Development of welding techniques and filler metals for high strength aluminum alloys second quarterly report, 1 oct. - 31 dec. 1964

Welding techniques and filler metals for high strength aluminum alloys evaluated by bulge test progra

Development of welding techniques and filler metals for high strength aluminum alloys Annual summary report, 27 Jun. 1964 - 27 Jun. 1965

Welding techniques and filler metals for high strength aluminum alloy

A Commercial Aircraft Fuel Burn and Emissions Inventory for 2005–2011

The commercial aircraft fuel burn and emission estimates of CO2, CO, H2O, hydrocarbons, NOx and SOx for 2005–2011 are given as the 4-D Aircraft Fuel Burn and Emissions Inventory. On average, the annual fuel burn and emissions of CO2, H2O, NOx, and SOx increased by 2%–3% for 2005–2011, however, annual CO and HC emissions decreased by 1.6% and 8.7%, respectively because of improving combustion efficiency in recent aircraft. Approximately 90% of the global annual aircraft NOx emissions were emitted in the NH between 2005 and 2011. Air traffic within the three main industrialised regions of the NH (Asia, Europe, and North America) alone accounted for 80% of the global number of departures, resulting in 50% and 45% of the global aircraft CO2 and NOx emissions, respectively, during 2005–2011. The current Asian fleet appears to impact our climate strongly (in terms of CO2 and NOx) when compared with the European and North American fleet. The changes in the geographical distribution and a gradual shift of the global aircraft NOx emissions as well as a subtle but steady change in regional emissions trends are shown in particular comparatively rising growth rates between 0 and 30°N and decreasing levels between 30 and 60°N

Economically optimal farmer supervision of crop robots

One of the key issues in regulation of crop robots is the need for human supervision. Economic analysis indicates that autonomous farming potentially reduces agricultural production costs, but such costs may often become higher than conventional when constant on-site human supervision is required by law. However, there are cases where a higher level of crop robot supervision helps maximise profits even if it is not mandated by law, such as when field operations or crop robots inherently require frequent human intervention. The objective of this study is to identify economically optimal levels of farmer supervision of crop robots in the absence of regulation through the HFH-LP optimisation model developed at Harper Adams University, Newport (UK). Four scenarios characterised by different human intervention requirements are developed and compared with two baseline scenarios to identify thresholds at which farm management decisions would change from remote supervision of crop robots to on-site supervision. The findings of this analysis show that the economically optimal farmer supervision of crop robots falls within a range which is substantially lower than the 100% level mandated by jurisdictions such as the EU and California. More specifically, the economically optimal supervision of crop robots falls between 13% and 85% of machine field time across scenarios depending on: (i) the required number of human interventions in a given field operation; (ii) the supervisor's location; and (iii) the number of crop robots being used in that operation. The economic effects of these three factors reveal crucial implications for health and safety regulators and draw attention to crop robot reliability as a priority for researchers, entrepreneurs, and crop robot manufacturers

The impact of swarm robotics on arable farm size and structure in the UK

Swarm robotics has the potential to radically change the economies of size in agriculture and this will impact farm size and structure in the UK. This study uses a systematic review of the economics of agricultural robotics literature, data from the Hands Free Hectare (HFH) demonstration project which showed the technical feasibility of robotic grain production, and farm-level linear programming (LP) to estimate changes in the average cost curve for wheat and oilseed rape from swarm robotics. The study shows that robotic grain production is technically and economically feasible. A preliminary analysis suggests that robotic production allows medium size farms to approach minimum per unit production cost levels and that the UK costs of production can compete with imported grain. The ability to achieve minimum production costs at relatively small farm size means that the pressure to “get big or get out” will diminish. Costs of production that are internationally competitive will mean reduced need for government subsidies and greater independence for farmers. The ability of swarm robotics to achieve minimum production costs even on small, irregularly shaped fields will reduce pressure to tear out hedges, cut infield trees and enlarge fields

Economics of autonomous equipment for arable farms

By collecting more data at a higher resolution and by creating the capacity to implement detailed crop management, autonomous crop equipment has the potential to revolutionise precision agriculture (PA), but unless farmers find autonomous equipment profitable it is unlikely to be widely adopted. The objective of this study was to identify the potential economic implications of autonomous crop equipment for arable agriculture using a grain-oilseed farm in the United Kingdom as an example. The study is possible because the Hands Free Hectare (HFH) demonstration project at Harper Adams University has produced grain with autonomous equipment since 2017. That practical experience showed the technical feasibility of autonomous grain production and provides parameters for farm-level linear programming (LP) to estimate farm management opportunities when autonomous equipment is available. The study shows that arable crop production with autonomous equipment is technically and economically feasible, allowing medium size farms to approach minimum per unit production cost levels. The ability to achieve minimum production costs at relatively modest farm size means that the pressure to “get big or get out” will diminish. Costs of production that are internationally competitive will mean reduced need for government subsidies and greater independence for farmers. The ability of autonomous equipment to achieve minimum production costs even on small, irregularly shaped fields will improve environmental performance of crop agriculture by reducing pressure to remove hedges, fell infield trees and enlarge fields

Economics of field size and shape for autonomous crop machines

Field size and shape constrain spatial and temporal management of agriculture with implications for farm profitability, field biodiversity and environmental performance. Large, conventional equipment struggles to farm small, irregularly shaped fields efficiently. The study hypothesized that autonomous crop machines would make it possible to farm small, non-rectangular fields profitably, thereby preserving field biodiversity and other environmental benefits. Using the experience of the Hands Free Hectare (HFH) demonstration project, this study developed algorithms to estimate field times (h/ha) and field efficiency (%) subject to field size and shape in grain-oil-seed farms of the United Kingdom using four different equipment sets. Results show that field size and shape had a substantial impact on technical and economic performance of all equipment sets, but autonomous machines were able to farm small 1 ha rectangular and non-rectangular fields profitably. Small fields with equipment of all sizes and types required more time, but for HFH equipment sets field size and shape had least impact. Solutions of HFH linear programming model show that autonomous machines decreased wheat production cost by €15/ton to €29/ton and €24/ton to €46/ton for small rectangular and non-rectangular fields respectively, but larger 112 kW and 221 kW equipment with human operators was not profitable for small fields. Sensitivity testing shows that the farms using autonomous machines adapted easily and profitably to scenarios with increasing wage rates and reduced labour availability, whilst farms with conventional equipment struggled. Technical and economic feasibility in small fields imply that autonomous machines could facilitate biodiversity and improve environmental performance