Search

This study investigates the optimal design of carbon capture, transport and storage (CCTS) supply chains for decarbonizing industrial emitters. It builds upon previous analyses, which determine the cost-optimal design of CCTS supply chains while complying with specified emissions reduction scenarios, and determines optimal designs in terms of minimum cost and maximum resilience. The resilience of a supply chain is defined as its ability to permanently store the captured CO2 during the time horizon of interest, and it is quantified in terms of expected amount of carbon not stored under a fixed number of possible simultaneous failures. A mixed-integer linear program is developed to design CCTS supply chains that ensure a specified level of resilience while minimizing total system costs and CO2 emissions. The model is illustrated by determining the optimal decarbonization strategy in terms of costs and level of resilience for the Swiss waste-to-energy sector from 2025 to 2050. Overall, resilience is achieved with a cost increase with respect to the cost-optimal solution ranging from about 5% (backup truck connections to minimize the cost of the supply chain) to about 70% (backup pipeline connections to minimize the emissions of the supply chain) when the storage site is in the North Sea. When the storage site is available in Switzerland, the cost increase is much reduced and ranges from about 1% to 10% with respect to the cost-optimal solution., International Journal of Greenhouse Gas Control, 121, ISSN:1750-5836, ISSN:1878-0148

This work presents a novel optimization framework for the optimal design of carbon capture, transport, and storage supply chains in terms of installation, sizing and operation of carbon dioxide (CO2) capture and transport technologies. The optimal design problem is formulated as a mixed-integer linear program that minimizes the total costs of the supply chains while complying with different emissions reduction pathways over a deployment time horizon of 25 years. All design decisions are time-dependent and are taken with a yearly resolution. Whereas the model is general, here its features are illustrated by designing optimal supply chains to decarbonize the Swiss waste-to-energy sector, for various emission reduction pathways, when up to two storage sites are considered, namely one in the North Sea assumed to be already available and a hypothetical one in Switzerland assumed to be possibly available in the future. Findings show that, unless a domestic storage site becomes available soon, the transport cost is the greatest contribution to the overall costs, followed by the capture cost, while the storage cost plays only a minor role. Pipelines are the most cost-effective mode of transport for large volumes of transported CO2, especially when considering multi-year time horizons for the planning of the supply chains. Ship and barge connections are competitive with pipeline connections, whereas rail and truck connections are cost-optimal only when considering shortsighted time horizons or small volumes of CO2 transported., International Journal of Greenhouse Gas Control, 117, ISSN:1750-5836, ISSN:1878-0148

This paper presents a robotics workshop that aims to encourage high-school students to enrol at university STEAM-related degrees. It is included in a socio-educational program in which we have been involved for several years. The workshop attendees become familiar with the concept of robotics through a set of visual cards that we recently introduced, called STEAMOLUS cards. These cards introduce real-world problems to be solved while learning the basics of robotics. The results suggest theses cards contribute to develop students’ creativity and inspiration.

This study investigates the optimal design of CO2 value chains aimed at decarbonizing the waste to energy (WtE) sector on a national scale and presents the case study of Switzerland. Switzerland has 30 WtE plants that generate a total of 4.2 million tons of CO2 emissions per year. Half of these emissions are from biogenic sources and half are fossil-based, corresponding to 4.5% of the overall Swiss emissions. On the one hand, this indicates the relevance of decarbonizing the WtE sector. On the other hand, it implies that a net-negative-emissions WtE sector can be achieved by adopting carbon capture and storage (CCS) technologies. The CO2 value chains considered here consist in capturing CO2 at the WtE production sites, transporting it to the storage site, and permanently storing it underground. An optimization problem is formulated to determine the optimal design of the CO2 value chains in terms of size and location of carbon capture technologies, and structure of the network transporting the CO2 from the capture to the storage sites. The optimization algorithm is a mixed integer linear program that minimizes the total annual cost and CO2 emissions of the overall system. Several transport options are assessed, namely truck, train, pipeline and ship, as well as different transport paths.

Adaptive organisation-centred multi-agent systems can dynamically modify their organisational components to better accomplish their goals. Our research line proposes an abstract distributed architecture (2-LAMA) to endow an organisation with adaptation capabilities. This article focuses on regulation-adaptation based on a machine learning approach, in which adaptation is learned by applying a tailored case-based reasoning method. We evaluate the robustness of the system when it is populated by non compliant agents. The evaluation is performed in a peer-to-peer sharing network scenario. Results show that our proposal significantly improves system performance and can cope with regulation violators without incorporating any specific regulation-compliance enforcement mechanisms.

