scholarly journals Effect of Time Delays in Characterizing Continuous Mixing of Aqueous Xanthan Gum Solutions

2021 ◽  
Author(s):  
Vishal Kumar Patel
Keyword(s):  
Dynamic Model ◽  
Discrete Time ◽  
Time Domain ◽  
Time Delays ◽  
Xanthan Gum ◽  
Dynamic Models ◽  
Hybrid Genetic Algorithm ◽  
Mixed Volume ◽  
Model Parameters ◽  
Continuous Mixing

Aqueous xanthan gum solutions are non-Newtonian fluids, pseudoplastic fluids possessing yield stress. Their continuous mixing is an extremely complicated phenomenon exhibiting non idealities such as channeling, recirculation and stagnation. To characterize the continuous mixing of xanthan gum solutions, three dynamic models were utilized: (1) a dynamic model with 2 time delays in discrete time domain, (2) a dynamic model with 2 time delays in continuous time domain, and (3) a simplified dynamic model with 1 time delay in discrete time domain. A hybrid genetic algorithm was employed to estimate the model parameters through the experimental input-output dynamic data. The extents of channeling and fully-mixed volume were used to compare the performances of these three models. The dynamic model parameters exerting strong influence on the model response were identified. It was observed that the models with 2 time delays gave a better match with the experimental results.

scholarly journals Effect of Time Delays in Characterizing Continuous Mixing of Aqueous Xanthan Gum Solutions

2021 ◽  
Author(s):  
Vishal Kumar Patel
Keyword(s):  
Dynamic Model ◽  
Discrete Time ◽  
Time Domain ◽  
Time Delays ◽  
Xanthan Gum ◽  
Dynamic Models ◽  
Hybrid Genetic Algorithm ◽  
Mixed Volume ◽  
Model Parameters ◽  
Continuous Mixing

Aqueous xanthan gum solutions are non-Newtonian fluids, pseudoplastic fluids possessing yield stress. Their continuous mixing is an extremely complicated phenomenon exhibiting non idealities such as channeling, recirculation and stagnation. To characterize the continuous mixing of xanthan gum solutions, three dynamic models were utilized: (1) a dynamic model with 2 time delays in discrete time domain, (2) a dynamic model with 2 time delays in continuous time domain, and (3) a simplified dynamic model with 1 time delay in discrete time domain. A hybrid genetic algorithm was employed to estimate the model parameters through the experimental input-output dynamic data. The extents of channeling and fully-mixed volume were used to compare the performances of these three models. The dynamic model parameters exerting strong influence on the model response were identified. It was observed that the models with 2 time delays gave a better match with the experimental results.

Topology Optimization for Piecewise Dynamic Models Using a Genetic Algorithm

2010 ◽  
Author(s):  
Yi Liu ◽  
Dragan Djurdjanovic
Keyword(s):  
Genetic Algorithm ◽  
Topology Optimization ◽  
Dynamic Model ◽  
Dynamic Models ◽  
Optimization Procedure ◽  
Nonlinear Dynamic System ◽  
Local Model ◽  
Model Parameters ◽  
Highly Nonlinear ◽  
Node Connectivity

It has been demonstrated in the previous research that the node connectivity in the graph encoding the topological neighborhood relationships between local models in a piecewise dynamic model may significantly affect the cooperative learning process. It was shown that a graph with a larger connectivity leads to a quicker learning adaption due to more rapidly decaying transients of the estimation of local model parameters. In the same time, it was shown that the accuracy could be degraded by a larger bias in the asymptotic portion of the estimations of local model parameters. The efforts in topology optimization should therefore strive towards a high accuracy of the asymptotic portion of the estimator of local model parameters while simultaneously accelerating the decay of the estimation transients. In this paper, we pursue minimization of the residual sum of squares of a piecewise dynamic model after a predetermined number of training steps. The optimization of inter-model topology is implemented via a genetic algorithm that manipulates adjacency matrices of the graph underlying the piecewise dynamic model. An example of applying the topology optimization procedure on a peicewise linear model of a highly nonlinear dynamic system is provided to show the efficacy of the new method.

