Implicit Co-Simulation and Solver-Coupling: Efficient Calculation of Interface-Jacobian and Coupling Sensitivities/Gradients

Author(s):  
Jan Kraft ◽  
Stefan Klimmek ◽  
Tobias Meyer ◽  
Bernhard Schweizer

Abstract We consider implicit co-simulation and solver-coupling methods, where different subsystems are coupled in time domain in a weak sense. Within such weak coupling approaches, a macro-time grid is introduced. Between the macro-time points, the subsystems are integrated independently. The subsystems only exchange information at the macro-time points. To describe the connection between the subsystems, coupling variables have to be defined. For many implicit co-simulation and solver-coupling approaches an Interface-Jacobian is required. The Interface-Jacobian describes, how certain subsystem state variables at the interface depend on the coupling variables. Concretely, the Interface-Jacobian contains partial derivatives of the state variables of the coupling bodies with respect to the coupling variables. Usually, these partial derivatives are calculated numerically by means of a finite difference approach. A calculation of the coupling gradients based on finite differences may entail problems with respect to the proper choice of the perturbation parameters and may therefore cause problems due to ill-conditioning. A second drawback is that additional subsystem integrations with perturbed coupling variables have to be carried out. In this manuscript, analytical approximation formulas for the Interface-Jacobian are derived, which may be used alternatively to numerically calculated gradients based on finite differences. Applying these approximation formulas, numerical problems with ill-conditioning can be circumvented. Moreover, efficiency of the implementation may be increased, since parallel simulations with perturbed coupling variables can be omitted. The derived approximation formulas converge to the exact gradients for small macro-step sizes.

Author(s):  
Thanner Malai Perumal ◽  
Rudiyanto Gunawan

Studies performed at single-cell resolution have demonstrated the physiological significance of cell-to-cell variability. Various types of mathematical models and systems analyses of biological networks have further been used to gain a better understanding of the sources and regulatory mechanisms of such variability. In this work, we present a novel sensitivity analysis method, called molecular density function perturbation (MDFP), for the dynamical analysis of cellular heterogeneity. The proposed analysis is based on introducing perturbations to the density or distribution function of the cellular state variables at specific time points, and quantifying how such perturbations affect the state distribution at later time points. We applied the MDFP analysis to a model of signal transduction pathway involved in TRAIL (tumor necrosis factor-related apoptosis-inducing ligand)-induced apoptosis in HeLa cells. The MDFP analysis showed that caspase-8 activation regulates the timing of the switch-like increase of cPARP (cleaved poly(ADP-ribose) polymerase), an indicator of apoptosis. Meanwhile, the cell-to-cell variability in the commitment to apoptosis depended on mitochondrial outer membrane permeabilization (MOMP) and events following MOMP, including the release of Smac (second mitochondria-derived activator of caspases) and cytochrome-C from mitochondria, the inhibition of XIAP (X-linked inhibitor of apoptosis) by Smac and the formation of apoptosome.


1999 ◽  
Vol 122 (3) ◽  
pp. 542-550 ◽  
Author(s):  
Cyril Coumarbatch ◽  
Zoran Gajic

In this paper we show how to completely and exactly decompose the optimal Kalman filter of stochastic systems in multimodeling form in terms of one pure-slow and two pure-fast, reduced-order, independent, Kalman filters. The reduced-order Kalman filters are all driven by the system measurements. This leads to a parallel Kalman filtering scheme and removes ill-conditioning of the original full-order singularly perturbed Kalman filter. The results obtained are valid for steady state. In that direction, the corresponding algebraic filter Riccati equation is completely decoupled and solved in terms of one pure-slow and two pure fast, reduced-order, independent, algebraic Riccati equations. A nonsingular state transformation that exactly relates the state variables in the original and new coordinates (in which the required decomposition is achieved) is also established. The eighth order model of a passenger car under road disturbances is used to demonstrate efficiency of the proposed filtering technique. [S0022-0434(00)01703-2]


Author(s):  
Valeri Mladenov ◽  
Stoyan Kirilov

The basic purpose of the present paper is to propose an extended investigation and computer analysis of an anti-parallel memristor circuit with two equivalent memristor elements with different initial values of the state variables using a modified Boundary Condition Memristor (BCM) Model and the finite differences method. The memristor circuit is investigated for sinusoidal supply current at different magnitudes – for soft-switching and hard-switching modes, respectively. The influence of the initial values of the state variables on the circuit’s behaviour is presented as well. The equivalent i-v and memristance-flux and the other important relationshipsof the memristor circuit are also analyzed.


