Browsing by Subject "Simulation"

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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.
Agent-based modeling of human-environment interactions in a smallholder agricultural system in the Atlantic Forest (Ribeira Valley, SP, Brazil)
(2021) Munari, Lucia Chamlian; Berger, Thomas
Shifting cultivation systems (SCSs) have been practiced all over the tropics for centuries as the primary subsistence strategy for smallholders. However, since the mid-20th century, SCSs have been submitted to changes, driven by a combination of geographic, economic, socio-political, and demographic factors. Consequently, land use changes lead to agricultural intensification and the replacement of more profitable and permanent practices. The implementation of forest conservation policies (FCPs) is one of the changing drivers to SCSs. They have been designed to reduce or eliminate it, criminalize traditional practices, restrict resources access, displace locals, and increase inequalities and land conflicts. In Brazil, SCSs have been practiced by smallholders and indigenous groups, including Quilombolas, descendants of African enslaved who rebelled against the Portuguese regime. After the abolition of slavery, they remained spread over the country without any state legitimation. Their recognition and rights to ancestors land were possible only in 1988, with the Brazilian Constitution. The Ribeira Valley (Southeastern Brazil) is home to dozens of Quilombos, one of the most significant Atlantic Forest remnants, and high biodiversity. Its first Quilombos were formed in the 18th century and relied on SCS to survive, relatively isolated, up to the 1950s. However, in the context of SCS changes, Quilombos are under a transitional process in different dimensions, including constraints to their traditions by FCPs, generating conflicts. Inspired by this challenging scenario, the Thesis goals are to evaluate Quilombolas’ socioeconomic conditions and the perception of FCPs implementation and integrate two modeling tools. The tools will model the impact of agricultural transitions on family wealth, income, landscape structure, and tree community β diversity and model the impact of FCPs over the equal economic and ecological dimensions. Socioeconomic data were gathered in 2017 in 14 communities through interviews of 164 farmers. Quilombolas’ perception of FCPs and constraints for agricultural practice were investigated. The modeling implementation used MPMAS (Mathematical Programming-based Multi-Agent Systems) to simulate land use change in agriculture and forestry. MPMAS was integrated (through land use maps) with a Generalized Dissimilarity Modeling tool (GDM) to predict beta diversity as a function of environmental variation. The modeling exercise was implemented for Pedro Cubas territory, a Quilombo with 52 households located in Eldorado (SP). A combination of primary and secondary data from different sources was used, including a socioeconomic census of 2014 and a collection of tree data in 2016. Five economic/political scenarios were created for comparisons, with a baseline and four different counterfactual situations, varying in market access and FCPs versions. Seven yield curve scenarios and 30 Sobol’ repetitions were combined, totalizing 1050 simulations. A tradeoff analysis was applied over the political scenarios. MPMAS sensitivity/uncertainty analyses revealed variation on staples consumptions among yield curve scenarios, the sensitivity of income to different parameters, and each income source relevance. The GDM calibration highlighted the importance of climate predictors for tree species, indicating vulnerability to potential climate variability. Results revealed that only 32% of the families were practicing SCS in 2017, but it was still relevant for food security. 83% of the interviewees were unsatisfied with the FCPs, especially the timing of issuing the licenses for SCS. The political scenarios comparison indicates that agricultural intensification caused an improvement in average income. Still, it was accompanied by economic inequality, diminished rotation of plots, lower diversity of habitats, and a less permeable landscape structure (on fallows and because of the emergence of pasture and perennial areas). GDM results showed a significant change in landscape structure/tree community for at least 10% of the territory in the last decades. Regarding FCPs implementation, scenario comparison showed that well-being conditions improved when FCPs were excluded, although more ecological impacts occur. However, such effects refer to only 2.6% of the territory where 90% is covered by mature forest, and GDM indicates that the total ß diversity would not be significantly affected. The tradeoff analysis showed that FCPs are significant for conservation in the present context when perennials and pasture areas occur. In the isolated scenario case, when SCS is the only economic activity, a combination of good well-being and conservation performances was found, suggesting it is causing even lower environmental impacts. I recommend more flexible policies for SCS implementation in the Quilombos in general, for the potential of improving well-being conditions by impacting a small share of the territories. FCPs flexibilization would be even more relevant to the communities that don’t have access to alternatives to SCS.
