The Anonymous Widower

Optimal Prediction of Sand For Adhesion

This project was one of the winners in the First Of A Kind 2022 competition run by Innovate UK.

In this document, this is said about the project.

Project No: 10039258

Project title: Optimal Prediction of Sand For Adhesion
Lead organisation: GOVIA THAMESLINK RAILWAY LIMITED
Project grant: £153,228

Public description: Train services are affected by seasonal variables particularly leaf fall between September and
December. They can also be compromised by wet weather, icy and snowy conditions at a regional
or very localised level on a particular route. Maintaining wheel-rail contact to ensure adequate and
safe braking requires the use of sand in low adhesion conditions. Sand is dispensed to trains in
response to a combination of train service plans and of weather forecast. However, not all trains
are currently able to be replenished during overnight stabling and servicing with attendant risks of
delays and damage to trains and infrastructure. Also, there is a high level of safety risk when sand
replenishment on trains is carried out on a third-rail yard.

“Optimal Prediction of Sand for Adhesion” (OPSA) lead by Govia Thameslink Railway, the major
Train Operating Company on third rail in the UK, will deliver a more efficient and cost-effective
means of predicting the dispensing of sand to trains to ensure services are not compromised by
adhesion losses and train sets are not required to be removed from planned operating diagrams
because of inadequate on board sand supplies. The algorithm developed as a results of this project
will base the estimates on an integrated framework that includes the forecast adhesion, track
maintenance and the expected speed profile in order to capture the change in weather and the seasonal factors.

The algorithm developed represents a cost effective solution to predict the use of sand and
schedule the maintenance of trains enhancing in turn safety and reducing the impact of delays on
the timetable. The algorithm will be developed including direct measure of sand dispersion, braking,
wheel slip and line speed diagram also accounting for human behaviour effects such as driving
style.
Govia Thameslink Railway has engaged with Cranfield University to deliver the disruptive
innovation proposed in this project. The algorithm will enable a more efficient train scheduling
improving public performance measure (PPM) addressing train delay targeting in particular the
25% of delay up to 15 minutes cause by several concurrent issues including train rescheduling and
the National Rail Passenger Survey satisfaction.

My Thoughts And Conclusions

November 18, 2022 Posted by | Computing, Transport/Travel | , , , , , | 1 Comment

Rail Flood Defender

This project was one of the winners in the First Of A Kind 2022 competition run by Innovate UK.

In this document, this is said about the project.

Project No: 10038342

Project title: Rail Flood Defender
Lead organisation: University of Sheffield
Project grant: £249,770

Public description: Rail Flood Defender will deliver a more reliable railway network that is safer for all stakeholders,
and empower Network Rail (NR) and the UK to become global leaders in intelligent holistic rail
drainage management. It will future-proof rail transport against the effects of climate change where
more intense and regular rainstorm events are expected.

The project will explore principles of autonomous active flow control to reduce manual operations
associated with protecting rail infrastructure from the effects of flooding. It achieves this by taking
the latest advances in edge computing and applying it to real-time automation of mechanical and
electrical equipment to control the flows in rail drainage systems, thus protecting the track drainage
from being overloaded and flooded during rainstorm events.

The importance of managing rail drainage infrastructure cannot be overstated. It is designed to
carry stormwater safely water away from the track via a system of pipes and channels. When
drainage infrastructure is compromised or inadequate, flooding can occur. Flooding causes delays
to passengers and costs to asset owners, but crucially can also affect other assets such as
structures and signalling, which endangers human life (e.g. Watford Tunnel
Derailment https://www.gov.uk/raib-reports/derailment-and-subsequent-collision-at-watford). This
project aims to collaboratively investigate the application of AI-powered automated real-time control
(RTC) for protecting the railway system and mitigating any impact on adjacent land.
The feasibility project will identify how the following benefits and sustainability opportunities can be
delivered:

  • Reduce risk of rail services being disrupted during rainstorm events.
  • Make the drainage design process more efficient.
  • Avoid capitally and spatially expensive flood solutions (e.g. stormwater retention tanks).
  • Provide a means for automated flushing to clear blockages (reduce manual intervention).
  • Reduce surcharging on adjacent rural or urban areas.
  • Explore additional opportunities such as rainwater harvesting for agriculture.

