Real-Time Emission Prediction with Detailed Chemistry under Transient Conditions for Hardware-in-the-Loop Simulations

The increasing requirements to further reduce pollutant emissions, particularly with regard to the upcoming Euro 7 (EU7) legislation, cause further technical and economic challenges for the development of internal combustion engines. All the emission reduction technologies lead to an increasing complexity not only of the hardware, but also of the control functions to be deployed in engine control units (ECUs). Virtualization has become a necessity in the development process in order to be able to handle the increasing complexity. The virtual development and calibration of ECUs using hardware-in-the-loop (HiL) systems with accurate engine models is an effective method to achieve cost and quality targets. In particular, the selection of the best-practice engine model to fulfil accuracy and time targets is essential to success. In this context, this paper presents a physically- and chemically-based stochastic reactor model (SRM) with tabulated chemistry for the prediction of engine raw emissions for real-time (RT) applications. First, an efficient approach for a time-optimal parametrization of the models in steady-state conditions is developed. The co-simulation of both engine model domains is then established via a functional mock-up interface (FMI) and deployed to a simulation platform. Finally, the proposed RT platform demonstrates its prediction and extrapolation capabilities in transient driving scenarios. A comparative evaluation with engine test dynamometer and vehicle measurement data from worldwide harmonized light vehicles test cycle (WLTC) and real driving emissions (RDE) tests depicts the accuracy of the platform in terms of fuel consumption (within 4% deviation in the WLTC cycle) as well as NOx and soot emissions (both within 20%).

Validation of a multi-physics simulation platform for engine emissions modelling

This paper introduces a comprehensive and systematic Design of Experiments based methodology deployed in conjunction with a multi-physics engine air-path and combustion co-simulation, leading to the development of a global transient simulation capability for engine out NOx emissions. The proposed multi-physics engine simulation framework couples a real-time one-dimensional air flow model with a Probability Density Function based Stochastic Reactor Model that accounts for detailed in-cylinder combustion chemistry to predict combustion emissions. The integration challenge stemming from the different computation complexities and time scales required to ensure adequate fidelity levels across multi-physics simulations was addressed through a comprehensive Design of Experiments methodology to develop a reduction of the slower Stochastic Reactor Model simulation to enable a transient simulation focussed on NOx emissions. The Design of Experiments methodology, based on Optimal Latin Hypercube design experiments, was deployed on the multi-physics engine co-simulation platform and systematically validated against both steady state and transient light-duty Diesel engine test data. The surrogate selection process included the evaluation of a range of metamodels, with Kriging metamodels selected based on both the statistical performance criteria and consideration of physical phenomena trends. The transient validation was carried out on a simulated New European Drive Cycle against the experimental data available, showing good capability to capture transient NOx emission behaviour in terms of trends and values. The significance of the results is that it proves the transient and drive cycle capability of the multi-physics simulation platform, suggesting a promising potential applicability for early powertrain development work focussed on drive cycle emissions.

Calculation of the Neutron Parameters for Accelerator-Driven Subcritical Reactors

In this paper, the accelerator-driven subcritical reactor (ADSR) is simulated based on structure of the TRIGA-Mark II reactor. A proton beam is accelerated and interacts on the lead target. Two cases of using lead are considered here: firstly, solid lead is referred to as spallation neutron target and water as the coolant; secondly, molten lead is considered both as a target and as a coolant. The proton beam in the energy range from 115 MeV to 2000 MeV interacts with the lead to create neutrons. The neutron parameters as neutron yield Yn/p, neutron multiplication factor k, the radial and axial distributions of the neutron flux in the core have been calculated by using MCNPX program. The results show that the neutron yield increases as the energies of the proton beam increases. When using the lead target, the differences between the neutron yield are from 4.2% to 14.2% depending on the energies of the proton beam. The proportion of uranium in the mixtures should be around 24% to produce an effective neutron multiplier factor greater than 0.9. The neutron fluxes are much higher than the same calculations for the TRIGA-Mark II reactor model using tungsten target and light water coolant.

