scholarly journals A systems engineering approach to validation of a pulmonary physiology simulator for clinical applications

2010 ◽  
Vol 8 (54) ◽  
pp. 44-55 ◽  
Author(s):  
A. Das ◽  
Z. Gao ◽  
P. P. Menon ◽  
J. G. Hardman ◽  
D. G. Bates
Keyword(s):  
Simulation Model ◽  
Systems Engineering ◽  
Best Practice ◽  
Optimization Methods ◽  
Population Heterogeneity ◽  
Model Parameters ◽  
General Applicability ◽  
Disease Heterogeneity ◽  
Pulmonary Physiology

Physiological simulators which are intended for use in clinical environments face harsh expectations from medical practitioners; they must cope with significant levels of uncertainty arising from non-measurable parameters, population heterogeneity and disease heterogeneity, and their validation must provide watertight proof of their applicability and reliability in the clinical arena. This paper describes a systems engineering framework for the validation of an in silico simulation model of pulmonary physiology. We combine explicit modelling of uncertainty/variability with advanced global optimization methods to demonstrate that the model predictions never deviate from physiologically plausible values for realistic levels of parametric uncertainty. The simulation model considered here has been designed to represent a dynamic in vivo cardiopulmonary state iterating through a mass-conserving set of equations based on established physiological principles and has been developed for a direct clinical application in an intensive-care environment. The approach to uncertainty modelling is adapted from the current best practice in the field of systems and control engineering, and a range of advanced optimization methods are employed to check the robustness of the model, including sequential quadratic programming, mesh-adaptive direct search and genetic algorithms. An overview of these methods and a comparison of their reliability and computational efficiency in comparison to statistical approaches such as Monte Carlo simulation are provided. The results of our study indicate that the simulator provides robust predictions of arterial gas pressures for all realistic ranges of model parameters, and also demonstrate the general applicability of the proposed approach to model validation for physiological simulation.

Simulation of calcium homeostasis: modeling and parameter estimation

1983 ◽  
Vol 245 (5) ◽  
pp. R664-R672 ◽  
Author(s):  
S. Hurwitz ◽  
S. Fishman ◽  
A. Bar ◽  
M. Pines ◽  
G. Riesenfeld ◽  
...  
Keyword(s):  
Simulation Model ◽  
Plasma Calcium ◽  
Model Parameters ◽  
Estimation Of Parameters ◽  
Designed Experiments ◽  
Calcium Loading ◽  
Infusion Experiment ◽  
Dose Model ◽  
Edta Infusion

The system that regulates plasma calcium in the bird has been formalized into a model based on a series of differential equations and solved by computer simulation. Bone, kidney, and intestine have been considered as the control subsystems, with parathyroid hormone and 1,25-dihydroxycholecalciferol as the regulating hormones. The parameters used in the simulation model have been computed either from published results or by specifically designed experiments described here. For the estimation of parameters, an iterative procedure has been developed that was designed to minimize the sum of square errors between observed and system-simulated values. Parameters of 1,25-dihydroxycholecalciferol metabolism were experimentally obtained from the kinetic behavior of the 3H-labeled hormone in rachitic birds after a single dose. Model parameters have been adjusted using the results of in vivo calcium loading and validated by an EDTA infusion experiment. The simulation model has been used to study the hierarchy of the activities of the three control subsystems and of the regulating hormones, at different calcium intakes. Positive or negative errors in plasma calcium resulted in an asymmetry in the activities of the controlling systems, bone and kidney, whereas the intestine is characterized by its relatively long response time.

scholarly journals Influence of Selected Model Parameters on the Electromagnetic Levitation Melting Efficiency

2021 ◽  
Vol 11 (9) ◽  
pp. 3827
Author(s):  
Blazej Nycz ◽  
Lukasz Malinski ◽  
Roman Przylucki
Keyword(s):  
Electromagnetic Levitation ◽  
Optimization Methods ◽  
Calculation Model ◽  
Model Parameters ◽  
Starting Point ◽  
Low Efficiency ◽  
The Relationship ◽  
Reactive Metals ◽  
Electromagnetic Levitation Melting ◽  
Metal Melting

