2,131 research outputs found
Matrices for well-conditioned biorthogonal spline wavelet bases on the interval
No full textRefinement matrices for the wavelet bases described in Chapter 2 of the thesis "Adaptive tensor product wavelet methods for solving PDEs" (T.J. Dijkema, 2009).
Each directory of this data set contains the following matrices (in Matrix Market format):
m-j: two-scale matrix on level j (thesis p.12)
mass-j: mass matrix on level j
r-j, tr-j, trinit-j: transformation matrix R_j, \tilde{R}_j, \tilde{R}_j^{init} (thesis p.24-25)
The directory names are {d}-{td}-{ml}-{mr}-{tml}-{tmr} where:
d: Jackson estimate on primal side
td: Jackson estimate on dual side
ml / mr: number of vanishing moments on left/right boundary, primal side
tml / tmr: number of vanishing moments on left/right boundary, dual sid
Process system innovation by design: Towards a sustainable petrochemical industry
No full textTechnology, Policy and Managemen
Diffusion of combined heat and power in Dutch greenhouses: A case study
No full textThis report presents the case study of the rapid diffusion of combined heat and power (CHP) units in the Dutch greenhouse horticulture in the period 2003-2009. The aim of the case study is to find explanations for this particular transition, and to generalize on the nature of technology diffusion processes. The study is carried out by means of a literature study, and by means of interviews with sector stakeholders, including several greenhouse growers. In the theoretical framework, technology diffusion is conceptualized as a socio-technical transition, in which the interactions between different actors and the co-evolution of different societal domains form the key characteristics. We adopt a System-Network-Agent approach, as well as the theory of Universal Darwinism, in order to identify and examine the different developments and mechanisms that played a role in the CHP transition. The case study generates three types of insights: observed phenomena, key drivers, and evolutionary mechanisms. These insights contribute to the understanding of the emergence and evolution of technology diffusion in industrial sectors, which may help the formulation of national innovation policy. The five identified key drivers for the CHP diffusion are the opening of the energy market in 2002, the high spark spread during the transition period, the compatibility of output of a CHP unit with greenhouse demand, the flexibility provided by the heat buffer, and the cooperative and competitive greenhouse sector culture. We also found that the CHP diffusion has not been specifically aimed for by the Dutch government, but rather evolved out of interplay between developments in different societal domains. A general conclusion on technology diffusion is that, given the existing variety in social-technical systems and the developments emerging in these systems, each technology diffusion case will necessitate a different degree and nature of government involvement in order for the diffusion to become a success. Therefore, innovation policy makers should consider the co-evolutionary mechanisms inherent in technology diffusion processes.Engineering Systems and ServicesTechnology, Policy and Managemen
Past and future plant diversity of a coastal wetland driven by soil subsidence and climate change
No full textOn the island of Ameland (The Netherlands), natural gas has been extracted from a dune and salt marsh natural area since 1986. This has caused a soil subsidence of c. 1–25 cm, which can be used as a model to infer effects of future sea level rise. The aims of our study were (a) to relate the changes in the vegetation, and more specifically, in plant diversity, during the extraction period to soil subsidence and weather fluctuations, and (b) to use these relations to predict future changes due to the combination of ongoing soil subsidence and climate change. We characterised climate change as increases in mean sea level, storm frequency and net precipitation. Simultaneous observations were made of vegetation composition, elevation, soil chemistry, net precipitation, groundwater level, and flooding frequency over the period 1986–2001. By using multiple regression the changes in the vegetation could be decomposed into (1) an oscillatory component due to fluctuations in net precipitation, (2) an oscillatory component due to incidental flooding, (3) a monotonous component due to soil subsidence, and (4) a monotonous component not related to any measured variable but probably due to eutrophication. The changes were generally small during the observation period, but the regression model predicts large changes by the year 2100 that are almost exclusively due to sea level rise. However, although sea level rise is expected to cause a loss of species, this does not necessarily lead to a loss of conservancy valu
Exergy analysis for the comparison of processes: Case-study methanol
No full textLately much attention is paid to exergy analyses, but what are the prospects of these analyses? The primary incentive of this study was to find out whether exergy analyses should be used for the comparison and evaluation of processes. Hereto, a method based on the principle of exergy, has been developed. This method has been used to analyse and compare two methanol processes: the common ICI low pressure methanol process and the more recently developed Leading Concept Methanol (LCM) process, also by ICI. The intermediate production of synthesis gas in the first process takes place by steam reforming of methane, while the LCM process also employs partial oxidation with pure oxygen. The method developed determines the internal exergy losses (consumptions due to a process that takes place) and the external losses (exergy contained in heat or mass. Streams emitted to the environment). The internal exergy losses have been determined without taking into account the exergy values of a mass stream and thus without considering a reference environment. The external exergy losses have been determined by approximating the exergy values of mass streams. The