Browsing by Subject "Modell"

Now showing 1 - 12 of 12

A backscatter lidar forward operator for aerosol-representing atmospheric chemistry models
(2020) Geisinger, Armin; Wulfmeyer, Volker
State-of-the-art atmospheric chemistry models are capable of simulating the transport and evolution of aerosols and trace gases but there is a lack of reliable methods for model validation and data assimilation. Networks of automated ceilometer lidars (ACLs) could be used to fill this gap. These networks are already used for the detection of clouds and aerosols, providing a 3D dataset of atmospheric backscatter profiles. But as the aerosol number concentration cannot be obtained from the ACL data alone; one needs a backscatter-lidar forward model to simulate lidar profiles from the model variables. Such an operator allows then for a qualitative and quantitative model validation based on ACL data. In this work, a newly developed backscatter-lidar forward operator and the related sensitivity studies are presented and results of the forward operator applied on model output data are compared to measured ACL profiles in the frame of a case study. As case study, the eruption of the Icelandic volcano Eyjafjallajökull in 2010 was chosen and extensively analyzed. The Consortium for Small-scale Modeling - Aerosols and Reactive Trace gases (COSMO-ART) model of DWD (Deutscher Wetterdienst) was operated during this event for ash-transport simulations over Europe. For the forward model, the attenuated backscatter coefficient is used as lidar-independent variable, which only relies on the laser wavelength. To calculate the attenuated backscatter coefficient, the size-dependent aerosol number concentration and the scattering properties of each aerosol type and size have to be simulated. While the aerosol number concentration is a model output variable, the scattering properties were determined by extensive scattering calculations. As these scattering calculations require assumptions about the aerosol refractive indices and shapes, sensitivity studies were performed to estimate the uncertainties related to the particle properties as represented by the model system. An analysis of the particle shape effect for the extinction and backscatter coefficients resulted in huge differences of the scattering properties between spherical, ellipsoidal and cylindrical particle shapes. Due to a particle shape mixture in typical volcanic ash plumes, the application of non-spherical scattering calculation methods for estimating the effective optical properties requires more information related to the particle shape distribution (specifically: a particle size and shape distribution). As such information was not available for the present case study, it was necessary to assume spherical shaped volcanic ash particles but estimate the uncertainty related to this assumption within the frame of additional sensitivity studies. Finally, the forward modeled lidar profiles were compared to ACL measurements from stations of the German ACL network. The comparison required an extraction of common time and height intervals of the ACL and forward modeled COMSO-ART data as well as reshaping the datasets to the same vertical and temporal resolution. Significant differences between ACL profiles and the output of the forward operator applied to the COSMO-ART data were found. Some ash layer structures were at similar coordinates which is remarkable due to the uncertainties related to the model dynamics and the limited amount of measurement data that could be used for model validation. In detail, however, the major fraction of the compared time and height interval differed both in the relative signal intensity and the layer structures of the volcanic ash plume. Based on such quantitative comparison, a future data assimilation system could correct the model prediction of the forward modeled attenuated backscatter coefficient, the time of arrival, as well as the vertical structure of the volcanic ash plume. In summary, the continuous and distributed data stream provided by ACL stations was found to deliver valuable verification information for dispersion simulations of aerosol events. But major issues have been determined which limit current realizations of backscatter-lidar forward operators for aerosol transport simulations: First, it is suggested that the ACL systems improve their dynamic range and perform automatic calibration to increase the precision of ACL data and for calculating the measured attenuated backscatter coefficient with a minimum leftover of uncertainties. This will allow for the calculation of the attenuated backscatter coefficient in the presence of clouds as well as of faint aerosol signals. Second, the aerosols scattering properties have to be analyzed even more extensively which includes both the variety of aerosol sizes or types as well as the size distribution information. From the findings within this study, the particle size distribution was indentified to be a critical component when using monodisperse size classes.
