Increasing Endurance of an Autonomous Robot using an Immune-Inspired Framework

This paper describes the implementation of an online immune-inspired framework to help increase endurance of an autonomous robot. Endurance is defined as the ability of the robot to exert itself for a long period of time. The immune-inspired framework provides such capability by monitoring the behavior of the robot to ensure continuous and safe behavior. The immune-inspired framework combines innate and adaptive immune inspired algorithms. Innate uses a dendritic cell based innate immune algorithm, and adaptive uses an instance based B-cell approach. Results presented in this paper shows that when the robot is implemented with the immune-inspired framework, health and survivability of a robot is improved, therefore increasing its endurance

The impact of synthetic biology in chemical engineering - Educational issues

This paper describes the development of syntheticbiology as a distinct entity from current industrial biotechnology and the implications for a future based on its concepts. The role of the engineering design cycle, in syntheticbiology is established and the difficulties in making and exact analogy between the two emphasised. It is suggested that process engineers can offer experience in the application of syntheticbiology to the manufacture of products which should influence the approach of the synthetic biologist. The style of teaching for syntheticbiology appears to offer a new approach at undergraduate level and the challenges to the education of process engineers in this technology are raised. Possible routes to the development of syntheticbiology teaching are suggested

A SPEA2 Based Planning Framework for Optimal Integration of Distributed Generations

The paper presents a multi-objective optimisation method for analysing the best mix of renewable and non- renewable distributed generations (DG) in a distribution network. The method aims at minimising the total cost of the real power generation, line losses and CO2 emissions, and maximising the benefits from DG installations over a planning horizon of 20 years. The paper proposes new objective functions that take into account the longevity of DG operations as one of its selection criteria. The analysis utilises the Strength Pareto Evolutionary Algorithm 2 (SPEA2) for optimisation and MATPOWER for solving the optimal power flow problems

A Multi-Objective Planning Framework for Optimal Integration of Distributed Generations

This paper presents an evolutionary algorithm for analyzing the best mix of distributed generations (DG) in a distribution network. The multi-objective optimization aims at minimizing the total cost of real power generation, line losses and CO2 emissions, and maximizing the benefits from the DG over a 20 years planning horizon. The method assesses the fault current constraint imposed on the distribution network by the existing and new DG in order not to violate the short circuit capacity of existing switchgear. The analysis utilizes one of the highly regarded evolutionary algorithm, the Strength Pareto Evolutionary Algorithm 2 (SPEA2) for multi-objective optimization and MATPOWER for solving the optimal power flow problems

A conceptual approach to determine optimal indoor air quality: A mixture experiment method

Achieving good air quality in large residential and commercial buildings continues to be a top priority for owners, designers, building managers and occupants. The challenge is even greater today. There are many new materials, furnishing, products and processes used in these buildings that are potential source of contaminations and pollutants. A common problem to the indoor and outdoor environments is that of exposure to mixtures of air pollutants. Researchers and practitioners tend to focus on single pollutants (e.g. CO2, PM2.5) ignoring the mixtures combined effect. Fashion dictates to study the pollutant most thoroughly talked about. Distinguishing the effects of such co-pollutants is difficult. The conclusions about which component of a mixture is actually producing a given effect are sometimes less soundly based than could be wished. It is especially important in considering the indoor mixture of air pollutants as this mixture may be entirely different from those found outside. Exposures to raised levels of air pollutants can damage health, for example carbon monoxide can cause death and significant lasting disability. Controlling levels of indoor air pollutants is therefore important, as good indoor air quality is essential to health. There are three strategies for achieving acceptable indoor air quality: ventilation, source control and cleaning/filtration. Depending on the building and the specific characteristics of the location, these strategies can be used singly or in combination. However, mixture experiment would throw more light and understanding into indoor air composition and interaction properties and the combine effects it has on human health. Mixture experiments have been used extensively in other industries, for example the pharmaceutical industry and the agrochemical industry, for the production of tablets and the control of plant diseases and pests. Developing a mixture model for the internal microclimate for a particular building type and/or location may help us in developing better indicators, standards and policy document in the near future, when the levels of pollutants concentration can be successfully predicted