Anforderungs- und einsatzgerechte Auslegung von Fahrantrieben mobiler Erntemaschinen
(2019) Häberle, Steffen
Fahrantriebe mobiler Erntemaschinen werden im Rahmen einer fortschreitenden Automatisierung zunehmend zum integralen Bestandteil der Prozessführung. Komplexe Anforderungen, die sich aus deren Einsatz ergeben, haben zu einer Etablierung hydrostatischer Fahrantriebe geführt. Der zunehmende legislative Druck und die steigenden Vermarktungschancen kraftstoffsparender Technologien rücken die Effizienzbewertung von Antriebssystemen stärker in den Fokus der Forschung und Entwicklung. Standardisierte Bewertungssysteme lassen sich bei mobilen Arbeitsmaschinen, wegen deren Heterogenität und Vielfältigkeit ihrer Aufgaben, allerdings nur schwer umsetzen. Die vorliegende Arbeit zeigt einen allgemeingültigen methodischen Ansatz zur Effizienzbewertung anhand von Lastkollektiven und eines Simulationsmodells auf. Dieser lässt sich auf alle mobilen Arbeitsmaschinen mit quasistationären Lastanteilen anwenden. Am Beispiel eines Mähdreschers werden typische Einsatzbedingungen mit gemessenen Einsatzprofilen und Lastkollektiven ermittelt und in den Gesamtkontext möglicher Nutzungsszenarien kategorisiert. Mittels eines Antriebsstrangmodells wird damit die Energieausnutzung des Fahrantriebs, entsprechend den Einsatzbedingungen, berechnet. Basierend auf diesen Ergebnissen und einer detaillierten Anforderungsanalyse sind neue Antriebslösungen erarbeitet und entsprechenden Leistungsklassen zugeordnet worden. Für einen Referenzmähdrescher wird ein methodisch ausgewähltes Fahrantriebskonzept, ein sogenannter Summierungsantrieb, ausgelegt und modellbasiert bewertet. Die berechneten Ergebnisse der optimierten Antriebsvariante zeigen deutliche Verbesserungen der Energieausnutzung bei einem erhöhten Kundennutzen.
Development of multifunctional unmanned aerial vehicles versus ground seeding and outplanting: What is more effective for improving the growth and quality of rice culture?
(2022) Qi, Peng; Wang, Zhichong; Wang, Changling; Xu, Lin; Jia, Xiaoming; Zhang, Yang; Wang, Shubo; Han, Leng; Li, Tian; Chen, Bo; Li, Chunyu; Mei, Changjun; Pan, Yayun; Zhang, Wei; Müller, Joachim; Liu, Yajia; He, Xiongkui
The agronomic processes are complex in rice production. The mechanization efficiency is low in seeding, fertilization, and pesticide application, which is labor-intensive and time-consuming. Currently, many kinds of research focus on the single operation of UAVs on rice, but there is a paucity of comprehensive applications for the whole process of seeding, fertilization, and pesticide application. Based on the previous research synthetically, a multifunctional unmanned aerial vehicle (mUAV) was designed for rice planting management based on the intelligent operation platform, which realized three functions of seeding, fertilizer spreading, and pesticide application on the same flight platform. Computational fluid dynamics (CFD) simulations were used for machine design. Field trials were used to measure operating parameters. Finally, a comparative experimental analysis of the whole process was conducted by comparing the cultivation patterns of mUAV seeding (T1) with mechanical rice direct seeder (T2), and mechanical rice transplanter (T3). The comprehensive benefit of different rice management processes was evaluated. The results showed that the downwash wind field of the mUAV fluctuated widely from 0 to 1.5 m, with the spreading height of 2.5 m, and the pesticide application height of 3 m, which meet the operational requirements. There was no significant difference in yield between T1, T2, and T3 test areas, while the differences in operational efficiency and input labor costs were large. In the sowing stage, T1 had obvious advantages since the working efficiency was 2.2 times higher than T2, and the labor cost was reduced by 68.5%. The advantages were more obvious compared to T3, the working efficiency was 4 times higher than in T3, and the labor cost was reduced by 82.5%. During the pesticide application, T1 still had an advantage, but it was not a significant increase in advantage relative to the seeding stage, in which operating efficiency increased by 1.3 times and labor costs were reduced by 25%. However, the fertilization of T1 was not advantageous due to load and other limitations. Compared to T2 and T3, operational efficiency was reduced by 80% and labor costs increased by 14.3%. It is hoped that this research will provide new equipment for rice cultivation patterns in different environments, while improving rice mechanization, reducing labor inputs, and lowering costs.
