Verfahren zur echtzeitfähigen Simulation dynamischer Emissionsverläufe ausgewählter Schadstoffe von Ottomotoren

Im Rahmen dieser Arbeit werden Modellbildungsverfahren zur echtzeitfähigen Simulation wichtiger Schadstoffkomponenten im Abgasstrom von Verbrennungsmotoren vorgestellt. Es wird ein ganzheitlicher Entwicklungsablauf dargestellt, dessen einzelne Schritte, beginnend bei der Ver-suchsplanung über die Erstellung einer geeigneten Modellstruktur bis hin zur Modellvalidierung, detailliert beschrieben werden. Diese Methoden werden zur Nachbildung der dynamischen Emissi-onsverläufe relevanter Schadstoffe des Ottomotors angewendet. Die abgeleiteten Emissionsmodelle dienen zusammen mit einer Gesamtmotorsimulation zur Optimierung von Betriebstrategien in Hybridfahrzeugen. Im ersten Abschnitt der Arbeit wird eine systematische Vorgehensweise zur Planung und Erstellung von komplexen, dynamischen und echtzeitfähigen Modellstrukturen aufgezeigt. Es beginnt mit einer physikalisch motivierten Strukturierung, die eine geeignete Unterteilung eines Prozessmodells in einzelne überschaubare Elemente vorsieht. Diese Teilmodelle werden dann, jeweils ausgehend von einem möglichst einfachen nominalen Modellkern, schrittweise erweitert und ermöglichen zum Abschluss eine robuste Nachbildung auch komplexen, dynamischen Verhaltens bei hinreichender Genauigkeit. Da einige Teilmodelle als neuronale Netze realisiert werden, wurde eigens ein Verfah-ren zur sogenannten diskreten evidenten Interpolation (DEI) entwickelt, das beim Training einge-setzt, und bei minimaler Messdatenanzahl ein plausibles, also evidentes Verhalten experimenteller Modelle sicherstellen kann. Zum Abgleich der einzelnen Teilmodelle wurden statistische Versuchs-pläne erstellt, die sowohl mit klassischen DoE-Methoden als auch mittels einer iterativen Versuchs-planung (iDoE ) generiert wurden. Im zweiten Teil der Arbeit werden, nach Ermittlung der wichtigsten Einflussparameter, die Model-strukturen zur Nachbildung dynamischer Emissionsverläufe ausgewählter Abgaskomponenten vor-gestellt, wie unverbrannte Kohlenwasserstoffe (HC), Stickstoffmonoxid (NO) sowie Kohlenmono-xid (CO). Die vorgestellten Simulationsmodelle bilden die Schadstoffkonzentrationen eines Ver-brennungsmotors im Kaltstart sowie in der anschließenden Warmlaufphase in Echtzeit nach. Im Vergleich zur obligatorischen Nachbildung des stationären Verhaltens wird hier auch das dynami-sche Verhalten des Verbrennungsmotors in transienten Betriebsphasen ausreichend korrekt darge-stellt. Eine konsequente Anwendung der im ersten Teil der Arbeit vorgestellten Methodik erlaubt, trotz einer Vielzahl von Prozesseinflussgrößen, auch hier eine hohe Simulationsqualität und Ro-bustheit. Die Modelle der Schadstoffemissionen, eingebettet in das dynamische Gesamtmodell eines Ver-brennungsmotors, werden zur Ableitung einer optimalen Betriebsstrategie im Hybridfahrzeug ein-gesetzt. Zur Lösung solcher Optimierungsaufgaben bieten sich modellbasierte Verfahren in beson-derer Weise an, wobei insbesondere unter Verwendung dynamischer als auch kaltstartfähiger Mo-delle und der damit verbundenen Realitätsnähe eine hohe Ausgabequalität erreicht werden kann.

Agricultural practices and horizontal nutrient balances in urban gardens and the alternative use of urban agricultural land in Khartoum, Sudan

