Stochastic models of road geometry and wind condition for vehicle energy management and control

Modeling and simulation is commonly used to improve vehicle performance, to optimize vehicle system design, and to reduce vehicle development time. Vehicle performances can be affected by environmental conditions and driver behavior factors, which are often uncertain and immeasurable. To incorporate the role of environmental conditions in the modeling and simulation of vehicle systems, both real and artificial data are used. Often, real data are unavailable or inadequate for extensive investigations. Hence, it is important to be able to construct artificial environmental data whose characteristics resemble those of the real data for modeling and simulation purposes. However, to produce credible vehicle simulation results, the simulated environment must be realistic and validated using accepted practices. This paper proposes a stochastic model that is capable of creating artificial environmental factors such as road geometry and wind conditions. In addition, road geometric design principles are employed to modify the created road data, making it consistent with the real-road geometry. Two sets of real-road geometry and wind condition data are employed to propose probability models. To justify the distribution goodness of fit, Pearson's chi-square and correlation statistics have been used. Finally, the stochastic models of road geometry and wind conditions (SMRWs) are developed to produce realistic road and wind data. SMRW can be used to predict vehicle performance, energy management, and control strategies over multiple driving cycles and to assist in developing fuel-efficient vehicles.

Teaching 3-D geometry - the multi representational way

Sonja Kalbitzer and Esther Loong provide an excellent range of activities that promote geometric thinking through the exploration of three-dimensional objects. They also provide some discussion on assessing the tasks and providing student feedback.

The constructional geometry of early Javanese temples

The early development of Hindu Javanese architecture can be traced through interpretation of epigraphs, archaeological excavations, and comparison of extant temples with other traditions. However, while many scholars have speculated on connections between Javanese Hindu temples and presumed antecedents in India, these have been made on the basis of visual comparison and epigraphic interpretations. No Indian temple has been conclusively shown to be a model for the earliest Javanese temples. Archaeologist and temple historian Michael Meister has shown in his analysis of the geometric composition of early Hindu temples in South Asia how a ritual sixty-four square mandala was the geometric basis of temple construction during the formative period (fifth to eighth century) of the Indian architectural tradition. Working from an understanding of temple construction sequence as well as their ritual underpinnings, Meister found that the sixtyfour square mandala's dimensions correlate closely to the constructed dimensions at the level of the vedibandha (which corresponds with the plan level of the sanctuary threshold). Furthermore, he shows how the horizontal profile of the cella depends on the number of offsets and the proportional relationships between ech offset based on the subdivision of the sixty-four square grid. The authors have investigated whether a similar compositional basis can be found for the earliest Javanese temples on the Dieng Plateau in the highlands of central Java, despite differences in architectonic and symbolic expression. The analysis of relationships between ritual geometry and actual temple layouts for these buildings has the potential to furthering our understanding of the connections between Hindu temples in Java and those in India.

Geometry of compensatory feeding and water consumption in Drosophila melanogaster

Feeding behaviour is an expression of an animal’s underlying nutritional strategy. The study of feeding decisions can hence delineate nutritional strategies. Studies of Drosophila melanogaster feeding behaviour have yielded conflicting accounts, and little is known about how nutrients affect feeding patterns in this important model species. Here, we conducted two experiments to characterize nutrient prioritization and regulation. In a choice experiment, we allowed female flies to self-regulate their intake of yeast, sucrose and water by supplying individual flies with three microcapillary tubes: one containing only yeast of varying concentrations, another with just sucrose of varying concentrations, and the last with just water. Flies tightly regulated yeast and sucrose to a constant ratio at the expense of excess water intake, indicating that flies prioritize macronutrient regulation over excess water consumption. To determine the relative importance of yeast and sucrose, in a no-choice experiment, we provided flies with two microcapillary tubes: the first with one of the 28 diets varying in yeast and sucrose content and the other with only water. Flies increased total water intake in relation to yeast consumption but not sucrose consumption. Additionally, flies increased diet intake as diet concentration decreased and as the ratio of sugar to yeast equalized. Using a geometric scaling approach, we found that the patterns of diet intake can be explained by flies prioritizing protein and carbohydrates equally and by the lack of substitutability between the nutrients. We conclude by illustrating how our results harmonize conflicting results in the literature once viewed in a two-dimensional diet landscape.

A discrete simulation approach to spatial allocation of commodity production for revenue optimisation over a local region

A simulation approach is described for the spatial allocation of crops across a region in order to maximise total revenue. The model uses inputs from GIS-based land suitability analysis to provide data on yields for a range of commodities, where the land suitability for the crops can be determined by either biophysical models or multi-criteria analysis. The objective of the study was to gain some indication of the magnitude of improvement possible in revenue, based on the convergence results for the optimisation (subject to estimated production quantities and market prices). The basic structure of the model allows for scaling up to larger problems with additional inputs and finer cell resolution. The software produces a visualisation of crop spatial allocation across the region and is compatible with statistical uncertainty analysis. The results of model simulations revealed a significant increase in revenue is possible using this approach and, when projected over the full region, suggests the possibility of significant economic benefits.