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Brownbridge G.P.E.,University of Cambridge | Smallbone A.,Cmcl Innovations | Phadungsukanan W.,University of Cambridge | Mosbach S.,University of Cambridge | And 2 more authors.
SAE Technical Papers | Year: 2011

This paper describes the development of a novel data model for storing and sharing data obtained from engine experiments, it then outlines a methodology for automatic model development and applies it to a state-of-the-art engine combustion model (including chemical kinetics) to reduce corresponding model parameter uncertainties with respect engine experiments. These challenges are met by adopting the latest developments in the semantic web to create a shared data model resource for the IC engine development community. The relevant data can be extracted and then used to set-up simulations for parameter estimation by passing it to the relevant application models. A methodology for incorporating experimental and model uncertainties into the model optimization procedure is presented. Data from seven operating points have been extracted from the proposed data model and have been incorporated into a state-of-the-art in-cylinder IC engine model through the optimization of model parameters whilst accounting for the model parameter and experimental uncertainties. Copyright © 2011 SAE International.

Brownbridge G.,University of Cambridge | Azadi P.,University of Cambridge | Smallbone A.,Cmcl Innovations | Bhave A.,Cmcl Innovations | And 2 more authors.
Bioresource Technology | Year: 2014

This study presents a techno-economic assessment of algae-derived biodiesel under economic and technical uncertainties associated with the development of algal biorefineries. A global sensitivity analysis was performed using a High Dimensional Model Representation (HDMR) method. It was found that, considering reasonable ranges over which each parameter can vary, the sensitivity of the biodiesel production cost to the key input parameters decreases in the following order: algae oil content > algae annual productivity per unit area > plant production capacity > carbon price increase rate. It was also found that the Return on Investment (ROI) is highly sensitive to the algae oil content, and to a lesser extent to the algae annual productivity, crude oil price and price increase rate, plant production capacity, and carbon price increase rate. For a large scale plant (100,000. tonnes of biodiesel per year) the production cost of biodiesel is likely to be £0.8-1.6 per kg. © 2013 Elsevier Ltd.

Smallbone A.,Cmcl Innovations | Bhave A.,Cmcl Innovations | Coble A.,Cmcl Innovations | Mosbach S.,University of Cambridge | And 3 more authors.
SAE Technical Papers | Year: 2011

Regulations on emissions from diesel and gasoline fuelled engines are becoming more stringent in all parts of the world. Hence there is a great deal of interest in developing advanced combustion systems that offer the efficiency of a diesel engine, but with low PM and NOx. One promising approach is that of Partially-Premixed Compression Ignition (PPCI) or Low Temperature Combustion (LTC). Using this approach, PM can be reduced in compression ignition engines by promoting the mixing of fuel and air prior to combustion. This paper describes the application of an advanced combustion simulator for fuels, combustion and emissions to analyze the key processes which occur in PPCI combustion mode. A detailed chemical kinetic model with advanced PM population balance sub-model is employed in a PPCI engine context to examine the impact of ignition resistance on combustion, mixing, ignition and emissions. The ignition and combustion of a diesel-like fuel (n-heptane) and low octane gasoline-like fuel (84PRF) are compared using the model highlighting how the diesel-like fuel ignites at very rich equivalence ratios whereas the gasoline-like fuel ignites on the lean side. Sources of exhaust gas emissions are also identified. For the first time, a computational model is employed to demonstrate the trade-off between low PM emissions and "over-mixing" (sensitivity to cycle-to-cycle variations and combustion instability) for a full range of fuels with increasing ignition resistance. These results are then discussed noting that conventional hydrocarbon fuels which fulfill either a conventional diesel or gasoline standards are not necessarily consistent with those required to run an engine operating at it's optimal point in terms of PM emissions and combustion stability. Copyright © 2011 SAE International.

Etheridge J.,Cmcl Innovations | Bhave A.,Cmcl Innovations | Smallbone A.,Cmcl Innovations | Coble A.,Cmcl Innovations | And 2 more authors.
SAE Technical Papers | Year: 2011

Regulations concerning emissions from diesel and gasoline fuelled engines are becoming ever more stringent in all parts of the world. Historically these targets have been achieved through on-going technological development using an iterative process of computational modelling, design, build and test. Computational modelling is certainly the cheapest aspect within this process and if employed to meet more of the challenges associated with development, has the potential to significantly reduce developmental cost and time scales. Furthermore, computational models are an effective means to retain and apply often highly focused technical knowledge of complex processes within development teams thus delivering greater insight into processes. As such there is a great deal of interest in advanced simulation technologies; one such technology is srm suite™ which has proven effective in simulating in-cylinder combustion processes to enable engineers to identify optimal injection, valve train and spark timing operating strategy to achieve a particular load-speed point with reduced target emissions. The model accounts for the impact of fuel injection strategies, detailed chemical kinetics, turbulent mixing, and heat losses on the inhomogeneities associated with the in-cylinder composition and temperature, within practical computing time scales. In order to account for the valve train dynamics and engine breathing within the context of engine cycle simulation, the srm suite has been coupled with standard 1D engine cycle simulators and applied to investigate three industry relevant problems (1) investigating cycle-to-cycle variations on emissions in an SI engine, (2) investigating emissions at different injection timings, speeds and loads in a diesel engine operated with pilot injection and high levels of Exhaust Gas Recirculation (EGR), and (3) simulating a dual injection Homogeneous Charge Compression Ignition (HCCI) engine operated with an injection (fuel reformation) during Negative Valve Overlap (NVO). In each context, computational results are compared with experimental observations and conclusions presented. Copyright © 2011 SAE International and Copyright © 2011 SIAT, India.

Azadi P.,University of Cambridge | Brownbridge G.,University of Cambridge | Mosbach S.,University of Cambridge | Smallbone A.,Cmcl Innovations | And 4 more authors.
Applied Energy | Year: 2014

We determine the environmental impact of different biodiesel production strategies from algae feedstock in terms of greenhouse gas (GHG) emissions and non-renewable energy consumption, we then benchmark the results against those of conventional and synthetic diesel obtained from fossil resources. The algae cultivation in open pond raceways and the transesterification process for the conversion of algae oil into biodiesel constitute the common elements among all considered scenarios. Anaerobic digestion and hydrothermal gasification are considered for the conversion of the residues from the wet oil extraction route; while integrated gasification-heat and power generation and gasification-Fischer-Tropsch processes are considered for the conversion of the residues from the dry oil extraction route. The GHG emissions per unit energy of the biodiesel are calculated as follows: 41g e-CO2/MJb for hydrothermal gasification, 86g e-CO2/MJb for anaerobic digestion, 109g e-CO2/MJb for gasification-power generation, and 124g e-CO2/MJb for gasification-Fischer-Tropsch. As expected, non-renewable energy consumptions are closely correlated to the GHG values. Also, using the High Dimensional Model Representation (HDMR) method, a global sensitivity analysis over the entire space of input parameters is performed to rank them with respect to their influence on key sustainability metrics. Considering reasonable ranges over which each parameter can vary, the most influential input parameters for the wet extraction route include extractor energy demand and methane yield generated from anaerobic digestion or hydrothermal gasification of the oil extracted-algae. The dominant process input parameters for the dry extraction route include algae oil content, dryer energy demand, and algae annual productivity. The results imply that algal biodiesel production from a dried feedstock may only prove sustainable if a low carbon solution such as solar drying is implemented to help reducing the water content of the feedstock. © 2013 Elsevier Ltd.

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