A monetary-fiscal theory of prices in modern DSGE models
(2018) Schröder, Christian Philipp; Spahn, Peter
Starting with the Eurozone crisis in 2010, fiscal variables such as the government budget position and public debt of certain member countries as well as the design of the European Monetary Union as a whole came under close scrutiny again. Furthermore, as a consequence of the global financial crisis, the economic profession faced accusations that, using the established ‘workhorse models,’ it was not able to provide answers to the pertinent questions of the time. From the perspective of economic theory, two main issues can be outlined against this background: (1) How do the so-called DSGE (dynamic stochastic general-equilibrium) models work which form a quasi-consensus in practice, research, and teaching nowadays? This relates especially to determinacy, that is, the mathematical property of being able to draw unique conclusions from a given set of assumptions. (2) What roles do the main fields of macroeconomic policy---fiscal and monetary policy---play in this? The exposition of these items is carried out within a formally consistent theoretical model which adheres to common standards and strikes a balance between staying general enough for a broad range of approaches and being sufficiently specific to yield tangible results. Following a brief introduction, Chapter 2 presents a microfounded (‘baseline’) general-equilibrium model that acts as a foundation for subsequent analysis. The only substantial exception is the excursus in Chapter 3. It deals with interactions between the entities of the consolidated government sector, namely the treasury and the central bank, and in doing so also touches on traditional models which cannot be reconciled entirely with modern theory. One of the main aspects is the “unpleasant monetarist arithmetic” that describes the long-standing explanation for fiscally induced inflation. The fourth chapter then takes up the baseline model and ‘closes’ it by defining monetary as well as fiscal policy, both of which can be active (that is, dominant) or passive. Resulting from this classification are two stable macroeconomic regimes (monetary or fiscal dominance) plus two undesirable outcomes (explosive instability or indeterminacy of central model variables). Monetary dominance is tantamount to the prevailing world view—central banks can independently pursue a measure of price stability while governments have to follow a sustainable (Ricardian) fiscal policy—whereas fiscal dominance gives rise to a “fiscal theory of the price level” in which the treasury sets budget surpluses without regard for other variables and monetary policy can be an implicit accomplice at most. This latter regime ultimately puts price stability into the hands of the treasury. Initially, the only public liability is debt (there is no money at this stage); however, the is model is able to determine unique price levels in the stable regimes. Chapter 5 introduces several isolated complications to the model described so far. One is the role of money, especially in the fiscalist model variant; it shows that the main results remain unchanged if monetary policy is conducted via money-supply instead of interest-rate policy. Further considerations are the zero lower bound on interest rates (in a graphic analysis) as well as limits to public-sector liabilities. Subsequently, Chapter 6 applies the baseline model of Chapter 2 to the open economy—more precisely, a monetary union consisting of two countries. Since monetary policy is supranational here, outcomes crucially depend on national fiscal policies. While the baseline model assumes flexible prices, Chapter 7 adds the considerable complication of nominally rigid prices. A mostly ‘plain-vanilla’ New-Keynesian model emerges which, following common practice, is then linearized and simulated in Matlab/Dynare. At the core of the analysis lie the two stable regimes carved out in Chapter 4. The central implications of the monetary-fiscal theory derived so far are adjusted gradually, but remain in place generally. Towards the end, the thesis highlights empirical issues (verifiability of the regimes, historical case studies). Finally, the results obtained beforehand culminate in a comprehensive discussion of the monetary-fiscal theory, including a distinction from traditional approaches. Chapter 10 concludes.