Einfluss der mechanischen und pneumatischen Anregung auf die Entmischung und Abscheidung in der Mähdrescherreinigungsanlage
(2021) Beckmann, Konstantin
Due to the legal limitation of the maximum machine width the throughput increase is realized by further developing of the process technology. This requires precise knowledge of the ongoing processes. The aim of this work is the metrological investigation of the combine cleaning system according to the white-box model by analyzing the process sequence of the sub-processes.This enhances process understanding and enables the validation and verification of DEM-CFDsimulations. The evaluation of the segregation and separation process is based on the movement behavior of grain and straw. For this purpose, 2D high-speed x-ray images, static 3D reconstructions and 2D high-speed camera images are analyzed. The segregation in the lower layers is limited by the compression of the material layer due to its own weight. Due to the higher porosity the segregation of the grain near the wall is slightly faster. Additional relative movements of the material based on the superimposed conveying process. The resulting voids are used for a faster segregation. The influence decreases with increasing mechanical and pneumatic excitation in vertical direction. The influencing factors on the movement behavior of the material in the cleaning system is investigated with a test-rig. In the unloaded state the airflow decreases along the sieve. Due to higher sieve loads the airflow is flatter. Therefore the maximum air speed under the lower sieve is shifted to larger sieve lengths. The front area of the upper sieve is less loaded. The air passes by these areas and causes an increase of the air speed. High air speeds in the winnowing steps result in a high grain separation. A high component of the air velocity in the conveying direction between the sieves causes a shift of the separation on the lower sieve to longer lengths. The air throughput must be within the limits between a sufficient material fluidisation and a low conveying process on the sieves. In addition to identifying development potential, the results are used to verify DEM-CFDsimulations. There are deviations of movement behavior between grain and straw. Nevertheless,the influencing factors can also be examined qualitatively on the basis of the simulations.
Entwicklung einer kontextbasierten Systemarchitektur zur Verbesserung des kooperativen Einsatzes mobiler Arbeitsmaschinen
(2018) Steckel, Thilo; Griepentrog, Hans
In contrast to industrial production processes, agricultural processes are characterized by high uncertainty in terms of planning and execution. Main reasons for this are system-induced high environmental exposure, high complexity of the technical systems, a low division of labor and the lack of applicable systems for decision-making and support.Low process transparency and suboptimal decisions result from that. This observation becomes measurable by comparison of installed performance, determined under ideal conditions, and realized performance, determined from literature and telematics data, which are at a level of approximately 40 to 50%. In the present work the causes for this gap are analyzed and a method for their reduction is developed. Key to improving the situation is the systematic use of context-oriented approaches. The context dimensions time, space and system are described and related to each other. In this way, decision-relevant process conditions in agricultural work processes can be described in a structured manner. On the basis of these contexts, components are derived which, in a subsequent system architecture, enable the automated identification, description and evaluation of process contexts. On this basis concrete measures for the improvement of processes can be derived within the scope of the given possibilities (eg machine performance, drivability). The principle of system architecture is exemplified by the example of the harvesting of silo maize (chipping, transport, storage). The process is modeled from a contextual viewpoint and implemented as agent-based simulation, taking into account the above defined components. In order to carry out the simulation, performance (eg. throughput) and cost-relevant (eg. fuel consumption) parameters are recorded on real machines and production functions are developed. The simulation provides the costs and time requirements for a given process configuration (performance of the forage harvester, number, speed and capacity of the transport vehicles as well as number and mass compacting vehicles). In a parameter configuration based on this simulation a solution space is created which can be used to derive advantageous behaviors. Performance-determining parameters in the determined limits and defines step size are used for that. In addition to the simulation, a mathematical method for the generation of logistic characteristics is developed. Simulation and characteristic fields provide the possibility discreet or continuous approaches of the processes. For verification, results are compared with an empirical survey by questioning farmers and contractors. The described approach allows qualified decisions to improve cooperation in processes and thus contribute to the reduction of the abovementioned performance gap. However, the limits of the improvements result from the locally prevailing environmental conditions and must be defined by the user. Further steps for the control and optimization of processes can be developed on the described approach.