My Thoughts And Conclusions

Fifty years ago, I wrote and provided the software, that the Water Resources Board used to plan the water flows and new reservoirs in a large part of England. As over the intervening years, there have been few water shortages due to lack of reservoirs, I am led to believe that the WRB must have done a good job.

Now fifty years later our computing capabilities are much more advanced and I feel that the aims of this project are readily achievable.

November 18, 2022 Posted by | Transport/Travel | , , , | 1 Comment

FEIDS – FOAS Enabled Intruder Detection System

This project was one of the winners in the First Of A Kind 2022 competition run by Innovate UK.

In this document, this is said about the project.

Project No: 10038989

Project title: FEIDS – FOAS Enabled Intruder Detection System
Lead organisation: THALES GROUND TRANSPORTATION SYSTEMS LIMITED
Project grant: £223,660

Public description: Intruders in a railway environment and critical sites are a major problem for the rail industry, and
one that can cause severe delays if not prevented. Conventional monitoring technology is low
range, impractical and has a high deployment and operational cost. Instead, a system that can
monitor the perimeter of a large area with minimal human supervision and can be used to direct rail
staff to the correct location is required to introduce work efficiencies.

Thales’ subcontractor Focus Sensors have developed the technologies capable of delivering a
persistent perimeter detection system that can detect persons approaching a site before they reach
the perimeter boundary and alert railway staff to their precise location. This will support railway staff
to respond effectively and reduce delay minutes, insuring efficiency and cost benefits.

We propose to showcase a first-of-a-kind application of Focus Sensors’ next-generation Fibre Optic
Acoustic Sensing (FOAS) technology to deliver accurate and real-time information and alerts on
intruders or potential intruders in a rail environment using our lateral-positioning technology
developed for detection trains. This capability will enable security staff to rapidly respond to
incidents and ensure intruders can be dealt with quickly and efficiently.

The FOAS-Enabled Intrusion Detection System (FEIDS) will use FOAS to detect objects moving
near the fibre/perimeter, identify them and determine the distance from a boundary. This monitoring
is both real-time and persistent, enabling alerts to be sent when a person or vehicle gets too close
to or crosses a boundary. The high fidelity of the system means that an intruder’s location can be
determined to an accuracy of +/- 50cm, and this information is crucial to ensuring that on-site
security teams are able to quickly and efficiently deal with the intruder.

This technology can be utilised both along sections of the railway and at specific, sensitive sites.
Due to the long range and autonomous nature of the system, it drastically reduces the workload of
railway staff. Staff will be provided with an automatic alert that will provide them with information on
the nature of the intruder(s) and the exact location. This reduces the time for intervention, enabling
trains slowed due to the risk to resume at normal speed quicker, lowering the impact of trespass. It
also increases the likelihood of trespassers being stopped committing vandalism, which can disrupt
operations, and reduces the likelihood of reoffending.

My Thoughts And Conclusions

November 18, 2022 Posted by | Computing, Transport/Travel | , , , | 1 Comment

Protection and Resilience for OLE using ComputerVision Techniques (PROLECT)

This project was one of the winners in the First Of A Kind 2022 competition run by Innovate UK.

In this document, this is said about the project.

Project No: 10037158

Project title: Protection and Resilience for OLE using ComputerVision Techniques (PROLECT)
Lead organisation: ONE BIG CIRCLE LTD
Project grant: £247,115

Public description: 

This project will utilise Computer Vision techniques applied to existing video footage and capturing
a new type of video sensor to address two main challenges which are exacerbated by weather
events and can result in the railway being closed. Providing means in which these type of challenge
can be predicted and prevented will help provide the railway to become more resilient to weather
events and season agnostic.

