O Povo Disciplinar de Geografia e a Tradução na Política de Currículo

Esta dissertação se constitui em uma investigação sobre as políticas de currículo para o Ensino de Geografia no nível médio. Proponho, especificamente, através do significante flutuante interdisciplinaridade, compreender os processos de precipitação da subjetivação da Geografia na tradução da política de integração curricular. Me aproprio de aportes pós-estruturais, marcadamente aproximados à teoria do discurso de Ernesto Laclau, com vistas a pensar a política de currículo como se dando através de lutas discursivas, marcadas pelo antagonismo e pela exclusão. Para pensar estes movimentos, inicialmente busco situar a perspectiva de currículo como texto, como textualização, com foco na interpretação de Lopes e Macedo de que o currículo é produzido na articulação de discursos. Busco, com esta leitura curricular, compreender os sentidos produzidos para/pela Geografia no nível médio, no âmbito de uma construção também discursiva como a do currículo integrado. Em razão da instabilidade inserida à reflexão sobre as políticas de currículo, elementos como a disciplina e as subjetivações constituídas na relação com ela passaram a configurar o cenário de análise que procurei construir. Nesse sentido, problematizo a leitura de comunidade disciplinar de Goodson ao focalizar a perspectiva laclauniana de povo como cadeia de equivalência. Com isso, procuro reconceptualizar a leitura de subjetividade política tendo em vista as demandas que a fazem ser. Este exercício se desdobrou em uma proposta de pensar a construção de um sujeito político disciplinar por meio da decisão frente ao outro, ao que é interpretado como negação de si. Aqui, penso o discurso de integração curricular como um outro possível, que pode ser interpretado como oposição ao currículo por disciplinas e, portanto, como ameaça à Geografia. O movimento estratégico com vistas à compreensão desta tradução se deu por intermédio da abordagem à textualização desta política, através do entrelaçamento do corpus teórico aos textos dos Parâmetros, Orientações Curriculares para o Ensino Médio e de entrevistas realizadas com lideranças, pesquisadores e consultores, envolvidos na produção da política. Estes elementos empíricos são lidos como momentos da política, como distintos contextos de resposta(s), que buscam suplementar a falta do sujeito, do que quer ser. Tendo a interdisciplinaridade como um dos meios pelos quais se significa a integração curricular na área de ciências humanas, onde está a Geografia, discuto o modo como esse significante é traduzido pelo povo disciplinar da Geografia. Uma tradução, resposta, à ameaça de um outro, desconhecido, que é interpretado como algo que expõe a subjetividade, o povo da Geografia, ao risco. Em função dos temores colocados, atento para uma performance de tentativa de blindagem ante ao outro. Tal manifestação é entendida como a tradução da interdisciplinaridade como característica da Geografia, como sua própria feição, como a si mesma. Concluo chamando a atenção para o que interpreto como uma luta pela estabilização do antagonismo, entre a integração e o disciplinar (a Geografia), e focalizo a tradução de sentidos do outro como possibilidade de existir e, nessa leitura, afirmar uma propriedade que se constitui provisoriamente como aquilo que é suposto como questionado pelo outro, algo de que se depende para continuar

The roles of energy and material efficiency in meeting steel industry CO2 targets.

Identifying strategies for reducing greenhouse gas emissions from steel production requires a comprehensive model of the sector but previous work has either failed to consider the whole supply chain or considered only a subset of possible abatement options. In this work, a global mass flow analysis is combined with process emissions intensities to allow forecasts of future steel sector emissions under all abatement options. Scenario analysis shows that global capacity for primary steel production is already near to a peak and that if sectoral emissions are to be reduced by 50% by 2050, the last required blast furnace will be built by 2020. Emissions reduction targets cannot be met by energy and emissions efficiency alone, but deploying material efficiency provides sufficient extra abatement potential.