Entwicklung und Applikation eines instationären Reifenmodells zur Fahrdynamiksimulation von Ackerschleppern
(2009) Ferhadbegovic, Bojan
The driving speed of modern agricultural tractors increased continuously during the last years. Nowadays, a maximum driving speed of 50 km/h is standard for agricultural tractors in Germany. To be able to drive safely at such high speeds, the agricultural tractors are equipped with a suspended front axle. However, a rear axle suspension for standard tractors is still too expensive and has thus not prevailed yet. The increasing percentage of transportation duties and the efforts to increase the productivity generate a high demand for even faster agricultural tractors. Therefore, the first standard tractor with a maximum driving speed of 60 km/h was presented in 2005. This speed was achievable without a major change of the vehicle?s basic design. However, even higher driving speeds will require substantial modifications of the vehicle?s concept and are thus not expected very soon. Since the agricultural tractors are designed mainly for the field work, their driving dynamics characteristics on the road are not always perfect. The high vehicle masses, possible insufficiencies in the construction and interaction of various vehicle components together with the missing rear axle suspension can lead to critical behaviour of the vehicle, especially during high speed cornering. The entire suspension on the rear axle is accomplished by the tyres. Since the agricultural tyres are mainly designed for carrying high loads and generating high draft forces on soft soil, their driving dynamics properties on the road are rather insufficient. They usually have a radial run-out with an amplitude of 1-2 mm. Due to the rather low damping of the agricultural tyres, this rather small run-out can cause vibrations with a quite high amplitude, especially if the excitation is close to the eigenfrequency of the vehicle. Furthermore, the tyre inflation pressure varies between 0.8 and 2.0 bar - which is a relatively large span - making the vehicle setup more difficult. To analyse the driving dynamics of agricultural tractors and to identify possible problems and insufficiencies at an early stage of development simulation models are used. A very important part of a vehicle model is the tyre model. Being the link between the vehicle and the ground, the tyre has a high influence on the vehicle behaviour. It is therefore essential to use an accurate tyre model. Most of the commercially available tyre models today are optimized for passenger car tyres and are thus of limited use for soft and large agricultural tyres. In this doctoral thesis at the University of Hohenheim a dynamic model for agricultural tyres on rigid surfaces was developed ? the Hohenheim Tyre Model. It is a hybrid model since it needs physical parameters like spring and damper coefficients as well as empirically obtained data for the tyre-ground-characteristics. The Hohenheim Tyre Model uses the wheel speeds and the speed of the tyre tread to calculate the deflection velocity and the deflection of the tyre and subsequently uses both values as inputs for spring-damper-elements. The force calculated in these so-called Voigt-Kelvin-Elements is finally used to determine the slip and the slip angle of the wheel. The tyre model was created in MATLAB/Simulink and can be coupled to any multi-body-software. The model allows to calculate the transient tyre behaviour in three dimensions with a low computational effort, which makes it adequate for driving dynamics simulation. It takes the nonlinearities of the tyre into account and calculates the forces for pure longitudinal or lateral slip as well as for combined slip conditions.
