84,608 research outputs found
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High-Performance Integrated Window and FaƧade Solutions for California
The researchers developed a new generation of high-performance faƧade systems and supporting design and management tools to support industry in meeting Californiaās 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 faƧade with minimal energy requirements. (3) A daylight-redirecting louver system was prototyped to redirect sunlight 15ā40 feet from the window. Simulations estimated that lighting energy use could be reduced by 35ā54 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 faƧade 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 Californiaās clean energy goals require making a fundamental shift from todayās ad-hoc assemblages of static components to turnkey, intelligent, responsive, integrated building faƧade systems. These systems offered significant reductions in energy use, peak demand, and operating cost in California
Design of a high power production target for the Beam Dump Facility at CERN
The Beam Dump Facility (BDF) project is a proposed general-purpose facility
at CERN, dedicated to beam dump and fixed target experiments. In its initial
phase, the facility is foreseen to be exploited by the Search for Hidden
Particles (SHiP) experiment. Physics requirements call for a pulsed 400 GeV/c
proton beam as well as the highest possible number of protons on target (POT)
each year of operation, in order to search for feebly interacting particles.
The target/dump assembly lies at the heart of the facility, with the aim of
safely absorbing the full high intensity Super Proton Synchrotron (SPS) beam,
while maximizing the production of charmed and beauty mesons. High-Z materials
are required for the target/dump, in order to have the shortest possible
absorber and reduce muon background for the downstream experiment. The high
average power deposited on target (305 kW) creates a challenge for heat
removal. During the BDF facility Comprehensive Design Study (CDS), launched by
CERN in 2016, extensive studies have been carried out in order to define and
assess the target assembly design. These studies are described in the present
contribution, which details the proposed design of the BDF production target,
as well as the material selection process and the optimization of the target
configuration and beam dilution. One of the specific challenges and novelty of
this work is the need to consider new target materials, such as a molybdenum
alloy (TZM) as core absorbing material and Ta2.5W as cladding.
Thermo-structural and fluid dynamics calculations have been performed to
evaluate the reliability of the target and its cooling system under beam
operation. In the framework of the target comprehensive design, a preliminary
mechanical design of the full target assembly has also been carried out,
assessing the feasibility of the whole target system.Comment: 17 pages, 18 figure
A Parallel General Purpose Multi-Objective Optimization Framework, with Application to Beam Dynamics
Particle accelerators are invaluable tools for research in the basic and
applied sciences, in fields such as materials science, chemistry, the
biosciences, particle physics, nuclear physics and medicine. The design,
commissioning, and operation of accelerator facilities is a non-trivial task,
due to the large number of control parameters and the complex interplay of
several conflicting design goals. We propose to tackle this problem by means of
multi-objective optimization algorithms which also facilitate a parallel
deployment. In order to compute solutions in a meaningful time frame a fast and
scalable software framework is required. In this paper, we present the
implementation of such a general-purpose framework for simulation-based
multi-objective optimization methods that allows the automatic investigation of
optimal sets of machine parameters. The implementation is based on a
master/slave paradigm, employing several masters that govern a set of slaves
executing simulations and performing optimization tasks. Using evolutionary
algorithms as the optimizer and OPAL as the forward solver, validation
experiments and results of multi-objective optimization problems in the domain
of beam dynamics are presented. The high charge beam line at the Argonne
Wakefield Accelerator Facility was used as the beam dynamics model. The 3D beam
size, transverse momentum, and energy spread were optimized
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Photovoltaic and Behind-the-Meter Battery Storage: Advanced Smart Inverter Controls and Field Demonstration
Project alliancing at National Museum of Australia: Collaborative process
Project alliancing is a new alternative to traditional project delivery systems, especially in the commercial building sector. The Collaborative Process is a theoretical model of people and systems characteristics that are required to reduce the adversarial nature of most construction projects. Although developed separately, both are responses to the same pressures. Project alliancing was just used successfully to complete the National Museum of Australia. This project was analyzed as a case study to determine the extent to which it could be classified as a ācollaborative projectā. Five key elements of The Collaborative Process were reviewed and numerous examples from the management of this project were cited that support the theoretical recommendations of this model. In the case of this project, significant added value was delivered to the client and many innovations resulted from the collective work of the parties to the contract. It was concluded that project alliances for commercial buildings offer many advantages over traditional project delivery systems, which are related to increasing the levels of collaboration among a project management team
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Integrated Dynamic Facade Control with an Agent-based Architecture for Commercial Buildings
Dynamic faƧades have significant technical potential to minimize heating, cooling, and lighting energy use and peak electric demand in the perimeter zone of commercial buildings, but the performance of these systems is reliant on being able to balance complex trade-offs between solar control, daylight admission, comfort, and view over the life of the installation. As the context for controllable energy-efficiency technologies grows more complex with the increased use of intermittent renewable energy resources on the grid, it has become increasingly important to look ahead towards more advanced approaches to integrated systems control in order to achieve optimum life-cycle performance at a lower cost. This study examines the feasibility of a model predictive control system for low-cost autonomous dynamic faƧades. A system architecture designed around lightweight, simple agents is proposed. The architecture accommodates whole building and grid level demands through its modular, hierarchical approach. Automatically-generated models for computing window heat gains, daylight illuminance, and discomfort glare are described. The open source Modelica and JModelica software tools were used to determine the optimum state of control given inputs of window heat gains and lighting loads for a 24-hour optimization horizon. Penalty functions for glare and view/ daylight quality were implemented as constraints. The control system was tested on a low-power controller (1.4 GHz single core with 2 GB of RAM) to evaluate feasibility. The target platform is a low-cost ($35/unit) embedded controller with 1.2 GHz dual-core cpu and 1 GB of RAM. Configuration and commissioning of the curtainwall unit was designed to be largely plug and play with minimal inputs required by the manufacturer through a web-based user interface. An example application was used to demonstrate optimal control of a three-zone electrochromic window for a south-facing zone. The overall approach was deemed to be promising. Further engineering is required to enable scalable, turnkey solutions
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