Current Research Projects
Carbon Capture Simulation Initiative
The Carbon Capture Simulation Initiative (CCSI) is a partnership among national laboratories, industry and academic institutions that will develop and deploy state-of-the- art computational modeling and simulation tools to accelerate the commercialization of carbon capture technologies from discovery to development, demonstration, and ultimately the widespread deployment to hundreds of power plants. The CCSI Toolset will provide end users in industry with a comprehensive, integrated suite of scientifically validated models with uncertainty quantification, optimization, risk analysis and decision making capabilities. more..
ASCEM: Advanced Simulation Capability for Environmental Management
The ASCEM: Advanced Simulation Capability for Environmental Management project will bring together significant National Laboratory expertise in environmental and computational systems science to develop an advanced modeling capability for resolving contaminant release, transport, fate, and remediation issues across the EM complex. The multidisciplinary, multi-institutional team will develop an open source modeling platform within a state-of-the-art high performance computing (HPC) framework to produce the next generation simulation software needed to address the prediction, risk reduction, and decision support challenges faced by DOE Environmental Management (EM) sites.
National Soil Carbon Network (NSCN)
The National Soil Carbon Network (NSCN) is an community of scientists from academia, government, and the private sector working towards a large-scale synthesis of soil C research in the United States. The principal goals of the Network are to produce databases, models, and maps that enable users to understand: 1) how much C is stored in U.S. soils, 2) how long this C remains in the soil, and 3) the factors that make this soil C vulnerable to being lost (i.e., emitted to the atmosphere). Overarching these goals is the need for a spatially explicit approach, since measurements of soil C storage, turnover, and vulnerability all vary at spatial scales from several meters to thousands of kilometers, as well as across different depths within an individual soil profile. The NSCN is compiling soil sampling, archiving and analysis protocols, sharing scientific, analytical and logistical infrastructure, synthesizing products beneficial to stakeholders and scientists, developing a community-accessible database. more..
Carbon Flux Data Analysis and Collaboration Infrastructure
FLUXNET is a global network of over 400 carbon flux measurement sensor towers that provide a wealth of long-term carbon, water and energy flux data and metadata. The data from these towers is critical to understanding climate change through cross-site, regional, ecosystem, and global-scale analyses. During this project we have developed a data server to support collaborative analysis of carbon-climate data. That fluxdata.org data server now contains more than 960 site years of ½ hourly carbon flux data from over 250 sites around the world and is relied on by over 110 paper teams which use the server to obtain and analyze FLUXNET data. We support the global FLUXNET synthesis activity. more..
Digital Hydrology and Water Resources Engineering using the California Data Cube
The science of hydrology was formerly driven by the practical needs of the engineering profession where floods, droughts, and water quality could be estimated from prior but limited environmental data collected by various state and federal agencies. Population growth in the United States has placed demands on water resources that can not be met by traditional means and anticipated climate change is casting doubt on the prior assumptions that historical data can be used to predict future conditions. The science of hydrology has shifted to more sensor-based systems for stream flows and spatially distributed meteorological conditions obtained from ground and satellite systems. The sensor data are coupled with weather and climate models at finer and finer spatial resolution. The net result is a vastly increased data collection rate and the generation of model simulations that require storage, retrieval and archiving on a scale not previously contemplated. more..
Center for Enabling Distributed Petascale Science
The SciDAC-funded Center for Enabling Distributed Petascale Science (CEDPS) is focused on enabling high-performance distributed scientific applications to have fast, dependable data placement and the convenient construction of scalable services. CEDPS will also address the important problem of troubleshooting these and other related distributed activities. more..