Experimentelle Entwicklung einer modellbasierten prädiktiven Regelung für den flexiblen Betrieb von Biogasanlagen
(2023) Dittmer, Celina; Lemmer, Andreas
The transformation of the energy system requires controllable producers due to increasingly decentralised, fluctuating electricity generation from wind turbines and photovoltaics. Biogas plants can make a substantial contribution here by making plant operation more flexible and thus providing electricity as needed. Technical adjustments, such as the expansion of gas storage capacities and CHP output, can compensate for short-term fluctuations. However, in order to be able to shift the potential of electricity generation over longer periods of time, an adapted feed-in strategy is essential. The control of biogas production poses several challenges in practical implementation. First, the conversion of biomass into biogas is a complex process and must be considered individually for each biogas plant. Models developed so far use parameters for all characteristic process phases and influencing variables in order to be able to model anaerobic digestion. In contrast, biogas plants are often only rudimentarily equipped with measurement technology, so that corresponding parameters are not available. In this work, a model-predictive control of biogas plant operation was developed to enable demand-driven electricity generation. The aim was to develop models that are particularly well suited for practical use. Thus, for the first time, a successful application on almost all biogas plants could be possible without or with only minor adaptations to the existing measurement technology. All studies carried out in this thesis are based on a real-world laboratory, the "Unterer Lindenhof". This includes a practical biogas plant as well as an electrical consumption corresponding to that of a village with about 125 inhabitants. In a first step, forecasting models were evaluated to predict the electricity demand of the real-world laboratory over 48 hours in advance. Four models from the field of time series analysis were examined, one TBATS and three different ARIMA models. In an evaluation of 366 forecasts each, all four models performed sufficiently well to provide a set point for biogas plant operation, with average MAPE values of 13-16 %. Further investigations showed that forecasts can also be carried out over a period of up to 14 days without significant losses in forecast quality. In a further step, a model was developed to simulate biogas production. This is also based on time series analysis, or more precisely on a regression model. Thus, it differs significantly from previous developments in this field, which are mostly based on the complex ADM1. It turns out to be very advantageous that the developed simulation model uses as input parameters only historical data of the last four weeks of biogas production and the amount of solid substrates fed in, without considering their composition. The simulation of biogas production over 48 hours in advance is based on correlations resulting from these two data sets. An evaluation of the model over 366 simulations resulted in an average MAPE of 14-18 %. Data from both digesters of the biogas plant were used, which can be considered as independent systems, demonstrating the adaptability of the model. In a third step, the feeding schedule was developed for demand-based biogas production. For each 48 hours in advance, 1500 randomised feeding schedules were calculated. Some constraints were imposed, such as the maximum amount of substrate that is technically possible in the biogas plant. The biogas production expected from the feeding schedules could be calculated using the simulation model. By comparing the simulation with the desired biogas demand profile, the simulation with the least deviations could be determined and the appropriate feeding plan selected and implemented. The entire model predictive control system was used and thoroughly tested in a field trial at the real-world laboratory "Unterer Lindenhof". Over a period of 36 days, an average MAPE of less than 20 % was achieved in comparison between the real biogas production and the desired biogas demand. During the test period, the biogas demand was derived from the predicted electricity demand of the real-world laboratory. The investigations carried out show that the model-predictive control system developed enables demand-oriented electricity generation on full-scale and that, due to the models being very close to practice for the first time, adaptation to almost all biogas plants is possible.
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.
Mähdrescher : VDI-MEG-Kolloquium Landtechnik, Heft 40
(2013) Max-Eyth-Gesellschaft im VDI; Böttinger, Stefan
For intensive discussion of special topics the VDI-MEG colloquia are established since many years. "Combine" colloquia have been realized in turns with Dresden at the University of Hohenheim in 1988, 1997 and 2005. The fast development of grain harvest technologies, the optimization of assemblies, the ease of machine adjustment and the automation of many functions causes the necessity to review the situation and show the prospects for further development.
Models for the representation of ecological systems? The validity of experimental model systems and of dynamical simulation models as to the interaction with ecological systems
(2001) Haag, Daniel; Kaupenjohann, Martin
Models guide the investigation of ecological phenomena and the managemant of man-environment interactions. Based on six papers, this thesis critically examines characteristic features, limitations and the scientific and societal role of experimental model systems (as well-tried instruments of knowledge production) and of dynamical simulation models (as representatives of relatively recent computer models). Experimental model systems are described as materially and conceptually closed systems with a limited number of parameters. They consist of a material component which is encoded into a formal (numerical) system through the measurement of defined parameters. The transfer of statements derived from model systems to natural systems is critically discussed. Dynamical systems - the paradigm for the representation of ecosystems - permit the simultaneous handling of a large number of parameters. Dynamical systems are conceptually closed systems and are based on the notion of an abstract state (focussing on 'being'). I contrast this view with an image of ecosystems as conceptually open systems ('becoming') which emphasizes the evolutionary openness of ecological systems, the internal production of novelty, and the emergence of system level properties. Taking the nitrogen cycle and its human alterations as an example, model concepts and limitations to the derivation of cause-effect-relationships in ecological systems are illustrated. Acknowledging the limited predictive capacity of simulation models and the intrinsic perspectivity of the identification of 'relevant' phenomena and parameters and drawing on new forms of knowledge production (as described by science studies), a modified role for model building and for simulation models - particularly with respect to science for policy - is sketched.