A study of pasture cropping as an alternative cropping system for sub-saharan Africa
(2020) Orford, Rohan; Asch, Folkard
With food security and soil degradation being a major concern and hurdle in the development goals of sub-Saharan Africa (SSA), there has been and continues to be an attempt to find an alternative cropping system to conventional monocropping that rehabilitates soils whilst increasing productivity and efficiency of the subsistence cropping system. Such a cropping system needs to be realistically adoptable within the SSA social and ecological constraints. An alternative Australian winter rainfall relay cropping system coined pasture cropping (PaCr) was identified as an option that may surmount some of these limitations.This research involved completing a field trial through to model scale introductory assessment of the water dynamics in PaCr and the implications thereof in yield, water use efficiency (WUE) and competition for water; ultimately assessing the potential of PaCr in SSA. PaCr was adapted to an intercropping system for SSA summer rainfall conditions. The three treatments included the representative subsistence crop cowpea (Vigna unguiculate) and a common indigenous pasture (Eragrostis curvula) and an additive PaCr setup of cowpea directly seeded into pasture in water limited (rainfed) field trials in Pretoria, South Africa between 2013-2015. The DM yields of PaCr were 17% and 293% higher in both seasons compared to the conventional cowpea monocrop yield. When comparing PaCr yield to conventional pasture, there was a 12% and 89% higher yield in both seasons compared to the conventional pasture monocrop yield. The greater yield advantage in 2015 with the limited rainfall indicates that PaCr was most advantageous in terms of DM yield in a drier year which is a time of greatest risk and food insecurity. PaCr was also more WUE in both seasons, being significantly higher than the cowpea monocrop in 2015. Competition also showed a higher degree of competitiveness by cowpea in the wetter 2013-14 season and lower competitive ability in the drier 2015, whereas pasture showed little competitive response in 2013-14 and attaining significantly higher yields than the monocrop in 2015. The results of the field trials were used to adapt the University of Pretoria’s Soil Water Balance (SWBsci) crop model to simulate an intercropping system. Observed field results were compared to simulated results and statistical goodness of fit indicators were assessed, concluding that with all the variations of season and systems, the results were acceptable as an inaugural adaptation of the Soil Water Balance model. Other relevant crop water use parameters were extrapolated from the simulated data allowing for a more complete insight into the field trials. With the adapted SWBsci model, 14-year simulations were run in three different climates and on three different soil types for all three cropping systems to map out the viability of PaCr across an aridity index continuum as a reference for further application in research or in industry and to stress test SWBsci. Results demonstrated that PaCr was only advantageous in dry sub-humid to humid conditions on clay-loam to sandy soils, whereas pasture was dominant in more semi-arid conditions on the three different soils. Cowpea only performed better on clay soils in dry-sub humid to sub humid conditions. These advantages are attributed to differing plant water availability at various root depths suiting growth and/or competition of either one or both crops. These plant water availability differences were determined by water holding capacity of various soil types and rainfall volumes. From a WUE perspective, the pasture and PaCr did have a higher WUE but with the extreme variation in rainfall there was no significant difference. But pasture and PaCr both had a very high WUE in arid to semi-arid conditions due to the deeper roots of pasture accessing stored soil water. Competition also showed insignificant results due to the variation in the rainfall. However, in more arid to semi-arid conditions on clay-loam and sand competition outweighed facilitation thus resulting in land equivalent ratios (LER) of below 1, whereas on clay for the same aridity levels the average LER was greater than one. This was attributed to cowpea have a better competitive ability when clay water holding capacity confined plant available water to the top soil layers. The converse is true in the dry sub-humid conditions and wetter conditions because LER was less than one on clay soils while being greater than one on clay-loam and sand. This was attributed to the lower water holding capacity of sand spreading the plant available water through the profile allowing for niche root partitioning to be effective. For subsistence farmers, PaCr out-yielded the cowpea monocrop in arid conditions on all three soil types and on clay in semi-arid conditions. In the wetter dry sub-humid conditions, PaCr out-yielded cowpea on sand. In the wet sub-humid conditions PaCr does well on clay-loam and sand, but cowpea yields under these conditions are more than adequate to make the choice of PaCr debatable form a yield point of view. However, if soil rehabilitation is a necessity in the sub-humid areas, this makes PaCr a very realistic option.
