Tag: Research

Systems Engineering, the journal of The International Council on Systems Engineering (INCOSE) has published my most recent paper, entitled “A systems-engineering approach to nation-scale problems: Municipal solid waste management in Saudi Arabia“.

Paper Overview (TL;DR)

We applied systems-engineering techniques to investigate how municipal solid waste (MSW) is treated, using Saudi Arabia as a case study. We built a mathematical model of the system and used it to investigate different scenarios.

This model showed that a combination of anaerobic digestion (for food and organic waste), recycling and incineration (for non-recyclable materials) would reduce the total mass of waste to landfill by 73%. Not only that, this approach reduced the effect of the waste management on the environment by 98%.

Motivation

In Saudi Arabia, municipal solid waste (MSW) is currently disposed of in landfill (dumping it in a hole). This causes irreparable environmental harm and increased hazard from the possibility of landfill fires.

However, the Saudi MSW system is a large, multi-stakeholder (lots of people are interested in the outcome) system. This makes it a great system to develop “nation-scale” (really big) systems engineering tools on.

System Model

My previous work has focussed on modelling rail vehicles and infrastructure, and using these models to investigate how to reduce their emissions. So we took that and applied it to this giant system – the Saudi MSW system:

Then we built a mathematical model of the system, so that we could understand how the narrow system of interest (the waste stream) behaved when we changed some of the inputs. (This involved lots of checking through other people’s work to see how these things should be modelled!) Finally, we came up with a (pretty complex!) system model that looked like this:

Then, we made some assumptions about about the makeup of the waste, and the likely population growth over the next 30 years. With that done, we could then answer two basic questions: What happens if we do nothing? What happens if Saudi citizens reduce their waste per person from 1.38kg/day to 1.14kg/day (in line with the UK)? And the answer is:

Using the Model

Then, we took this freshly made model and applied it to a range of possible scenarios that we’d devised, based on what we would do, and what other people had suggested:

Scenario number	What it involved
Scenario 0 (baseline)	Everything to landfill
Scenario 0.1	Everything to landfill, but less waste per person (1.14 kg/person/day)
Scenario 0.2	Everything to landfill with much less waste per person (1.02 kg/person/day)
Scenario 1	Food, glass and metal to landfill. Everything else is incinerated
Scenario 2	Everything except glass and metal goes to anaerobic digestion
Scenario 3	Anaerobic digestion or recycling for everything. (Incineration for textiles)
Scenario 4	Anaerobic digestion or recycling for everything. (Landfill for textiles)

And this gave us some pretty graphs, showing how much waste went to landfill in each year for each of the scenarios. (Each of the measures was given 10 years to implement, because making new infrastructure takes time.)

Then, we could look at how much went to landfill in total over the 30-year horizon of the simulation:

This is pretty clear! S3 leads to the lowest total mass to landfill over the 30 years of the study. Job done!

Environmental Impact

Well, almost. Finally, we wanted to check how the environmental effects of each of the scenarios compared. For this we used a commercial life cycle analysis (LCA) tool called SimaPro. We modelled each of the scenarios in this tool, and compared the DALY for each of them. (DALY stands for disability-adjusted life year, or how much of an effect a certain action has on people’s lives. The higher the number, the worse the effect on us.)

You can see that all of the changes suggested by our systems engineering for waste management study have reduced the hazard the waste poses to people’s lives. In fact, Scenario 3 has only 2% of the impact on people’s lives of the current system. This is encouraging!

Conclusions

The results of this study into systems engineering for waste management are encouraging!

1. Just reducing the amount of waste people create would reduce the amount of waste to landfill by 89 million tonnes over 30 years.
2. Scenario 3 (anaerobic digestion of most waste, combined with recycling and limited incineration of non-recyclable materials) is the winner! This would save 328 million tonnes of waste going to landfill over the next 30 years.
3. Scenario 3 also reduces the impact of waste management on people’s health by 98% compared to the current system.

Other work

For more information on my research, please check out my Research page.