Numerische Modellierung und Simulation der räumlichen und zeitlichen Variabilität von Lachgasemissionen aus Agrarökosystemen
(2005) Huber, Stefan; Doluschitz, Reiner
The aim of this dissertation is to characterize the spatial and temporal variability of nitrous oxide emissions from agroecosystems by means of linking mathematical simulation models to Geographical Information-Systems (GIS). Specifically, this study tries to accomplish a methodological goal and a thematic goal. A general software framework for the linkage of agroecosystem-modells and GIS by employing object-oriented and component-based concepts is developed. As an example for the implementation of this framework, the agroecosystem-modell DNDC, the two-dimensional soil water model SWMS2d, and GIS are integrated to the new model Spatial DNDC. This new model is applied to the study of the spatial and temporal variability of nitrous oxide emissions from agroecosystems at different scales. The simulation of the emissions at 281 independent soil profiles from a 40 ha field in Michigan/USA for nine years shows a large temporal and spatial variability ranging from 0.35 to 4.21 kg N2O-N/ha/a. Except for three years the yearly emissions are always lognormal distributed. While comparing simulated and measured daily emissions cannot be regarded as satisfactorily, it can be shown that the median of the daily N2O-emission rates can be employed as a characteristic measure for the given site. The influence of lateral soil water movement on the emission of N2O is studied by employing SpatialDNDC on a dataset from Scheyern/Bavaria, which comprises measurement data for five sites along hill-slope transect for the year 1997. The simulated daily emission rates are very similar for the five sites and are in good agreement with the measurements. The temporal variability of the daily emission rates is largely shaped by the occurrence of nitrogen fertilization-events and following precipitation events. By looking at the yearly emissions a distinct, downslope-directed gradient can be seen with the highest emission of 6.87 kg N2O-N/ha/a at the highest hill position, and the lowest emission of 6.37 kg N2O-N/ha/a at the lowest hill position. This gradient can be explained by the soil water household which is largely influenced by a dry period in spring. Due to lateral water movement plants growing at lower positions have more water available for early-spring growth leading to higher water extraction during the dry period. Therefore the average soil water content, which is a major impact factor for N2O-emissions in SpatialDNDC, lower at the downslope positions as compared to the upslope positions. The modelling of N2O from agroecosystems in the North-China-Plain can merely be regarded as a test case for application of SpatialDNDC to larger regions and whole nations, respectively, since detailed input and validation data are missing. The three simulation studies show distinctively the two main problems of the regional usage of agroecosystem models: On the one hand detailed input data are missing leaving for the modeller only the option to make simplifying assumptions and thereby introducing great uncertainty into simulation results. On the other hand regional calibration and validation data are missing, which are crucial to the realistic depiction of variability within large study regions.
Optimum schemes for hybrid maize breeding with doubled haploids
(2011) Wegenast, Thilo; Melchinger, Albrecht E.
In hybrid maize breeding, the doubled haploid technique is increasingly replacing conventional recurrent selfing for the development of new lines. In addition, novel statistical methods have become available as a result of enhanced computing facilities. This has opened up many avenues to develop more efficient breeding schemes and selection strategies for maximizing progress from selection. The overall aim of the present study was to compare the selection progress by employing different breeding schemes and selection strategies. Two breeding schemes were considered, each involving selection in two stages: (i) developing DH lines from S0 plants and evaluating their testcrosses in stage one and testcrosses of the promising DH lines in stage two (DHTC) and (ii) early testing for testcross performance of S1 families before production of DH lines from superior S1 families and then evaluating their testcrosses in the second stage (S1TC-DHTC). For both breeding schemes, we examined different selection strategies, in which variance components and budgets varied, the cross and family structure was considered or ignored, and best linear unbiased prediction (BLUP) of testcross performance was employed. The specific objectives were to (1) maximize through optimum allocation of test resources the progress from selection, using the selection gain (ΔG) or the probability to select superior genotypes (P(q)) as well as their standard deviations as criteria, (2) investigate the effect of parental selection, varying variance components and budgets on the optimum allocation of test resources for maximizing the progress from selection, (3) assess the optimum filial generation (S0 or S1) for DH production, (4) compare various selection strategies - sequential selection considering or ignoring the cross and family structure - for maximizing progress from selection, (5) examine the effect of producing a larger number of