Dominik Bongartz

Cleaner production of cleaner fuels: wind-to-wheel - environmental assessment of CO2-based oxymethylene ether as a drop-in fuel

The combustion of fossil fuels within the transportation sector is a key driver of global warming (GW) and leads to harmful emissions of nitrogen oxides (NOx) and particulates (soot). To reduce these negative impacts of the transportation sector, synthetic fuels are currently being developed, which are produced from renewable energy stored via catalytic conversion of hydrogen (H2) and carbon dioxide (CO2). A promising class of synthetic fuels are oxymethylene ethers (OMEs). This study conducts a prospective environmental assessment of an OME-based fuel using Life Cycle Assessment (LCA). We investigate an OME1-diesel-blend (OME1-blend), where OME1 replaces 24 mass% of diesel fuel. Such an OME1-blend could be a first step towards an OME transition. For the production of OME1 from CO2-based methanol, we consider both the established route via condensation with formaldehyde and a novel direct pathway based on catalytic combination with CO2 and hydrogen. To close the carbon loop, CO2 supply via biogas and direct air capture is considered. In a best-case scenario, hydrogen is produced by water electrolysis using electricity from wind power in the European Union as an input. The direct pathway reduces the required process steps from three to two and is shown to allow for an improved utilization of the energy provided by hydrogen: the exergy efficiency is increased from 74% to 86%. For combustion, we conducted experiments in a single cylinder engine to determine the full spectrum of engine-related emissions. The engine data provide the input for simulations of the cumulative raw emissions over the Worldwide Harmonized Light Vehicles Test Procedures (WLTP) cycle for a mid-size passenger vehicle. Our well-to-wheel LCA shows that OME1 has the potential to serve as an almost carbon-neutral blending component: replacing 24 mass% of diesel by OME1 could reduce the GW impact by 22% and the emissions of NOx and soot even by 43% and 75%, respectively. The key to achieving these benefits is the integration of renewable energy in hydrogen production. The cumulative energy demand (CED) over the life cycle is doubled compared to fossil diesel. With sufficient renewable electricity available, OME1-blends may serve as a promising first step towards a more sustainable transportation sector.

Deterministic global optimization of process flowsheets in a reduced space using McCormick relaxations

Deterministic global methods for flowsheet optimization have almost exclusively relied on an equation-oriented formulation where all model variables are controlled by the optimizer and all model equations are considered as equality constraints, which results in very large optimization problems. A possible alternative is a reduced-space formulation similar to the sequential modular infeasible path method employed in local flowsheet optimization. This approach exploits the structure of the model equations to achieve a reduction in problem size. The optimizer only operates on a small subset of the model variables and handles only few equality constraints, while the majority is hidden in externally defined functions from which function values and relaxations for the objective function and constraints can be queried. Tight relaxations and their subgradients for these external functions can be provided through the automatic propagation of McCormick relaxations. Three steam power cycles of increasing complexity are used as case studies to evaluate the different formulations. Unlike in local optimization or in previous sequential approaches relying on interval methods, the solution of the reduced-space formulation using McCormick relaxations enables dramatic reductions in computational time compared to the conventional equation-oriented formulation. Despite the simplicity of the implemented branch-and-bound solver that does not fully exploit the tight relaxations returned by the external functions but relies on further affine relaxation at a single point using the subgradients, in some cases it can solve the reduced-space formulation significantly faster without any range reduction than the state-of-the-art solver BARON can solve the equation-oriented formulation.

Infeasible Path Global Flowsheet Optimization Using McCormick Relaxations

Deterministic global methods for flowsheet optimization have almost exclusively relied on equation-oriented formulations. The automatic propagation of McCormick relaxations and subgradients enables an alternative formulation similar to sequential modular infeasible path methods in local optimization that operate in a reduced space while moving most model variables and equations to external functions. The application of this reduced-space formulation is demonstrated for the Williams-Otto process. For suitable choices of tear streams and additional variables and equations left to the optimizer, it enables significant reductions in computational time compared to equation-oriented formulations.