System equivalent model mixing

This paper presents frequency response function (FRF) expansion techniques that minimize the difference between the analytical and predicted FRF matrices to satisfy the FRF constraints. The measured FRF relationships at a small number of locations were used as constraints. The expansion method is useful for estimating the rotational FRFs that are difficult to measure or apply using frequency-based substructuring (FBS) techniques. The validity of the proposed method, including the effects of external noise, was confirmed using numerical examples. An FBS algorithm was also derived by incorporating the FRFs of each substructure, and the compatibility conditions were transformed into FRFs with pseudomasses at the joint nodes. A discrepancy between the FRFs of the synthesized system estimated using the proposed method and the analysis results of the entire system was observed in the numerical example, and the reasons for the discrepancy were investigated and discussed. It is estimated that the proposed FBS method can be enhanced by combining it with other dynamic substructuring techniques and supplementing additional information, such as measured FRFs.

A novel model order reduction method for the construction of parametric dynamic compact thermal models of nonlinear heat diffusion problems is proposed. The method extends a previous method, recently proposed by the Authors, for the construction of parametric dynamic compact thermal models of linear heat diffusion problems. The method has been validated through the analysis of a simple die in which high levels of non-linearities and large variations of parameters occur.

Detailed kinetic models at the network reaction level are usually constructed using enzymatic mechanistic rate equations and the associated kinetic parameters. However, during the cellular life cycle thousands of different reactions occur, which makes it very difficult to build a detailed large-scale ldnetic model. In this work, we provide a critical overview of specific limitations found during the reconstruction of the central carbon metabolism dynamic model from E. coli (based on kinetic data available). In addition, we provide clues that will hopefully allow the systems biology community to more accurately construct metabolic dynamic models in the future. The difficulties faced during the construction of dynamic models are due not only to the lack of kinetic information but also to the fact that some data are still not curated. We hope that in the future, with the standardization of the in vitro enzyme protocols the approximation of in vitro conditions to the in vivo ones, it will be possible to integrate the available kinetic data into a complete large scale model. We also expect that collaborative projects between modellers and biologists will provide valuable kinetic data and permit the exchange of important information to solve most of these issues.

CO2 geo‐sequestration into saline aquifers and an enhanced geothermal system (EGS) are two of the most effective solutions to reduce CO2 emissions into the atmosphere. The significance of thermal‐hydrological‐mechanical‐chemical (THMC) interactions is well identified in these two processes: fluid and heat flow, solute transport within a three‐phase mixture; stresses and displacements related to geomechanical effects; non‐isothermal effects on fluid properties and reaction processes; and equilibrium and kinetics of fluid‐rock and gas‐rock chemical interactions. In this paper, a novel numerical model is developed to describe the THMC processes mathematically. One mean stress formulation, which is simplified from the geomechanical equations with full stress tensor, is employed to solve mean stresses and displacements. Chemical equilibrium and kinetics are considered to quantitatively simulate geochemical reaction associated with solute transport. A sequentially coupled computational framework is proposed and used to solve reactive transport of water, gas components, and chemical species in subsurface formation with geomechanics. It is designed to keep a generalized computational structure for different THMC processes. A practical case with complex chemical compositions is presented to analyze the THMC processes quantitatively on the coupled effects of geochemistry and geomechanics during CO2 geo‐sequestration. In addition, a practical EGS case is presented to address the mutual effects of each THMC process quantitatively, especially the mutual effects of stress and chemical reaction. Heat transfer affects mean stress and geochemical reactions; mean stress impacts the solute transport and successive chemical reactions; and geochemical reactions are shown to have significant impact on the mean stress, pressure, or temperature.

In this paper, a scheme for constructing the flat frequency spectrum of interleaved frequency division multiple access (IFDMA) is proposed. Since IFDMA is one of the single carrier modulation schemes, the frequency spectrum components are fluctuated and depend on the information data sequence. Even if IFDMA modulation scheme makes frequency spectrum dispersive for obtaining frequency diversity gain, frequency diversity gain is reduced by the fluctuation of frequency spectrum. In addition, in decision directed channel estimation (DDCE), which achieves good channel estimation accuracy in fast fading environment, the accuracy of channel transfer function estimated at the significant attenuated frequency component is much degraded. In the proposed technique, random phase sequence is multiplied to the information data sequence for constructing the flat frequency spectrum. As a result, the frequency diversity gain is enlarged and the accuracy of channel estimation by DDCE is improved. Furthermore we propose the blind estimation technique for the random phase sequence selected by transmitter. We show the effects of the proposed scheme by computer simulation.