candidates within promising crosses and S1 families on the progress from selection, and (6) determine the effect of BLUP, where information from genetically related candidates is integrated in the selection criteria, on the progress from selection. For both breeding schemes, the best strategy was to select among all S1 families and/or DH lines ignoring the cross structure. Further, in breeding scheme S1TC-DHTC, the progress from selection increased with variable sizes of crosses and S1 families, i.e., larger numbers of DH lines devoted to superior crosses and S1 families. Parental cross selection strongly influenced the optimum allocation of test resources and, consequently, the selection gain ΔG in both breeding schemes. With an increasing correlation between the mean testcross performance of the parental lines and the mean testcross performance of their progenies, the superiority in progress from selection compared to randomly chosen parents increased markedly, whereas the optimum number of parental crosses decreased in favor of an increased number of test candidates within crosses. With BLUP, information from genetically related test candidates resulted in more precise estimates of their genotypic values and the progress from selection slightly increased for both optimization criteria ΔG and P(q), compared with conventional phenotypic selection. Analytical solutions to enable fast calculations of the optimum allocation of test resources were developed. This analytical approach superseded matrix inversions required for the solution of the mixed model equations. In breeding scheme S1TC-DHTC, the optimum allocation of test resources involved (1) 10 or more test locations at both stages, (2) 10 or fewer parental crosses each with 100 to 300 S1 families at the first stage, and (3) 500 or more DH lines within a low number of parental crosses and S1 families at the second stage. In breeding scheme DHTC, the optimum number of test candidates at the first stage was 5 to 10 times larger, whereas the number of test locations at the first stage and the number of DH lines at the second stage was strongly reduced compared with S1TC-DHTC. The possibility to reduce the number of parental crosses by selection among parental lines is of utmost importance for the optimization of the allocation of test resources and maximization of the progress from selection. Further, the optimum allocation of test resources is crucial to maximize the progress from selection under given economic and quantitative-genetic parameters. By using marker information and BLUP-based genomic selection, more efficient selection strategies could be developed for hybrid maize breeding.
Potentialbewertung effizienzsteigernder Technologien bei Landmaschinen in Verfahrensketten mit Körnerfruchternte
(2023) Meiners, Arwid Steffen
Reducing fuel consumption in agricultural process chains through increased energy efficiency in machine use is effectively achieved through process-oriented approaches. Although European targets for greenhouse gas reduction are increasingly being demanded legislatively and socially, the farmer’s pressure to act is primarily motivated intrinsically due to economic constraints. There are technologies existing on the market that contribute to increasing machine and process efficiency. To this day, however, it is difficult to evaluate their economic use on a farm-specific basis before deciding on investments. The complexity of agricultural process chains encourages and demands comprehensive approaches for both the use and the evaluation of efficiency-increasing technologies and measures. The objective of this research is to develope and apply a proper evaluation method. As a virtual evaluation environment, a machine model is created which can be used to calculate time-related fuel consumption of agricultural machine combinations under the influence of efficiency-increasing technologies. Supplemented by a process model, the consumption of individual process chains and entire crop rotations can be simulated. A modular model topology allows flexible combinations of tractors and implements for process chains with grain crop production. Corresponding simulation models are built and parametrised. The focus is on developing a model for self-propelled harvesters and on parameterising it for application as a combine harvester. As a data basis for the process components, load and performance data are collected in field tests using a state-of-the-art hybrid combine harvester. At the same time this contributes to the general data availability of performance requirements of process components in harvesting operations. In the model application, a potential evaluation of efficiency-increasing technologies and measures, such as optimised traction conditions, driving strategies or reduced intensities in tillage and harvesting, is carried out on a virtual model farm representing typical process chains with grain crop production in the region of South Hanover. Optimisation potentials for three- and five-part crop rotations are established along the individual process steps. Specific recommendations from individual technology analyses are made for efficient use of the machinery in use. As an overall assessment, a potential for reducing fuel consumption of about 26% resulting from optimised machine efficiency can be identified.
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.