A parameter identification method for robot dynamic models using a balancing mechanism

Robotica ◽  
1989 ◽  
Vol 7 (4) ◽  
pp. 327-337 ◽  
Author(s):  
T. G. Lim ◽  
H. S. Cho ◽  
W. K. Chung
Keyword(s):  
Dynamic Model ◽  
Dynamic Models ◽  
Least Square ◽  
Estimation Accuracy ◽  
Model Parameters ◽  
Robot Dynamics ◽  
Dynamic Parameters ◽  
Joint Torques ◽  
Motion Data ◽  
Identification Method

SUMMARYAccurate modeling of robot dynamics is a prerequisite for the design of model-based control schemes and enhancement of the performance of the robot. The dynamic parameters associated with a pseudo-inertia matrix are often difficult to identify accurately because the inertia torques are small in comparison to gravity loadings, thus creating signal processing problem. The identification method presented in this paper utilizes a balancing mechanism which increases the estimation accuracy of the dynamic parameters. The balancing mechanism has the effect of amplifying the inertia-related torque signal by eliminating gravity loadings acting on the robot joints. A series of motion data were experimentally obtained through sequential test steps. By incorporating the measured information about joint torques, angular positions, velocities and accelerations the least square algorithm was used to identify the dynamic parameters. The estimated values were converted to those of the original robot model to obtain its dynamic model parameters. The identified robot dynamic model was shown to be accurate enough to predict the actual robot motions.

Nonlinear Dynamic Model of a Two-Stage Pressure Relief Valve for Designers

2001 ◽  
Vol 124 (1) ◽  
pp. 62-66 ◽  
Author(s):  
Pei-Sun Zung ◽  
Ming-Hwei Perng
Keyword(s):  
Dynamic Model ◽  
Nonlinear Dynamic ◽  
Dynamic Models ◽  
Operating Conditions ◽  
Model Parameters ◽  
Nonlinear Dynamic Model ◽  
Relief Valve ◽  
Two Stage ◽  
Pressure Relief ◽  
Wide Range

This paper presents a handy nonlinear dynamic model for the design of a two stage pilot pressure relief servo-valve. Previous surveys indicate that the performance of existing control valves has been limited by the lack of an accurate dynamic model. However, most of the existing dynamic models of pressure relief valves are developed for the selection of a suitable valve for a hydraulic system, and assume model parameters which are not directly controllable during the manufacturing process. As a result, such models are less useful for a manufacturer eager to improve the performance of a pressure valve. In contrast, model parameters in the present approach have been limited to dimensions measurable from the blue prints of the valve such that a specific design can be evaluated by simulation before actually manufacturing the valve. Moreover, the resultant model shows excellent agreement with experiments in a wide range of operating conditions.

scholarly journals Discrete-Time Model of Seasonal Plankton Bloom

2020 ◽  
Vol 15 (2) ◽  
pp. 235-250
Author(s):  
G.P. Neverova ◽  
O.L. Zhdanova ◽  
A.I. Abakumov
Keyword(s):  
Dynamic Model ◽  
Discrete Time ◽  
Field Experiments ◽  
Initial Conditions ◽  
Numerical Study ◽  
Classical System ◽  
Zooplankton Community ◽  
Dynamic Mode ◽  
Model Parameters ◽  
Delayed Response

The most interesting results in modeling phytoplankton bloom were obtained based on a modification of the classical system of phytoplankton and zooplankton interaction. The modifications using delayed equations, as well as piecewise continuous functions with a delayed response to intoxication processes, made it possible to obtain adequate phytoplankton dynamics like in nature. This work develops a dynamic model of phytoplankton-zooplankton community consisting of two equations with discrete time. We use recurrent equations, which allows to describe delay in response naturally. The proposed model takes into account the phytoplankton toxicity and zooplankton response associated with phytoplankton toxicity. We use a discrete analogue of the Verhulst model to describe the dynamics of each of the species in the community under autoregulation processes. We use Holling-II type response function taking into account predator saturation to describe decrease in phytoplankton density due to its consumption by zooplankton. Growth and survival rates of zooplankton also depend on its feeding. Zooplankton mortality, caused by an increase in the toxic substances concentration with high density of zooplankton, is included in the limiting processes. An analytical and numerical study of the model proposed is made. The analysis shows that the stability loss of nontrivial fixed point corresponding to the coexistence of phytoplankton and zooplankton can occur through a cascade of period doubling bifurcations and according to the Neimark-Saker scenario leading to the appearance of quasiperiodic fluctuations as well. The proposed dynamic model of the phytoplankton and zooplankton community allows observing long-period oscillations, which is consistent with the results of field experiments. As well, the model have multistability areas, where a variation in initial conditions with the unchanged values of all model parameters can result in a shift of the current dynamic mode.