The article presents the results of multivariate calculations for the levitation metal melting system. The research had two main goals. The first goal of the multivariate calculations was to find the relationship between the basic electrical and geometric parameters of the selected calculation model and the maximum electromagnetic buoyancy force and the maximum power dissipated in the charge. The second goal was to find quasi-optimal conditions for levitation. The choice of the model with the highest melting efficiency is very important because electromagnetic levitation is essentially a low-efficiency process. Despite the low efficiency of this method, it is worth dealing with it because is one of the few methods that allow melting and obtaining alloys of refractory reactive metals. The research was limited to the analysis of the electromagnetic field modeled three-dimensionally. From among of 245 variants considered in the article, the most promising one was selected characterized by the highest efficiency. This variant will be a starting point for further work with the use of optimization methods.

scholarly journals Formulating the history matching problem with consistent error statistics

2021 ◽  
Author(s):  
Geir Evensen
Keyword(s):  
Simulation Model ◽  
Measurement Errors ◽  
History Matching ◽  
Critical Role ◽  
Bayes Theorem ◽  
Conditional Probability Density ◽  
Model Parameters ◽  
Rate Data ◽  
Matching Problem ◽  
Reservoir Prediction

AbstractIt is common to formulate the history-matching problem using Bayes’ theorem. From Bayes’, the conditional probability density function (pdf) of the uncertain model parameters is proportional to the prior pdf of the model parameters, multiplied by the likelihood of the measurements. The static model parameters are random variables characterizing the reservoir model while the observations include, e.g., historical rates of oil, gas, and water produced from the wells. The reservoir prediction model is assumed perfect, and there are no errors besides those in the static parameters. However, this formulation is flawed. The historical rate data only approximately represent the real production of the reservoir and contain errors. History-matching methods usually take these errors into account in the conditioning but neglect them when forcing the simulation model by the observed rates during the historical integration. Thus, the model prediction depends on some of the same data used in the conditioning. The paper presents a formulation of Bayes’ theorem that considers the data dependency of the simulation model. In the new formulation, one must update both the poorly known model parameters and the rate-data errors. The result is an improved posterior ensemble of prediction models that better cover the observations with more substantial and realistic uncertainty. The implementation accounts correctly for correlated measurement errors and demonstrates the critical role of these correlations in reducing the update’s magnitude. The paper also shows the consistency of the subspace inversion scheme by Evensen (Ocean Dyn. 54, 539–560 2004) in the case with correlated measurement errors and demonstrates its accuracy when using a “larger” ensemble of perturbations to represent the measurement error covariance matrix.

FE-basierte Analyse*/FE-based analysis of the influence of remachining on component characteristics adjusted by forming processes

2018 ◽  
Vol 108 (01-02) ◽  
pp. 41-46
Author(s):  
F. Vogel ◽  
M. Tiffe ◽  
M. Metzger ◽  
D. Prof. Biermann
Keyword(s):  
Simulation Model ◽  
Fe Analysis ◽  
Experimental Investigations ◽  
Model Parameters ◽  
Sequential Process ◽  
Process Chain ◽  
Innovative Material

Bei der Auslegung verknüpfter Prozessschritte zur Herstellung von Bauteilen mit gezielt eingestellten Eigenschaften finden vermehrt FE-basierte Simulationssysteme Anwendung, um den Aufwand experimenteller Untersuchungen insbesondere im Hinblick auf den gesteigerten Einsatz innovativer Werkstoffkonzepte gering zu halten. Im Folgenden wird die Ausarbeitung von Konzepten zur Anpassung von Parametern zur Materialmodellierung sowie zur Verknüpfung von Einzelsimulationen der Prozesskette erläutert.   Regarding the increased application of innovative material concepts in sequential process steps for manufacturing components with tailored properties, the FE-analysis can be used to reduce the effort of experimental investigations. In this article, the development of concepts for the adjustment of simulation model parameters and the conjunction of process chain single simulations are described.

scholarly journals Model Driven Combat Effectiveness Simulation Systems Engineering

2020 ◽  
Vol 70 (1) ◽  
pp. 54-59
Author(s):  
Zhi Zhu ◽  
Yonglin Lei ◽  
Yifan Zhu
Keyword(s):  
Decision Making ◽  
Simulation Model ◽  
Conceptual Model ◽  
Systems Engineering ◽  
Simulation Models ◽  
Proof Of Concept ◽  
Model Driven Engineering ◽  
Model Driven ◽  
Combat Effectiveness ◽  
Simulation Systems

Model-driven engineering has become popular in the combat effectiveness simulation systems engineering during these last years. It allows to systematically develop a simulation model in a composable way. However, implementing a conceptual model is really a complex and costly job if this is not guided under a well-established framework. Hence this study attempts to explore methodologies for engineering the development of simulation models. For this purpose, we define an ontological metamodelling framework. This framework starts with ontology-aware system conceptual descriptions, and then refines and transforms them toward system models until they reach final executable implementations. As a proof of concept, we identify a set of ontology-aware modelling frameworks in combat systems specification, then an underwater targets search scenario is presented as a motivating example for running simulations and results can be used as a reference for decision-making behaviors.

