simulationmodels is often very complex and time-consuming. Thus, simplified methods that generate calibrated building energy simulationmodels can be beneficial. In this context, a simplified approach to calibrate building energy models based on collected
This research aims at demonstrating techniques in complex dynamic building energy simulation methods that greatly reduce the otherwise very time-consuming - in particular cases even week-long - computation time of simulation models, however marginal difference arises in the energy results of the simulations. Different test simulations were created to examine how to simplify the models without altering the energy and comfort results, which lead to reduce also the working hours spent on building the model. The building physics behavior of the zones, heating and cooling equipment in the complex model were studied and tested to understand how those can be used, merged or simplified in order to speed up both computation time and model building phase. The IDA ICE complex dynamic building energy simulation program offers two methods - periodic and dynamic - for calculation, which were compared in this program. Test simulations provide information about possible differences between the results of these calculation methods, in order to define the appropriate use of these methods.
The paper introduces a simulation, which was developed by Michael Krassa to model the opinion contagion. Krassa developed his model by using the theory of the spiral of silence that says that the perception of the public opinion influences the opinion assertion of the people and the threshold models that show how much support one person needs for the public assertion of his opinion. With the help of these relationships Krassa integrated the social networks in his model. We applied Krassa's mathematical model to two cases, the parliamentary elections of 2002 and the EU-parliamentary elections of 2004 in Hungary. We used hypothetical thresholds to examine the data because the actual threshold values are not known. The results of the simulation show that it can happen that we measure the minority opinion to be higher than the real distribution of the opinions as a consequence of the different distribution of the threshold values of the opinion assertion. This can be one explanation of the wrong electoral forecast. The problem is that the model helps little to give a better forecast because we have no data about the threshold values and we do not know the point where the dynamics of the opinion contagion stands at the time of the survey.
The practical implementation of precision crop production nowadays is becoming more and more widespread. Numerous experiments and farmers’ practical experiences verify the positive impacts of precision nutrient supply on farming. Precision weed control started to spread later, partly due to technical difficulties, partly to the lack of necessary software support that was developed later. The introduction of a new technology requires complex farm-management decisions, including the consideration of economic correlations (costs-yield-income) as well as high-level skills and significant investments from the farmer. These investments can be returned from the income surplus realized through increasing yields and decreasing farming costs. Extra income can also come from the decreasing material costs which, however, do not necessarily compensate the extra costs of implementing the new technology and depends very much on the utilization of savings from different herbicide doses used for the treatment of plots, considering the soil qualities. This study, utilising the data of a technological experiment carried out in Hungary, presents the results of a stochastic simulation model developed with the adaptation of finite element method. The examination was executed at sub-plot level, dividing the plots into small parcels. Our aim was to examine the impact of precision nutrient application and differentiated spraying of herbicides on production costs and yield, as well as the impact of changes on gross margin (income) and the returns on technological development.
We approximated the influence of global climate change on the energy consumption of maize by a simulation model in Keszthely, referring to the average July weather. The period of 1961–1990 was considered as the basic run. We quantified the changes of the close past on the basis of the decade between 1997 and 2006. The other 6 scenarios were elaborated on the one hand by downscaling the IPCC (2007) report (A2 and B2), on the other hand by taking into account a more serious weather change. At determining plant and soil characteristics of the individual scenarios we applied the principle of analogy being extensively used in meteorological practice; in this method we selected the values of that year from the observation data series of almost 30 years that were the closest to the year to be simulated. The ratio of latent heat decreased by 4.8% only at doubling CO
concentration. The largest difference in the ratio of sensible and latent heat was in the case of the run containing the highest warming up and largest precipitation decrease, where the ratio of latent heat increased by 8.8%.One of the causes of global warming is the raised CO
concentration narrowed the stoma openings by 14.3% in itself; it is the quantified value of the positive impact of global warming on plant evaporation, referring to Keszthely. Warming up over 6 °C raised the latent heat compared to the basic run in a statistically justifiable way in the case of each scenario; according to this, in Keszthely, assuming an average July, even in the case of a temperature rise of 6 °C there are some humidity reserves that can be used for transpiration by maize plant. Precipitation loss of 30% associated with warming up of 9 °C, however, reduced this reserve to a minimum. In our opinion, water seems to be the bottleneck of the future; farmers have to prepare to face the lack of water, even in the case if nowadays the forecast of precipitation changes is rather volatile.
Authors:Mohammad Reza Ganjali Bonjar, Kristóf Roland Horváth, Bálint Baranyai, and István Kistelegdi
facades' most advantageous, orientation dependent WWR. The simulationmodel was elaborated in a former study, consisting of 30 climate zones in “Cube A”, 49 thermal blocks in “Cube B” and 71 rooms in “Cube C”. All HVAC systems are modeled identically to
Matthews, R., Stephens, W., Hess, T., Middleton, T., Graves, A. 2002: Applications of crop/soil simulationmodels in tropical agricultural systems. Adv. in Agronomy , 76 , 31-124.
Applications of crop/soil simulationmodels in
Authors:Viktória Kállai, Gábor L. Szepesi, and Péter Mizsey
(in this case the heat flow of the reboiler was that) [ 17 ]. 3 Dynamic simulationmodels and influences of the used disturbances 3.1 First investigated dynamic simulationmodel The dynamic models were also made with the Unisim Design process simulator
Harnos, N., Erdélyi, É. (2008): Alkalmazkodási stratégiák őszi búza termelékenységének fenntartásához szimulációs modellek használatával. (Adaptation strategies for sustaining the productivity of winter wheat using simulationmodels.) pp. 309–328. In