A connection between two vessels or other tubular structures is known as anastomosis, one of the most common procedures in its field but, at the same time, one of the most complex suture-based techniques. This procedure requires not only a lot of skill and dexterity but also a lot of attention and plenty of concentration from the surgeon. This makes many of the actions to be performed irregularly, exposing the patient to human error resulting from the monotony. On the other hand, the field of robotics has earned itself a place in medicine, especially as assistants during a surgical intervention. Even so, medical robotics is quite young and still has not done much in the field of vessel anastomosis. Therefore, this paper presents a preliminary study of the most common suturing techniques, taking into account their typology and performance, within all the possible anastomosis procedures known. Subsequently, a detailed study of workflow and actions during an anastomosis is made, obtaining a diagram for each of the suturing techniques studied. This allows analyzing all procedures and to create a tool to find those actions and repeated tasks and/or common in all of them, indicating which of these are potential candidates for an automation study. This preliminary work focuses on finding where robotics can help to avoid rutinary tasks, which can be learned in a mechanical level and therefore, relatively easy to be automated using a robotic system or to assist the surgeon in certain tasks that need a lot of skill and attention.

Organisations in multi-agent systems (MAS) have proven to be successful in regulating agent societies. Nevertheless, changes in agents' behaviour or in the dynamics of the environment may lead to a poor fulfilment of the system's purposes, and so the entire organisation needs to be adapted. In this paper we focus on endowing the organisation with adaptation capabilities, instead of expecting agents to be capable of adapting the organisation by themselves. We regard this organisational adaptation as an assisting service provided by what we call the Assistance Layer. Our generic Two Level Assisted MAS Architecture (2-LAMA) incorporates such a layer. We empirically evaluate this approach by means of an agent-based simulator we have developed for the P2P sharing network domain. This simulator implements 2-LAMA architecture and supports the comparison between different adaptation methods, as well as, with the standard BitTorrent protocol. In particular, we present two alternatives to perform norm adaptation and one method to adapt agents' relationships. The results show improved performance and demonstrate that the cost of introducing an additional layer in charge of the system's adaptation is lower than its benefits. © 2010 Springer-Verlag.

Existing organisational centred multi-agent systems (MAS) regulate agents' activities. Nevertheless, population and/or environmental changes may lead to a poor fulfilment of the system's purposes, and therefore, adapting the whole organisation becomes key. This is even more needed in open MAS, where participants are unknown beforehand, they may change over time, and there are no guarantees about their behaviours nor capabilities. Hence, in this paper we focus on endowing an organisation with self-adaptation capabilities instead of expecting agents to increase their behaviour complexity. We regard this organisational adaptation as an assisting service provided by what we call the Assistance Layer. Our abstract Two Level Assisted MAS Architecture (2-LAMA) incorporates such a layer. We empirically evaluate our adaptation mechanism in a P2P scenario by comparing it with the standard BitTorrent protocol. Results provide a performance improvement and show that the cost of introducing an additional layer in charge of system's adaptation is lower than its benefits.

Existing organisational centred multi-agent systems regulate agents’ activities. However, population/environmental changes may lead to a poor fulfilment of system’s goals, and therefore, adapting the whole organisation becomes key. In this paper, we propose to use Case-Based Reasoning learning to adapt norms that regulate agents’ behaviour. Moreover, we empirically evaluate this approach in a P2P scenario., This work is partially funded by IEA (TIN2006-15662-C02-01), EVE (TIN2009-14702-C02-01 / TIN2009-14702-C02-02) and AT (CONSOLIDER CSD2007-0022) projects, EU-FEDER funds, the Catalan Gov. (Grant 2005-SGR-00093), and M. Esteva’s Ramon y Cajal contract.

From a system's perspective ---as opposed to an individual agent perspective---, MAS adaptation is now becoming an important topic, since it can help to obtain expected outcomes under changing circumstances. In this paper, we propose a MAS architecture (2-LAMA) to adapt social conventions in dynamic systems. The proposed architecture consist of two layers: the conventional MAS system (we call domain-level) and an additional layer or meta-level in charge of adaptation. A Peer-to-Peer scenario helps us to illustrate our approach. The resulting model changes participant organisation depending on environment and agent changes. Finally, we present some preliminary results of the empirical evaluation of our approach.

Organisational centred multi-agent systems (MAS) have proved to be effective to regulate agents' activities. Nevertheless, population and/or environmental changes may lead to a pour fulfilment of the system's purposes, and therefore, adapting the whole organisation becomes key. This paper presents a MAS simulator devoted to test organisations with self-adaptation capabilities in P2P scenarios. More specifically, our simulator implements different sharing P2P methods ---some of them with self-adaptation--- and so, it can be used as a testbed for comparing them.

Similarly to institutions in human societies, an Electronic Institution (EI) provides a structured framework for a Multi-Agent System (MAS) to regulate agents' interactions. However, current EIs cannot regulate a previously existing dynamic social system and deal with its agent population behaviour changes. This paper suggests a solution consisting of two EI extensions to incorporate situatedness and adaptation to the institution. These two properties are usually present at an agent level, but this paper studies how to bring them to an organisational level. While exposing our approach, we use a traffic scenario example to illustrate its concepts.

Usually, MAS design and implementation involves a coordination model that structures agent interactions and an infrastructure in charge of enacting it. We propose the term Coordination Support to denote the services offered by this infrastructure. Such services can be grouped in different layers. We propose an additional Assistance layer devoted to assist coordination rather than just to enable it. This layer is illustrated by means of a Peer-to-Peer sharing network (P2P) scenario, so that the benefits of our proposal can be empirically evaluated.