Numerical and Experimental Analysis of Self Piercing Riveting Process with Carbon Fiber-Reinforced Plastic and Aluminium Sheets

2013 ◽  
Vol 554-557 ◽  
pp. 1045-1054 ◽  
Author(s):  
Welf Guntram Drossel ◽  
Reinhard Mauermann ◽  
Raik Grützner ◽  
Danilo Mattheß
Keyword(s):  
Finite Element ◽  
Carbon Fiber ◽  
Finite Element Model ◽  
Simulation Model ◽  
Process Parameters ◽  
Process Model ◽  
Element Model ◽  
Model Parameters ◽  
Fiber Reinforced ◽  
Carbon Fiber Reinforced

In this study a numerical simulation model was designed for representing the joining process of carbon fiber-reinforced plastics (CFRP) and aluminum alloy with semi-tubular self-piercing rivet. The first step towards this goal is to analyze the piercing process of CFRP numerical and experimental. Thereby the essential process parameters, tool geometries and material characteristics are determined and in finite element model represented. Subsequently the finite element model will be verified and calibrated by experimental studies. The next step is the integration of the calibrated model parameters from the piercing process in the extensive simulation model of self-piercing rivet process. The comparison between the measured and computed values, e.g. process parameters and the geometrical connection characteristics, shows the reached quality of the process model. The presented method provides an experimental reliable characterization of the damage of the composite material and an evaluation of the connection performances, regarding the anisotropic property of CFRP.

scholarly journals Weighting neurons by selectivity produces near-optimal population codes

2019 ◽  
Vol 121 (5) ◽  
pp. 1924-1937
Author(s):  
Elizabeth Zavitz ◽  
Nicholas S. C. Price
Keyword(s):  
A Priori ◽  
Maximum Level ◽  
Optimization Methods ◽  
Neuronal Population ◽  
Direction Selectivity ◽  
Motion Direction ◽  
Temporal Area ◽  
Linear Discriminant ◽  
Preferred Direction

Perception is produced by “reading out” the representation of a sensory stimulus contained in the activity of a population of neurons. To examine experimentally how populations code information, a common approach is to decode a linearly weighted sum of the neurons’ spike counts. This approach is popular because of the biological plausibility of weighted, nonlinear integration. For neurons recorded in vivo, weights are highly variable when derived through optimization methods, but it is unclear how the variability affects decoding performance in practice. To address this, we recorded from neurons in the middle temporal area (MT) of anesthetized marmosets ( Callithrix jacchus) viewing stimuli comprising a sheet of dots that moved coherently in 1 of 12 different directions. We found that high peak response and direction selectivity both predicted that a neuron would be weighted more highly in an optimized decoding model. Although learned weights differed markedly from weights chosen according to a priori rules based on a neuron’s tuning profile, decoding performance was only marginally better for the learned weights. In the models with a priori rules, selectivity is the best predictor of weighting, and defining weights according to a neuron’s preferred direction and selectivity improves decoding performance to very near the maximum level possible, as defined by the learned weights. NEW & NOTEWORTHY We examined which aspects of a neuron’s tuning account for its contribution to sensory coding. Strongly direction-selective neurons are weighted most highly by optimal decoders trained to discriminate motion direction. Models with predefined decoding weights demonstrate that this weighting scheme causally improved direction representation by a neuronal population. Optimizing decoders (using a generalized linear model or Fisher’s linear discriminant) led to only marginally better performance than decoders based purely on a neuron’s preferred direction and selectivity.

