Numerical modeling and simulation of PEM fuel cells: Progress and perspective

This paper provides a comprehensive review on the research and development in multi-scale numerical modeling and simulation of PEM fuel cells. An overview of recent progress in PEM fuel cell modeling has been provided. Fundamental transport phenomena in PEM fuel cells and the corresponding mathematical formulation of macroscale models are analyzed. Various important issues in PEM fuel cell modeling and simulation are examined in detail, including fluid flow and species transport, electron and proton transport, heat transfer and thermal management, liquid water transport and water management, transient response behaviors, and cold-start processes. Key areas for further improvements have also been discussed.

Novel Application-oriented Transient Fuel Model of a Port Fuel Injection S. I. Engine

Most researches on transient fuel control of port fuel injection S.I. engine are carried out from the perspective of advanced mathematical theories. When it comes to practical control, there exist many limitations although they are more intelligent. In order to overcome the fuel wetting effect of PFI engine, the application-oriented transient fuel control is studied by analyzing the key parameters which are closely related with the engine transient characteristics. Both validity and simplicity are taken into consideration. Based on the fuel wall-wetting theory and popular fuel compensation strategy, short-term transient fuel（STF） and long-term transient fuel（LTF）, as well as their individual decay approaches, are introduced. STF is to compensate the drastic fuel film loss caused by sudden throttle change, while the function of LTF is to compensate the fuel film loss by manifold air pressure（p） fluctuation. Each of them has their respective pros and cons. The engine fuel mass and air mass are also calculated for air-fuel ratio（AFR） according to ideal gas state equation and empirical equations. The vehicle acceleration test is designed for model validation. The engine experiences several mild and heavy accelerations corresponding to the gear change during vehicle acceleration. STF and LTF control are triggered reliably. The engine transient fuel control simulation adopts the same inputs as the test to ensure consistency. The logged test data are used to check the model output. The results show that the maximum fuel pulse width（FPW） error reaches 2 ms, and it only occurs under engine heavy acceleration condition. The average FPW error is 0.57 ms. The results of simulation and test are close overall, which indicates the accuracy of steady and transient fuel. The proposed research provides an efficient approach not only suitable for practical engineering application, but also for AFR prediction, fuel consumption calculation, and further studies on emission control.

Study of visualized simulation and analysis of nuclear fuel cycle system based on multilevel flow model

Complex energy and environment system, especially nuclear fuel cycle system recently raised socialconcerns about the issues of economic competitiveness, environmental effect and nuclear proliferation. Only underthe condition that those conflicting issues are gotten a consensus between stakeholders with different knowledgebackground, can nuclear power industry be continuingly developed. In this paper, a new analysis platform has beendeveloped to help stakeholders to recognize and analyze various socio-technical issues in the nuclear fuel cycle systembased on the functional modeling method named Multilevel Flow Models (MFM) according to the cognition theoryof human being. Its character is that MFM models define a set of mass, energy and information flow structures onmultiple levels of abstraction to describe the functional structure of a process system and its graphical symbol representationand the means-end and part-whole hierarchical flow structure to make the represented process easy to beunderstood. Based upon this methodology, a micro-process and a macro-process of nuclear fuel cycle system wereselected to be simulated and some analysis processes such as economics analysis, environmental analysis and energybalance analysis related to those flows were also integrated to help stakeholders to understand the process of decision-making with the introduction of some new functions for the improved Multilevel Flow Models Studio, and finallythe simple simulation such as spent fuel management process simulation and money flow of nuclear fuel cycleand its levelised cost analysis will be represented as feasible examples.

Mathematical Modelling and Experimental Investigation of a Low Temperature Proton Exchange Membrane Fuel Cell

This paper presents dynamic modeling of 1000 W EC6C Proton Exchange Membrane fuel cell (PEMFC) manufactured by Edibon. Experiments were carried out to investigate the performance of the system and a dynamic electrical model was implemented in Matlab/Simulink. The simulation model was able to predict efficiency, power and fuel cell potential. The model was also tested with load variations to find out the real time responses. The results were validated by experimental findings. The comparison showed that the model was effective and could be used in optimization of the fuel cell system operated at low temperatures under 80 degrees.

