A Dynamic Model for the Design of Methanol to Hydrogen Steam Reformers for Transportation Applications

2004 ◽  
Vol 126 (2) ◽  
pp. 149-158 ◽  
Author(s):  
Gregory L. Ohl ◽  
Jeffrey L. Stein ◽  
Gene E. Smith
Keyword(s):  
Response Time ◽  
Dynamic Model ◽  
First Principles ◽  
Initial Conditions ◽  
Design Parameters ◽  
Physical Parameters ◽  
Steam Reformer ◽  
Powerful Means ◽  
Steam Reformers ◽  
Transportation Applications

As an aid to improving the dynamic response of the steam reformer, a dynamic model is developed to provide preliminary characterizations of the major constraints that limit the ability of a reformer to respond to the varying output requirements occurring in vehicular applications. This model is a first principles model that identifies important physical parameters in the steam reformer. The model is then incorporated into a design optimization process, where minimum steam reformer response time is specified as the objective function. This tool is shown to have the potential to be a powerful means of determining the values of the steam reformer design parameters that yield the fastest response time to a step input in hydrogen demand for a given set of initial conditions. A more extensive application of this methodology, yielding steam reformer design recommendations, is contained in a related publication.

Fundamental Factors in the Design of a Fast-Responding Methanol-to-Hydrogen Steam Reformer for Transportation Applications

1996 ◽  
Vol 118 (2) ◽  
pp. 112-119 ◽  
Author(s):  
G. L. OhI ◽  
J. L. Stein ◽  
G. E. Smith
Keyword(s):  
Life Cycle ◽  
Power Plant ◽  
Dynamic Response ◽  
Response Time ◽  
Initial Conditions ◽  
Design Parameters ◽  
Maximum Output ◽  
Energy Storage Devices ◽  
Steam Reformer ◽  
Transportation Applications

Improving the dynamic response of the steam reformer in a fuel cell power plant designed for transportation applications will enable the power plant to operate in a transient manner with a reduced need for supplementary batteries and their associated cost, weight, and life cycle limitations. As a method of seeking improvements to the dynamic response, a sixth-order dynamic model of a steam reformer is used with a design optimization process to determine the values of the steam reformer design parameters which will yield the fastest response time to a step input in hydrogen demand under a variety of initial conditions. Results of this analysis suggest that a steam reformer designed to have a maximum output of approximately 12,600 mol/h of hydrogen and optimized for fast response could have response times on the order of 15–20 s. A sensitivity analysis suggests that this response can be achieved primarily by reducing the thermal capacity of the reformer and improving the rate of heat transfer to the gaseous constituents within the reformer. With a steam reformer response time on the order of 15–20 s, supplementary energy storage devices, such as the ultracapacitor and flywheel, become more feasible. These devices are attractive because they have superior life cycle and power density characteristics when compared with traditional chemical batteries.

scholarly journals A Shock Mitigation of Pedestrian-Vehicle Impact Using Active Hood Lift System: Deploying Time Investigation

2016 ◽  
Vol 2016 ◽  
pp. 1-17 ◽  
Author(s):  
Tae-Hoon Lee ◽  
Gun-Ha Yoon ◽  
Seung-Bok Choi
Keyword(s):  
Response Time ◽  
Design Parameters ◽  
Passenger Vehicle ◽  
Governing Equations ◽  
Total Response Time ◽  
Shock Mitigation ◽  
Vehicle Impact ◽  
Driving Speed ◽  
Working Principle ◽  
Principal Design

This paper investigates the deploying time (or response time) of an active hood lift system (AHLS) of a passenger vehicle activated by gunpowder actuator. In this work, this is accomplished by changing principal design parameters of the latch part mechanism of the hood system. After briefly introducing the working principle of the AHLS operated by the gunpowder actuator, the governing equations of the AHLS are formulated for each different deploying motion. Subsequently, using the governing equations, the response time for deploying the hold lift system is determined by changing several geometric distances such as the distance from the rotational center of the pop-up guide to the point of the latch in the axial and vertical directions. Then, a comparison is made of the total response time to completely deploy the hood lift system with the existing conventional AHLS and proposed AHLS. In addition, the workable driving speed of the proposed AHLS is compared with the conventional one by changing the powder volume of the actuator.