Simulating knowledge diffusion in four structurally distinct networks : an agent-based simulation model
(2015) Kudic, Muhamed; Mueller, Matthias; Bogner, Kristina; Buchmann, Tobias
In our work we adopt a structural perspective and apply an agent-based simulation approach to analyse knowledge diffusion processes in four structurally distinct networks. The aim of this paper is to gain an in-depth understanding of how network characteristics, such as path length, cliquishness and the distribution and asymmetry of degree centrality affect the knowledge distribution properties of the system. Our results show – in line with the results of Cowan and Jonard (2007) – that an asymmetric or skewed degree distribution actually can have a negative impact on a network’s knowledge diffusion performance in case of a barter trade knowledge diffusion process. Their key argument is that stars rapidly acquire so much knowledge that they interrupt the trading process at an early stage, which finally disconnects the network. However, our findings reveal that stars cannot be the sole explanation for negative effects on the diffusion properties of a network. In contrast, interestingly and quite surprisingly, our simulation results led to the conclusion that in particular very small, inadequately embedded agents can be a bottleneck for the efficient diffusion of knowledge throughout the networks.
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.
Standard and Shuffled Halton sequences in a Mixed Logit Model
(2008) Staus, Alexander
Modeling consumer choice in different areas has lead to an increase use of discrete choice models. Probit or Multinomial Logit Models are often the base of further empirical research of consumer choice. In some of these models the equations to solve have no closed-form expression. They include multi-dimensional integrals which can not be solved analytically. Simulation methods have been developed to approximate a solution for these integrals. This paper describes the Standard Halton sequence and a modification of it, the Shuffled Halton sequence. Both are simulation methods which can reduce computational effort compared to a random sequence. We compare the simulation methods in their coverage of the multi-dimensional area and in their estimation results using data of consumer choice on grocery store formats.
With all my senses : restorative environments through holistic sensory impressions
(2017) Sona, Brid; Steidle, Anna
Growing awareness of psychological health problems is resulting in various research areas exploring new approaches to fostering personal resources. Restorative Environments Theory (RET) has shown that mundane natural environments support personal resources. Although other restorative environments may exist besides mundane natural environments, their systematic examination is still lacking. In the real world, users experience environments through all their senses. However, most of the recovery research focuses on investigation of single sensory impressions. Thus, concrete insights into how various ambient qualities of an environment may affect users’ perception are still needed. The main aim of this doctoral thesis is to enhance the existing theoretical framework of restorative environments and to give an overview of research while pointing out where more research is needed. Further, the thesis includes identification of restorative environments and their specific ambient qualities. Based on the explored environments, the present research will point out psychological pathways to obtain recommendations for the design of restorative environments. The first research project was an explorative study to identify restorative places and their ambient qualities. In accordance with restoration research, participants described natural outdoor environments which they sought for recovery. In addition, they described indoor environments. Depending on the type of depletion and the environmental setting, specific environments and ambient qualities were evaluated as more important for the restorative potential of the place than others. This explorative research supports theory building and enables creation of restorative environments through holistic sensory impressions. Finally, strengths, limitations and practical implications for designing and improving restorative environments are discussed. The second research project takes up the findings of the first project by simulating sensory-enriched break environments. Based on the impact of holistic sensory impressions, this project is one of the first to reveal the impact of the recovery process of simulated environments on personal resources through congruent sensory impressions. Analyses confirmed that sensory-enriched environments were perceived as more pleasant and more restorative than less enriched environments, which in turn facilitated the recovery of personal resources. The results point out the relevance of holistic sensory impressions to fostering recovery. Implications and limitations of sensory enrichment in break environments are discussed. To broaden generalizability, the third research project comprises three field experiments investigating recovery during break interventions which offered virtual restorative environments with differing degrees of immersion and different types of environments. Building on previous research (Grimshaw, 2014), the third project posited that a higher degree of immersion in the simulated environment increases perceived realism, which becomes apparent in higher positive perceptions and recovery outcomes. Moreover, environments with different degrees of stimulation were anticipated to evoke distinct successful recovery. Previous research had mainly focused on calming environments for recovery. Additionally, this project also tested whether stimulating environments promote recovery outcomes. Results mainly confirmed the proposed hypotheses. The relevance of immersion and the impact of different types of natural environments on recovery are discussed. Overall, the current research emphasizes the impact of holistic sensory impressions in enhancing positive perceptions of the environment and, consequently, various recovery outcomes. The conducted studies uncover the psychological pathway from the processes of sensory perception to environmental recovery perception, followed by recovery outcomes. Beside these theoretical insights, the current research delivers concrete recommendations for designing restorative (virtual) environments in the workplace.