Stampede: Middleware for Monitoring and Troubleshooting of Large-Scale Applications on National Cyberinfrastructure
Many applications that use large distributed cyberinfrastructure resources involve a large numbers of inter-dependent jobs that are best represented as scientific workflows. For example, astronomers examining the structure of galaxies, bioinformaticians studying the underpinnings of complex diseases, and earthquake scientists simulating the impact of earthquakes in California. Although domain scientists have access to high-performance resources that allow them to scale-up their applications to hundreds of thousands of jobs, the associated tasks of managing these applications, monitoring their progress, and troubleshooting problems as they occur remain difficult. This work provides robust and scalable workflow monitoring services that can be used to track the progress of applications as they are executing on the distributed cyberinfrastructure. New anomaly detection and troubleshooting services are being developed to alert users to problems with the application and cyberinfrastructure services and allow them to quickly navigate and mine the application execution records to locate the source of the problem. more..
ATLAS Software Architecture
The Large Hadron Collider will create almost a billion proton-proton collisions per second at an energy of 14 trillion electron volts. These collisions will take place at four points around a 27-kilometer ring, where the four main LHC experiments‚ ALICE, ATLAS, CMS and LHCb‚Äîare located. ATLAS is one of two general-purpose experiments designed to cover the largest possible range of LHC physics. The largest-volume detector ever constructed, ATLAS is 148 feet long, 82 feet wide and 82 feet high, and weighs about 7,700 tons. more..
Daya Bay Software and Computing
Recent discoveries in neutrino physics have shown that the Standard Model of particle physics is incomplete. The observation of neutrino oscillations has unequivocally demonstrated that the masses of neutrinos are nonzero. The small magnitude of neutrino masses (less than 2 eV) and the surprisingly large size of the two mixing angles thus far measured have provided important clues and constraints to extensions of the Standard Model. The third mixing angle, ?13, is small and has not yet been determined. The Daya Bay collaboration will perform a precision measurement of this mixing angle by searching for the disappearance of electron antineutrinos from the nuclear reactor complex in Daya Bay, China, one of the most prolific sources of antineutrinos in the world. more..
PDG workspace
The Particle Data Group (PDG) is an international collaboration charged with summarizing Particle Physics, as well as related areas of Cosmology and Astrophysics. In 2008, the PDG consisted of 170 authors from 108 institutions in 20 countries. The summaries are published in even-numbered years as a now 1340-page book, the Review of Particle Physics. PDG distributes 16,000 copies of the book. The Review has been called the bible of particle physics; over the years, it has been cited in 30,000 papers. The review is also published and maintained as a fully hyper-linked web site. The computing infrastructure supporting the PDG was conceived and built in the late eighties and although it was modern for its time, it is no longer able to support the many participants in the review and the process of creating the review. We are working with the PDG group to research, design, and build a new interactive workspace that enables all the participants in the review process to collaborate and input data directly into the review infrastructure. more..
Scientific Cloud Computing
Cloud computing is an emerging paradigm for enabling on-demand computing capabilities. The goal is to discover if the Cloud Computing offerings are suitable for running any of the scientific applications currently running on mid-range compute resources. The project is working with a broad range of science disciplines and cloud architectures to evaluate the utility and trade-off of these cloud architectures for different science disciplines and problems.
Knowledge Discovery and Dissemination - BLACKBOOK
The KDD BLACKBOOK is currently undergoing a significant redesign that will change its basic structure. The ACS Department is helping to develop the testing framework for these new components.
Past Research Projects
Open Science Grid
Open Science Grid (www.opensciencegrid.org) (OSG) is a national cyber infrastructure for scientific computing enabling geographically distributed collaborations (virtual organizations) to share and aggregate resources to advance the scale and timeliness of deriving scientific results from massive datasets. Impact of OSG - provides middleware and operational infrastructure for two dozen active virtual organizations (scientific collaborations) to do distributed computing around the U.S. on four dozen active sites consuming an average 20,000 CPU's over the past year. more..
Semantics and Metadata for Ecoinformatics
This project creates tools, techniques, designs and standards on the leading edge of semantics and metadata technologies. Demonstrations are in the area of ecoinformatics (health and the environment). Results are broadly useful in many areas, including energy, defense and intelligence. The focus of the effort is to advance capabilities to link the semantics expressed in concept systems, metadata and data. Example application areas include the semantic web, the use of semantics in scientific models, and more generally, semantic computing. more..
