Modeling and Computational Methods for Dynamic Arc Root Transfer at Electrods

Computational methods for bird strike simulations: A review

System identification (SI) is referred to as the procedure of building mathematical models for the dynamic systems using the measured data. Several modeling methods and types of models were studied by classifying SI in different ways, such as (1) black box, gray box, and white box; (2) parametric and non-parametric; and (3) linear SI, nonlinear SI, and evolutionary SI. A study of the literature also reveals that extensive focus has been paid to computational intelligence methods for modeling the output variables of the systems because of their ability to formulate the models based only on data obtained from the system. It was also learned that by embedding the features of several methods from different fields of SI into a given method, it is possible to improve its generalization ability. Popular variants of genetic programming such as multi-gene genetic programming is suggested as an alternative approach with its four shortcomings discussed as future aspects in paving way for evolutionary system identification.

Systematic methods for efficient modeling and dynamics computation are developed, using the Lagrangian assumed modes method. The methods greatly reduce the number of mathematical operations (i.e. multiplications and additions) required for the modeling and dynamics computation of flexible manipulators. The link deflection is described by a truncated modal expansion. The operations of 3*3 matrices and/or 3*1 vectors only exist in the methods. All the dynamics computations are performed in the link coordinate systems, in which the kinematics information is computed with the forward recursion from the base to the hand tip and the dynamics information is computed with the return recursion. As compared with other existing methods, the methods proposed here are computationally more simple, systematic, and efficient. Simulation results for a single-link flexible robot manipulator are presented to verify the methods and the algorithms proposed. >

Aircraft vulnerability modeling and computation methods based on product structure and CATIA

Conferences are often organized within specialty disciplines, compartmentalizing information exchange by field of specialty. In the midst of these successful conferences there remains a niche for unifying, cross-cutting, interdisciplinary gatherings, where specialists can have exposure to diverse fields, a chance to meet new people in or near their individual areas of research, and participate in special sessions different from their own field. The proposed meeting of the 2nd International Conference on Mathematical Modelling and Computational Methods in Science and Engineering (ICMMCMSE-2020), has this purpose, to serve as a catalyst for computational mathematics among cutting edge applications in science and engineering.The fields of Mathematical Modelling and Computational Methods and their applications to major areas such as Fluid Dynamics, Structural Mechanics, Semiconductor Modelling, Electromagnetics and CAD/CAM. Multidisciplinary applications of these fields to critical societal and technological problems encountered in sectors like Aerospace, Car and Ship Industry, Electronics, Energy, Finance, Chemistry, Medicine, Biosciences, Environmental sciences, Graph theory are of particular interest.Computational mathematics, science and engineering are rapidly growing multidisciplinary areas with connections to business, economics, engineering, and mathematics and computer science through academia as well as industry. There is furthermore a constant need in these fields for the quick and efficient advancement of information exchange with an expert audience.Altogether, the intent of this conference is to exchange information and to promote the transfer between the research community and industry consistent with the development and applications of computational methods in science and technology. So, the conference theme provides opportunity to initiate and develop such activities among the researchers, scientists and engineers from all over the world.The overwhelming response to our call-for-papers indicates the popularity of this conference and confirms that the 2nd ICMMCMSE-2020 has become the world-wide forum for all aspects of Mathematics and Computer Science in science and technology. There are totally 575 participants have been registered for the conference. Out of this, 315 have been registered and presented their research findings in the “Contributed Talk” sessions and rest of the 260 participants have been registered themselves as a Listener for the conference. Thanks to this response, all important fields of the 2nd ICMMCMSE-2020 techniques, technology and exploitation are covered by their contributions. To our pleasure several Keynote and Invited sessions has been organised by eminent professors from USA, Turkey, Romania, UK, Thailand, New Zealand, UAE, Australia, some of the leading institutions in India like IIT’s and IIST.I would like to express my sincere thanks to all the authors for their outstanding contributions, sponsors for our conference RUSA 2.0, Elsevier Publishing Company, IOP Publishing Company, MDPI, AIMS Press and Hindawi Publishing House and in particular the members of the program board for their competent evaluation of the large number of submissions. Likewise, I would also like to express my appreciation to all the invited chairs for their careful preparation of the invited sessions. Dr. R. Raja Convener 2nd ICMMCMSE-2020

3 - Computational methods

The liberalization, volatility and high competition of financial markets are all factors that expose companies to new risks and challenges, requiring a continuous innovation of models, techniques and tools for managing share price value and other related risks. This paper provides a model to implement a subsystem that should support the management decision on the trading segment of its own shares, based on intelligent agents with regards to identifying, collecting, structuring and updating data instruments, with analysis mechanisms of the main price and volatility indicators. Our conclusion is that the use of computational intelligence methods in modeling of share price value is both a requirement and an option in managing financial-foreign exchange risks, given that companies are subject to a wide range of risks and volatility is the defining feature in which they operate.

Homology modeling is one of the computational structure prediction methods that are used to determine protein 3D structure from its amino acid sequence. It is considered to be the most accurate of the computational structure prediction methods. It consists of multiple steps that are straightforward and easy to apply. There are many tools and servers that are used for homology modeling. There is no single modeling program or server which is superior in every aspect to others. Since the functionality of the model depends on the quality of the generated protein 3D structure, maximizing the quality of homology modeling is crucial. Homology modeling has many applications in the drug discovery process. Since drugs interact with receptors that consist mainly of proteins, protein 3D structure determination, and thus homology modeling is important in drug discovery. Accordingly, there has been the clarification of protein interactions using 3D structures of proteins that are built with homology modeling. This contributes to the identification of novel drug candidates. Homology modeling plays an important role in making drug discovery faster, easier, cheaper, and more practical. As new modeling methods and combinations are introduced, the scope of its applications widens.

