Comparison of Computational Approaches for Rapid Aerodynamic Assessment of Small UAVs

Computational Fluid Dynamic (CFD) methods were used to determine the basic aerodynamic, performance, and stability and control characteristics of the unmanned air vehicle (UAV), Kahu. Accurate and timely prediction of the aerodynamic characteristics of small UAVs is an essential part of military system acquisition and air-worthiness evaluations. The forces and moments of the UAV were predicted using a variety of analytical methods for a range of configurations and conditions. The methods included Navier Stokes (N-S) flow solvers (USM3D, Kestrel and Cobalt) that take days to set up and hours to converge on a single solution; potential flow methods (PMARC, LSAERO, and XFLR5) that take hours to set up and minutes to compute; empirical methods (Datcom) that involve table lookups and produce a solution quickly; and handbook calculations. A preliminary aerodynamic database can be developed very efficiently by using a combination of computational tools. The database can be generated with low-order and empirical methods in linear regions, then replacing or adjusting the data as predictions from higher order methods are obtained. A comparison of results from all the data sources as well as experimental data obtained from a wind-tunnel test will be shown and the methods will be evaluated on their utility during each portion of the flight envelope

Experience with Process Modeling in the Marvel Software Development Environment Kernel

We have been working for several years on rule-based process modeling and the implementation of such models as part of the foundation for software development environments. We have defined a kernel, called MARVEL, for such an architecture and implemented several successive versions of the kernel and several small environments using the kernel. We have evaluated our results to date, and discovered several significant flaws and delineated several important open problems. Although the details are specific to rule-based process modeling, we believe that our insights will be valuable to other researchers and developers contemplating process modeling mechanisms

SMILE/ MARVEL: Two Approaches to Knowledge-Based Programming Environments

This technical report consists of three related papers in the area of intelligent assistance for software development and maintenance. Intelligent Assistance without Artificial Intelligence describes SMILE, a software engineering environment that assists teams of programmers without using AI technology. An Architecture for Intelligent Assistance in Software Development presents an AI approach to generalizing the capabilities of SMILE. Granularity Issues in a Knowledge-Based Programming Environment briefly describes MARVEL, an intelligent assistant based on this AI approach, and compares it to SMILE

Fifth graders' perceptions of mobile phones and GIS technology

The era of M-learning, specifically the use of mobile phones, has been hardly noticeable in elementary schools. GIS technology is also rarely implemented there. In this study, 5th grade students' perceptions of the use of GIS technology through mobile phones were examined as part of an environmental education program designed to help preserve endangered species. The results show that the students provided special, valuable, critical and mature perspectives on the advantages and disadvantages of using mobile phones as part of the innovative pedagogy they apply in school. The use of the mobile phone and the new application as part of M-Learning made it easier for most students to create authentic learning, that is, learning focused on problems in the real world, and included a project of relevance and interest to the learners. The process of learning through mobile phones and GIS technology, which combined the creative use of teaching methods unfamiliar to students, focused on and was adapted to the learners' abilities, offering a diagnosis and constructive guidance based on success and community. In conclusion, 5th grade students testified that their elementary school could enter the M-Learning era by integrating mobile phones and adopting a student-centered learning approach

Five years of designing wireless sensor networks in the Doñana Biological Reserve (Spain): an applications approach

Wireless Sensor Networks (WSNs) are a technology that is becoming very popular for many applications, and environmental monitoring is one of its most important application areas. This technology solves the lack of flexibility of wired sensor installations and, at the same time, reduces the deployment costs. To demonstrate the advantages of WSN technology, for the last five years we have been deploying some prototypes in the Doñana Biological Reserve, which is an important protected area in Southern Spain. These prototypes not only evaluate the technology, but also solve some of the monitoring problems that have been raised by biologists working in Doñana. This paper presents a review of the work that has been developed during these five years. Here, we demonstrate the enormous potential of using machine learning in wireless sensor networks for environmental and animal monitoring because this approach increases the amount of useful information and reduces the effort that is required by biologists in an environmental monitoring task