森林流域单元水文模型的构建与应用

目前全球缺水、水污染、洪涝灾害以及水土流失仍然非常严重，尤其在我国北方地区。流域水文模型可用来进行不同需水管理的情景分析，为解决我国水问题提供科学依据。分布式水文模型是流域水文模型的发展方向，具有显著特点：1）应用前景广泛，不仅可以模拟流域水文过程，还可以协助模拟泥沙或污染物的运移过程，为水利工程设计、水土保持、环境保护等领域提供技术支持；2）能够预测流域土地利用或气候变化下的流域水文响应过程变化，为管理部门提供决策支持；3）模型所需要的参数全部具有物理意义，可通过实际测量确定，适合模拟实测系列较短或是无观测流域的水文过程；4）对于目前国际水文界的前沿问题—水文尺度转换提供了一种有效的解决途径。 然而分布式水文模型还不完善，如1)真实性问题。对一些水文过程和边界条件还不确定。2)尺度转换问题。目前很少考虑尺度对参数有效性的影响。3)检验问题。还无法判断对有些难以测量的水文状态变量的模拟正确与否。4)计算时间和数据存储的问题。有些分布式水文模型虽然具有很强的水文物理基础和完善的模型结构，但是计算时间过长和(或)数据存储过大，难以应用。上述问题的核心就是对分布式水文模型的核心—单元水文模型的研究不够，需要为进一步完善单元水文模型进行研究。 本文采用饱和入渗理论、Saint-Venant方程、Richards方程、Penman-Monteith方程等等构建了以有限差分法求解的适用于森林流域的单元水文模型，并通过实验室模拟试验和坡地径流场资料进行了验证，主要结论为： 通过不同坡度和不同雨强下的室内坡面产汇流实验模拟，表明：该模型模拟的坡面流和壤中流过程与实测过程基本一致，峰现时间、径流历时、峰值流量、出流总量模拟值与实测值的相对误差均较小，基本小于10%。模型的模拟精度较高，实用性较强，为深入研究壤中流机制和改进流域降雨-径流模型提供了理论依据。 通过坡地径流观测场实测资料的验证，表明：该模型模拟的坡面流过程精度较高，累计流量的精度更高于小时过程的精度，离差系数、效率系数、确定系数均较理想，具有应用价值，有助于改善分布式水文模型在森林流域的模拟效果。

逆向物流流量不确定闭环供应链鲁棒运作策略设计

考虑一类同时具有再分销、再制造和再利用的闭环供应链在逆向物流流量不确定环境下的运作问题.采用具有已知概率的离散情景描述逆向物流流量的不确定性,利用基于情景分析的鲁棒线性优化方法建立该闭环供应链的多目标运作模型.设计了一个数值算例,其结果验证了运作策略的鲁棒性.在该算例基础上,分析了逆向物流流量的大小对闭环供应链系统运作性能的影响.

Climate and energy scenarios for Ireland to 2050 using the Irish TIMES energy systems model

Due to growing concerns regarding the anthropogenic interference with the climate system, countries across the world are being challenged to develop effective strategies to mitigate climate change by reducing or preventing greenhouse gas (GHG) emissions. The European Union (EU) is committed to contribute to this challenge by setting a number of climate and energy targets for the years 2020, 2030 and 2050 and then agreeing effort sharing amongst Member States. This thesis focus on one Member State, Ireland, which faces specific challenges and is not on track to meet the targets agreed to date. Before this work commenced, there were no projections of energy demand or supply for Ireland beyond 2020. This thesis uses techno-economic energy modelling instruments to address this knowledge gap. It builds and compares robust, comprehensive policy scenarios, providing a means of assessing the implications of different future energy and emissions pathways for the Irish economy, Ireland’s energy mix and the environment. A central focus of this thesis is to explore the dynamics of the energy system moving towards a low carbon economy. This thesis develops an energy systems model (the Irish TIMES model) to assess the implications of a range of energy and climate policy targets and target years. The thesis also compares the results generated from the least cost scenarios with official projections and target pathways and provides useful metrics and indications to identify key drivers and to support both policy makers and stakeholder in identifying cost optimal strategies. The thesis also extends the functionality of energy system modelling by developing and applying new methodologies to provide additional insights with a focus on particular issues that emerge from the scenario analysis carried out. Firstly, the thesis develops a methodology for soft-linking an energy systems model (Irish TIMES) with a power systems model (PLEXOS) to improve the interpretation of the electricity sector results in the energy system model. The soft-linking enables higher temporal resolution and improved characterisation of power plants and power system operation Secondly, the thesis develops a methodology for the integration of agriculture and energy systems modelling to enable coherent economy wide climate mitigation scenario analysis. This provides a very useful starting point for considering the trade-offs between the energy system and agriculture in the context of a low carbon economy and for enabling analysis of land-use competition. Three specific time scale perspectives are examined in this thesis (2020, 2030, 2050), aligning with key policy target time horizons. The results indicate that Ireland’s short term mandatory emissions reduction target will not be achieved without a significant reassessment of renewable energy policy and that the current dominant policy focus on wind-generated electricity is misplaced. In the medium to long term, the results suggest that energy efficiency is the first cost effective measure to deliver emissions reduction; biomass and biofuels are likely to be the most significant fuel source for Ireland in the context of a low carbon future prompting the need for a detailed assessment of possible implications for sustainability and competition with the agri-food sectors; significant changes are required in infrastructure to deliver deep emissions reductions (to enable the electrification of heat and transport, to accommodate carbon capture and storage facilities (CCS) and for biofuels); competition between energy and agriculture for land-use will become a key issue. The purpose of this thesis is to increase the evidence-based underpinning energy and climate policy decisions in Ireland. The methodology is replicable in other Member States.

