Fireside corrosion of heat exchanger materials for advanced solid fuel fired power plants

To address the challenge of climate change, future energy systems need to have reduced greenhouse gas emissions and increased efficiencies. For solid fuel fired combustion plants, one route towards achieving this is to increase the system’s steam temperatures and pressures. Another route is to co-fire renewable fuels (such as biomass) with coals. Fireside corrosion performance of two candidate superheater/reheater alloys has been characterised at higher heat exchanger surface temperature. Samples of the alloys (a stainless steel, Sanicro 25 and a nickel-based alloy, IN740) were exposed in fireside corrosion tests at 650 °C, 700 °C and 750 °C, in controlled atmosphere furnaces using the ‘deposit recoat’ test method to simulate superheater/reheater exposure for 1000 h. After exposure, the samples were analysed using dimensional metrology to determine the extent and distributions of corrosion damage in terms of surface recession and internal damage. At 650 °C, the stainless steel and nickel-based alloy performed similarly, while at 700 °C and above, the median damage to the steel was at least 3 times greater than for the nickel-based alloy. Optical and electronic microscopy studies were used to study samples’ damage morphologies after exposure. Intergranular damage and pits were found in sample cross sections, while chromium depletion was found in areas with internal damage. For high-temperature applications, the higher cost of the nickel-based alloy could be offset by the longer life they would allow in plant with higher operating temperatures.European Union funding RFCS-2015/70995

Fireside performance of different coatings in biomass power plant

The energy sector will need to employ novel strategies to reduce greenhouse gas emissions, such as the increase of steam temperatures/pressures or the use of low carbon fuels (i.e. biomass). Both cause heat exchanger materials’ degradation issues, due to the formation of more/different corrosive deposits, which requires the use of expensive nickel-based materials or coatings. This paper focuses on the behaviour of three different coatings (HVOF NiCrFeSi, laser clad FeCrAl and Laser Clad NiCrFeSi) deposited on TP347HFG, at 700°C (up to 1000 h exposure). Tests were performed using the ‘deposit recoat’ method (KCl deposit) in simulated biomass combustion environments. Cross-sections were analysed using dimensional metrology, to determine distributions of metal loss and internal damage. Intergranular damage and pits were identified using SEM/EDX. A ‘diffusion cell’ behaviour was observed, which led to depletion of alloying elements from the coating and consequent increase in damage. The results suggested a severe degradation of all coatings.European Union funding: RFCS-2015/70995

High temperature corrosion of HVOF coatings in laboratory-simulated biomass combustion superheater environments

This study examines the fireside corrosion of FeCrAl, NiCr, NiCrAlY and A625 coatings applied by ‘high velocity oxy fuel’(HVOF) and exposed to simulated biomass firing conditions (gas composition CO2, N2, SO2 and HCl). The coatings and a typical base steel alloy (T92) were exposed to simulated conditions at 600 °C for 1000 h in a laboratory scale furnace. Samples were coated with a potassium chloride deposit. Samples were then cold mounted in a low-shrinkage epoxy resin and then cross-sectioned. Corrosion was assessed by dimensional metrology comparing the coating thickness change of the samples. The cross-sections of the ‘worst’ and ‘best’ coatings were examined. Results show that all but one coating (HVOF NiCr) outperformed the T92 alloy. No coating composition or method was conclusively better. Evidence of Cr depletion as well as the formation of a sulphidation layer have been found in the exposed samples with coatings. The formation of a K2SO4 layer has also been observed on all coated specimens.Innovate UK: 10116

The Sustainability of the Gig Economy Food Delivery System (Deliveroo, UberEATS and Just-Eat):Histories and Futures of Rebound, Lock-in and Path Dependency

Online food delivery has transformed the last-mile of food and grocery delivery, with unnoticed yet often significant impacts upon the transport and logistics network. This new model of food delivery is not just increasing congestion in urban centers though, it is also changing the contours and qualities of those doing delivery – namely through gig economy work. This new system of food consumption and provision is rapidly gaining traction, but assessments around its current and future sustainability tend to hold separate the notions of social, environmental and economic sustainability – with few to date working to understand how these can interact, influence and be in conflict with one another. This paper seeks to work with this broader understanding of sustainability, whilst also foregrounding the perspectives of gig economy couriers who are often marginalized in such assessments of the online food delivery system. We make use of systems thinking and Campbell’s (1996) conflict model of sustainability to do this. In assessing the online food delivery in this way, we seek to not only provide a counternarrative to some of these previous assessments, but to also challenge those proposing the use of gig economy couriers as an environmentally sustainable logistics intervention in other areas of last-mile logistics to consider how this might impact the broader sustainability of their system, now and in the future

Investigating the scope for integrating uncrewed aerial vehicles (UAVs) into mixed-mode fleets to support national health service (NHS) logistics operations