A review of TRISO-coated particle nuclear fuel performance models

The success of high temperature gas cooled reactor depends upon the safety and quality of the coated particle fuel. The understanding and evaluation of this fuel requires the development of an integrated mechanistic fuel performance model that fully describes the mechanical and physicochemical behavior of the fuel particle under irradiation. In this paper, a review of the analytical capability of some of the existing computer codes for coated particle fuel was performed. These existing models and codes include FZJ model, JAERI model, Stress3 model, ATLAS model, PARFUME model and TIMCOAT model. The theoretic model, methodology, calculation parameters and benchmark of these codes were classified. Based on the failure mechanism of coated particle, the advantage and limits of the models were compared and discussed. The calculated results of the coated particles for China HTR-10 by using some existing code are shown. Finally, problems and challenges in fuel performance modeling were listed.

Fuel Burning Rate Model for Stratified Charge Engine

A zero-dimensional single-zone double-curve model is presented to predict fuel burning rate in stratified charge engines, and it is integrated with GT-Power to predict the overall performance of the stratified charge engines. The model consists of two exponential functions for calculating the fuel burning rate in different charge zones. The model factors are determined by a non-linear curve fitting technique, based on the experimental data obtained from 30 cases in middle and low loads. The results show good agreement between the measured and calculated cylinder pressures, and the deviation between calculated and measured cylinder pressures is less than 5%. The zerodimensional single-zone double-curve model is successful in the combustion modeling for stratified charge engines.

Experimental Testing and Validation of the Mathematical Model for a Self-Humidifying PEM Fuel Cell

This paper presents an experimental testing and validation results for a zero-dimensional self-humidifying PEM (Proton Exchange Membrane) fuel cell stack. The model incorporates major electric and thermodynamic variables and parameters involved in the operation of the PEM fuel cell under different operational conditions. The mathematical equations are modelled by using Matlab-Simulink tools in order to simulate the operation of the developed model with a commercially available 1 kW Horizon (H-1000) PEM fuel cell stack, which is used for the purposes of model validation and tuning of the developed model. The model is mathematically modelled and presented in the recent published work of authors. The observations from model simulations provide sufficient evidence and support to the results and observations obtained from testing 1 kW Horizon (H-1000) PEM fuel cell stack used in this research. The developed model can be used as a generic model and simulation platform for a self-humidifying PEM fuel cell with an output power varying from 50 W to 1 kW, with extrapolation to higher powers is also possible.

DYNAMIC MODELS OF AQUIFEROUS CONTENT OF LIVING FUELS

Forest fire occurrence is closely relative with fuel water content. There are a lot of research about dead fuels. but forest fuels consist of both dead fuels and living fuels. Each large fire occurrence has a good relationship with living fuels. Especially living fuels can influence the production and development of big forest fire, so, we selected Tahe, in Daxingan Mountains, as observation site. According to actual data,we can establish a set of models of different living fuel water content variation with linear -regression method.

DYNAMIC MODELS OF MOISTURE CONTENT OF FOREST FUELS

The fuel moisture content is an integral part of any workable fire danger-rating system. This paper presented dynamic models for estimating 1-h, 10-h. 100-h and 1000-h timelag fuels, that were developed by multiple regression and stepwise variable selection of statistics. The variables include both meteorological factors and moisture contents observed prior to the day correspondingly. The analysis revealed that the fuel moisture content are correlated positively with the precipitation of 24 hours prior to the observation time, and negatiyely with air temperature at observing height of 1.5 meter in forest.

Hybrid dynamic model of polymer electrolyte membrane fuel cell stack using variable neural network

The polymer electrolyte membrane（PEM） fuel cell has been regarded as a potential alternative power source,and a model is necessary for its design,control and power management.A hybrid dynamic model of PEM fuel cell,which combines the advantages of mechanism model and black-box model,is proposed in this paper.To improve the performance,the static neural network and variable neural network are used to build the black-box model.The static neural network can significantly improve the static performance of the hybrid model,and the variable neural network makes the hybrid dynamic model predict the real PEM fuel cell behavior with required accuracy.Finally,the hybrid dynamic model is validated with a 500 W PEM fuel cell.The static and transient experiment results show that the hybrid dynamic model can predict the behavior of the fuel cell stack accurately and therefore can be effectively utilized in practical application.