use of a reference environment has been avoided because there is no universal reference environment and to avoid the complicated calculations necessary for the determination of the exergy values of mass streams. Another aspect of the method is that the whole process starting from raw materials available on earth has been analysed, which means that for the LCM process also an oxygen plant was considered. From the analyses and comparison, the LCM process has indeed been improved where exergy analysis indicated that most of the exergy is lost in the ICI low pressure methanol process, namely the reformer. According to the results of the energy analyses the purification section instead of the reformer should be improved. The exergy loss decreased from 9.76 to 6.65 MJ per kg of methanol for the LCM process. Also a decrease in the amount of energy wasted could be noticed from 9.75 to 8.00 MJ per kg methanol for the LCM process. Comparison of these processes with an 'ideal' methanol process demonstrated that about 60 respectively 40 per cent of the calculated exergy losses could be avoided for the ICI low pressure methanol process and the LCM process. It also appeared that synthesis gas could better be produced by a combination of steam reforming and partial oxidation than just by steam reforming. Exergy analysis results in other places where improvements could best be made than energy analysis and can, in contrast with energy analysis, be used for the evaluation of the reactions taking place in a process by determining internal exergy losses. Therefore it is recommended to apply exergy analysis for the comparison and evaluation of processes.Applied SciencesChemical Technology and Materials ScienceApplied Thermodynamics and Phase Equilibri
On the Potential to Manage a Transition to Sustainability in the Westland
No full textThe Westland-Oostland Greenport is a large Dutch industrial cluster that is economically, socially and culturally important. Like many industries and regions, the greenport is facing serious challenges as a result of globalisation, energy supplies, and greenhouse gas emissions. These challenges can be understood as sustainability issues that come from an imbalance between the economic and social values that the greenport presently enjoys and the environmental values that it lacks. Greenports are complex adaptive systems, which means that the different challenges and values are all interconnected in complex and dynamic ways. This also means that improving the greenport is a matter of helping it evolve from its current state of imbalance toward a new state of sustainable balance that will help the greenport endure long into the future. The problems of unsustainability are growing increasingly urgent, which means the greenport can hardly afford to wait for a spontaneous change toward sustainability. Unfortunately, complex adaptive systems and state changes within those systems cannot be managed top-down. Thus, the Westland-Oostland Greenport wants to know `How can we manage a transition to sustainability?' In response, the greenport is interested in Transition Management (TM), an approach to scientific research and policy formation that proposes to steer complex adaptive systems toward sustainability through a blend of bottom-up and top-down measures. TM certainly looks promising, but it is not yet clear ``what is the scope or feasibility of managing transitions''. On behalf of the Westland-Oostland Greenport, this work uses TM to explore how a transition to sustainability might be managed within in the Westland-Oostland Greenport. At the same time, this work also reflects on TM itself by questioning whether sustainable transitions can be managed at all. The Research Questions There are two main research questions, each with two sub-questions. The first main research question is ``Can TM help the Westland-Oostland Greenport manage a transition to sustainability?'' which can be broken down into the following sub-questions: What new understanding and insight can be gained from applying TM to the Westland-Oostland Greenport? What influence, policy recommendations and practical advice can be derived from the new understanding and insights gained by applying TM approach to the Westland-Oostland Greenport? The second main research question is ``How can TM be improved as a consequence of being applied in the Westland-Oostland Greenport?'' which has the following sub-questions: What potentially problematic assumptions can be seen within the TM approach as it was applied to the Westland-Oostland Greenport? What insights, further questions, or improvements for TM come from exploring these problematic assumptions? The Research Methods The research begins with a literature review to explore the most important ideas of complex adaptive systems, sustainability and TM. The first main research question is then addressed by applying several research methods to the Westland-Oostland Greenport, all of which are consistent with TM. These research methods include a case study, a participatory workshop, and an agent-based model. Next, the second main research question is addressed through a series of relatively abstract agent-based models and modelling experiments. Each model is designed to test an assumption within TM about how complex adaptive systems work or about how transitions can be managed. Results Part I covers the application of various research methods to the Westland-Oostland Greenport. Each of these produces a set of new insights into the greenport and its sustainability problems. On the whole, the insights tend to relate to specifics, such as the identification of specific drivers behind a diffusion of interest, specific gaps in local sustainability policies, and specific stakeholder features that influence relevant behaviour. Many of these insights are turned into practical recommendations that policy-makers could use to help manage a transition to sustainability within the greenport. For example, recognising the specific drivers behind a particularly rapid and important technology diffusion can help