Updating Substructure Models With Dynamic Boundary Conditions

1995 ◽  
Author(s):  
Michael Link ◽  
Zheng Qian
Keyword(s):  
Boundary Conditions ◽  
Dynamic Stiffness ◽  
Design Parameters ◽  
Physical Parameters ◽  
Model Parameters ◽  
Dynamic Boundary Conditions ◽  
Main Structure ◽  
Modal Data ◽  
Residual Structure ◽  
Dynamic Boundary

Abstract In recent years procedures for updating analytical model parameters have been developed by minimizing differences between analytical and preferably experimental modal analysis results. Provided that the initial analysis model contains parameters capable of describing possible damage these techniques could also be used for damage detection. In this case the parameters are updated using test data before and after the damage. Looking at complex structures with hundreds of parameters one generally has to measure the modal data at many locations and try to reduce the number of unknown parameters by some kind of localization technique because the measurement information is generally not sufficient to identify all the parameters equally distributed all over the structure. Another way of reducing the number of parameters shall be presented here. This method is based on the idea of measuring only a part of the structure and replacing the residual structure by dynamic boundary conditions which describe the dynamic stiffness at the interfaces between the measured main structure and the remaining unmeasured residual structure. This approach has some advantage since testing could be concentrated on critical areas where structural modifications are expected either due to damage or due to intended design changes. The dynamic boundary conditions are expressed in Craig-Bampton (CB) format by transforming the mass and stiffness matrices of the unmeasured residual structure to the interface degrees of freedom (DOF) and to the modal DOFs of the residual structure fixed at the interface. The dynamic boundary stiffness concentrates all physical parameters of the residual structure in only a few parameters which are open for updating. In this approach damage or modelling errors within the unmeasured residual structure are taken into account only in a global sense whereas the measured main structure is parametrized locally as usual by factoring mass and stiffness submatrices defining the type and the location of the physical parameters to be identified. The procedure was applied to identify the design parameters of a beam type frame structure with bolted joints using experimental modal data.

scholarly journals mumpce_py: A Python Implementation of the Method of Uncertainty Minimization Using Polynomial Chaos Expansions

2017 ◽  
Vol 122 ◽  
Author(s):  
David A. Sheen
Keyword(s):  
Measurement Uncertainty ◽  
First Principles ◽  
Polynomial Chaos ◽  
Software Tool ◽  
Physical Models ◽  
Physical Parameters ◽  
Experimental Measurements ◽  
Uncertainty Minimization ◽  
Polynomial Chaos Expansions ◽  
Parameter Values

The Method of Uncertainty Minimization using Polynomial Chaos Expansions (MUM-PCE) was developed as a software tool to constrain physical models against experimental measurements. These models contain parameters that cannot be easily determined from first principles and so must be measured, and some which cannot even be easily measured. In such cases, the models are validated and tuned against a set of global experiments which may depend on the underlying physical parameters in a complex way. The measurement uncertainty will affect the uncertainty in the parameter values.

scholarly journals First-Principles Calculations of High-Pressure Physical Properties of Ti0.5Ta0.5 Alloy

Symmetry ◽  
2020 ◽  
Vol 12 (5) ◽  
pp. 796
Author(s):  
Fang Yu ◽  
Yu Liu
Keyword(s):  
High Pressure ◽  
Physical Properties ◽  
First Principles ◽  
Theoretical Study ◽  
Applied Pressure ◽  
Lattice Parameter ◽  
Physical Parameters ◽  
First Principles Calculations ◽  
Analysis Method ◽  
Metallic Bond

In this paper, an in-depth theoretical study on some physical properties of Ti0.5Ta0.5 alloy with systematic symmetry under high pressure is conducted via first-principles calculations, and relevant physical parameters are calculated. The results demonstrate that the calculated parameters, including lattice parameter, elastic constants, and elastic moduli, fit well with available theoretical and experimental data when the Ti0.5Ta0.5 alloy is under T = 0 and P = 0 , indicating that the theoretical analysis method can effectively predict the physical properties of the Ti0.5Ta0.5 alloy. The microstructure and macroscopic physical properties of the alloy cannot be destroyed as the applied pressure ranges from 0 to 50GPa, but the phase transition of crystal structure may occur in the Ti0.5Ta0.5 alloy if the applied pressure continues to increase according to the TDOS curves and charge density diagram. The value of Young’s and shear modulus is maximized at P = 25   GPa . The anisotropy factors A ( 100 ) [ 001 ] and A ( 110 ) [ 001 ] are equal to 1, suggesting the Ti0.5Ta0.5 alloy is an isotropic material at 28 GPa, and the metallic bond is strengthened under high pressure. The present results provide helpful insights into the physical properties of Ti0.5Ta0.5 alloy.