Agent-based modeling of climate change adaptation in agriculture : a case study in the Central Swabian Jura
(2014) Troost, Christian; Berger, Thomas
Using the MPMAS multi-agent software, the present thesis implements an agro-economic agent-based model to analyze climate change adaptation of agricultural production in the Central Swabian Jura. It contributes to the DFG PAK 346 FOR 1695 research projects dedicated to improve the understanding of processes that shape structure and functions of agricultural landscapes in the context of climate change at regional scale. In the context of this example, this thesis discusses, develops and tests novel approaches to deal with four notorious challenges that have so far hampered the empirical use of agent-based models for applied economic analysis: data availability, process uncertainty, model validity and computational requirements. The model is used to examine climatic effects on agriculture, changes in agricultural price responses and biogas support and agri-environmental policies illustrating the applicability of the model to adaptation analysis. The first part of the thesis is dedicated to a methodological discussion of the use of mathematical programming-based multi-agent systems, such as MPMAS, for the analysis of agricultural adaptation to climate change. It synthesizes knowledge about the potential impacts of climate change and processes of farmer adaptation and reviews existing agent-based models for their potential contribution to adaptation analysis. The major focus of the first part is a discussion of available approaches to model validation, calibration and uncertainty analysis and their suitability for the use with mathematical programming-based agent-based models. This discussion is based on four principles required to ensure the validity of conclusions drawn from modeling studies: (i) a transparent model documentation, (ii) that the invariant elements of the model can really be expected to be invariant between scenarios assessed, (iii) that empirical calibration of the model is limited to the extent warranted by available observation and knowledge about the expected error distribution, and (iv) that the effect of process uncertainty on the conclusions is evaluated and communicated. Based on these conclusions, generic extensions of the MPMAS toolbox are developed to allow the application of suitable approaches for validation and uncertainty analysis. The second part of the thesis describes the application of the newly developed methodology in the construction and use of the Central Swabian Jura model. The model focuses on an endogenous representation of heterogeneity in agent behavior, an empirical parameterization of the model, and an incorporation of climate effects on possible crop rotations and suitable days for field work besides the expected effects on yields. It extends the demographic, investment and land market components of MPMAS to improve the simulation of structural change over time. The model was used to analyze potential effects of climate change adaptation on agricultural production and land use in the study area. The results show that besides effects on yields also other climate change-induced effects on the conditions of agricultural production may have important impacts on land use decisions of farmers and deserve more attention in climate change impact analysis. Potential impacts of changes in the time slots suitable for field work and an additional rotation option are predicted to be comparable to the impact of the changes in yields predicted by a crop growth model. Results point to an expansion of wheat and silage maize areas at the expense of barley areas. The partial crowding out of summer barley by wheat area held for current price relations and is less strong at higher relative prices for summer barley. Price response analysis indicated that winter wheat production enters into a substitutive relationship with summer barley production under climate change conditions, while competition with winter barley area diminishes. This leads also to a higher elasticity of the wheat area with respect to relative summer barley prices. The model was then used to analyze biogas support through the Renewable Energy Act (EEG) and the support for grassland extensification and crop rotation diversification through the MEKA scheme. Especially simulated participation in crop rotation diversification is strongly reduced in the climate change scenarios, while the investments in biogas plants are slightly increased. The conditions established by the latest EEG revision imply that further development of biogas capacity will crucially depend on the existence of demand for excess process heat, because the alternative option of using high manure shares seems to be rather unattractive for farmers in the area according to the simulation results.
Konfliktkostenmanagement – Wirtschaftlichkeitskontrolle im Konflikt- und Kommunikationsmanagement
(2014) Audi, Manuel; Brettschneider, Frank
Conflict management is a method of limiting the negative effects of conflict while increasing the positive ones. Conflict cost management has not yet been considered as a major task of the conflict management process. The dissertation bridges this gap by developing a theoretical model which aims to ensure a systematical management of direct and indirect conflict costs. The conflict cost management model is being integrated into the conflict and communication management process. The model can be incorporated in the organizational management process as an independent approach to identify, measure and control conflict costs. Furthermore the model can be used to manage the profitability of different interventions aiming to prevent and/or to treat existing or potential conflicts.
Land use management under climate change : a microeconomic analysis with emphasis on risk
(2018) Reinmuth, Evelyn; Dabbert, Stephan
This cumulative dissertation was conducted under a grant from the German Research Foundation (DFG) for the research group FOR 1695 - “Agricultural Landscapes under Global Climate Change – Processes and Feedbacks on a Regional Scale”. The goal of the sub-project from which this dissertation stems from was to explore, extend and strengthen the scientific basis for learning and risk strategies and the adaptation behavior of farmers’ economic planning decisions in crop production under the influence of climate change. The integrated bioeconomic simulation model FarmActor, was to be used as an experimental tool to develop an interdisciplinary methodological approach supported by empirical work in two study regions in Southwest Germany, the Kraichgau and the Swabian Alb. This dissertation examines risk in the context of land use management and specifically crop production. Risk in this context is related to how outcome distributions are affected by climatic influences. Risk strategies assess these contributions and account for them in the resulting decisions. The thesis is written as a cumulative dissertation and is composed of five articles. Four articles have been published by peer-reviewed journals. A fifth article has been published as a peer-reviewed conference proceeding. The article at fifth place represents the results of the main focus of this dissertation as presented in the following. Available economic models assume that