The following two areas will be addressed:

  • Extreme hot weather causes OLE wires to extend and cause the tensioners to come into contact with the ground which can reduce tension and cause damage or event dewirement. Utilising existing video footage this project will automatically identify OLE tensioners, position and measure them and generate an live asset map with current status level. This can be utilised as part of a digital twin model and fed into systems which are able to alert maintainers to the issue so they are able to take preventative action.
  • Hot, cold and humid weather can also have an impact causing Corona discharge from electrical assets such as insulators. The Corona discharge is an early warning sign of potential damage and failure of the equipment and can be measured as part of a predictive maintenance regime to prioritise preventative maintenance activities. This project will install a UV Corona camera onto a measurement fleet or in-service train and enable automated data capture with real-time data transmission and processing. The results will be evaluated by experienced working groups to tune and amend the level of Corona events to ensure an optimum level of precision and recall ensuring an operationally useful tool.

Both of these events can have very impacts on the railway in terms of delay, safety and customer
experience. By providing tools which have the capability of preventing these from occurring the
railway will have an increased resilience to the weather conditions.

My Thoughts And Conclusions

November 18, 2022 Posted by | Transport/Travel | , , | 1 Comment

NextGen Data-Driven Timetable Performance Optimisation Tool

This project was one of the winners in the First Of A Kind 2022 competition run by Innovate UK.

In this document, this is said about the project.

Project No: 10037862

Project title: NextGen Data-Driven Timetable Performance Optimisation Tool
Lead organisation: ARTONEZERO LIMITED
Project grant: ££157,826

Public description:

During the pandemic, the on-time reliability of services significantly increased due to the reduction
in the number of services and passengers.

However, as passengers have returned to the railway performance has once again deteriorated.

This has an even greater impact on the industry post-pandemic as passengers’ expectations for services that are reliable and run on-time is even higher. Increased delays and passenger dissatisfaction therefore leads to an even greater decreased revenue from ticket sales.

Poor performance is in large part due to a poorly planned timetable that is often operationally unachievable or cannot handle minor perturbations. This is due to the timetable usually being planned with simulations and the method does not in how trains performing in reality at junction or stations.

Through years of working closely with performance, planning and operational teams, we’ve identified that by using granular train movement data and machine learning techniques, the actual performance of the existing timetable could be accurately calculated. This would enable planners with accurate information to make faster and better planning decisions that are based on real-world evidence.

Our Timetable Analysis tool will deliver automatically updated insights and recommendations to planners that is highly aligned to the planning process. Utilising both on-track (track circuit) and onfleet (GPS and OTMR) data, the tool will provide an integrated view to both Network Rail and TOC teams.

Fundamentally this tool will result in a step change in the speed and quality of timetable planning, moving away from the use of limited simulations and anecdotal experience to a fully evidenced-based approach.

November 18, 2022 Posted by | Computing, Transport/Travel | , | 1 Comment

EventGo – Intelligent Rail Service Demand Forecasting for Event-Based Travel

This project was one of the winners in the First Of A Kind 2022 competition run by Innovate UK.

In this document, this is said about the project.

Project No: 10037294

Project title: EventGo – Intelligent Rail Service Demand Forecasting for Event-Based Travel
Lead organisation: YOU. SMART. THING. LIMITED
Project grant: £249,946

Public description: 

Aim: EventGo will demonstrate a first-of-a-kind solution for accurately predicting how large visitor events impact demand for specific railway services, generating advance insight on rail capacity, and enhancing the ability of TOC planning teams to optimally plan and deliver railway timetables and services. Data-enabled decision-making is expected to improve overall TOC operational performance, as demand is more precisely matched with supply in order to realise new cost efficiencies, improve yield, and deliver enhanced customer experiences. The project outcomes address the competition’s plan resilience and recoverability theme.

Challenge: Large visitor events create extreme demand peaks within the railway network. Though such events are often scheduled months in advance, accurately predicting how this demand is likely to impact a specific scheduled railway service is notoriously complex due to the lack of advance data about visitors’ travel plans. In leu, TOCs often rely on best guess estimations. As recent UEFA Champions League finals in Pairs demonstrated, underestimating visitor travel can have severe consequences for an organisation’s reputation, and visitor safety.