Evolution and stationarity of liquid toroidal drop in compressional Stokes flow

2017 ◽  
Vol 835 ◽  
pp. 1-23 ◽  
Author(s):  
B. K. Ee ◽  
O. M. Lavrenteva ◽  
I. Smagin ◽  
A. Nir
Keyword(s):  
Cross Sections ◽  
Capillary Number ◽  
Initial Conditions ◽  
Extensional Flow ◽  
Building Blocks ◽  
Physical Parameters ◽  
Ambient Fluid ◽  
Medicinal Substances ◽  
Expansion Dynamic ◽  
Axisymmetric Disturbances

Dynamics of fluid tori in slow viscous flow is studied. Such tori are of interest as future carriers of biological and medicinal substances and are also viewed as potential building blocks towards more complex particles. In this study the immiscible ambient fluid is subject to a compressional flow (i.e., bi-extensional flow), and it comprises a generalization of our earlier report on the particular case with viscosity ratio$\unicode[STIX]{x1D706}=1$(see Zabarankinet al.,J. Fluid Mech., vol. 785, 2015, pp. 372–400), where$\unicode[STIX]{x1D706}$is the ratio between the torus viscosity and that of the ambient fluid. It is found that, for all viscosity ratios, the torus either collapses towards the axis of symmetry or expands indefinitely, depending on the initial conditions and the capillary number,Ca. During these dynamic patterns the cross-sections exhibit various forms of deformation. The collapse and expansion dynamic modes are separated by a limited deformation into a deformed stationary state which appears to exist in a finite interval of the capillary number,$0<Ca<Ca_{cr}(\unicode[STIX]{x1D706})$, and is unstable to axisymmetric disturbances, which eventually cause the torus either to collapse or to expand indefinitely. The characteristic dimensions and shapes of these unstable stationary tori and their dependence on the physical parametersCaand$\unicode[STIX]{x1D706}$are reported.

A Hybrid Neural Network Approach for the Development of Friction Component Dynamic Model

2004 ◽  
Vol 126 (1) ◽  
pp. 144-153 ◽  
Author(s):  
M. Cao ◽  
K. W. Wang ◽  
Y. Fujii ◽  
W. E. Tobler
Keyword(s):  
Neural Network ◽  
First Principles ◽  
Physical Parameters ◽  
Neural Net ◽  
Asperity Contact ◽  
Neural Network Approach ◽  
Hybrid Neural Network ◽  
Friction Component ◽  
Improved Performance ◽  
Viscous Torque

In this research, a new hybrid neural network is developed to model engagement behaviors of automotive transmission wet friction component. Utilizing known first principles on the physics of engagement, special modules are created to estimate viscous torque and asperity contact torque as preprocessors to a two-layer neural network. Inside these modules, all the physical parameters are represented by neurons with various activation functions derived from first principles. These new features contribute to the improved performance and trainability over a conventional two-layer network model. Both the hybrid and conventional neural net models are trained and tested with experimental data collected from an SAE#2 test stand. The results show that the performance of the hybrid model is much superior to that of the conventional model. It successfully captures detailed characteristics of the friction component engagement torque as a function of time over a wide operating range.

scholarly journals Experimental Study of Substrate Limitation and Light Acclimation in Cultures of the Microalgae Scenedesmus obliquus—Parameter Identification and Model Predictive Control

Processes ◽  
2020 ◽  
Vol 8 (12) ◽  
pp. 1551
Author(s):  
Federico Alberto Gorrini ◽  
Jesús Miguel Zamudio Lara ◽  
Silvina Inés Biagiola ◽  
José Luis Figueroa ◽  
Héctor Hernández Escoto ◽  
...  
Keyword(s):  
Model Predictive Control ◽  
Dynamic Model ◽  
Predictive Control ◽  
Initial Conditions ◽  
Incident Light ◽  
Chlorophyll Concentration ◽  
Scenedesmus Obliquus ◽  
Light Illumination ◽  
Bulk Substrate ◽  
Determination Of Parameters

In this study, the parameters of a dynamic model of cultures of the microalgae Scenedesmus obliquus are estimated from datasets collected in batch photobioreactors operated with various initial conditions and light illumination conditions. Measurements of biomass, nitrogen quota, bulk substrate concentration, as well as chlorophyll concentration are achieved, which allow the determination of parameters with satisfactory confidence intervals and model cross-validation against independent data. The dynamic model is then used as a predictor in a nonlinear model predictive control strategy where the dilution rate and the incident light intensity are simultaneously manipulated in order to optimize the cumulated algal biomass production.

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