Robust food supply supply chains:An integrated framework for vulnerability assessment and disturbance management

The operation of supply chains (SCs) has for many years been focused on efficiency, leanness and responsiveness. This has resulted in reduced slack in operations, compressed cycle times, increased productivity and minimised inventory levels along the SC. Combined with tight tolerance settings for the realisation of logistics and production processes, this has led to SC performances that are frequently not robust. SCs are becoming increasingly vulnerable to disturbances, which can decrease the competitive power of the entire chain in the market. Moreover, in the case of food SCs non-robust performances may ultimately result in empty shelves in grocery stores and supermarkets.
The overall objective of this research is to contribute to Supply Chain Management (SCM) theory by developing a structured approach to assess SC vulnerability, so that robust performances of food SCs can be assured. We also aim to help companies in the food industry to evaluate their current state of vulnerability, and to improve their performance robustness through a better understanding of vulnerability issues. The following research questions (RQs) stem from these objectives:
RQ1: What are the main research challenges related to (food) SC robustness?
RQ2: What are the main elements that have to be considered in the design of robust SCs and what are the relationships between these elements?
RQ3: What is the relationship between the contextual factors of food SCs and the use of disturbance management principles?
RQ4: How to systematically assess the impact of disturbances in (food) SC processes on the robustness of (food) SC performances?
To answer these RQs we used different methodologies, both qualitative and quantitative. For each question, we conducted a literature survey to identify gaps in existing research and define the state of the art of knowledge on the related topics. For the second and third RQ, we conducted both exploration and testing on selected case studies. Finally, to obtain more detailed answers to the fourth question, we used simulation modelling and scenario analysis for vulnerability assessment.
Main findings are summarised as follows.
Based on an extensive literature review, we answered RQ1. The main research challenges were related to the need to define SC robustness more precisely, to identify and classify disturbances and their causes in the context of the specific characteristics of SCs and to make a systematic overview of (re)design strategies that may improve SC robustness. Also, we found that it is useful to be able to discriminate between varying degrees of SC vulnerability and to find a measure that quantifies the extent to which a company or SC shows robust performances when exposed to disturbances.
To address RQ2, we define SC robustness as the degree to which a SC shows an acceptable performance in (each of) its Key Performance Indicators (KPIs) during and after an unexpected event that caused a disturbance in one or more logistics processes. Based on the SCM literature we identified the main elements needed to achieve robust performances and structured them together to form a conceptual framework for the design of robust SCs. We then explained the logic of the framework and elaborate on each of its main elements: the SC scenario, SC disturbances, SC performance, sources of food SC vulnerability, and redesign principles and strategies.
Based on three case studies, we answered RQ3. Our major findings show that the contextual factors have a consistent relationship to Disturbance Management Principles (DMPs). The product and SC environment characteristics are contextual factors that are hard to change and these characteristics initiate the use of specific DMPs as well as constrain the use of potential response actions. The process and the SC network characteristics are contextual factors that are easier to change, and they are affected by the use of the DMPs. We also found a notable relationship between the type of DMP likely to be used and the particular combination of contextual factors present in the observed SC.
To address RQ4, we presented a new method for vulnerability assessments, the VULA method. The VULA method helps to identify how much a company is underperforming on a specific Key Performance Indicator (KPI) in the case of a disturbance, how often this would happen and how long it would last. It ultimately informs the decision maker about whether process redesign is needed and what kind of redesign strategies should be used in order to increase the SC’s robustness. The VULA method is demonstrated in the context of a meat SC using discrete-event simulation. The case findings show that performance robustness can be assessed for any KPI using the VULA method.
To sum-up the project, all findings were incorporated within an integrated framework for designing robust SCs. The integrated framework consists of the following steps: 1) Description of the SC scenario and identification of its specific contextual factors; 2) Identification of disturbances that may affect KPIs; 3) Definition of the relevant KPIs and identification of the main disturbances through assessment of the SC performance robustness (i.e. application of the VULA method); 4) Identification of the sources of vulnerability that may (strongly) affect the robustness of performances and eventually increase the vulnerability of the SC; 5) Identification of appropriate preventive or disturbance impact reductive redesign strategies; 6) Alteration of SC scenario elements as required by the selected redesign strategies and repeat VULA method for KPIs, as defined in Step 3.
Contributions of this research are listed as follows. First, we have identified emerging research areas - SC robustness, and its counterpart, vulnerability. Second, we have developed a definition of SC robustness, operationalized it, and identified and structured the relevant elements for the design of robust SCs in the form of a research framework. With this research framework, we contribute to a better understanding of the concepts of vulnerability and robustness and related issues in food SCs. Third, we identified the relationship between contextual factors of food SCs and specific DMPs used to maintain robust SC performances: characteristics of the product and the SC environment influence the selection and use of DMPs; processes and SC networks are influenced by DMPs. Fourth, we developed specific metrics for vulnerability assessments, which serve as a basis of a VULA method. The VULA method investigates different measures of the variability of both the duration of impacts from disturbances and the fluctuations in their magnitude.
With this project, we also hope to have delivered practical insights into food SC vulnerability. First, the integrated framework for the design of robust SCs can be used to guide food companies in successful disturbance management. Second, empirical findings from case studies lead to the identification of changeable characteristics of SCs that can serve as a basis for assessing where to focus efforts to manage disturbances. Third, the VULA method can help top management to get more reliable information about the “health” of the company.
The two most important research opportunities are: First, there is a need to extend and validate our findings related to the research framework and contextual factors through further case studies related to other types of (food) products and other types of SCs. Second, there is a need to further develop and test the VULA method, e.g.: to use other indicators and statistical measures for disturbance detection and SC improvement; to define the most appropriate KPI to represent the robustness of a complete SC. We hope this thesis invites other researchers to pick up these challenges and help us further improve the robustness of (food) SCs.