2010 ◽  
Vol 13 (02) ◽  
pp. 335-354 ◽  
Author(s):  
KYO YAMAMOTO ◽  
SEISHO SATO ◽  
AKIHIKO TAKAHASHI

This paper studies the probability distribution and option pricing for drawdown in a stochastic volatility environment. Their analytical approximation formulas are derived by the application of a singular perturbation method (Fouque et al., 2000). The mathematical validity of the approximation is also proven. Then, numerical examples show that the instantaneous correlation between the asset value and the volatility state crucially affects the probability distribution and option prices for drawdown.


Author(s):  
Jan Kraft ◽  
Tobias Meyer ◽  
Bernhard Schweizer

Abstract This contribution deals with the parallelization of multibody systems by making use of co-simulation techniques. The overall model is split into a user-defined number of subsystems, which are coupled and computed by means of a co-simulation approach. The co-simulation methods considered here are weak coupling approaches, which implies that each subsystem is solved independently from the other subsystems within a macro-time step. Information (i.e. coupling variables) is only exchanged between the subsystems at certain communication-time points (macro-time points). Within each macro-time step, the unknown coupling variables are approximated by extrapolation polynomials. The separate integration of the subsystems is the crucial point for a parallelized computation. A main drawback of many co-simulation implementations is that they are based on a constant macro-step size. Using an equidistant communication-time grid may in many practical applications be not very efficient with respect to computation time, especially in connection with highly nonlinear models or in context with models with strongly varying quantities. Here, a co-simulation approach is presented which incorporates a macro-step size and order control algorithm. Numerical examples show the benefit of this implementation and the significant reduction in computation time compared to an implementation with an equidistant communication-time grid.


1974 ◽  
Vol 22 ◽  
pp. 145-148
Author(s):  
W. J. Klepczynski

AbstractThe differences between numerically approximated partial derivatives and partial derivatives obtained by integrating the variational equations are computed for Comet P/d’Arrest. The effect of errors in the IAU adopted system of masses, normally used in the integration of the equations of motion of comets of this type, is investigated. It is concluded that the resulting effects are negligible when compared with the observed discrepancies in the motion of this comet.


VASA ◽  
2014 ◽  
Vol 43 (1) ◽  
pp. 47-54 ◽  
Author(s):  
Weibin Huang ◽  
Weiwei Qin ◽  
Lei Lv ◽  
Haoyv Deng ◽  
Hao Zhang ◽  
...  

Background: Duffy antigen / receptor for chemokines (DARC) possesses high affinity for several chemokine subgroups of CC and CXC. Although DARC has been shown to play a role in many inflammatory diseases, its effect on chronic venous disease (CVD) remains unidentified. We explored whether the expression of DARC in skin tissue was activated under venous hypertension as well as the relationships between DARC and inflammation. Materials and methods: The inflammation in a rat model of venous hypertension caused by a femoral arterial-venous fistula (AVF) was studied. At specified intervals the pressure in the femoral veins was recorded within 42 days. Hindlimb skin specimens were harvested at different time points. The expressions of DARC, interleukin-8 (IL-8), and monocyte chemotactic protein-1 (MCP-1) in skin tissue were examined. Mononuclear cells infiltrated in skin tissue were detected. Results: Femoral venous pressures in AVF groups increased significantly at different time points (P < 0.01). DARC was expressed in skin tissue and its expression level increased significantly in AVF groups from the 7nd day on and was enhanced in a time-dependent manner within 42 days (P < 0.05). Meanwhile, both MCP-1 and IL-8 had higher levels, accompanied by increased mononuclear cells infiltrating into skin tissue (P < 0.05). Conclusions: A rat AVF model which can maintain venous hypertension for at least 42 days is competent for researching the pathogenesis of CVD. DARC, which plays a role in the inflammation of skin tissue under venous hypertension, may become a new molecular target for diagnosis and treatment of CVD at a very early stage.


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