The Influence of Measured Trajectory Based Model Parameters Correcting on Simulation Precision of Power System Dynamic Frequency

2013 ◽  
Vol 448-453 ◽  
pp. 2545-2550
Author(s):  
Gang Mu ◽  
Ming Li ◽  
Jun An ◽  
Xing Wei Xu ◽  
Shuai Shao
Keyword(s):  
Numerical Simulation ◽  
Simulation Model ◽  
Process Simulation ◽  
Northeast China ◽  
Operation Mode ◽  
Measured Data ◽  
Model Parameters ◽  
Conservative Operation ◽  
Generator Frequency ◽  
Dynamic Frequency

Although numerical simulation is an important method of researching dynamic frequency process, obvious deviations have been found between numerical simulation and the measured trajectory in many accidents. And the existing simulation model and parameters cannot describe the actual dynamic process of frequency accurately. Research was carried out on the influence of four parameters to the dynamic frequency process, which based on the WSCC system. The four parameters include the inertia constant of generator, generator frequency coefficient, dead band and turbine intermediate superheating coefficient. Northeast China power grid and measured data are used to verify the above research conclusion. Checking the dynamic frequency process simulation model and parameters can improve the accuracy of dynamic frequency process simulation on the base of the measured trajectory and the physical characteristics of the parameters. It can also give efficient foundation for the setting work of UFLS, overcoming the previous conservative operation mode and so on.

Construction of Multi-Domain System Simulation Model for Trade Studies in System Design Considering Multiple Scenes

2019 ◽  
Author(s):  
Kazuya Oizumi ◽  
Keita Ishida ◽  
Yoshihiro Uchibori ◽  
Kazuhiro Aoyama
Keyword(s):  
Simulation Model ◽  
System Design ◽  
Systems Engineering ◽  
System Simulation ◽  
Cognitive Model ◽  
Simulation Models ◽  
Modelling Method ◽  
Variable Transmission ◽  
Physical Phenomena ◽  
Model Based Systems Engineering

Abstract As a product is sold globally, usages of the product have much wider variety. Thus, a product needs to be designed considering multiple scenes. To certify that the product performs properly in any scene, industries started to apply Model Based Systems Engineering (MBSE). Whereas multi-domain system simulations are regarded as a prominent approach for the system design of a product, construction of model depends on knowledge and sense modelers. This paper proposes a modelling method to construct appropriate multi-domain system simulation models while reducing dependencies to senses of modelers. The proposed method comprises two parts. First, significant tradeoffs to be studied by the simulation are specified. Second, features of simulation models are deliberated for specified tradeoffs. To specify significant tradeoffs, product and scenes where the product is used are integrated into a model. Further, to deliberate features of simulation model, cognitive model of physical phenomena in a product is employed as well. The proposed method was applied to the development of continuously variable transmission to verify its validity.

scholarly journals In Silico Performance of a Recellularized Tissue-Engineered Transcatheter Aortic Valve

2019 ◽  
Vol 141 (6) ◽  
Author(s):  
Christopher Noble ◽  
Joshua Choe ◽  
Susheil Uthamaraj ◽  
Milton Deherrera ◽  
Amir Lerman ◽  
...  
Keyword(s):  
Mechanical Behavior ◽  
Heart Valves ◽  
Mechanical Response ◽  
Mechanical Performance ◽  
Fe Analysis ◽  
Model Parameters ◽  
Biaxial Testing ◽  
Principal Stresses

Commercially available heart valves have many limitations, such as a lack of remodeling, risk of calcification, and thromboembolic problems. Many state-of-the-art tissue-engineered heart valves (TEHV) rely on recellularization to allow remodeling and transition to mechanical behavior of native tissues. Current in vitro testing is insufficient in characterizing a soon-to-be living valve due to this change in mechanical response; thus, it is imperative to understand the performance of an in situ valve. However, due to the complex in vivo environment, this is difficult to accomplish. Finite element (FE) analysis has become a standard tool for modeling mechanical behavior of heart valves; yet, research to date has mostly focused on commercial valves. The purpose of this study has been to evaluate the mechanical behavior of a TEHV material before and after 6 months of implantation in a rat subdermis model. This model allows the recellularization and remodeling potential of the material to be assessed via a simple and inexpensive means prior to more complex ovine orthotropic studies. Biaxial testing was utilized to evaluate the mechanical properties, and subsequently, constitutive model parameters were fit to the data to allow mechanical performance to be evaluated via FE analysis of a full cardiac cycle. Maximum principal stresses and strains from the leaflets and commissures were then analyzed. The results of this study demonstrate that the explanted tissues had reduced mechanical strength compared to the implants but were similar to the native tissues. For the FE models, this trend was continued with similar mechanical behavior in explant and native tissue groups and less compliant behavior in implant tissues. Histology demonstrated recellularization and remodeling although remodeled collagen had no clear directionality. In conclusion, we observed successful recellularization and remodeling of the tissue giving confidence to our TEHV material; however, the mechanical response indicates the additional remodeling would likely occur in the aortic/pulmonary position.

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