The surge in the urban population evident in most developing countries is a worldwide phenomenon, and often the result of drought, conflicts, poverty and the lack of education opportunities. In parallel with the growth of the cities is the growing need for food which leads to the burgeoning expansion of urban and peri-urban agriculture (UPA). In this context, urban agriculture (UA) contributes significantly to supplying local markets with both vegetable and animal produce. As an income generating activity, UA also contributes to the livelihoods of poor urban dwellers. In order to evaluate the nutrient status of urban soils in relation to garden management, this study assessed nutrient fluxes (inputs and outputs) in gardens on urban Gerif soils on the banks of the River Nile in Khartoum, the capital city of Sudan. To achieve this objective, a preliminary baseline survey was carried out to describe the structure of the existing garden systems. In cooperation with the author of another PhD thesis (Ms. Ishtiag Abdalla), alternative uses of cow dung in brick making kilns in urban Khartoum were assessed; and the socio-economic criteria of the brick kiln owners or agents, economical and plant nutritional value of animal dung and the gaseous emission related to brick making activities were assessed. A total of 40 household heads were interviewed using a semi-structured questionnaire to collect information on demographic, socio-economic and migratory characteristics of the household members, the gardening systems used and the problems encountered in urban gardening. Based on the results of this survey, gardens were divided into three groups: mixed vegetable-fodder gardens, mixed vegetable-subsistence livestock gardens and pure vegetable gardens. The results revealed that UA is the exclusive domain of men, 80% of them non-native to Khartoum. The harvested produce in all gardens was market oriented and represented the main source of income for 83% of the gardeners. Fast growing leafy vegetables such as Jew’s mallow (Corchorous olitorius L.), purslane (Portulaca oleracea L.) and rocket (Eruca sativa Mill.) were the dominant cultivated species. Most of the gardens (95%) were continuously cultivated throughout the year without any fallow period, unless they were flooded. Gardeners were not generally aware of the importance of crop diversity, which may help them overcome the strongly fluctuating market prices for their produce and thereby strengthen the contributions of UA to the overall productivity of the city. To measure nutrient fluxes, four gardens were selected and their nutrients inputs and outputs flows were monitored. In each garden, all plots were monitored for quantification of nutrient inputs and outputs. To determine soil chemical fertility parameters in each of the studied gardens, soil samples were taken from three selected plots at the beginning of the study in October 2007 (gardens L1, L2 and H1) and in April 2008 (garden H2) and at the end of the study period in March 2010. Additional soil sampling occurred in May 2009 to assess changes in the soil nutrient status after the River Nile flood of 2008 had receded. Samples of rain and irrigation water (river and well-water) were analyzed for nitrogen (N), phosphorus (P), potassium (K) and carbon (C) content to determine their nutrient inputs. Catchment traps were installed to quantify the sediment yield from the River Nile flood. To quantify the nutrient inputs of sediments, samples were analyzed for N, P, K and organic carbon (Corg) content, cation exchange capacity (CEC) and the particle size distribution. The total nutrient inputs were calculated by multiplying the sediment nutrient content by total sediment deposits on individual gardens. Nutrient output in the form of harvested yield was quantified at harvest of each crop. Plant samples from each field were dried, and analyzed for their N, P, K and Corg content. Cumulative leaching losses of mineral N and P were estimated in a single plot in garden L1 from December 1st 2008 to July 1st 2009 using 12 ion exchange resins cartridges. Nutrients were extracted and analyzed for nitrate (NO3--N), ammonium (NH4+-N) and phosphate PO4-3-P. Changes in soil nutrient balance were assessed as inputs minus outputs. The results showed that across gardens, soil N and P concentrations increased from 2007 to 2009, while particle size distribution remained unchanged. Sediment loads and their respective contents of N, P and Corg decreased significantly (P < 0.05) from the gardens of the downstream lowlands (L1 and L2) to the gardens of the upstream highlands (H1 and H2). No significant difference was found in K deposits. None of the gardens received organic fertilizers and the only mineral fertilizer applied was urea (46-0-0). This equaled 29, 30, 54, and 67% of total N inputs to gardens L1, L2, H1, and H2, respectively. Sediment deposits of the River Nile floods contributed on average 67, 94, 6 and 42% to the total N, P, K and C inputs in lowland gardens and 33, 86, 4 and 37% of total N, P, K and C inputs in highland gardens. Irrigation water and rainfall contributed substantially to K inputs representing 96, 92, 94 and 96% of total K influxes in garden L1, L2, H1 and H2, respectively. Following the same order, total annual DM yields in the gardens were 26, 18, 16 and 1.8 t ha-1. Annual leaching losses were estimated to be 0.02 kg NH4+-N ha-1 (SE = 0.004), 0.03 kg NO3--N ha-1 (SE = 0.002) and 0.005 kg PO4-3-P ha-1 (SE = 0.0007). Differences between nutrient inputs and outputs indicated negative nutrient balances for P and K and positive balances of N and C for all gardens. The negative balances in P and K call for adoptions of new agricultural techniques such as regular manure additions or mulching which may enhance the soil organic matter status. A quantification of fluxes not measured in our study such as N2-fixation, dry deposition and gaseous emissions of C and N would be necessary to comprehensively assess the sustainability of these intensive gardening systems. The second part of the survey dealt with the brick making kilns. A total of 50 brick kiln owners/or agents were interviewed from July to August 2009, using a semi-structured questionnaire. The data collected included general information such as age, family size, education, land ownership, number of kilns managed and/or owned, number of months that kilns were in operation, quantity of inputs (cow dung and fuel wood) used, prices of inputs and products across the production season. Information related to the share value of the land on which the kilns were built and annual income for urban farmers and annual returns from dung for the animal raisers was also collected. Using descriptive statistics, budget calculation and Gini coefficient, the results indicated that renting the land to brick making kilns yields a 5-fold higher return than the rent for agriculture. Gini coefficient showed that the kiln owners had a more equal income distribution compared to farmers. To estimate emission of greenhouse gases (GHGs) and losses of N, P, K, Corg and DM from cow dung when used in brick making, samples of cow dung (loose and compacted) were collected from different kilns and analyzed for their N, P, K and Corg content. The procedure modified by the Intergovernmental Panel on Climate Change (IPCC, 1994) was used to estimate the gaseous emissions of cow dung and fuel wood. The amount of deforested wood was estimated according to the default values for wood density given by Dixon et al. (1991) and the expansion ratio for branches and small trees given by Brown et al. (1989). The data showed the monetary value of added N and P from cow dung was lower than for mineral fertilizers. Annual consumption of compacted dung (381 t DM) as biomass fuel by far exceeded the consumption of fuel wood (36 t DM). Gaseous emissions from cow dung and fuel wood were dominated by CO2, CO and CH4. Considering that Gerif land in urban Khartoum supports a multifunctional land use system, efficient use of natural resources (forest, dung, land and water) will enhance the sustainability of the UA and brick making activities. Adoption of new kilns with higher energy efficiency will reduce the amount of biomass fuels (cow dung and wood) used the amount of GHGs emitted and the threat to the few remaining forests.

