Alkali Activated Fuel Ash and Slag Mixes:Optimization Study from Mortars to Concrete Building Blocks

Alkali activated binders, based on ash and slag, also known as geopolymers, can play a key role in reducing the carbon footprint of the construction sector by replacing ordinary Portland cement in some concretes. Since 1970s, research effort has been ongoing in many research institutions. In this study, pulverized fuel ash (PFA) from a UK power plant, ground granulated blast furnace slag (GGBS) and combinations of the two have been investigated as geopolymer binders for concrete applications. Activators used were sodium hydroxide and sodium silicate solutions. Mortars with sand/binder ratio of 2.75 with several PFA and GGBS combinations have been mixed and tested. The optimization of alkali dosage (defined as the Na2O/binder mass ratio) and modulus (defined as the Na2O/SiO2 mass ratio) resulted in strengths in excess of 70 MPa for tested mortars. Setting time and workability have been considered for the identification of the best combination of PFA/GGBS and alkali activator dosage for different precast concrete products. Geopolymer concrete building blocks have been replicated in laboratory and a real scale factory trial has been successfully carried out. Ongoing microstructural characterization is aiming to identify reaction products arising from PFA/GGBS combinations.

Modeling study of woody biomass:Interactions of cellulose, hemicellulose, and lignin

Lignocellulosic biomass pretreatment and the subsequent thermal conversion processes to produce solid, liquid, and gas biofuels are attractive solutions for today's energy challenges. The structural study of the main components in biomass and their macromolecular complexes is an active and ongoing research topic worldwide. The interactions among the three main components, cellulose, hemicellulose, and lignin, are studied in this paper using electronic structure methods, and the study includes examining the hydrogen bond network of cellulose-hemicellulose systems and the covalent bond linkages of hemicellulose-lignin systems. Several methods (semiempirical, Hartree-Fock, and density functional theory) using different basis sets were evaluated. It was shown that theoretical calculations can be used to simulate small model structures representing wood components. By comparing calculation results with experimental data, it was concluded that B3LYP/6-31G is the most suitable basis set to describe the hydrogen bond system and B3LYP/6-31G(d,p) is the most suitable basis set to describe the covalent system of woody biomass. The choice of unit model has a much larger effect on hydrogen bonding within cellulose-hemicellulose system, whereas the model choice has a minimal effect on the covalent linkage in the hemicellulose-lignin system. © 2011 American Chemical Society.

Improving fuel economy application of the organic Rankine Cycle on a hybrid bus

Globally vehicle operators are experiencing rising fuel costs and increased
running expenses as governments around the world attempt to decrease carbon dioxide emissions and fossil fuel consumption, due to global warming and the drive to reduce dependency on fossil fuels. Recent advances in hybrid vehicle design have made great strides towards more efficient operation, with regenerative braking being widely used to capture otherwise lost energy. In this paper a hybrid series bus is developed a step further, by installing another method of energy capture on the vehicle. In this case, it is in the form of the Organic Rankine Cycle (ORC). The waste heat expelled to the exhaust and coolant streams is recovered and converted to electrical energy which is then stored in the hybrid vehicles batteries. The electrical energy can then be used for the auxiliary power circuit or to assist in vehicle propulsion, thus reducing the load on the engine, thereby improving the overall fuel economy of the vehicle and reducing carbon dioxide emissions.

Development of a PtSn bimetallic catalyst for direct fuel cells using bio-butanol fuel

Pt and PtSn catalysts were studied for n-butanol electro-oxidation at various temperatures. PtSn showed a higher activity towards butanol electro-oxidation compared to Pt in acidic media. The onset potential for n-butanol oxidation on PtSn is ~520 mV lower than that found on Pt, and significantly lower activation energy was found for PtSn compared with that for Pt.

A biogeography-based optimization algorithm with mutation strategies for model parameter estimation of solar and fuel cells

Mathematical models are useful tools for simulation, evaluation, optimal operation and control of solar cells and proton exchange membrane fuel cells (PEMFCs). To identify the model parameters of these two type of cells efficiently, a biogeography-based optimization algorithm with mutation strategies (BBO-M) is proposed. The BBO-M uses the structure of biogeography-based optimization algorithm (BBO), and both the mutation motivated from the differential evolution (DE) algorithm and the chaos theory are incorporated into the BBO structure for improving the global searching capability of the algorithm. Numerical experiments have been conducted on ten benchmark functions with 50 dimensions, and the results show that BBO-M can produce solutions of high quality and has fast convergence rate. Then, the proposed BBO-M is applied to the model parameter estimation of the two type of cells. The experimental results clearly demonstrate the power of the proposed BBO-M in estimating model parameters of both solar and fuel cells.

An improved TLBO with elite strategy for parameters identification of PEM fuel cell and solar cell models

Clean and renewable energy generation and supply has drawn much attention worldwide in recent years, the proton exchange membrane (PEM) fuel cells and solar cells are among the most popular technologies. Accurately modeling the PEM fuel cells as well as solar cells is critical in their applications, and this involves the identification and optimization of model parameters. This is however challenging due to the highly nonlinear and complex nature of the models. In particular for PEM fuel cells, the model has to be optimized under different operation conditions, thus making the solution space extremely complex. In this paper, an improved and simplified teaching-learning based optimization algorithm (STLBO) is proposed to identify and optimize parameters for these two types of cell models. This is achieved by introducing an elite strategy to improve the quality of population and a local search is employed to further enhance the performance of the global best solution. To improve the diversity of the local search a chaotic map is also introduced. Compared with the basic TLBO, the structure of the proposed algorithm is much simplified and the searching ability is significantly enhanced. The performance of the proposed STLBO is firstly tested and verified on two low dimension decomposable problems and twelve large scale benchmark functions, then on the parameter identification of PEM fuel cell as well as solar cell models. Intensive experimental simulations show that the proposed STLBO exhibits excellent performance in terms of the accuracy and speed, in comparison with those reported in the literature.

Co-tape casting fabrication, field assistant sintering and evaluation of a coke resistant La0.2Sr0.7TiO3-Ni/YSZ functional gradient anode supported solid oxide fuel cell

The ability to directly utilize hydrocarbons and other renewable liquid fuels is one of the most important issues affecting the large scale deployment of solid oxide fuel cells (SOFCs). Herein we designed La_0.2Sr_0.7TiO₃-Ni/YSZ functional gradient anode (FGA) supported SOFCs, prepared with a co-tape casting method and sintered using the field assisted sintering technique (FAST). Through SEM observations, it was confirmed that the FGA structure was achieved and well maintained after the FAST process. Distortion and delamination which usually results after conventional sintering was successfully avoided. The La_0.2Sr_0.7TiO₃-Ni/YSZ FGA supported SOFCs showed a maximum power density of 600mWcm^-2 at 750°C, and was stable for 70h in CH₄. No carbon deposition was detected using Raman spectroscopy. These results confirm the potential coke resistance of La_0.2Sr_0.7TiO₃-Ni/YSZ FGA supported SOFCs.