farmers assess climatic risks only through yields or costs when building their land use management risk strategy for crop production. However, the available methodological approaches have been criticized for either under- or overestimating farmers’ actual behavior. In reality, and as a basis for field allocation planning, farmers have additional knowledge from monitoring crop development throughout the whole season. Yield is actually just the last point in a long sequence of (economic) evaluative observations about the production process. This influences how farmers define not only the riskiness of a yield distribution but also its costs. We hypothesize that, because it is not possible to methodologically integrate process evaluations in economic planning decisions, models lack performance, and as a consequence, it is very difficult to conduct proper research on the climate’s influences on land use management decisions. In this original research, we present a newly developed downside risk measure based on evaluations throughout the production process that can be included in the planning process as an additional parameter—so-called Annual Risk Scores. A comparative static analysis was performed to demonstrate how ARS scores assess future climatic conditions in the example of winter wheat production in the Kraichgau region as supported by empirical data. It was shown that the mechanism is sensitive to different climatic conditions. Furthermore, the ARS scores provide a different picture of climatic influence compared to an analysis based only on yields. The last article presented in this dissertation represents an integrative review that promotes more efficient model development and the reuse of newly developed methodologies in the field of integrated bio-economic simulation models. The review is based on lessons learned from working with the simulation model. Thus, the intended and outstanding full implementation of the ARS mechanism is presented in the last part of the synthesis, where we advise including the ARS scores as another constraint in the field allocation mechanisms of the FarmActor model. This is expected to improve the integration of both bio-physical and economic dimensions for complex integrated bio-economic simulation models.
Multi-objective and multi-variate global sensitivity analysis of the soil-crop model XN-CERES in Southwest Germany
(2021) Witte, Irene; Streck, Thilo
Soil-crop models enjoy ever-greater popularity as tools to assess the im- pact of environmental changes or management strategies on agricultural production. Soil-crop models are designed to coherently simulate the crop, nitrogen (N) and water dynamics of agricultural fields. However, soil-crop models depend on a vast number of uncertain model inputs, i.e., initial conditions and parameters. To assess the uncertainty in the simulation results (UCSR) and how they can be apportioned among the model inputs of the XN-CERES soil-crop model, an uncertainty and global sensitivity analysis (GSA) was conducted. We applied two different GSA methods, moment-independent and variance-based methods in the sense of the Factor Prioritization and the Factor Fixing setting. The former identifies the key drivers of uncertainty, i.e., which model input, if fixed to its true value, would lead to the greatest reduction of the UCSR. The latter identifies the model inputs that cannot be fixed at any value within their value range without affecting the UCSR. In total we calculated six sensitivity indices (SIs). The overall objective was to assess the cross-sub-model impact of parameters and the overall determinability of the XN-CERES applied on a deep loess soil profile in Southwest Germany. Therefore, we selected 39 parameters and 16 target variables (TGVs) to be included in the GSA. Furthermore, we assessed a weekly time series of the parameter sensitivities. The sub-models were crop, water, nitrogen and flux. In addition, we also compared moment-independent (MI) and variance-based (VB) GSA methods for their suitability for the two settings. The results show that the parameters of the TGVs of the four groups cannot be considered independently. Each group is impacted by the parameters of the other groups. Crop parameters are most important, followed by the Mualem van Genuchten (MvG) parameters. The nitrate (NO3-) content and the matric potential are the two TGVs that are most affected by the inter- action of parameters, especially crop and MvG parameters. However, the model output of these two TGVs is highly skewed and leptokrutic. Therefore, the variance is an unsuitable representation of the UCSR, and the reliability of the variance-based sensitivity indices SIVB is curtailed. Nitrogen group parameters play an overall minor role for the uncertainty of the whole XN-CERES, but nitrification rates can be calibrated on ammonium (NH4+) measurements. Considering the initial conditions shows the high importance of the initial NO3-; content. If it could be fixed, the uncertainty of crop groups’ TGVs, the matric potential and the N content in the soil could be reduced. Hence, multi-year predictions of yield suffer from uncertainty due to the simulated NO3-; content. Temporally resolved parameter show the big dependence between the crop’s development stage and the other 15 TGVs becomes visible. High temporally resolved measurements of the development stage are important to univocally estimate the crop parameters and reduce the uncertainty in the vegetative and generative biomass. Furthermore, potential periods of water and N-limiting situations are assessed, which is helpful for deriving management strategies. In addition, it become clear that measurement campaigns should be conducted at the simulation start and during the vegetation period to have enough information to calibrate the XN-CERES. Regarding the performance of the different GSA methods and the different SIs, we conclude that the sensitivity measure relying on the Kolmogorov-Smirnov metric (betaks) is most stable. It converges quickly and has no issues with highly skewed and leptokrutic model output distributions. The assessments of the first-effect index and the betaks provide information on the additivity of the model and parameters that cannot be fixed without impacting the simulation results. In summary, we could only identify three parameters that have no direct impact on any TGV at any time and are hence not determinable from any measurements of the TGVs considered. Furthermore, we can conclude that the groups’ parameters should not be calibrated independently because they always affect the uncertainty of the selected TGV directly or via interacting. However, no TGV is suitable to calibrate all parameters. Hence, the calibration of the XN-CERES requires measurements of TGVs from each group, even if the modeler is only interested in one specific TGV, e.g., yield. The GSA should be repeated in a drier climate or with restricted rooting depth. The convergence of the values for the Sobol indices remains an issue. Even larger sample sizes, another convergence criteria or graphical inspection cannot alleviate the issue. However, we can conclude that the sub-models of the XN-CERES cannot be considered in- dependently and that the model does what it is designed for: coherently simulating the crop, N and water dynamics with their interactions.
