Improving skills in rounding off the whole number

This study was conducted to address teaching and learning skills in rounding off a whole number. This study consisted of 15 years 4 students from the Kong Nan Chinese Primary School, Parit Raja, Johor, Malaysia. Initial survey to identify this problem was carried out by analyzing the exercise books and exercises in pre-test. Based on these analyses, a large number of students were not proficient in relevant skills. A ‘q’ technique was introduced as an approach in teaching and learning to help students master the skills of rounding whole numbers. In summary, this technique helps students to remember the sequence of processes and process in rounding numbers. A total of four sessions of teaching and learning activities that take less than an hour have been implemented specifically to help students to master this technique. Results of the implementation of these activities have shown very positive results among the students. Two post tests were carried out to see the effectiveness of techniques and the results shows that 100% of students were able to answer correctly at least three questions correctly. The t-test analysis was clearly showed the effectiveness of ‘q’ technique. This technique also indirectly helps to maintain and increase student interest in learning Mathematics. This is shown with the active involvement of students in answering questions given by the teacher

Energy efficient engine: Preliminary design and integration studies

A mixed exhaust, direct drive fan turbofan configuration was selected from four candidates. This choice was based on its ability to exceed study goals of 12% lower thrust specific fuel consumption and 5% lower direct operating cost by the 1990's with commercially acceptable technical risk and relative mechanical simplicity. The evaluation leading to configuration selection is discussed. Necessary technology advancements are identified and related to the goals

NASA helicopter transmission system technology program

The purpose of the NASA Helicopter Transmission System Technology Program is to improve specific mechanical components and the technology for combining these into advanced drive systems to make helicopters more viable and cost competitive for commerical applications. The history, goals, and elements of the program are discussed

UC Berkeley's Cory Hall: Evaluation of Challenges and Potential Applications of Building-to-Grid Implementation

From September 2009 through June 2010, a team of researchers developed, installed, and tested instrumentation on the energy flows in Cory Hall on the UC Berkeley campus to create a Building-to-Grid testbed. The UC Berkeley team was headed by Professor David Culler, and assisted by members from EnerNex, Lawrence Berkeley National Laboratory, California State University Sacramento, and the California Institute for Energy & Environment. While the Berkeley team mapped the load tree of the building, EnerNex researched types of meters, submeters, monitors, and sensors to be used (Task 1). Next the UC Berkeley team analyzed building needs and designed the network of metering components and data storage/visualization software (Task 2). After meeting with vendors in January, the UCB team procured and installed the components starting in late March (Task 3). Next, the UCB team tested and demonstrated the system (Task 4). Meanwhile, the CSUS team documented the methodology and steps necessary to implement a testbed (Task 5) and Harold Galicer developed a roadmap for the CSUS Smart Grid Center with results from the testbed (Task 5a) and evaluated the Cory Hall implementation process (Task 5b). The CSUS team also worked with local utilities to develop an approach to the energy information communication link between buildings and the utility (Task 6). The UC Berkeley team then prepared a roadmap to outline necessary technology development for Building-to-Grid, and presented the results of the project in early July (Task 7). Finally, CIEE evaluated the implementation, noting challenges and potential applications of Building-to-Grid (Task 8). These deliverables are available at the i4Energy site: http://i4energy.org/

Advanced gearbox technology

An advanced 13,000 HP, counterrotating (CR) gearbox was designed and successfully tested to provide a technology base for future designs of geared propfan propulsion systems for both commercial and military aircraft. The advanced technology CR gearbox was designed for high efficiency, low weight, long life, and improved maintainability. The differential planetary CR gearbox features double helical gears, double row cylindrical roller bearings integral with planet gears, tapered roller prop support bearings, and a flexible ring gear and diaphragm to provide load sharing. A new Allison propfan back-to-back gearbox test facility was constructed. Extensive rotating and stationary instrumentation was used to measure temperature, strain, vibration, deflection and efficiency under representative flight operating conditions. The tests verified smooth, efficient gearbox operation. The highly-instrumented advanced CR gearbox was successfully tested to design speed and power (13,000 HP), and to a 115 percent overspeed condition. Measured CR gearbox efficiency was 99.3 percent at the design point based on heat loss to the oil. Tests demonstrated low vibration characteristics of double helical gearing, proper gear tooth load sharing, low stress levels, and the high load capacity of the prop tapered roller bearings. Applied external prop loads did not significantly affect gearbox temperature, vibration, or stress levels. Gearbox hardware was in excellent condition after the tests with no indication of distress

Chance-Constrained Outage Scheduling using a Machine Learning Proxy

Outage scheduling aims at defining, over a horizon of several months to years, when different components needing maintenance should be taken out of operation. Its objective is to minimize operation-cost expectation while satisfying reliability-related constraints. We propose a distributed scenario-based chance-constrained optimization formulation for this problem. To tackle tractability issues arising in large networks, we use machine learning to build a proxy for predicting outcomes of power system operation processes in this context. On the IEEE-RTS79 and IEEE-RTS96 networks, our solution obtains cheaper and more reliable plans than other candidates