DYNAMIC PREDICION OF FOREST FUEL LOADS BY GREY VERHULST MODEL

The variation of fuel loads after a fire for three forest types, phododendron -Larix gmetinii forest, herb--Larix gmelinii forest and herb--Betula plalyphlla forest , in the northern forest area of Daxing’anling region was discussed. The dynamic models were developed by gray theory for estimating the fuels loads of arbor- shrub, herbs’ grass, litter, and semi-decomposed litter, inflamma ble fuel and the total fuels in each forest type. After a fire, the inflammabIe fuel loads in phododendron-- Larix gmelinii forest and in the herb- - Betula platyphlla fores was estimated at 10.958 t/hm2and 10.473 t/hm2 respectively’ by 13 years later. and that was 12.297 t/hm 2 in herb--Larix gmeliniiforest by 7 years later.. It was predicated that a big fire may occur after 10 years based on inflammable fuel biomass accumulated.

Modeling and identification of a PEM fuel cell humidification system

A theoretical model of a humidifier of proton exchange membrane （PEM） fuel cell systems is developed and analyzed first in this paper. The model shows that there exists a strong nonlinearity in the system. Then, the system is identified using a wavelet networks method. To avoid the curse-of-dimensionality problem, a class of wavelet networks proposed by Billings is employed. The experimental data acquired from the test bench are used for identification. The one-step-ahead predictions and the five-step-ahead predictions are compared with the real measurements, respectively. It shows that the identified model can effectively describe the real system.

A Visual Integrated Analysis Platform for Nuclear Fuel Cycle System Based on Multilevel Flow Model

Complex Nuclear Fuel Cycle (NFC) system faces many socio-technical issues that need to obtain the consensus between stakeholders of different knowledge background. In this paper, a visualized analysis platform based on graphical functional modeling method, Multilevel Flow Model (MFM), is proposed to help those stakeholders to recognize and analyze various socio-technical issues in NFC system. Some new functions, such as “Reaction Function", “Switch Function" and “Conversion Function", are introduced to fulfill new simulation tasks for NFC system. Based upon this methodology, a micro-process and a macro-process of NFC system are simulated and meanwhile some key analysis variables, such as CO2 emission and cost flow, required by some analysis methods are deducted and displayed in the platform. And finally a sample simulation analysis is conducted based on MFM.

A discrete-event model to simulate the effect of truck bunching due to payload variance on cycle time, hauled mine materials and fuel consumption

Data collected from truck payload management systems at various surface mines shows that the payload variance is significant and must be considered in analysing the mine productivity,energy consumption,greenhouse gas emissions and associated cost.Payload variance causes significant differences in gross vehicle weights.Heavily loaded trucks travel slower up ramps than lightly loaded trucks.Faster trucks are slowed by the presence of slower trucks,resulting in‘bunching’,production losses and increasing fuel consumptions.This paper simulates the truck bunching phenomena in large surface mines to improve truck and shovel systems’efficiency and minimise fuel consumption.The study concentrated on completing a practical simulation model based on a discrete event method which is most commonly used in this field of research in other industries.The simulation model has been validated by a dataset collected from a large surface mine in Arizona state,USA.The results have shown that there is a good agreement between the actual and estimated values of investigated parameters.

Blended-fuel based EDC combustion model and its application in heptane-ethanol fire simulation

The blended-fuel based eddy-dissipation-concept combustion model was newly developed in the FireFOAM framework, and applied to simulate 30 cm×30 cm heptane-ethanol pool fire. Comparison was made of fire height, centerline temperature against experimental measurements, which shows that they match very well with each other. However, further studies are needed to examine the validation of this model in fire simulations with various scales.

Challenges in spent nuclear fuel final disposal:conceptual design models

<正>The disposal of spent nuclear fuel is a long-standing issue in nuclear technology.Mainly,UO_2 and metallic U arc used as a fuel in nuclear reactors.Spent nuclear fuel contains fission products and transuranium elements,which would remain radioactive for 10~4 to 10~8 years.In this brief communication,essential concepts and engineering elements related to high-level nuclear waste disposal are described.Conceptual design models are described and discussed considering the long-time scale activity of spent nuclear fuel or high level waste.Notions of physical and chemical barriers to contain nuclear waste are highiightened.Concerns regarding integrity,self-irradiation induced decomposition and thermal effects of decay heat on the spent nuclear fuel are also discussed.The question of retrievability of spent nuclear fuel after disposal is considered.