Local healthcare logistics systems carry a variety of cargoes to ensure patient care is maintained, though they account for a significant proportion of the total healthcare emissions footprint. Legislation and self-defined targets are driving the UK's National Health Service (NHS) to make their carbon impact net-zero; thus, this research investigated the scope for a multi-modal logistics network with vans, bikes, and uncrewed aerial vehicles/UAVs to support this goal. The unique contributions of this study include new approaches to solving the heterogeneous two-echelon vehicle routing problems associated with the collection of diagnostic specimens from community clinics. After initial investigations using a column generation heuristic, an adaptation of the Clarke and Wright Savings Algorithm with a bin packing algorithm was developed to evaluate the scope for integrating multi-mode fleets. The implications of good distribution practices and dangerous goods regulations were also explored, and new procedures were proposed. Meanwhile, an analysis of weather reliability criteria found that a 14 m/s peak gust tolerance would be essential for UAVs to match business-as-usual performance levels. Accounting for practicalities around payloads and delivery site constraints, case study data from the Solent region (UK) were applied to the algorithm. In a baseline case, 76 doctor's surgeries were served by 4 vans, costing £190k and generating 7.7 T CO2-eq. per year. It was found that introducing a mixed-mode system with 1 van and 10 UAVs could enable transit time reductions of up to 84% (209 mins to 33 mins), however, the resulting increase in operating costs (+133%, +£253k per year) and emissions (+211%, +19.5 T CO2-eq. per year) may prove difficult to justify. Furthermore, the absolute time savings may be inconsequential to patient care and the wider supply chain. In another case study involving 22 surgeries, van and bike combinations gave the lowest emission outcomes, with CO2-eq. reductions of up to 7% for a 3% increase in costs

Understanding the challenges of drone medical logistics services in developed nations

Uncrewed Aerial Vehicles (UAVs, or drones) have attracted considerable interest as a potential alternative logistics mode, with many studies suggesting that drones will offer faster and more reliable goods transport, whilst reducing associated energy, emissions, and costs compared to traditional modes. This may be true in some select settings and industries, but there are many barriers to achieving widespread implementation, particularly in developed nations.The number of trials of drone delivery has increased in recent years, with the majority being proof-of-concept experiments, never achieving sustained commercial operation. Furthermore, several major players in the logistics industry, e.g., Amazon and DHL, have more recently scaled back their development of such technologies, suggesting there are greater challenges that make the integration of UAVs into existing logistics operations less viable. Arguably the most successful drone delivery system in the world is primarily based in Rwanda, where Zipline routinely deliver blood stocks from central hubs, reaching hospitals significantly faster and more reliably than by road. To the authors’ knowledge, Zipline remains the only commercial national drone logistics operation currently active in the world, posing the question as to why take-up has not been more rapid.There is a general trend towards using drones in the medical sector, where there is potential for expedited delivery of time-sensitive, high-value cargoes to have significant impacts on patient care. Evidence identifies a range of trials carrying goods, such as diagnostic specimens, vaccines, and blood stocks, where delivery times are critical to ensure goods are outside of controlled conditions for as little time as possible or to improve the health outcomes of patients. Whilst this may give some perceived benefits, current legislation with regards to good carriage has not been designed for or applied to autonomous, uncrewed aircraft. In the case of UAVs, their vibration profiles can be significantly different to that of traditional land-based modes, with higher frequencies potentially damaging some of the more sensitive medical products (e.g., haemolysis of blood, etc.). As a result, UAV operators will need to evidence that their platforms do not adversely affect the products carried.To a certain extent, packaging may assist in this endeavour; however, regulations and industry standards may also limit the scope to adapt designs and hence limit the opportunities for UAVs. Dangerous goods regulations prescribe specific design criteria to reduce the likelihood of spillage and damage, and medical regulators require that temperature ranges are not exceeded during transit. This has led to rigorously tested standardised packaging being widely adopted in developed nations, leaving little margin for change which impacts on the minimum carrying requirements for UAVs. Furthermore, until UAVs are more widely adopted, these standards are unlikely to change, meaning that in the short term, drone platforms need to be selected such that the weights and volumes of existing payloads can be carried.Additional safety precautions in developed nations limit the use of package drop systems, meaning vertical take-off and landing (VTOL) functionality will be required to realise the benefits of point-to-point delivery. Meanwhile, a fixed-wing element will enable a greater travel range, particularly if electrically powered. Thus, for anything meaningful to be carried, it is likely that the UAVs used will be fairly large, and VTOL-fixed-wing hybrid setups. In the authors’ experience of testing such technology, a 5-metre wingspan drone with 0.75-metre propellors meets these requirements. Despite meeting the payload requirements, the selected drone does introduce some further limitations with regards to the availability of practical landing sites which don’t detract from their existing function (e.g., removal of public greenspace). The addition of overflight risk also restricts the scope for straight-line flights in order to reduce safety concerns in the event of a crash.Amongst further challenges, it may appear that drone services in developed nations are extremely limited in scope; however, there are still some use cases that will benefit from such a service. Factors that limit the potential of surface transportation, such as road quality, detour index/circuity factor (i.e., how indirect routes are), and the payload due to be carried, can all contribute to how great the benefits of a drone service can be. Through a comparison of successful delivery services, this research also explores what it takes to better existing logistics methods