Regionalising a soil-plant model ensemble to simulate future yields under changing climatic conditions
(2023) Bendel, Daniela Silke; Streck, Thilo
Models are supportive in depicting complex processes and in predicting their effects. Climate models are applied in many areas to assess the possible consequences of climate change. Even though Global Climate Models (GCM) have now been regionalised to the national level, their resolution of down to 5x5 km2 is still rather coarse from the perspective of a plant modeller. Plant models were developed for the field scale and work spatially explicitly. This requires to make adjustments if they are applied at coarser scales. The regionalisation of plant models is reasonable and advantageous against the background of climate change and policy advice, both gaining in importance. The higher the spatial and temporal heterogeneity of a region, the greater the computational need. The (dis)aggregation of data, frequently available in differing resolutions or quality, is often unavoidable and fraught with high uncertainties. In this dissertation, we regionalised a spatially-explicit crop model ensemble to improve yield projections for winter wheat under a changing climate. This involved upscaling a crop model ensemble consisting of three crop models to the Stuttgart region, which has an area of 3,654 km2. After a thorough parameter estimation performed with a varying number of Agricultural Response Units on a high-performance computing cluster, yield projections up to the year 2100 were computed. The representative concentration pathways of the Intergovernmental Panel on Climate Change (IPCC) RCP2.6 (large reduction of CO2 emissions) and RCP8.5 (worst case scenario) served as a framework for this effort. Under both IPCC scenarios, the model ensemble predicts stable winter wheat yields up to 2100, with a moderate decrease of 5 dt/ha for RCP2.6 and a small increase of 1 dt/ha for RCP8.5. The variability within the model ensemble is particularly high for RCP8.5. Results were obtained without accounting for a potential progress in wheat breeding.
Reifenparameterermittlung aus Fahrversuchen mit einem Ackerschlepper unter besonderer Berücksichtigung des Hohenheimer Reifenmodells
(2017) Schulze Zumkley, Hendrik
Die Landwirtschaft weltweit strebt eine zunehmende Industrialisierung und Effizienzsteigerung an. Ein Ansatz dazu ist die Verkürzung der Transport- und Umsetzzeiten von Gütern und Maschinen durch Steigerung der Höchstgeschwindigkeit, insbesondere von Ackerschleppern und selbstfahrenden Landmaschinen. Unter Beibehaltung der notwendigen Sicherheit ist dieses Ziel jedoch nur mit aufwendigerer Technik möglich. Ein weiteres Ziel ist die Fahrzeugentwicklung zu beschleunigen und zu präzisieren, was mit Simulationswerkzeugen wie der Mehrkörpersimulation gelingen soll. Wesentliches Element der Gesamtfahrzeugsimulation ist die Modellierung des Reifenverhaltens. Kommerzielle Reifenmodelle sind zahlreich verfügbar. Die Eignung für Ackerschlepperreifen und besonders ihre Parametrierung ist jedoch stark eingeschränkt. Es gibt nur sehr wenige Prüfstände, die in der Lage sind, Reifen mit einem Durchmesser größer 2 m zu vermessen. In dieser Arbeit wird daher die Alternative geprüft, mit einem messtechnisch ausgestatteten Ackerschlepper aus Fahrversuchen einzelne Reifenparameter zu ermitteln. Das Hohenheimer Reifenmodell dient wegen der Verfügbarkeit des Codes und der weitgehenden Allgemeingültigkeit der verwendeten Parameter als Grundlage.
