The electric discharge across a varistor granule filled air gap under a fast-rising voltage pulse was investigated for surge protection applications. The effects of temperature and pressure on the arc and the electrical conduction were analyzed by the characteristic changes in voltage waveforms triggered by a fast-rising high voltage pulse. In addition to the gap size, experimental results show that competing mechanisms among arc conduction, conduction through the varistor granule network, thermionic emission from Joule heating at granule-to-granule contact points, and the magnitude of the switching voltage dictate the maximum surge protection voltage for the filled air gap. Experimental evidence indicated that accumulated degradation was created at small contact points between varistor granules by repetitive assaults from longer duration, high voltage pulses. The uniqueness of using varistor over other dielectric granules in an air gap for surge protection is identified and discussed.
In the present work, a three-dimension (3-D) model of polymer electrolyte fuel cells (PEFCs) is employed to investigate the complex, non-isothermal, two-phase flow in the gas diffusion layer (GDL). Phase change in gas flow channels is explained, and a simplified approach accounting for phase change is incorporated into the fuel cell model. It is found that the liquid water contours in the GDL are similar along flow channels when the channels are subject to two-phase flow. Analysis is performed on a dimensionless parameter Da0 introduced in our previous paper [Y. Wang and K. S. Chen, Chemical Engineering Science 66 (2011) 3557–3567] and the parameter is further evaluated in a realistic fuel cell. We found that the GDL's liquid water (or liquid-free) region is determined by the Da0 number which lumps several parameters, including the thermal conductivity and operating temperature. By adjusting these factors, a liquid-free GDL zone can be created even though the channel stream is two-phase flow. Such a liquid-free zone is adjacent to the two-phase region, benefiting local water management, namely avoiding both severe flooding and dryness.
Goma 6.0 is a finite element program which excels in analyses of multiphysical processes, particularly those involving the major branches of mechanics (viz. fluid/solid mechanics, energy transport and chemical species transport). Goma is based on a full-Newton-coupled algorithm which allows for simultaneous solution of the governing principles, making the code ideally suited for problems involving closely coupled bulk mechanics and interfacial phenomena. Example applications include, but are not limited to, coating and polymer processing flows, super-alloy processing, welding/soldering, electrochemical processes, and solid-network or solution film drying. This document serves as a user's guide and reference.
ASME 2012 6th International Conference on Energy Sustainability, ES 2012, Collocated with the ASME 2012 10th International Conference on Fuel Cell Science, Engineering and Technology
Two of the most daunting problems facing humankind in the twenty-first century are energy security and climate change. This report summarizes work accomplished towards addressing these problems through the execution of a Grand Challenge LDRD project (FY09-11). The vision of Sunshine to Petrol is captured in one deceptively simple chemical equation: Solar Energy + xCO{sub 2} + (x+1)H{sub 2}O {yields} C{sub x}H{sub 2x+2}(liquid fuel) + (1.5x+.5)O{sub 2} Practical implementation of this equation may seem far-fetched, since it effectively describes the use of solar energy to reverse combustion. However, it is also representative of the photosynthetic processes responsible for much of life on earth and, as such, summarizes the biomass approach to fuels production. It is our contention that an alternative approach, one that is not limited by efficiency of photosynthesis and more directly leads to a liquid fuel, is desirable. The development of a process that efficiently, cost effectively, and sustainably reenergizes thermodynamically spent feedstocks to create reactive fuel intermediates would be an unparalleled achievement and is the key challenge that must be surmounted to solve the intertwined problems of accelerating energy demand and climate change. We proposed that the direct thermochemical conversion of CO{sub 2} and H{sub 2}O to CO and H{sub 2}, which are the universal building blocks for synthetic fuels, serve as the basis for this revolutionary process. To realize this concept, we addressed complex chemical, materials science, and engineering problems associated with thermochemical heat engines and the crucial metal-oxide working-materials deployed therein. By project's end, we had demonstrated solar-driven conversion of CO{sub 2} to CO, a key energetic synthetic fuel intermediate, at 1.7% efficiency.
Current computational models for proton exchange membrane fuel cells (PEMFCs) include a large number of parameters such as boundary conditions, material properties, and numerous parameters used in sub-models for membrane transport, two-phase flow and electrochemistry. In order to successfully use a computational PEMFC model in design and optimization, it is important to identify critical parameters under a wide variety of operating conditions, such as relative humidity, current load, temperature, etc. Moreover, when experimental data is available in the form of polarization curves or local distribution of current and reactant/product species (e.g., O2, H2O concentrations), critical parameters can be estimated in order to enable the model to better fit the data. Sensitivity analysis and parameter estimation are typically performed using manual adjustment of parameters, which is also common in parameter studies. We present work to demonstrate a systematic approach based on using a widely available toolkit developed at Sandia called DAKOTA that supports many kinds of design studies, such as sensitivity analysis as well as optimization and uncertainty quantification. In the present work, we couple a multidimensional PEMFC model (which is being developed, tested and later validated in a joint effort by a team from Penn State Univ. and Sandia National Laboratories) with DAKOTA through the mapping of model parameters to system responses. Using this interface, we demonstrate the efficiency of performing simple parameter studies as well as identifying critical parameters using sensitivity analysis. Finally, we show examples of optimization and parameter estimation using the automated capability in DAKOTA.
In this paper, we report the progress made in our project recently funded by the US Department of Energy (DOE) toward developing a computational capability, which includes a two-phase, three-dimensional PEM (polymer electrolyte membrane) fuel cell model and its coupling with DAKOTA (a design and optimization toolkit developed and being enhanced by Sandia National Laboratories). We first present a brief literature survey in which the prominent/notable PEM fuel cell models developed by various researchers or groups are reviewed. Next, we describe the two-phase, three-dimensional PEM fuel cell model being developed, tested, and later validated by experimental data. Results from case studies are presented to illustrate the utility of our comprehensive, integrated cell model. The coupling between the PEM fuel cell model and DAKOTA is briefly discussed. Our efforts in this DOE-funded project are focused on developing a validated computational capability that can be employed for PEM fuel cell design and optimization.
A two-dimensional, multi-physics computational model based on the finite-element method is developed for simulating the process of solar thermochemical splitting of carbon dioxide (CO{sub 2}) using ferrites (Fe{sub 3}O{sub 4}/FeO) and a counter-rotating-ring receiver/recuperator or CR5, in which carbon monoxide (CO) is produced from gaseous CO{sub 2}. The model takes into account heat transfer, gas-phase flow and multiple-species diffusion in open channels and through pores of the porous reactant layer, and redox chemical reactions at the gas/solid interfaces. Results (temperature distribution, velocity field, and species concentration contours) computed using the model in a case study are presented to illustrate model utility. The model is then employed to examine the effects of injection rates of CO{sub 2} and argon neutral gas, respectively, on CO production rate and the extent of the product-species crossover.