46: District Heating – Cost-optimal heat generation for a municipal utility company of a midsize city
District heating could play an essential role in the cost-effective decarbonisation of the energy system due to its flexibility to integrate a large share of renewable energy sources. However, it faces certain challenges related to the increasing energy efficiency at the consumer side, changing technical requirements, and increasingly dynamic markets.

45: Digital Engineering Workflow Applied to ICEs with Alternative Fuels
Recent development and research show that alternative fuels from various decarbonization sources/processes such as CO2 capture and utilisation, are suitable substitutions for conventional fuels in order to reduce the greenhouse gas footprint and air pollution. In addition, there is increasing interest in exploiting carbon-neutral fuels during ICE development in order to meet the ever-stringent emissions regulations.

44: Machine Learning techniques to evaluate power conversion efficiency of organic photovoltaics
This use-case focuses on building and testing the performance of computational models for predicting power conversion efficiency of OPVs based on the SMILES-derived structural information of the donor candidates as well as assessing impact and implications of the choice of training data: large but synthetic vs small but experimental datasets.

43: Digital Engineering Workflows for ARAI’s Powertrain Development
This use-case demonstrates the capability of kinetics & SRM Engine Suite in detailed physico-chemical engine modelling for combustion characteristics and engine-out emissions evaluations. This use-case also demonstrate the capability of MoDS in generating high-dimensional, fast response surrogate models for transient cycle simulations in MATLAB.

42: Multi-Objective Optimisation (MOO) with Multi-Criteria Decision Making (MCDM)
Digital engineering approaches such as Multi-Objective Optimisation (MOO) and Multi-Criteria Decision Making (MCDM) are receiving increasing attention in today’s industry. MOO and MCDM enable engineers and researchers to further optimise their existing engine without relying extensively on measurement data, hence saving time and costs.

41: Lean Burn Spark Ignition Engine Simulations
Simulating gasoline fuelled lean burn spark ignition combustion engine to study the effects of leaner fuel on engine power output and gas phase emissions.

40: Modelling study of Carbon Black (CB) formation at different operating conditions
Carbon Black (CB) is a nano-sized material that is often regarded as a pure form of soot. This use-case describes a modelling study of CB formation in PFR reactors using Method of Moments (MOM) and Method of Sections (SECT) models to predict properties such as average particle size, number of primaries per aggregate PSD, and concentration profiles for selected gaseous species.

39: Transient Particulate Emissions Simulation
Presenting a digital engineering workflow that calibrates and validates a detailed physico-chemical model based on measurements data, which populates and augments the data to produce emissions “maps”.

38: Application of kinetics to Chemical Vapor Deposition (CVD) Process
A generic reactor network feature in kinetics is applied to model surface and gas phase chemistry involved in the CVD process.

37: Morphology and Fractal dimension of carbon black aggregates
A detailed stochastic approach using kinetics to predict the evolution of fractal dimension of carbon black aggregates along the length of the reactor.

36: A reactor network approach in kinetics to model the gas-phase synthesis of nanoparticles in DC plasma reactors
Here, kinetics is used to predict the characteristics of nanomaterials produced in Direct Current (DC) plasma reactors using a fast-response toolkit able to accurately capture relevant properties of both particle and gas phase.

35: Hot-wall reactor for the gas-phase synthesis of inorganic nanomaterials
To accurately and rapidly simulate the gas-phase systhesis of inorganic nanomaterials in a hot-wall reactor, accounting for the interaction between particle and gas phase.

34: Estimating PM and PN emissions with the SRM Engine Suite coupled to a 1D engine cycle model
Using the SRM Engine Suite to account for the effects of different compositions at engine-out on tailpipe emissions in internal combustion engines.

33: Simulating IC engines: From fuel to engine-out and tailpipe emissions
SRM Engine Suite integrated with a commercial 1D engine cycle simulator to model engine-out and tailpipe emissions as a function of fuel, combustion mode, and aftertreatment.

32: Predictive HD Engine Modelling with the SRM Engine Suite and MoDS
Full in-cylinder pressure and emissions-modelling workflow of a CAT C4.4 engine, including automatic calibration of the SRM Engine Suite with MoDS.

31: IC Engine Simulation via Cloud
Applying the SRM Engine Suite to Dual-Fuel IC Engines run on the CloudSME platform.

30: Automated statistical analysis and calibration of advanced process models
Performing rapid analysis of sensitive and uncertain model parameters for computationally intensive processes, in the presence of inter-dependencies and model discontinuities.

29: Rapid engine map generation and automatic model calibration for downsized IC engines
Developing fast-response models to generate engine performance and CO2 footprint maps for naturally aspirated and downsized engines.

28: Applying kinetics to Simulate Fischer Tropsch
Detailed microkinetics model (with novel features including surface coverage profiles) coupled with advanced parameter estimation techniques used to study FT synthesis on Co/?-Al2O3.

