• Maxmaladaptation, occupant behaviour and energy performance gap

      Levermore, Geoffrey; orcid: 0000-0001-5723-8309; email: geoff.levermore@manchester.ac.uk (SAGE Publications, 2021-03-15)
      Occupant behaviour is a key factor in the energy consumption and performance of a building. However, it is difficult to model and simulate hence there is often a mismatch between the predicted and actual performance of a new or refurbished buildings and surprising variations in the consumptions of similar and identical buildings. Although environmental conditions affect people significantly, there are also non-environmental factors including how well employers manage people and how well dwelling occupants understand their controls. Rarely are these factors considered in building performance, especially commercial buildings. Poor management can lead to varying degrees of occupant maladaptation. Maladaptation taken here to mean behaviour patterns that are detrimental to the optimal functioning of the building. This paper proposes a novel concept for designers that examines the worst possible energy performance gap (“extreme” scenario testing) where the theoretical occupants do their best to make the building consume as much energy as possible. The novel concept is called “maxmaladaptation”. By considering maxmaladaptation, designers can attempt to reduce it, so reducing the energy gap. This paper briefly reviews the energy gap and social psychology and its contribution to understanding energy consumption with some examples, underlying the concept of maxmaladaptation. Practical application: Building energy performance gaps often exist because predicted design consumptions are often less than actual consumptions due to the occupants not behaving as designers expect. Using the concept of maxmaladaptation, an extreme scenario of maximum energy use by occupants, designers can design buildings to avoid unexpected energy consumption. Often the influences of occupant behaviour are not considered in detail. Social psychology gives an insight into non-environmental factors that can cause maladaptation, a constituent of maxmaladaptation.
    • Simulating Ionising Radiation in Gazebo for Robotic Nuclear Inspection Challenges

      Wright, Thomas; orcid: 0000-0002-9913-5487; email: thomas.wright@manchester.ac.uk; West, Andrew; orcid: 0000-0003-4553-8640; email: andrew.west@manchester.ac.uk; Licata, Mauro; email: m.licata@lancaster.ac.uk; Hawes, Nick; orcid: 0000-0002-7556-6098; email: nickh@robots.ox.ac.uk; Lennox, Barry; orcid: 0000-0003-0905-8324; email: barry.lennox@manchester.ac.uk (MDPI, 2021-07-07)
      The utilisation of robots in hazardous nuclear environments has potential to reduce risk to humans. However, historical use has been largely limited to specific missions rather than broader industry-wide adoption. Testing and verification of robotics in realistic scenarios is key to gaining stakeholder confidence but hindered by limited access to facilities that contain radioactive materials. Simulations offer an alternative to testing with actual radioactive sources, provided they can readily describe the behaviour of robotic systems and ionising radiation within the same environment. This work presents a quick and easy way to generate simulated but realistic deployment scenarios and environments which include ionising radiation, developed to work within the popular robot operating system compatible Gazebo physics simulator. Generated environments can be evolved over time, randomly or user-defined, to simulate the effects of degradation, corrosion or to alter features of certain objects. Interaction of gamma radiation sources within the environment, as well as the response of simulated detectors attached to mobile robots, is verified against the MCNP6 Monte Carlo radiation transport code. The benefits these tools provide are highlighted by inclusion of three real-world nuclear sector environments, providing the robotics community with opportunities to assess the capabilities of robotic systems and autonomous functionalities.