The Proceedings of the IMechE, Part D: Journal of Automobile Engineering has published a new article of mine, entitled Modelling and Experimental Validation of the Performance of a Digital Displacement® Hydraulic Hybrid Truck. I did this work in partnership with Danfoss. The paper is open-access and freely downloadable.

Paper Overview (TL;DR)

We added hydraulic hybridisation to a light truck and improved its fuel economy by 23%. We also used simulation to show that hydraulic hybridisation can improve the fuel economy by up to 95%, depending on the type of driving

Motivation

My previous work has shown that hydraulic hybridisation is effective at reducing the fuel consumption of heavy goods vehicles. However, this research was limited due to the hardware used and wasn’t tested in a controlled environment (on a rolling road, or ‘dynamometer‘).

In this work, Danfoss converted a light truck to a hydraulic hybrid using their Digital Displacement® technology, and tested it on a dynamometer.

The Vehicle Conversion

Danfoss converted a light truck to a hydraulic hybrid using a Digital Displacement® pump/motor. (A pump/motor can produce negative [braking] torque and a positive [accelerating] torque, rather than just one or the other.) The system stores recovered energy in a high-pressure hydraulic accumulator.

Test Results

First, we checked to see how consistent the drivers were. They were remarkably consistent; the distance covered in the tests had a standard deviation of 0.3%! After that, we checked the results from the logging equipment to make sure it was sensible.

Next, we looked at how the fuel usage of the hybrid vehicle compared to the un-altered vehicle. (Hint: it used a lot less fuel!)

Model Validation

After that, we checked to make sure our model was a reasonable fit with the experimental data .(This step is called ‘validation‘, and is a common technique in engineering.)

Model Performance

Now that we had a working model, the next step was to use this model to investigate what benefits might be achievable if we could change some of the system parameters. We found that with some small parameter changes, and by turning off the engine when it wasn’t being used, the vehicle would use much less fuel. It used 36% less fuel over this cycle!

Next, we looked at the performance on a more common drive cycle, the WLTP cycle. In this case the hybrid truck used 19% less fuel than the original diesel vehicle – not bad!

Conclusions

The main conclusions of our paper were:

1. It’s possible to use Digital Displacement technology to make a hydraulic hybrid truck.
2. Hybridising the vehicle reduces fuel consumption by 19-36%, depending on the drive cycle.

If you want more information, please check out the full paper online.

There is more information on my other decarbonisation work on electric vehicles and rail vehicles as well.

The Proceedings of the Institution of Mechanical Engineers, Part F: Journal of Rail and Rapid Transit has published a new article of mine, entitled Development and control of a rail vehicle model to reduce energy consumption and carbon dioxide emissions. The paper is open-access and freely downloadable.

Paper Overview

We made a detailed model of a bi-mode rail vehicle and used control to reduce its carbon emissions (decarbonisation).

The Rail Vehicle Model

A bi-mode train is one that can run on electricity from overhead wires (sometimes called overhead line equipment or OLE), or by generating electricity from the on-board diesel generator. Then we used vehicle data to make sure the model represented the behaviour of the real train.

Control for Decarbonisation

We used that model to look at a range of controllers for reducing the CO₂ emitted by the train (decarbonisation) during its run from London Paddington to Plymouth in the UK. Our controller reduced the CO₂ emissions of the train by 19%. Without this controller, the train produces around 42g of CO₂ per passenger-kilometre of diesel running.

Intermittent Electrification

We also investigated some simple ‘intermittent electrification’, where only some sections the route are electrified. (Some people also call this discontinuous or discrete electrification.) You can see the results of this analysis in the picture, below.

The figure shows that intermittent electrification can be more effective than continuous electrification at reducing carbon dioxide emissions. It also shows that selective engine shutdown can be used for the decarbonisation of a bi-mode rail vehicle.

If you’d like more information on my work on railway decarbonisation, check out the project webpage, or get in touch!

Funding

This project was generously funded by the RSSB (project COF-IPS-02). We would also like to thank Hitachi Rail, Angel Trains, Great Western Railway and Chiltern Railways for their support.