27: Simulating in-cylinder turbulence and bulk flows
Building an advanced turbulence model with sufficient detail to simulation the most important engine flow field parameters (swirl, tumble, squish, injection etc.) and integrate these models into the SRM Engine Suite.

26: Applying Neural Networks to advanced engineering
Applying Neural Networks as surrogates to two turbo-compressor maps.

25: applying a Monte Carlo analysis to project management
MoDS is applied to estimate the overall duration of a project: A Monte Carlo analysis is carried out to determine the probability of meeting a 20 day deadline.

24: global sensitivity analysis of fuel consumption
Building a virtual vehicle to run over multiple standardised and real-world drive-cycles, identifying the most important design parameters in minimising fuel efficiency.

23: automated model calibration and parameter estimation
A common example of parameter estimation is carried out routinely in IC engine design and development. In this simple example, we seek to calibrate a IC engine model and complete a parameter estimation using measurements of engine power and torque as a function of engine speed.

22: Treating external 3rd software as black box model
Creating a user friendly interface to treat a third-party proprietary software (Dynasty) as a black box model to perform optimisation

21: Data-driven surrogate models and analysis for friction application using MoDS
Reducing the computational expense associated with predictive modelling of friction losses and IC engine performance in the design phase.

20: virtual engine mapping of Tier IV HD diesel engines for non-road applications
Calibrating the SRM Engine Suite against a reduced data set and applying these parameters to extrapolate over the while engine load-speed map of a state-of-the-art diesel engine.

19: fuels, combustion and emissions analysis in a fraction of the time
Comparing the predictive capabilities of 3D-CFD and the SRM Engine Suite using a VM MOTORI 2516 Turbocharged 4-valve DI engine.

18: meeting PM-NOx limits through numerical feasibility analysis
Simulating a CIDI engine to meet the next generation of Tier 4 NOx/PM emissions targets through numerically led design of experiments.

17: the impact of fuel properties on “knocking” combustion in boosted spark ignition engines
Simulating combustion in SI Engine under knocking conditions for a variety of fuels, completing a “blind test” of the model.

16: diesel engine optimisation
Using the SRM Engine Suite to identify minimum exhaust gas emissions for a load-speed point.

15: Accounting for uncertainties in advanced model parameter estimations
Applying in-house parameter estimation metholodogies to estimate unknown model parameters in a complex granulation model.

14: Ab initio modelling of nanoparticle systems
Coupling a kinetics model developed from first principles (using quantum mechanics and statistical thermodynamics) with a detailed population balance model to simulate an industrial scale reactor.

13: Investigating the SI-HCCI transition
Using the SRM Engine Suite (coupled with commercial software), to simulate SI-HCCI transition and investigate the resulting emissions.

12: Investigating fuel reforming in an HCCI engine with dual injection strategy
Investigating the effect ot fuel reforming in an HCCI engine operated with NVO and a dual injection strategy.

11: Improving engine stability and exhaust emissions through optimisation of the control strategy
Simulation and tabulation of the SI-HCCI transition, to enable optimisation of control parameters, with the aim of improving the stability and reducing emissions during the transition.

10: Impact of EGR on combustion and emission in a CNG engine
Simulating combustion and emission of a CNG fuelled combustion engine operating in HCCI mode at high EDR rates.

09: probability density function methods for turbulent reacting flows
Combining a conventional CFD code with efficient implementations of two recent probability density function-based reaction models.

08: Transforming data into knowledge – automated model development for IC engines
Developing more robust models by integrating experiments and models such that model parameters can be obtained automatically using novel optimisation techniques.

07: Predictive combustion simulations for “downsized” direct injection spark-ignition engines
Here, the SRM Engine Suite is used to simulate DISI engine combustion to identify the sources of pre-ignition and knock in “downsized” DISI engines.

06: Examining soot emission from boosted diesel engines at high EGR
Computing the size distribution, composition, and morphology of soot formed in IC engines.

05: Optimisation of combustion chamber geometry for improved exhaust emissions
Coupling a 3D CFD code with the SRM Engine Suite to simulate diesel fuelled engine combustion with detailed chemical kinetics.

04: Engine operation design optimisation for modern DISI engines
Simulating the NOx, CO, HC, and soot emissions produced by a DISI engine and optimise fuel injection timings.

03: Advanced combustion concepts and bio-fuels for reduced CO2 emissions
Developing a model for the simulation of the combustion and emissions on bio-fuels.

02: Partially-Premixed Compression Ignition (PPCI) and Low Temperature Combustion (LTC modes)
Using the SRM Engine Suite to simulate multiple injection strategies in PPCI combustion mode and identify sources of emissions.

01: Models for simultaneous optimisation of engine and fuel
Here, the SRM Engine Suite is used to develop a model for the simulation of real fuels such as gasoline and diesel.