Modeling the combined efficacy of rilotumumab (R; AMG 102) plus epirubicin/cisplatin/capecitabine (ECX) for the treatment of locally advanced or metastatic gastric or esophagogastric junction (G/EGJ) cancer.

2012 ◽  
Vol 30 (15_suppl) ◽  
pp. 2594-2594 ◽  
Author(s):  
Sameer Doshi ◽  
Steven Kathman ◽  
Rui Tang ◽  
Per Olsson Gisleskog ◽  
Elwyn Loh ◽  
...  
Keyword(s):  
Tumor Growth ◽  
Dynamic Model ◽  
Discrete Time ◽  
Tumor Size ◽  
Survival Model ◽  
Population Pharmacokinetic ◽  
Model Parameters ◽  
Combined Effects ◽  
Phase 2 ◽  
Tumor Reduction

2594 Background: R is an investigational, fully human monoclonal antibody to hepatocyte growth factor/scatter factor (HGF/SF) that inhibits signaling though the MET receptor. In a double-blind, placebo-controlled, phase 2 trial of 121 patients with G/EGJ cancer, R (7.5 or 15 mg/kg) + ECX showed trends for improved progression-free survival (PFS) and overall survival compared to ECX alone. The combined effects of R and ECX on tumor reduction and PFS were modeled using the phase 2 data. Methods: A population pharmacokinetic (PK) model was used to estimate R PK parameters and individual R concentrations (C) over time. A tumor dynamic model was developed to characterize the combined effects of R with ECX on tumor growth and cell death and to evaluate the impact of baseline patient characteristics and lab values on model parameters. A discrete time-survival model was developed with PFS and C data to evaluate the effect of R, ECX, and the interaction between R and ECX on PFS within a given time interval. Results: R exhibited linear PKs with an estimated mean clearance of 0.216 L/d/70 kg. The tumor dynamic model suggested that R and ECX worked jointly to reduce tumor size from baseline via inhibition of the tumor growth rate constant (Kgrowth) and stimulation of the death rate of tumor cells (Kdeath). Assuming the maximal inhibition of Kgrowth is 100%, the estimated mean C that provided 50% maximal Kgrowth inhibition (EC50) was 6.71 µg/mL. The mean (SD) estimated effect of 7.5 and 15 mg/kg R on Kgrowth was 90.1% (3.8%) and 95.5% (1.9%) inhibition, respectively. None of the tested baseline factors appeared to significantly affect tumor reduction by R + ECX. In the discrete time-survival model, the R and ECX combination significantly improved PFS, and the model suggests that the magnitude of the effect of one treatment was dependent on the other. Conclusions: R and ECX appeared to work in combination to decrease tumor size and to improve PFS.

Optimal Web Guiding

2009 ◽  
Vol 132 (1) ◽  
Author(s):  
Aravind Seshadri ◽  
Prabhakar R. Pagilla
Keyword(s):  
Dynamic Model ◽  
Dynamic Models ◽  
Fiber Optic ◽  
Operating Conditions ◽  
Model Parameters ◽  
Linear Quadratic ◽  
Position Measurement ◽  
Series Of Experiments ◽  
Correct Application ◽  
Selection Of

This paper presents an optimal web guiding strategy based on the dynamic analysis of the lateral web behavior and a new fiber optic lateral web position measurement sensor. First, a lateral dynamic model of a moving web is revisited with an emphasis on correct application of appropriate boundary conditions. Then the dynamic models of two common intermediate guides (remotely pivoted guide and offset-pivot guide) are investigated. The effect of various model parameters on lateral web behavior is analyzed and discussions on proper selection of the parameters are given. Based on the model analysis, we discuss the design of a linear quadratic optimal controller that is capable of accommodating structured parametric uncertainties in the lateral dynamic model. The optimal guide control system is evaluated by a series of experiments on a web platform with different web materials under various operating conditions. Implementation of the controller with a new fiber optic lateral sensor for different scenarios is discussed. Results show good guiding performance in the presence of disturbances and with uncertainties in the model parameters.

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