policy-makers drive desirable diffusions in the future. Similarly, identifying gaps in current sustainability policies allows policy-makers to develop more effective programmes without duplicating existing programmes. Not all of the insights are easily converted to direct policy recommendations; some are better understood as advice on the process and typical problems associated with policy formation. For example, recognising that innovators are quick to embrace change is usually seen as a good thing when policy-makers want to encourage a desirable change, but quickly becomes problematic after a desired change has been effected and further change is seen as less desirable changes. Some specific insights could not have been predicted, but none were inconsistent with general TM expectations. For example, energy market liberalisation proved to be one of the most important drivers of the combined heat and power technology diffusion, even though the technology diffusion was not an intended or expected consequence of long term national energy market policies. TM expects transitions and diffusions to occur when `windows of opportunity' are opened. Thus, even though this particular diffusion was not an intended result of its most important driver, neither was it an especially surprising outcome. In this way, the policy recommendations based on the insights uncovered in Part I are all consistent with the theory of TM and with past TM policy recommendations. Part II covers the agent-based models that investigate various potentially problematic assumptions within TM. Each of these models produces new insights, some of which can be related to the Westland-Oostland Greenport but most of which relate to TM itself. None of the assumptions held up particularly well to investigation. As a result, and unlike the relatively cut-and-dried insights in Part I, the insights in Part II are best understood as calls for more critical analysis of TM, creative reinterpretation of past observations, and innovative approaches to understanding complex adaptive systems and sustainability. For example, the first of four agent-based models tested the commonly relied upon TM assumption that a large and diverse committee can produce a more objective system description that can a single individual. The results of that model suggested that all system definitions are mutually exclusive of all others, regardless of how they were produced, suggesting that no system description is obviously more objective than any other. Another agent-based model examined the pervasive TM assumption that innovation and selection are opposing forces but found no evidence to support the proposed innovation-selection relationship nor the many TM programmes that rely on the assumed relationship. Importantly, these insight do not claim to offer a definitive answer or superior explanation to replace the TM assumptions examined by the models. For example, the conclusion that diverse committees do not produce more objective system definitions but does not entail any proposal for an alternative process or structure that produces more objective system definitions. Likewise, refuting the assumed relationship between innovation and selection is not the same as proving that innovation and selection have some other relationship instead, although an alternative view of innovation and selection is offered as a possibility for further investigation. As a consequence of the different research questions and approaches used, the policy recommendations and insights from Part II are less practical and specific than those from Part I. For example, policy-makers are not advised to avoid large and diverse committees when creating system descriptions, but are urged to focus on the actual benefits of wider public engagement rather than unsubstantiated assumptions about objectivity. Also unlike Part I, some of the insight and recommendations of Part II are aimed at users or proponents of TM rather than directly at policy-makers. For example, many TM practices rely on using (more) objective system descriptions. By undermining the assumed objectivity of system descriptions, the experimental results call the validity of all of these practices into question. When the results of all four of the various agent based modelling experiments are taken together, serious inconsistencies become visible within TM, some of its assumptions begin to appear very flawed, and the whole field looks as if it would benefit from some deep and critical self-reflection. Conclusions Overall, the works finds that applying TM research methods to a complex adaptive system generates new insights about the specific details of that systems, much of which can be used to create practical recommendations or justify policies in relation to sustainability efforts. The new insights and details revealed by the research may be surprising in their uniqueness or specificity, showing that TM research can be extremely valuable. Despite their potentially surprising uniqueness or specificity, TM research methods are unlikely to produce any results, insights or policy guidance that are truly unexpected or that are inconsistent with established TM theory or existing policy proposals. At the same time, it is important to note that TM has not yet managed a transition to sustainability. Perhaps TM merely needs more time to achieve the desired outcome, but it is also possible that more and more of the same TM efforts will only produce more and more of the same lack of success. The work also finds that TM, as it currently stands, contains some incoherent ideas and relies on some unsupported assumptions. These inconsistencies and assumptions may be hindering TM efforts to achieve sustainability, so TM is encouraged to critically reflect on its ideas about complex adaptive systems, transitions and sustainability as well as its own processes, research methods and sustainability efforts. In so doing, TM may correct some problems, discover new and better ways to work, and become a more effective tool for managing systems and moving them toward sustainability. This critical self-analysis may also reveal that TM is fundamentally flawed and should be discarded, but that too could inspiring researchers to devise entirely new approaches that are more successful in achieving sustainability.Infrastructure Systems & ServicesTechnology, Policy and Managemen