Adaptive and Online Health Monitoring System for Autonomous Aircraft

Good situation awareness is one of the key attributes required to maintain safe flight, especially for an Unmanned Aerial System (UAS). Good situation awareness can be achieved by incorporating an Adaptive Health Monitoring System (AHMS) to the aircraft. The AHMS monitors the flight outcome or flight behaviours of the aircraft based on its external environmental conditions and the behaviour of its internal systems. The AHMS does this by associating a health value to the aircraft's behaviour based on the progression of its sensory values produced by the aircraft's modules, components and/or subsystems. The AHMS indicates erroneous flight behaviour when a deviation to this health information is produced. This will be useful for a UAS because the pilot is taken out of the control loop and is unaware of how the environment and/or faults are affecting the behaviour of the aircraft. The autonomous pilot can use this health information to help produce safer and securer flight behaviour or fault tolerance to the aircraft. This allows the aircraft to fly safely in whatever the environmental conditions. This health information can also be used to help increase the endurance of the aircraft. This paper describes how the AHMS performs its capabilities

A Two-Stage Approach to Defining an Affected Community based on the Directly Affected Population and Sense of Community

Studies have demonstrated the inadequacy of relying on existing administrative boundaries or simple proximity to define an affected community. The proposal and siting of hazardous facilities can have a range of impacts upon people across wide areas, with some more affected than others as a result of living with the physical impacts of construction or the fear associated with perceived risk. We term those most affected the Directly Affected Population and propose a two-stage model for identifying an affected community which places those most affected at the centre of the definition. The second stage is to identify the relationships those most affected have with the wider elements of the Sense of Community to discover the existing community or communities which are affected. Illustrated by the siting of a low level radioactive waste disposal facility at Dounrey in the north of Scotland, we show that elements of the lived community experience may have very different shapes, extents and conflicting interests which pose challenges for their incorporation into a siting process. The two-stage model presented in this paper, by placing those most directly affected at the centre and working from there out into the existing communities, identifies issues early in any siting process to improve their incorporation and amelioration

Explanation-based learning with analogy for impasse resolution

This paper proposes an algorithm for the inclusion of analogy into Explanation-Based Learning (EBL). Analogy can be used when an impasse is reached to extend the deductive closure of EBL’s domain theory. This enables the generation of control laws, via EBL, for hardware which is not catered for in the domain theory. This advantage addresses a problem which represents a dearth in the current literature. Integrated Modular Avionics (IMA) literature has thus far been concerned with the architectural considerations. This paper seeks to address the impact of hardware changes on the controllers within an IMA architecture. An algorithm is proposed and applied to control an aviation platform with an incomplete domain theory. Control rules are generated when no deductive explanations are possible, which still reflect the intent of the domain theory

Energy from waste and the food processing industry

The provision of a secure, continuous energy supply is becoming an issue for all sectors of society and the foodprocessingindustry as a major energy user must address these issues. This paper identifies anaerobic digestion as an opportunity to go some way to achieving energy security in a sustainable manner. However, a number of energy management and waste reduction concepts must also be brought into play if the environmental, social and economic aspects of sustainability are to be balanced. The reporting of such activity will help to promote the green credentials of the industry. Cleaner production, supply chain and life cycle assessment approaches all have a part to play as tools supporting a new vision for integrated energy and waste management. Our reliance on high-energyprocessing, such as canning and freezing/chill storage, might also need re-assessment together with processing based on hurdle technology. Finally, the concepts of energy and power management for a distributed energy generation system must be brought into the foodprocessingindustry

Sustainability of the chemical manufacturing industry - Towards a new paradigm?

This paper describes the current situation of the chemicalmanufacturingindustry, with special reference to Europe and looks to the future sustainability demands on the sector, and the implications of these demands for chemical engineering education. These implications include definitions of sustainability criteria for the sector and the need for transparent reporting under the Triple Bottom Line approach. The response of the education system to the sustainability agenda over the years and a number of strategies to incorporate it into courses are described. The important role of chemical (or more generally, process) engineers in delivering sustainable solutions is emphasised but this also suggests that anew way of thinking about the discipline is required. Indeed, this paper argues that the demand for a sustainable chemicalmanufacturing sector could bring about the next paradigm shift in the discipline which has been predicted for some time