objective genetic algorithm (MOGA), non-dominated sorting genetic algorithm (NSGA-II), real-coded GA (RCGA), direction-based GA, self-adaptive multi-population (SAMP) Rao algorithms, and basic Rao algorithms. The proposed quasi-oppositional-based Rao algorithms are found superior or competitive to the other optimization algorithms considered.

A self-adaptive population Rao algorithm for optimization of selected bio-energy systems

R. Venkata Rao,Hameer Singh Keesari 한국CDE학회 2021 Journal of computational design and engineering Vol.8 No.1

This work proposes a metaphor-less and algorithm-specific parameter-less algorithm, named as self-adaptive population Rao algorithm, for solving the single-, multi-, and many-objective optimization problems. The proposed algorithm adapts the population size based on the improvement in the fitness value during the search process. The population is randomly divided into four sub-population groups. For each sub-population, a unique perturbation equation is randomly allocated. Each perturbation equation guides the solutions toward different regions of the search space. The performance of the proposed algorithm is examined using standard optimization benchmark problems having different characteristics in the single- and multi-objective optimization scenarios. The results of the application of the proposed algorithm are compared with those obtained by the latest advanced optimization algorithms. It is observed that the results obtained by the proposed method are superior. Furthermore, the proposed algorithm is used to identify optimum design parameters through multi-objective optimization of a fertilizer-assisted microalgae cultivation process and many-objective optimization of a compression ignition biodiesel engine system. From the results of the computational tests, it is observed that the performance of the self-adaptive population Rao algorithm is superior or competitive to the other advanced optimization algorithms. The performances of the considered bio-energy systems are improved by the application of the proposed optimization algorithm. The proposed optimization algorithm is more robust and may be easily extended to solve single-, multi-, and many-objective optimization problems of different science and engineering disciplines.

AN INITIAL VALUE TECHNIQUE FOR SINGULARLY PERTURBED DIFFERENTIAL-DIFFERENCE EQUATIONS WITH A SMALL NEGATIVE SHIFT

Rao, R. Nageshwar,Chakravarthy, P. Pramod The Korean Society for Computational and Applied M 2013 Journal of applied mathematics & informatics Vol.31 No.1

In this paper, we present an initial value technique for solving singularly perturbed differential difference equations with a boundary layer at one end point. Taylor's series is used to tackle the terms containing shift provided the shift is of small order of singular perturbation parameter and obtained a singularly perturbed boundary value problem. This singularly perturbed boundary value problem is replaced by a pair of initial value problems. Classical fourth order Runge-Kutta method is used to solve these initial value problems. The effect of small shift on the boundary layer solution in both the cases, i.e., the boundary layer on the left side as well as the right side is discussed by considering numerical experiments. Several numerical examples are solved to demonstate the applicability of the method.

PROBLEMS AND PROSPECTS OF COOPERATIVE MOVEMENT IN UNIFIED KOREA UNDER MARKET ECONOMY

Rao, R. M. Mohan 한국협동조합학회 1992 韓國協同組合硏究 Vol.10 No.-

Optimization of submerged arc welding process parameters using quasi-oppositional based Jaya algorithm

R. Venkata Rao,Dhiraj P. Rai 대한기계학회 2017 JOURNAL OF MECHANICAL SCIENCE AND TECHNOLOGY Vol.31 No.5

Submerged arc welding (SAW) is characterized as a multi-input process. Selection of optimum combination of process parameters of SAW process is a vital task in order to achieve high quality of weld and productivity. The objective of this work is to optimize the SAW process parameters using a simple optimization algorithm, which is fast, robust and convenient. Therefore, in this work a very recently proposed optimization algorithm named Jaya algorithm is applied to solve the optimization problems in SAW process. In addition, a modified version of Jaya algorithm with oppositional based learning, named “Quasi-oppositional based Jaya algorithm” (QO-Jaya) is proposed in order to improve the performance of the Jaya algorithm. Three optimization case studies are considered and the results obtained by Jaya algorithm and QO-Jaya algorithm are compared with the results obtained by well-known optimization algorithms such as Genetic algorithm (GA), Particle swarm optimization (PSO), Imperialist competitive algorithm (ICA) and Teaching learning based optimization (TLBO).

Design, Synthesis and Biological Evaluation of Novel Analogs of Bortezomib

Rao, R. Janaki Rama,Rao, A.K.S. Bhujanga,Swapna, K.,Rani, B. Baby,Kumar, S. Prasanna,Awantika, S.,Murthy, Y.L.N. Korean Chemical Society 2011 대한화학회지 Vol.55 No.5

Novel analogs of bortezomib were designed, synthesized and in vitro biological evaluation was carried out using human tumor cell lines A549 and PC3. Docking studies of these analogs of bortezomib was discussed. According to biological investigations, the inhibitors 4, 6, and 8 were found to be more potent than reference drug candidate bortezomib. A549 cell line showed significant sensitivity towards 4, 6, and 8 with $IC_{50}$ values 14.03, 18.5, and 12.4 nM, respectively, and PC3 cell line showed IC50 values 26.1, 37.0, and 21.2 nM, respectively. The $IC_{50}$ values of bortezomib in these cell lines are 27.3 nM and 42.0 nM.

COMMON FIXED POINTS FOR MAPS IN D-METRIC SPACE USING STRONGLY TANGENTIAL AND ORBITALLY LOWER SEMI-CONTINUITY CONDITIONS

Rao, K.P.R.,Rao, K.R.K.,Raju, V.C.C. 충청수학회 2006 충청수학회지 Vol.19 No.1

In this paper, we obtain some unique common fixed point theorems for four self-maps and pair of maps in D-metric space using orbitally lower semi continuity conditions.

An initial value technique for singularly perturbed differential-difference equations with a small negative shift

R. Nageshwar Rao,P. Pramod Chakravarthy 한국전산응용수학회 2013 Journal of applied mathematics & informatics Vol.31 No.1

In this paper, we present an initial value technique for solvingsingularly perturbed differential difference equations with a boundary layerat one end point. Taylor’s series is used to tackle the terms containing shiftprovided the shift is of small order of singular perturbation parameter andobtained a singularly perturbed boundary value problem. This singularlyperturbed boundary value problem is replaced by a pair of initial valueproblems. Classical fourth order Runge–Kutta method is used to solvethese initial value problems. The effect of small shift on the boundarylayer solution in both the cases, i.e., the boundary layer on the left sideas well as the right side is discussed by considering numerical experiments. Several numerical examples are solved to demonstate the applicability ofthe method.

Optimum static balancing of a robot manipulator using TLBO algorithm

Rao, R. Venkata,Waghmare, Gajanan Techno-Press 2018 Advances in robotics research Vol.2 No.1

This paper presents the performance of Teaching-Learning-Based Optimization (TLBO) algorithm for optimum static balancing of a robot manipulator. Static balancing of robot manipulator is an important aspect of the overall robot performance and the most demanding process in any robot system to match the need for the production requirements. The average force on the gripper in the working area is considered as an objective function. Length of the links, angle between them and stiffness of springs are considered as the design variables. Three robot manipulator configurations are optimized. The results show the better or competitive performance of the TLBO algorithm over the other optimization algorithms considered by the previous researchers.