Co-Evolutionary Method For Modelling Large Scale Socio-Technical Systems Evolution
No full textExactly predicting the future of an evolving large scale socio-technical system is impossible. Yet, if we are to sustainably manage the industrial and infrastructure systems our society depends on, we must understand how the actions we take today will affect the evolution of these systems. Simulating how the social and technical networks co-evolve over time allows us to explore possible system futures. This knowledge can help today’s decision makers to steer the system away from undesirable evolutionary pathways. Creating models that capture the complexity of socio-technical systems co-evolution requires multiple formalisms to be encoded in a modeling framework that itself evolves. This thesis presents a method for creating Agent Based Models that suitably represent complex evolving systems. The method involves a co-evolution between the technical aspects of model development, the social process involving the stakeholders, the collection of relevant domain knowledge and the encoding of facts. Through seven case studies the method is demonstrated to yield subsequent generations of richer and ever more useful simulation models.Section Energy and IndustryTechnology, Policy and Managemen
Fostering Climate Resilient Electricity Infrastructures
No full textHeat waves, hurricanes, floods and windstorms - recent years have seen dramatic failures in electricity infrastructures sparked by short-term departures of environmental conditions from their norms. Driven by a changing climate, such deviations are anticipated to increase in severity and/or frequency over the coming decades. This will have important implications for the systems that supply and transport our electricity. In light of this, resilience is an essential characteristic of future infrastructure systems. The notion of resilience implicitly accepts the possibility of unforeseen disruptions and failures and focuses on the capacity of systems to handle them - to survive unexpected perturbation, recover from adversity and gracefully degrade - as well as an ability to adapt and learn over time. How can we foster a climate resilient electricity infrastructure in the Netherlands? To address this question, this thesis synthesizes insights from multiple computer models using multiple modeling techniques. These models stress the nature of the electricity infrastructure as a complex and evolving system, interconnected within itself and with other infrastructures. Beyond these insights, the thesis contributes a framework, an approach and a set of tools for supporting the development of climate resilient electricity infrastructures in the Netherlands and elsewhere.ESSTechnology, Policy and Managemen
Understanding socio-technical change: A system-network-agent approach
No full textTransitions are processes of change that have always occurred in society: for example, the production of goods changed from handcraft to machine-made. In recent years, these transitions attract more and more attention, mainly because societies now wish to actively bring about certain changes, such as the reduction of the use of fossil fuels – the so-called energy transition. This raises several questions, such as: how do ‘transitions’ evolve and to what extent can the course of such a process be influenced? This PhD thesis tries to improve the understanding of those transitions that have both a social and a technological aspect. This thesis presents a method of analysis with which these processes of socio-technical change can be captured in their full breadth and be modelled, which can serve as a basis for the simulation of a transition. Central to this approach is that we analyse the dynamics of the entire system, of the individual actors and of the actor networks at the same time as well as the interactions between these levels. This is the ‘System-Network-Agent approach’ that is proposed in this thesis. This method of analysis was applied in two in-depth case studies: about the transition in Brazil towards the use of bio-ethanol as car fuel, and the transition in the Netherlands towards a supply-chain approach for the treatment of household waste. Several lessons can be learned from these case studies. First, government can affect a transition, but not effect it. Government can try to start a transition process, but it depends on many other circumstances and actors – which cannot be controlled by government – whether the desired change is actually achieved. Moreover, both case studies show that a hierarchical government with a clear policy focus is more effective in bringing about changes than a government that keeps all options open and seeks to reach social consensus first. For example, the most significant change concerning the treatment of household waste in the last century in the Netherlands occurred during the German occupation in World War II. Drastic events, such as a crisis or very high oil prices, play an important role in transitions. They can be an incentive for the development of alternatives to the current practice or help to align the preferences of different actors. As such, drastic events can provide a window of opportunity in a transition, but they could also hinder such a process. From the case studies we conclude that the system, network and agent levels are all needed in a transition. A ‘top-down transition’ needs bottom-up acceptance, whereas a ‘bottom-up transition’ will not succeed if it is blocked from the top. The proposed ‘System-Network-Agent approach’ has proven to be a powerful tool to capture exactly those interdependencies, as this thesis shows.Infrastructure Systems & ServicesTechnology, Policy and Managemen
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