3,332 research outputs found
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Photovoltaic and Behind-the-Meter Battery Storage: Advanced Smart Inverter Controls and Field Demonstration
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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/
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High-Performance Integrated Window and Façade Solutions for California
The researchers developed a new generation of high-performance façade systems and supporting design and management tools to support industry in meeting California’s greenhouse gas reduction targets, reduce energy consumption, and enable an adaptable response to minimize real-time demands on the electricity grid. The project resulted in five outcomes: (1) The research team developed an R-5, 1-inch thick, triplepane, insulating glass unit with a novel low-conductance aluminum frame. This technology can help significantly reduce residential cooling and heating loads, particularly during the evening. (2) The team developed a prototype of a windowintegrated local ventilation and energy recovery device that provides clean, dry fresh air through the façade with minimal energy requirements. (3) A daylight-redirecting louver system was prototyped to redirect sunlight 15–40 feet from the window. Simulations estimated that lighting energy use could be reduced by 35–54 percent without glare. (4) A control system incorporating physics-based equations and a mathematical solver was prototyped and field tested to demonstrate feasibility. Simulations estimated that total electricity costs could be reduced by 9-28 percent on sunny summer days through adaptive control of operable shading and daylighting components and the thermostat compared to state-of-the-art automatic façade controls in commercial building perimeter zones. (5) Supporting models and tools needed by industry for technology R&D and market transformation activities were validated. Attaining California’s clean energy goals require making a fundamental shift from today’s ad-hoc assemblages of static components to turnkey, intelligent, responsive, integrated building façade systems. These systems offered significant reductions in energy use, peak demand, and operating cost in California
Recent Developments in Cultural Heritage Image Databases: Directions for User-Centered Design
published or submitted for publicatio
Telescience Testbed Pilot Program
The Telescience Testbed Pilot Program is developing initial recommendations for requirements and design approaches for the information systems of the Space Station era. During this quarter, drafting of the final reports of the various participants was initiated. Several drafts are included in this report as the University technical reports
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FABRIC: A National-Scale Programmable Experimental Network Infrastructure
FABRIC is a unique national research infrastructure to enable cutting-edge and exploratory research at-scale in networking, cybersecurity, distributed computing and storage systems, machine learning, and science applications. It is an everywhere-programmable nationwide instrument comprised of novel extensible network elements equipped with large amounts of compute and storage, interconnected by high speed, dedicated optical links. It will connect a number of specialized testbeds for cloud research (NSF Cloud testbeds CloudLab and Chameleon), for research beyond 5G technologies (Platforms for Advanced Wireless Research or PAWR), as well as production high-performance computing facilities and science instruments to create a rich fabric for a wide variety of experimental activities
Computing and data processing
The applications of computers and data processing to astronomy are discussed. Among the topics covered are the emerging national information infrastructure, workstations and supercomputers, supertelescopes, digital astronomy, astrophysics in a numerical laboratory, community software, archiving of ground-based observations, dynamical simulations of complex systems, plasma astrophysics, and the remote control of fourth dimension supercomputers
Managing big data experiments on smartphones
The explosive number of smartphones with ever growing sensing and computing capabilities have brought a paradigm shift to many traditional domains of the computing field. Re-programming smartphones and instrumenting them for application testing and data gathering at scale is currently a tedious and time-consuming process that poses significant logistical challenges. Next generation smartphone applications are expected to be much larger-scale and complex, demanding that these undergo evaluation and testing under different real-world datasets, devices and conditions. In this paper, we present an architecture for managing such large-scale data management experiments on real smartphones. We particularly present the building blocks of our architecture that encompassed smartphone sensor data collected by the crowd and organized in our big data repository. The given datasets can then be replayed on our testbed comprising of real and simulated smartphones accessible to developers through a web-based interface. We present the applicability of our architecture through a case study that involves the evaluation of individual components that are part of a complex indoor positioning system for smartphones, coined Anyplace, which we have developed over the years. The given study shows how our architecture allows us to derive novel insights into the performance of our algorithms and applications, by simplifying the management of large-scale data on smartphones
DIDET: Digital libraries for distributed, innovative design education and teamwork. Final project report
The central goal of the DIDET Project was to enhance student learning opportunities by enabling them to partake in global, team based design engineering projects, in which they directly experience different cultural contexts and access a variety of digital information sources via a range of appropriate technology. To achieve this overall project goal, the project delivered on the following objectives: 1. Teach engineering information retrieval, manipulation, and archiving skills to students studying on engineering degree programs. 2. Measure the use of those skills in design projects in all years of an undergraduate degree program. 3. Measure the learning performance in engineering design courses affected by the provision of access to information that would have been otherwise difficult to access. 4. Measure student learning performance in different cultural contexts that influence the use of alternative sources of information and varying forms of Information and Communications Technology. 5. Develop and provide workshops for staff development. 6. Use the measurement results to annually redesign course content and the digital libraries technology. The overall DIDET Project approach was to develop, implement, use and evaluate a testbed to improve the teaching and learning of students partaking in global team based design projects. The use of digital libraries and virtual design studios was used to fundamentally change the way design engineering is taught at the collaborating institutions. This was done by implementing a digital library at the partner institutions to improve learning in the field of Design Engineering and by developing a Global Team Design Project run as part of assessed classes at Strathclyde, Stanford and Olin. Evaluation was carried out on an ongoing basis and fed back into project development, both on the class teaching model and the LauLima system developed at Strathclyde to support teaching and learning. Major findings include the requirement to overcome technological, pedagogical and cultural issues for successful elearning implementations. A need for strong leadership has been identified, particularly to exploit the benefits of cross-discipline team working. One major project output still being developed is a DIDET Project Framework for Distributed Innovative Design, Education and Teamwork to encapsulate all project findings and outputs. The project achieved its goal of embedding major change to the teaching of Design Engineering and Strathclyde's new Global Design class has been both successful and popular with students
Remote sensing information sciences research group
Research conducted under this grant was used to extend and expand existing remote sensing activities at the University of California, Santa Barbara in the areas of georeferenced information systems, matching assisted information extraction from image data and large spatial data bases, artificial intelligence, and vegetation analysis and modeling. The research thrusts during the past year are summarized. The projects are discussed in some detail
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