A drone service to support the Isle of Wight NHS in the UK

With interest in drone delivery growing throughout the world, this study explores the challenges associated with developing a medical drone logistics service to support the National Health Service on the Isle of Wight in the UK. Two separate trials were undertaken to investigate the potential for drone delivery in this area, carrying medical goods and aseptic cancer medicines. The first trial took place using a fixed-wing drone during COVID-19 lockdown restrictions, whilst the second used hybrid fixed-wing vertical take-off and landing (VTOL) drone. Key findings suggested that electric VTOL drones present significant advantages in terms of point-to-point direct servicing, emissions, and time-savings, though range and payload limitations introduce further challenges. Legislation, airspace management, and technology findings were also made, with legacy regulations causing barriers to carriage of medical goods by drone. Future work seeks to understand the costs and benefits of a more sustained service in a medical setting

Quantifying weather tolerance criteria for delivery drones - a UK case study

As demand for final mile delivery has increased, the use of delivery drones is being explored in many countries, including the UK. Despite offering perceived benefits over existing methods in terms of delivery speed and reliability, there is little understanding of the design criteria needed for drones to actually realise them. This paper investigates how reliability and resilience of deliveries vary by transport mode, relating to the delivery success (i.e., can a delivery be made in a given timewindow), and the flexibility of this success (i.e., how many different time windows are possible).Comparing the performance of current UK ground transport modes and drones using historic weather and reliability data, a review of the factors that contribute to what makes a reliable and weather resistant drone service is presented. Results suggested that a significant wind tolerance would be required to achieve a level of service equal to ground transportation, with VTOL platforms requiring tolerances ranging from 14 m/s (Solent region), to more than 23 m/s (Scottish Hebrides). Fixed-wing platform tolerances were not as high, with a tolerance of 10 m/s achieving flights on almost all days in all case study areas.It is likely that some locations cannot reliably be served by drone and must depend on contingency options when flights are not possible. With significant variations in tolerance requirements, and notable seasonal variances, applications of delivery drones should be considered on a case-by-case basis, comparing to existing modes, to ensure reliable supply chains are realised.</p

Are drones safer than vans?: A Comparison of Routing Risk in Logistics

Drones are being considered as an alternative transport mode to ground based van networks. Whilst the speed and application of such networks has been extensively studied, the safety aspects of such modes have not been directly compared. Using UK Department for Transport data and a drone flight planning approach using a probabilistic risk model, an estimation of fatality rates for seven origin-destination (O-D) pairs was undertaken in a theoretical case study of medical deliveries in the Southampton area of the UK. Using failure rates from the literature, results indicated that commercial vehicles (&lt;3.5 T) were safer than drones in all cases by ≤12.73 (12.73 times more fatalities by drone than by road). With the O-D pairs covering a range of localities, routes covering more mileage on minor roads were found to be the least safe but were still ≥1.87 times safer than drone deliveries. Sensitivity tests on the modelled drone failure rates suggested that the probability of a failure would have to be ≤5.35×10−4 per flight-hour for drone risk to be equal to van risk. Investigating the circuity of drone routes (how direct a route is) identified that level of risk had a significant impact on travel distances, with the safest paths being 273% longer than the riskier, straight-line flight equivalent. The findings suggest that the level of acceptable risk when designing drone routes may negatively impact on the timeliness of drone deliveries due to the increased travel distance and time that could be incurred

Improving the efficiency of patient diagnostic specimen collection with the aid of a multi-modal routing algorithm

The Sustainable Specimen Collection Problem (SSCP), in which diagnostic specimens are collected from GP surgeries (doctor’s office/clinics) and subsequently transported to a hospital laboratory for analysis using more sustainable transport modes, is introduced in this paper. Using a weightedobjective function, we solve a new multi-objective problem using cycle consolidation to limit driving time and the numbers of vans used whilst improving overall service quality, reducing costs and emissions. This particular heterogeneous vehicle routing problem is explored and applied to tworeal-world case studies in the UK, where 97 and 22 sites (respectively) are currently served, using a column generation based heuristic algorithm with some additional improvement heuristics. The results demonstrated a potential improvement in the system’s maximum delivery time between 41% and 74% compared to business-as-usual activity using solely road vehicles. Road vehicle (van) fleets could be reduced by up to 40%, and the total driving time across the fleet by between 41% and 65%. Operational costs were estimated to increase by up to 38%, though additional workloads for gig-economy cycle couriers and improvement in specimen quality and service reliability may make this trade-off worthwhile. Tailpipe CO2 emissions were also reduced by up to 43%. The proposed algorithm was effective, reducing computational time by up to 99% whilst achieving an average of 5% deviation from optimality