Learning business strategies for competitive electronic marketplaces

This paper presents a Multi-Agent Market simulator designed for developing new agent market strategies based on a complete understanding of buyer and seller behaviors, preference models and pricing algorithms, considering user risk preferences and game theory for scenario analysis. This tool studies negotiations based on different market mechanisms and, time and behavior dependent strategies. The results of the negotiations between agents are analyzed by data mining algorithms in order to extract rules that give agents feedback to improve their strategies. The system also includes agents that are capable of improving their performance with their own experience, by adapting to the market conditions, and capable of considering other agent reactions.

Agent-based simulation of electronic marketplaces with decision support

This paper presents a Multi-Agent Market simulator designed for analyzing agent market strategies based on a complete understanding of buyer and seller behaviors, preference models and pricing algorithms, considering user risk preferences and game theory for scenario analysis. The system includes agents that are capable of improving their performance with their own experience, by adapting to the market conditions, and capable of considering other agents reactions.

Virtual power producers market strategies

This paper presents MASCEM - a multi-agent based electricity market simulator. MASCEM uses game theory, machine learning techniques, scenario analysis and optimisation techniques to model market agents and to provide them with decision-support. This paper mainly focus on the MASCEM ability to provide the means to model and simulate Virtual Power Producers (VPP). VPPs are represented as a coalition of agents, with specific characteristics and goals. The paper detail some of the most important aspects considered in VPP formation and in the aggregation of new producers and includes a case study.

MASCEM - an electricity market simulator providing coalition support for virtual power players

This paper presents MASCEM - a multi-agent based electricity market simulator. MASCEM uses game theory, machine learning techniques, scenario analysis and optimization techniques to model market agents and to provide them with decision-support. This paper mainly focus on the MASCEM ability to provide the means to model and simulate Virtual Power Players (VPP). VPPs are represented as a coalition of agents, with specific characteristics and goals. The paper details some of the most important aspects considered in VPP formation and in the aggregation of new producers and includes a case study based on real data.