Determining the characteristics of the dynamic behavior of carbon dioxide in a rock mass is a stage in the process of assessing a potential CO2 storage reservoir. The aim of this study was to analyze the process of CO2 storage in saline aquifers of the selected regions of the Upper Silesian Coal Basin in Poland. The construction of dynamic simulation models was based on static models of real deposit structures developed on a regional scale. Different simulation variants of the CO2 storage process were adopted, varying in terms of injection efficiency and duration of individual simulation phases. The analysis examined the influence of the degree of hydrodynamic openness of the structure on the CO2 storage process, in each of the variants. The results of numerical simulations showed that among the three analyzed geological formations, the Dębowiec formation is the most prospective for potential CO2 storage and is characterized by the most favorable geological and hydrogeological parameters. In the best variant of the simulation, in which the safety of CO2 storage in the rock mass was taken into account, the total amount of CO2 injected in a single directional well was approximately 8.54 million Mg of CO2 during 25 years of injection.

Conceptualization and finite element groundwater flow modeling of a flooded underground mine reservoir in the Asturian Coal Basin, Spain

New statistical models of nonergodic cognitive systems and their pathologies

We recently developed a dynamic force matching technique for converting a coarse-grained (CG) model of a molecular system, with a CG potential energy function, into a dynamic CG model with realistic dynamics [A. Davtyan et al., J. Chem. Phys. 142, 154104 (2015)]. This is done by supplementing the model with additional degrees of freedom, called "fictitious particles." In that paper, we tested the method on CG models in which each molecule is coarse-grained into one CG point particle, with very satisfactory results. When the method was applied to a CG model of methanol that has two CG point particles per molecule, the results were encouraging but clearly required improvement. In this paper, we introduce a new type (called type-3) of fictitious particle that exerts forces on the center of mass of two CG sites. A CG model constructed using type-3 fictitious particles (as well as type-2 particles previously used) gives a much more satisfactory dynamic model for liquid methanol. In particular, we were able to construct a CG model that has the same self-diffusion coefficient and the same rotational relaxation time as an all-atom model of liquid methanol. Type-3 particles and generalizations of it are likely to be useful in converting more complicated CG models into dynamic CG models.

This paper denotes approaches to discrete-continuous process simulation via E-network. It covers principals of discrete-continuous process simulation via E-networks using the scheme of the interaction of static and dynamic components modeling. The construction of discrete-continuous process dynamic models is based on the state space method and is implemented by using E-network.

The paper describes a new approach to model building GRIPS (Graphic Interactive Programming System). GRIPS is a software package enabling the model builder to quickly develop a running program of his simulation model by simply putting his flow chart on the computer and let GRIPS do the rest. The block diagram of a model is sketched on a video screen using a lightpen. The program then interactively requests all necessary information such as model parameters and initial conditions to carry out a simulation run. The set of equations necessary and sufficient to describe the behavior of the dynamic model is generated internally from the available input information. After the model response is computed the user may choose among several formats for output of the results. Graphical representation as well as numerical results can be output on the screen or teletype. Structural and parametric changes of the model are easily accomplished and the effect of these changes can be observed almost immediately.KeywordsBlock DiagramEpidemic ModelVideo ScreenMini ComputerStructural InterconnectionThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Nanoscale electrothermal co-simulation: compact dynamic models of hyperbolic heat transport and self-consistent device Monte Carlo

This article explores how learning biological concepts can be facilitated by playing a video game that depicts interactions and processes at the subcellular level. Particularly, this article reviews the effects of a real-time strategy game that requires players to control the behavior of a virus and interact with cell structures in a way that resembles the actual behavior of biological agents. The evaluation of the video game presented here aims at showing that video games have representational advantages that facilitate the construction of dynamic mental models. Ultimately, the article shows that when video game’s characteristics come in contact with expert knowledge during game design, the game becomes an excellent medium for supporting the learning of disciplinary content related to dynamic processes. In particular, results show that students who participated in a game-based intervention aimed at teaching biology described a higher number of temporal-dependent interactions as measured by the coding of verbal protocols and drawings than students who used texts and diagrams to learn the same topic.

Experimental structural geology

With the increase of on-orbit maintenance and support requirements, the application of a space manipulator is becoming more promising. In actual operation, the strong coupling of the free-floating space robot itself and the unknown disturbance of the contact target caused a major challenge to the robot base posture control. Traditional Reaction Null Space (RNS) motion planning and control methods require the construction of precise dynamic models, which is impossible in reality. In order to solve this problem, this paper proposes a new Adaptive Reaction Null Space (ARNS) path planning and control strategy for the contact of free-floating space robots with unknown targets. The ARNS path planning strategy is constructed by the Variable Forgetting Factor Recursive Least Squares (VFF–RLS) algorithm. At the same time, a robust adaptive control strategy based on the Strategy Self-Adaption Differential Evolution–Extreme Learning Machine (SSADE–ELM) algorithm is proposed to track the dynamic changes of the planned path. The algorithm enables us to intelligently learn and compensate for the unknown disturbance. Then, this paper constructs a robust controller to compensate model uncertainty. A striking feature of the proposed strategy is that it does not require an accurate system model or any information about unknown attributes. This design can dynamically implement RNS path tracking performance. Finally, through simulation and experiment, the proposed algorithm is compared with the existing methods to prove its effectiveness and superiority.