The exporting of theoretical concepts and modelling methods from physics and mechanics to the world of biomolecules and cell biology is increasing at a fast pace. The role of mechanical forces and stresses in biology and genetics is just starting to be appreciated, with implications going from cell adhesion, migration, division, to DNA transcription and replication, to the mechanochemical transduction and operation of molecular motors, and more. Substantial advances in experimental techniques over the past 10 years allowed to get unprecedented insight into the elasticity and mechanical response of many different proteins, cytoskeletal filaments, nucleic acids, both in vitro and, more recently, directly inside the cell. In a parallel effort, also theoretical models and computational methods are evolving into a rather specialized toolbox. However, several key issues need to be addressed when applying to life sciences the theories and methods typically originating from the fields of condensed matter and solid mechanics. The presence of a solvent and its dielectric properties, the many subtle effects of entropy, the non-equilibrium thermodynamics conditions, the dominating role of weak forces such as Van der Waals dispersion, hydrophobic interactions, and hydrogen bonding, impose a special caution and a thorough consideration, up to possibly rethinking some basic physics concepts. Discussing and trying to elucidate at least some of the above issues is the main aim of the present, partial and non-exhaustive, contribution.KeywordsBiomoleculesMechanical propertiesConfigurational entropyMolecular dynamicsJarzynski identity

Effects of wind flow structure, particle flow and deposition pattern on photovoltaic energy harvest around a block

This paper is devoted to mathematical analysis of three-dimensional boundary-layer flow and heat transfer over a wedge. The boundary layer is formed due to the flow of a viscous and incompressible fluid and grows downstream along the walls of the wedge. This is appropriately approximated by a power of distances along both lateral directions. This analysis introduces a shear-to-strain-rate parameter $$\gamma$$ in the study which plays an essential role in three-dimensional boundary-layer study. A set of boundary-layer equations along with the conservation of energy has been transformed into a coupled nonlinear ordinary differential equations. Two methods are employed. The fluid–wedge interaction problem is solved in the circumstances where the equations are linearized and obtained the solutions in terms of confluent hypergeometric functions, and otherwise, the full-nonlinear problem numerically using the Keller-box method. In the former case, the results of eigenfunction analysis that is based on asymptotic study of the problem qualitatively support the latter numerical results. In either methods, the existence of solutions and range of parameter domain depending on various physical quantities is successfully analyzed. The two different approaches give good agreement with each other in predicting the velocity and temperature profiles in three-dimensional boundary layer. However, both approaches show that a solution to the problem exist only $$-\,1< \gamma < \infty$$ . Since the Reynolds number is asymptotically large, the flow clearly divides into two regions showing the effects of viscosity and thermal conductivity. The velocity and thermal profiles are found to be benign. Flow always attached to the wedge surfaces and, thus, related thicknesses are becoming thinner. Extensive comparisons of the various results are made and a possible explanation on the results is discussed in some detail.

Most computational protein structure prediction methods are designed for either template based or template-free (ab initio) structure prediction. The approaches that integrate the prediction capabilities of both template-based modeling and template-free modeling are needed to synergistically combine the two kinds of methods to improve protein structure prediction. In this work, we develop a new method to integrate several protein structure prediction methods including our template-based MULTICOM server, our ab initio contact-based protein structure prediction method CONFOLD, our multi-template-based model generation tool MTMG, and locally installed external Rosetta, I-TASSER and RaptorX protein structure prediction tools to improve protein structure prediction of a fullspectrum difficulty ranging from easy, to medium and to hard. Our method participated in the 11(th) community-wide Critical Assessment of Techniques for Protein Structure Prediction (CASP11) in 2014 as MULTICOM-NOVEL server. It was ranked among top 10 methods for protein tertiary structure prediction according to the official CASP11 assessment, which demonstrates that integrating complementary modeling methods is useful for advancing protein structure prediction.

The Na+/K+ pump, often thought of as a background function in neuronal activity, contributes an outward current (Ipump) that responds to the internal concentration of Na+ ([Na+]i). In bursting neurons, such as those found in central pattern generator (CPG) neuronal networks that produce rhythmic movements, the [Na+]i and therefore the Ipump, can be expected to vary throughout the burst cycle. This responsiveness to electrical activity, combined with independence from membrane potential, endow Ipump with dynamical properties not common to channel-based currents (e.g., voltage- or transmitter-gated or leak channels). Moreover, in many neurons, the pump's activity is modulated by a variety of modulators, further expanding the potential role of Ipump in rhythmic bursting activity. This paper shows how to use a combination of modeling and dynamic clamp methods to determine how Ipump and its interaction with persistent Na+ current influence rhythmic activity in a CPG. Specifically, this paper will focus on a dynamic clamp protocol and computational modeling methods in heart interneurons of medicinal leeches.

We compare local and global polynomial solution methods for DSGE models with Epstein- Zin-Weil utility. We show that model implications for macroeconomic quantities are relatively invariant to choice of solution method but that a global method can yield substantial improvements for asset prices and welfare costs. The divergence in solution quality is highly dependent on parameters which affect value function sensitivity to TFP volatility, as well as the magnitude of TFP volatility itself. This problem is pronounced for calibrations at the extreme of those accepted in the asset pricing literature and disappears for more traditional macroeconomic parameterizations.

Stochastic modeling of coal fracture network by direct use of micro-computed tomography images