Capturing Emergent Semantics from Social Annotation Systems

The ongoing growth of the World Wide Web, catalyzed by the increasing possibility of ubiquitous access via a variety of devices, continues to strengthen its role as our prevalent information and commmunication medium. However, although tools like search engines facilitate retrieval, the task of finally making sense of Web content is still often left to human interpretation. The vision of supporting both humans and machines in such knowledge-based activities led to the development of different systems which allow to structure Web resources by metadata annotations. Interestingly, two major approaches which gained a considerable amount of attention are addressing the problem from nearly opposite directions: On the one hand, the idea of the Semantic Web suggests to formalize the knowledge within a particular domain by means of the "top-down" approach of defining ontologies. On the other hand, Social Annotation Systems as part of the so-called Web 2.0 movement implement a "bottom-up" style of categorization using arbitrary keywords. Experience as well as research in the characteristics of both systems has shown that their strengths and weaknesses seem to be inverse: While Social Annotation suffers from problems like, e. g., ambiguity or lack or precision, ontologies were especially designed to eliminate those. On the contrary, the latter suffer from a knowledge acquisition bottleneck, which is successfully overcome by the large user populations of Social Annotation Systems. Instead of being regarded as competing paradigms, the obvious potential synergies from a combination of both motivated approaches to "bridge the gap" between them. These were fostered by the evidence of emergent semantics, i. e., the self-organized evolution of implicit conceptual structures, within Social Annotation data. While several techniques to exploit the emergent patterns were proposed, a systematic analysis - especially regarding paradigms from the field of ontology learning - is still largely missing. This also includes a deeper understanding of the circumstances which affect the evolution processes. This work aims to address this gap by providing an in-depth study of methods and influencing factors to capture emergent semantics from Social Annotation Systems. We focus hereby on the acquisition of lexical semantics from the underlying networks of keywords, users and resources. Structured along different ontology learning tasks, we use a methodology of semantic grounding to characterize and evaluate the semantic relations captured by different methods. In all cases, our studies are based on datasets from several Social Annotation Systems. Specifically, we first analyze semantic relatedness among keywords, and identify measures which detect different notions of relatedness. These constitute the input of concept learning algorithms, which focus then on the discovery of synonymous and ambiguous keywords. Hereby, we assess the usefulness of various clustering techniques. As a prerequisite to induce hierarchical relationships, our next step is to study measures which quantify the level of generality of a particular keyword. We find that comparatively simple measures can approximate the generality information encoded in reference taxonomies. These insights are used to inform the final task, namely the creation of concept hierarchies. For this purpose, generality-based algorithms exhibit advantages compared to clustering approaches. In order to complement the identification of suitable methods to capture semantic structures, we analyze as a next step several factors which influence their emergence. Empirical evidence is provided that the amount of available data plays a crucial role for determining keyword meanings. From a different perspective, we examine pragmatic aspects by considering different annotation patterns among users. Based on a broad distinction between "categorizers" and "describers", we find that the latter produce more accurate results. This suggests a causal link between pragmatic and semantic aspects of keyword annotation. As a special kind of usage pattern, we then have a look at system abuse and spam. While observing a mixed picture, we suggest that an individual decision should be taken instead of disregarding spammers as a matter of principle. Finally, we discuss a set of applications which operationalize the results of our studies for enhancing both Social Annotation and semantic systems. These comprise on the one hand tools which foster the emergence of semantics, and on the one hand applications which exploit the socially induced relations to improve, e. g., searching, browsing, or user profiling facilities. In summary, the contributions of this work highlight viable methods and crucial aspects for designing enhanced knowledge-based services of a Social Semantic Web.