Project: A mature EventGo prototype solution will be deployed by UK TOC planning team to predict how a series of sporting fixtures between January and March 2023 in the Yorkshire region are likely to impact time-tabled railway services. During this period, partners will investigate how advanced insight generated by EventGo can be exploited by planners to make intelligent adjustments to scheduled services, e.g., adding capacity to specific services to match high
demand, to ensure optimal asset utilisation and deliver the highest level of customer experience.

Value: Demonstration in a live railway environment allows partners to both verify the accuracy of the model’s rail travel demand prediction, and to evidence the business value such intelligence can have on TOC operations. In addition, accrued results will facilitate product approval procedures and raise the visibility of the novel solution in the target market.

Consortium: The project is led by You. Smart. Thing. (“YST”), a specialist in intelligent mobility solutions, and supported by two UK TOCs, a top-tier sporting institution and stadium management company, and regional government partners. Professional project management is provided by In The Round (“ITR”), a UK-based consultancy specialising large visitor events travel management.

My Thoughts And Conclusions

I have been caught up in bad event planning several times and feel that this project could be very useful to plan passenger movement at large events.

I doubt, it will be a solution, that only has UK applications.

November 18, 2022 Posted by | Computing, Transport/Travel | , , | 1 Comment

ERiCS – Emissions Reductions in Closed Stations

This project was one of the winners in the First Of A Kind 2022 competition run by Innovate UK.

In this document, this is said about the project.

Project No: 10038627

Project title: ERiCS – Emissions Reductions in Closed Stations
Lead organisation: PORTERBROOK LEASING COMPANY LIMITED
Project grant: £59,459

Public description:

We have previously developed an exhaust aftertreatment system to install on Porterbrook’s Class 170 and Class 158/9 vehicles. This technology successfully showed we could significantly reduce the emissions from mid-life diesel trains.

All aftertreatment systems, including those fitted to new diesel engines, work effectively at higher exhaust temperatures but when the train is idling in a station, the aftertreatment is much less effective. This innovation is to develop a new exhaust gas heating solution with geo-fencing capability to dramatically improve the effectiveness of the exhaust
aftertreatment system in covered stations.

The innovation is a development of an electrically heated catalyst which has been used in road applications but is entirely new to rail and could unlock the in-station benefits of aftertreatment systems on diesel trains. This will specifically target NOx and complement PM reduction in stations caused by trains idling and provide a viable retrofit option until full electrification is available.

The innovation will be led by rolling stock asset owner Porterbrook with their partner Eminox who has supplied rail exhaust solutions to diesel engines for several decades. In Phase 1, the project will carry out work to prove the technology on a bench test at Eminox’s test facility. Later in Phase 2, if we are successful, working with our operating partner East Midlands Railway, we propose to demonstrate the additional benefit in emissions reductions in stations by fitting the equipment onto a suitable DMU, and validating the test results in passenger service. This new innovation enhances the business case for fleet roll out of this technology by offering additional benefits where it matters to passengers, staff and neighbours at railway stations. Both Porterbrook and Eminox are delighted to continue the development of their after-treatment system to specifically target emissions in stations, this will take abatement solutions to the next level and provide greener railways. Neil Bamford, Fleet Director at East Midlands Trains said, “The project aligns well to our sustainability objectives, as it offers the opportunity to provide tangible benefits for emissions reduction in stations. We look forward to working with the consortium”

My Thoughts And Conclusions

November 18, 2022 Posted by | Transport/Travel | , , , | 1 Comment

Zero Emission Powering of Auxiliary Loads In Stations

This project was one of the winners in the First Of A Kind 2022 competition run by Innovate UK.

In this document, this is said about the project.

Project No: 10038972

Project title: Zero Emission Powering of Auxiliary Loads In Stations
Lead organisation: WABTEC UK LIMITED
Project grant: £59,921

Public description:

This project provides a solution to substantially reduce emissions including NOx and PM when diesel passenger trains are idling.

