Final Report for "Dynamic friction in magnetized electron coolers for relativistic beams"
Explore the source record for details and available documents.
SEARCH · Engineering Papers
Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.
Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.
Explore the source record for details and available documents.
Explore the source record for details and available documents.
Presentation describes project to develop a framework for access to large datasets (i.e., millions of database objects, dynamically calculated values, or raster datasets that exceed 100s of Megabytes) from smart mobile devices with dynamic network bandwidths.
The Open Energy Data Initiative (OEDI) aims to improve and automate access of high-value energy data sets across the U.S. Department of Energy's (DOE's) programs, offices, and national laboratories. Sponsored by DOE, this platform is being implemented by the National Renewable Energy Laboratory (NREL) to make data actionable and discoverable by researchers and industry to accelerate analysis and advance innovation. Partners at other national laboratories will help utilize the platform for analysis, can be directly involved in determining requirements, and will be resources for providing new datasets that can be shared with the public to expand innovation.
Explore the source record for details and available documents.
Explore the source record for details and available documents.
Explore the source record for details and available documents.
Abstract not provided.
Optimization of environmental restoration efforts at complex groundwater sites involves the development of a conceptual and often numerical flow and transport models. Typically, a limited number of simulations are done to assess the impact of parameter uncertainty, to evaluate remedial alternatives and develop a remedy, or to modify an existing remedy. A limited number of simulations are performed because each simulation can take upwards of several hours per simulation and until now the ability to conduct the 100's to 1000's of simulations needed to derive an optimal remedy was beyond the reach of the everyday practitioner. HGL has developed and implemented new parallel simulation and optimization methods in their software and has successfully deployed applications on high performance Cloud-based computing platforms. This advancement removes the impediment of burdensome and unpredictable runtime requirements these types of projects have typically exhibited using heuristic trial-and-error or even automated serial computation approaches. A parallel numerical solver has been added to the subsurface flow and transport simulator MODFLOW-SURFACT{sup TM} and has demonstrated reductions in solution time by as much as a factor of 9.8. This is accomplished by distributing the numerical computations of every time step over multiple processors. The integrated parallel simulation and optimization method uses the breadth and depth search approach; iteratively producing sets of tens or 100's of candidate solutions that are evaluated concurrently instead sequentially (i.e. one model evaluation at a time). Solutions within 80-100% of the globally optimal solution are regularly found expending only 5-10% of the usual computational effort using this new parallel optimization method (reducing computation effort by 10 to 20 times). Distributing optimal search runs across multiple processors additionally reduces calendar time to solutions. Practitioners evaluating multiple conceptual site models, model calibration by auto-calibration methods and remedial design by heuristics can enjoy significant reductions in model solution time by using the parallel numerical matrix solver in the physics-based simulator. Combining investigation and design analysis with breadth and depth parallel optimization methods, projects at the fringe of practical optimization, along with projects that were beyond the reach of formal optimization methods are now wholly feasible and tractable optimization problems. (authors)
Online monitoring using cloud-based applications presentation. Enabling online monitoring using cloud services will require additional sensors, systems and choices.
Explore the source record for details and available documents.
Explore the source record for details and available documents.
This is a slide deck developed to present to a potential end-user interested in our tool. This is intended to be a presentation resource in lieu of doing a live-demonstration.
The use of clouds to execute high-performance computing (HPC) applications has greatly increased recently. Clouds provide several potential advantages over traditional supercomputers and in-house clusters. The most popular cloud is currently Amazon EC2, which provides fixed-cost and variable-cost, auction-based options. The auction market trades lower cost for potential interruptions that necessitate checkpointing; if the market price exceeds the bid price, a node is taken away from the user without warning. We explore techniques to maximize performance per dollar given a time constraint within which an application must complete. Specifically, we design and implement multiple techniques to reduce expected cost by exploiting redundancy in the EC2 auction market. We then design an adaptive algorithm that selects a scheduling algorithm and determines the bid price. We show that our adaptive algorithm executes programs up to seven times cheaper than using the on-demand market and up to 44 percent cheaper than the best non-redundant, auction-market algorithm. We extend our adaptive algorithm to incorporate application scalability characteristics for further cost savings. In conclusion, we show that the adaptive algorithm informed with scalability characteristics of applications achieves up to 56 percent cost savings compared to the expected cost for the base adaptive algorithm run at a fixed, user-defined scale.
Advanced modeling and simulation has enabled the design of a variety of innovative products and the analysis of numerous complex phenomenon. There are significant barriers to widespread adoption of these tools. In particular, advanced modeling and simulation: (1) is considered complex to use, (2) needs in-house expertise, and (3) requires high capital costs. In this paper, we describe the development of an end-to-end, advanced modeling and simulation cloud platform that encapsulates best practices for scientific computing in the cloud, and demonstrate using Hydra-TH as a prototypical application. As an alternative to traditional advanced modeling and simulation workflows, our Web-based approach simplifies the processes, decreases the need for in-house computational science and engineering experts, and lowers the capital investments. In addition to providing significantly improved, intuitive software, the environment offers reproducible workflows where the full lifecycle of data from input to final analyzed results can be saved, shared, and even published.
The Clouds kernel design was through several design phases and is nearly complete. The object manager, the process manager, the storage manager, the communications manager, and the actions manager are examined.
The Clouds project is well underway to its goal of building a unified distributed operating system supporting the object model. The operating system design uses the object concept of structuring software at all levels of the system. The basic operating system was developed and work is under progress to build a usable system.
Historically, cloud structures, dynamics, and precipitation processes have been observed and measured with sensors from two different spatial resolutions. Laser-based sensors have volume resolutions on the order of 10(exp -4) to 10(exp -2) cubic meters for a 1-s sample. Radar systems operating at wavelengths between 1 and 10 cm have resolutions on the order of 10(exp 4) to 10(exp 7) cubic meters. The resolutions of micro-wave systems depend primarily on the system RF bandwidth and antenna bandwidth. Both resolution regimes were useful in the study of cloud structures and processes - the former for determining resolution on the individual cloud particle scale and the latter for studying the coarse characteristics of cloud dynamics and structure. There are, however, cloud processes and structures that occur on scales that lie between these two regimes: the process of entrainment, where outside air is brought within the cloud boundaries; the mixing of in-cloud particles with different histories; cloud particle coalescence; and ice formation. The use of mm-wave (30- to 300-GHz) radars offers an opportunity to observe cloud processes at these scales and determine their influence on precipitation development, cloud albedos, cloud lifetimes, chemical cycling of tract substances, aircraft icing, and other meteorological phenomena. To determine the usefulness of a 35-GHz radar for observing these precipitation and cloud processes, a research program was initiated. The objectives of this program are to develop a 35-GHz radar, to measure scattering from precipitation and clouds, and to develop a model to compute scattering from clouds using the finite-difference time-domain (FDTD) technique.