Response Surface Modeling of Fuel Rich and Fuel Lean Catalytic Combustion of the Stabilized Confined Turbulent Gaseous Diffusion Flames

The Response Surface Methodology (RSM) has been applied to explore the thermal structure of the experimentally studied catalytic combustion of stabilized confined turbulent gaseous diffusion flames. The Pt/γAl2O3 and Pd/γAl2O3 disc burners were situated in the combustion domain and the experiments were performed under both fuel-rich and fuel-lean conditions at a modified equivalence (fuel/air) ratio (&oslash;) of 0.75 and 0.25 respectively. The thermal structure of these catalytic flames developed over the Pt and Pd disc burners were inspected via measuring the mean temperature profiles in the radial direction at different discrete axial locations along the flames. The RSM considers the effect of the two operating parameters explicitly (r), the radial distance from the center line of the flame, and (x), axial distance along the flame over the disc, on the measured temperature of the flames and finds the predicted maximum temperature and the corresponding process variables. Also the RSM has been employed to elucidate such effects in the three and two dimensions and displays the location of the predicted maximum temperature.

Statistical model for combustion of high-metal magnesium-based hydro-reactive fuel

We investigate experimentally and analytically the combustion behavior of a high-metal magnesium-based hydro- reactive fuel under high temperature gaseous atmosphere. The fuel studied in this paper contains 73% magnesium powders. An experimental system is designed and experiments are carried out in both argon and water vapor atmo- spheres. It is found that the burning surface temperature of the fuel is higher in water vapor than that in argon and both of them are higher than the melting point of magnesium, which indicates the molten state of magnesium particles in the burning surface of the fuel. Based on physical considerations and experimental results, a mathematical one-dimensional model is formulated to describe the combustion behavior of the high-metal magnesium-based hydro-reactive fuel. The model enables the evaluation of the burning surface temperature, the burning rate and the flame standoff distance each as a function of chamber pressure and water vapor concentration. The results predicted by the model show that the burning rate and the surface temperature increase when the chamber pressure and the water vapor concentration increase, which are in agreement with the observed experimental trends.

Evaluation of the International Vehicle Emission (IVE) model with on-road remote sensing measurements

Intemational Vehicle Emissions （IVE） model funded by U.S. Environmental Protection Agency （USEPA） is designed to estimate emissions from motor vehicles in developing countries. In this study, the IVE model was evaluated by utilizing a dataset available from the remote sensing measurements on a large number of vehicles at five different sites in Hangzhou, China, in 2004 and 2005. Average fuel-based emission factors derived from the remote sensing measurements were compared with corresponding emission factors derived from IVE calculations for urban, hot stabilized condition. The results show a good agreement between the two methods for gasoline passenger cars＇ HC emission for all 1VE subsectors and technology classes. In the case of CO emissions, the modeled results were reasonably good, although systematically underestimate the emissions by almost 12%-50% for different technology classes. However, the model totally overestimated NOx emissions. The IVE NOx emission factors were 1.5-3.5 times of the remote sensing measured ones. The IVE model was also evaluated for light duty gasoline truck, heavy duty gasoline vehicles and motor cycles. A notable result was observed that the decrease in emissions from technology class State II to State I were overestimated by the IVE model compared to remote sensing measurements for all the three pollutants. Finally, in order to improve emission estimation, the adjusted base emission factors from local studies are strongly recommended to be used in the IVE model.

Fuel classification and mapping from satellite imagines

This paper summarizes the fuel type systems currently adopted by the fire danger rating systems or fire behavior prediction systems of some countries, such as Canada, the United States, Australia, Greece, and Switzerland. As an example, the Canadian Forest Fire Danger Rating System organizes fuel types into five major groups, with a total of 16 discrete fuel types recognized. In the United States National Fire Danger Rating System, fuel models are divided into four vegetation groups and twenty fire behavior fuel models. The Promethus System （Greece） divides fuels into 7 types, and Australia has adopted only three distinct fuel types： open grasslands, dry eucalyptus forests, and heath/shrublands. Four approaches to mapping fuels are acceptable： field reconnaissance, direct mapping methods, indirect mapping methods, and gradient modeling. Satellite remote-sensing techniques provide an alternative source of obtaining fuel data quickly, since they provide comprehensive spatial coverage and enough temporal resolution to update fuel maps in a more efficient and timely manner than traditional aerial photography or fieldwork. Satellite sensors can also provide digital information that can be easily tied into other spatial databases using Geographic Information System （GIS） analysis, which can be used as input in fire behavior and growth models. Various fuel-mapping methods from satellite remote sensing are discussed in the paper. According to the analysis of the fuel mapping techniques worldwide, this paper suggests that China should first create appropriate fuel types for its fire agencies before embarking on developing a national fire danger rating system to improve the current data situation for it＇s fire management programs.