There are over 3,500 passenger rail vehicles in the UK currently fitted with a diesel engine, the large majority of these would significantly benefit from emissions reduction, especially in and around stations, where diesel engines currently continue to idle, or elevated idle whilst stationary, sometimes for up to 30 minutes at a terminal station. This is a significant contributor to local air quality issues from NOx, PM emissions etc.

Brecknell Willis aim to further develop their existing current collection product portfolio by producing
a low-cost, automated shore supply for powering the auxiliary loads of each vehicle and enabling
the diesel engines to be disabled while stationary.

This project will enable several key cost and decarbonisation benefits to the railway.

  • It shall enable zero emissions, including NOx and PM, in and around the station, by
    enabling a DMU to dwell at any enabled station or depot with the engine switched off
    through an automated shore supply.
  • It shall enable a proportional average reduction in all emissions, through reduced fuel consumption due to not using the diesel engine whilst the vehicle is stationary.
  • It shall enable reduced operating costs for the train operator through fuel saving.
  • It will not require any modification to the existing diesel engines or drivetrain and will compliment any other decarbonisation initiatives.
  • It shall provide a substantially lower cost and risk solution when compared to any other previous or current hybrid solutions.

My Thoughts And Conclusions

 

November 18, 2022 Posted by | Transport/Travel | , , | 4 Comments

Axle Mounted Motor For Retrofit To DMU’s To Enable Zero Emissions In Stations

This project was one of the winners in the First Of A Kind 2022 competition run by Innovate UK.

In this document, this is said about the project.

Project No: 10038683

Project title: Axle Mounted Motor For Retrofit To DMU’s To Enable Zero Emissions In Stations
Lead organisation: WABTEC UK LIMITED
Project grant: £59,450

Public description: This project provides a solution to substantially reduce emissions including NOx and PM when
diesel passenger trains are idling.
There are over 3,500 passenger rail vehicles in the UK currently fitted with a diesel engine, the
large majority of these would significantly benefit from emissions reduction, especially in and
around stations, where diesel engines currently continue to idle, or elevated idle whilst stationary,
sometimes for up to 30 minutes at a terminal station. This is a significant contributor to local air
quality issues from NOx, PM emissions etc.

Furthermore, rail vehicles require large amounts of energy and power to accelerate (and therefore
contributing more emissions), and yet, on the approach to stations significant amounts of energy
are “lost” through “braking”.

This project will address both issues by recovering the braking energy during deceleration and reusing it for auxiliary loads in station and traction to accelerate out of station, this will enable diesel
engines to be isolated in and around stations, whilst also reducing the average emissions such as
PM and NOx over a complete drive cycle by up to 35% and operational costs by up to 30%.

Our objective is to develop and integrate a small, low mass, yet high peak torque and peak power,
axle mounted motor, for retrofit and upgrade for DMU/DEMU passenger vehicle applications. This
motor shall enable kinetic energy recovery during the braking application and also provide power to
the trailer bogie wheels whilst accelerating.

This project will enable several key cost and decarbonisation benefits to the railway.

  • It shall enable zero emissions, including NOx and PM, in and around the station, by
    enabling a DMU to approach, dwell and depart from a station with the engine switched off.
  • It shall enable a proportional average reduction in all emissions, through reduced fuel consumption resulting from the electrical energy recovery from regenerative braking and re-deployment through auxiliary and traction use.
  • It shall enable less brake wear thus reducing particulate emissions from brake pads especially around stations.
  • It shall enable reduced operating costs for the train operator through fuel saving, engine/transmission maintenance savings and brake pad saving.
  • It will not require any modification to the existing diesel engines or drivetrain and will compliment any other decarbonisation initiatives.
  • It shall provide a substantially lower cost and risk solution when compared to any other previous or current hybrid solutions.

My Thoughts And Conclusions

This is a classic simple solution, that could have big benefits.

I suspect, it can also be paired with Wabtec’s other proposal; Zero Emission Powering of Auxiliary Loads In Stations.

November 18, 2022 Posted by | Energy, Transport/Travel | , , , | 7 Comments