Validation of a Fixed Bed Reactor Model for Dimethyl Ether Synthesis Using Pilot-Scale Plant Data

The one-dimensional (1D) mathematical model of fixed bed reactor was developed for dimethyl ether (DME) synthesis at pilot-scale (capacity: 25–28 Nm3/h of syngas). The reaction rate, heat, and mass transfer equations were correlated with the effectiveness factor. The simulation results, including the temperature profile, CO conversion, DME selectivity, and DME yield of the outlet, were validated with experimental data. The average error ratios were below 9.3%, 8.1%, 7.8%, and 3.5% for the temperature of the reactor, CO conversion, DME selectivity, and DME yield, respectively. The sensitivity analysis of flow rate, feed pressure, H2:CO ratio, and CO2 mole fraction was investigated to demonstrate the applicability of this model.

Multi-objective optimization of an industrial slurry phase ethylene polymerization reactor

Slurry polymerization processes using Zeigler–Natta catalysts are most widely used for the production of polyethylene due to their several advantages over other processes. Optimal operating conditions are required to obtain the maximum productivity of the polymer at minimal cost while ensuring operational safety in the slurry phase ethylene polymerization reactors. The main focus of this multi-objective optimization study is to obtain the optimal operating conditions corresponding to the maximization of productivity and yield at a minimal operating cost. The tuned reactor model has been optimized. The single objective optimization (SOO) and multi-objective optimization (MOO) problems are solved using non-dominating sorting genetic algorithm-II (NSGA-II). A complete range of Pareto optimal solutions are obtained to obtain the maximum productivity and polymer yield at different input costs.

Hydrogenation of CO/CO2 mixtures under unsteady-state conditions: Effect of the carbon oxides on the dynamic methanation process

The Power-to-Gas (PtG) process offers the opportunity to store fluctuating renewable energy in form of chemical energy by hydrogenating carbon oxides into methane. In addition, potential carbon point sources often consist of CO/CO2 (COx) mixtures. Hence, reactor design requires kinetic models valid for unsteady-state operation and a broad spectrum of feed gas compositions. In order to provide the required experimental data basis for derivation of kinetic expressions valid under transient conditions, the dynamic response of a continuously operated fixed-bed methanation reactor is studied by applying periodic step-changes in the feed composition. The obtained results are evaluated based on a simple reactor model, providing the molar flow rate exchanged between the gas bulk and the solid surface for CO, CO2, CH4, and H2O. The results further reveal that the transient kinetic processes at the catalyst surface strongly affect the reactor response under reaction conditions of technical relevance.

Process Intensification in Photocatalytic Decomposition of Formic Acid over a TiO2 Catalyst by Forced Periodic Modulation of Concentration, Temperature, Flowrate and Light Intensity

The effect of forced periodic modulation of several input parameters on the rate of photocatalytic decomposition of formic acid over a TiO2 thin film catalyst has been investigated in a continuously stirred tank reactor. The kinetic model was adopted based on the literature and it includes acid adsorption, desorption steps, the formation of photocatalytic active sites and decomposition of the adsorbed species over the active titania sites. A reactor model was developed that describes mass balances of reactive species. The analysis of the reactor was performed with a computer-aided nonlinear frequency response method. Initially, the effect of amplitude and frequency of four input parameters (flowrate, acid concentration, temperature and light intensity) were studied. All single inputs provided only a minor improvement, which did not exceed 4%. However, a modulation of two input parameters, inlet flowrate and the acid molar fraction, considerably improved the acid conversion from 80 to 96%. This is equivalent to a factor of two increase in residence time at steady-state operation at the same temperature and acid concentration.

Análisis térmico de los elementos de sujeción del núcleo de un reactor trifásico

In this thesis work the temperature distribution in the frame bolts of a 5 MVA, 115 kV, 60 Hz, three-phase five-limbs shunt reactor is obtained utilizing the finite element method (FEM) and the commercial ANSYS Maxwell software. This because the reactor actually failed while it was running, the failure occurred progressively as the screw insulation was damaged and caused an unwanted temperature rise. A time-harmonic analysis is performed to compute the magnetic field distribution in the reactor and the power losses in the frame bolts. A three-dimensional (3-D) shunt reactor model is utilized, and Maxwell’s equations are solved utilizing scalar and vectorial magnetic potentials. The 3-D electromagnetic shunt reactor model is validated by comparing the value of inductance measured in the laboratory with the value of inductance computed in the 3-D FE simulation. In addition, the core losses computed in the FE simulation are compared with the core losses measured in the laboratory. This thesis work is important for transformer manufacturers which requires an adequate shunt reactor model to analyze it under different operation conditions and to optimize the actual design.