Reabilitação de um imóvel industrial em Marvila: projeto de investimento

Trabalho de Projeto para obtenção do grau de Mestre em Engenharia Civil

Energia Solar Fotovoltaica como Fonte Alternativa de Produção de Energia Elétrica em Angola

Neste trabalho é efetuado o dimensionamento de sistemas fotovoltaicos para serem instalados em edificações localizadas em Angola com o objetivo de analisar a produção de energia elétrica através de sistemas fotovoltaicos. Utilizando o software PVsyst na versão 6.3.2 foram dimensionados três sistemas fotovoltaicos, dois sistemas destinados a ser instalados numa residência, um ligado à rede e o outro autónomo e por fim um sistema fotovoltaico ligado à rede para uma instalação industrial. A determinação dos custos de investimento nos três sistemas foi obtida de forma aproximada, tendo como base preços dos equipamentos no mercado Português e considerando os custos de importação de mercadorias no mercado Angolano. Para os sistemas ligados à rede é analisada a rentabilidade financeira do investimento durante o período de vida útil dos módulos fotovoltaicos considerando três cenários distintos. No primeiro cenário o valor da remuneração pela energia vendida pelo produtor é igual ao valor pago pela energia comprada. No segundo e terceiros cenário de análise económica pretende-se encontrar uma tarifa de energia que torne o investimento rentável com um período de amortização de 7 e 12 anos respetivamente.

Decision‐Making in Public Good Dilemmas: Theory and Agent‐Based Simulation

In many real world contexts individuals find themselves in situations where they have to decide between options of behaviour that serve a collective purpose or behaviours which satisfy one’s private interests, ignoring the collective. In some cases the underlying social dilemma (Dawes, 1980) is solved and we observe collective action (Olson, 1965). In others social mobilisation is unsuccessful. The central topic of social dilemma research is the identification and understanding of mechanisms which yield to the observed cooperation and therefore resolve the social dilemma. It is the purpose of this thesis to contribute this research field for the case of public good dilemmas. To do so, existing work that is relevant to this problem domain is reviewed and a set of mandatory requirements is derived which guide theory and method development of the thesis. In particular, the thesis focusses on dynamic processes of social mobilisation which can foster or inhibit collective action. The basic understanding is that success or failure of the required process of social mobilisation is determined by heterogeneous individual preferences of the members of a providing group, the social structure in which the acting individuals are contained, and the embedding of the individuals in economic, political, biophysical, or other external contexts. To account for these aspects and for the involved dynamics the methodical approach of the thesis is computer simulation, in particular agent-based modelling and simulation of social systems. Particularly conductive are agent models which ground the simulation of human behaviour in suitable psychological theories of action. The thesis develops the action theory HAPPenInGS (Heterogeneous Agents Providing Public Goods) and demonstrates its embedding into different agent-based simulations. The thesis substantiates the particular added value of the methodical approach: Starting out from a theory of individual behaviour, in simulations the emergence of collective patterns of behaviour becomes observable. In addition, the underlying collective dynamics may be scrutinised and assessed by scenario analysis. The results of such experiments reveal insights on processes of social mobilisation which go beyond classical empirical approaches and yield policy recommendations on promising intervention measures in particular.

The first five years of the EU Impact Assessment system: a risk economics perspective on gaps between rationale and practice

In 2003 the European Commission started using Impact Assessment (IA) as the main empirical basis for its major policy proposals. The aim was to systematically assess ex ante the economic, social and environmental impacts of EU policy proposals. In parallel, research proliferated in search for theoretical grounds for IAs and in an attempt to evaluate empirically the performance of the first sets of IAs produced by the European Commission. This paper combines conceptual and evaluative studies carried out in the first five years of EU IAs. It concludes that the great discrepancy between rationale and practice calls for a different theoretical focus and a higher emphasis on evaluating empirically crucial risk economics aspects of IAs, such as the value of statistical life, price of carbon, the integration of macroeconomic modelling and scenario analysis.

Using proxies to calculate the carbon impact of investment into electricity network assets

Replacement and upgrading of assets in the electricity network requires financial investment for the distribution and transmission utilities. The replacement and upgrading of network assets also represents an emissions impact due to the carbon embodied in the materials used to manufacture network assets. This paper uses investment and asset data for the GB system for 2015-2023 to assess the suitability of using a proxy with peak demand data and network investment data to calculate the carbon impacts of network investments. The proxies are calculated on a regional basis and applied to calculate the embodied carbon associated with current network assets by DNO region. The proxies are also applied to peak demand data across the 2015-2023 period to estimate the expected levels of embodied carbon that will be associated with network investment during this period. The suitability of these proxies in different contexts are then discussed, along with initial scenario analysis to calculate the impact of avoiding or deferring network investments through distributed generation projects. The proxies were found to be effective in estimating the total embodied carbon of electricity system investment in order to compare investment strategies in different regions of the GB network.