Simulation der Trennprozesse im Mähdrescher
(1999) Beck, Folker
Die Kosten für Versuche nehmen in der Mähdrescherentwicklung weiter zu. Außerdem ist die zur verfügung stehende Zeit während der Ernte begrenzt. Deshalb wird ein Simulationswerkzeug für die Trennprozesse im Mähdrescher entwickelt, mit dem sich der Gutfluß im Mähdrescher schon beid er Entwicklung jederzeit und kostengünstig am rechner nachvollziehen lässt. Das Simulationswerkzeug ist außerdem zur Untersuchung physikalischer Zusammenhänge bei der Korn/Stroh/Spreu-trennung geeignet, da es auf stochastischen, mathemnatisch-physikalischen Modellen für die Teilprozesse in Dreschwerk, Schüttler, Vorbereitungsboden, Fallstufe und Obersieb der Reinigungsanlage aufbaut. In laborversuchen werden sämtliche Teilprozeßmodelle einzeln experimentell bestätigt. beispielhaft durchgeführte Simulationsrechnungen für den Gesamt-mähdrescher bei Variation von Durchsatz, dreschtrommel-Drehzahl, Dreschkorblänge und Länge des Vorbereitungsbodens zeigen gute Übereinstimmung und machen Potential für zukünftige Entwicklungen deutlich.
Untersuchungen der Kräfte an schräglaufenden angetriebenen Ackerschlepperrädern
(1991) Armbruster, Karlheinz
Mit einer Einzelradmesseinrichtung wurden an Ackerschlepper-Antriebsrädern bei Radschräglauf und Schlupf gleichzeitig auftretende Längs- und Seitenkräfte an Reifen unterschiedlicher Größe auf verschiedenen Fahrbahnen gemessen. Die Ergebnisse wurden dargestellt und unter Berücksichtigung des Einflusses von Fahrgeschwindigkeit und Schlupf auf die Bodeneigenschaften durch Modellrechnungen beschrieben. Steigender Schlupf führt zu größeren Triebkräften, eine Zunahme des Schräglaufwinkels zu einem degressiven Anstieg der Seitenkräfte. Die Radführungskräfte nehmen vor allem mit der Radlast zu. Größere Raddurchmesser führen zu höheren Triebkräften, breitere Reifen zu größeren Seitenkräften. Eine Zunahme der Längskräfte führt zu einem Rückgang der Seitenkräfte. Das Maximum der Seitenkräfte liegt im Bereich geringen negativen Schlupfes und geringer negativer Triebkräfte.
Ein validiertes Reifenmodell zur Simulation des fahrdynamischen und fahrkomfortrelevanten Verhaltens von Ackerschleppern bei Hindernisüberfahrt
(2015) Witzel, Paul
Am Institut für Agrartechnik der Universität Hohenheim wurden im Rahmen vieler Forschungsprojekte die speziellen Eigenschaften von Ackerschlepperreifen untersucht und modelliert. Dabei standen zumeist fahrdynamisch relevante Themen im Vordergrund. Das Hohenheimer Reifenmodell fasst die dabei gewonnenen Erkenntnisse in einem dreidimensionalen, transienten Ansatz zusammen. Mit dem nichtlinearen Modell kann die Fahrdynamik von Landmaschinen auf ebenem, festem Untergrund untersucht werden. Im Rahmen dieser Arbeit wurde das Hohenheimer Reifenmodell funktional erweitert, so dass Längs- und Vertikalkräfte bei der Überfahrt von Unebenheiten berechnet werden können. Mit dem erweiterten Hohenheimer Reifenmodell sind somit nicht nur fahrdynamische Untersuchungen möglich. Es kann auch dazu genutzt werden, den Fahrkomfort betreffende Merkmale zu analysieren und zu optimieren. Bei der Entwicklung standen eine einfache Parametrierbarkeit, kurze Rechenzeiten und eine hohe Modellgüte im Vordergrund.