Integrated Modeling and Ontology Project
DOE NA-22 recently initiated planning for multi-lab assessment projects in the area of nuclear proliferation. The Ontology Development sub-team will develop and demonstrate approaches, techniques, methods and processes that utilize emerging technologies for the development of an ontological structure to support assessment and monitoring missions. The core ontology will have an overall structure that can be applied to the nuclear proliferation area, but the semiconductor device manufacturing industry will serve as a demonstration context with content that is not classified. LBNL is developing an initial ontology which will be released to successively larger audiences and iteratively developed as comments are received. more..
On-Demand Overlays for Scientific Applications
Scientific computations and collaborations increasingly rely on the network to provide high-speed data transfer, dissemination of results, access to instruments, support for computational steering, etc. Networks with redundant high-speed paths need algorithms to effectively allocate bandwidth across multiple paths for a single application. This capability is required for two important communication classes within the DOE scientific community: large point-to-point transfers and periodic data dissemination from a single sender to multiple receivers. The overall goal of this project was to perform the research and development necessary to create proof-of-concept on-demand overlays for scientific applications that make efficient and effective use of the available network resources. more..
Supernova Factory
The Nearby Supernova Factory (SNfactory) is an experiment to develop Type Ia supernovae as tools to measure the expansion history of the Universe and explore the nature of Dark Energy. It is the largest data volume supernova search currently in operation. The SNfactory is an international collaboration between several groups in the United States and France. more..
Deep Sky
Deep Sky is an astronomical image database of unprecedented depth, temporal breadth, and sky coverage. Image data are gathered from the Near Earth Asteroid Tracking (NEAT) project from the 3-CCD and Quest112-CCD cameras on the Samuel Oschin telescope at the Palomar Observatory in San Diego County, California. Containing a total of eleven million images, or 70 terabytes of image data, Deep Sky covers nearly the entire northern sky. more..
Wide Field Infrared Survey Telescope (WFIRST)
The goal of the WFIRST Mission is to explore the properties of dark energy and measure how cosmic expansion has changed over time. The WFIRST is a wide-field-of-view near-infrared imaging and low-resolution spectroscopy observatory operating in space, allowing scientists to study the cosmic acceleration using multiple techniques and extrasolar planets. WFIRST is a partnership between NASA and the DOE. The two agencies will work together to develop the science and the instrumentation to carry out the space-based dark energy investigation. Both NASA and DOE will participate in data analysis and science operations.
IceCube Data Acquisition
IceCube is an NSF funded, international collaboration building a high-energy neutrino detector at the South Pole. Neutrino's are detected in the clear deep ice below the South Pole via digital optical modules which send data to a surface counting house wherein a data-acquisition system processes the raw data through triggering algorithms into data files. These data files are further processed and filtered then sent north via satellite links for further physics analysis. The goal of the project is to gain a better understanding of the Universe via high-energy neutrinos. The detector is currently 2/3rd complete.
BOSS: Baryon Oscillation Spectroscopic Survey
The BOSS: Baryon Oscillation Spectroscopic Survey will map out the baryon acoustic oscillation (BAO) signature with unprecedented accuracy and greatly improve the constraints on the acceleration of the expansion rate of the Universe. The BOSS survey will use all of the dark and grey time at the Apache Point Observatory (APO) 2.5-m telescope for five years from 2009-2014, as part of Sloan Digital Sky Survey III.
Geospatial Image Verification and Validation
GSV is a project to create the theory, develop the methodology, and produce imagery for verifying and validating geospatial image processing algorithms. Geospatial imagery plays an important role in the detection and characterization of nuclear weapons proliferation. The amount of data produced by existing geospatial sensors overwhelms the abilities of human analysts, and future sensing capabilities will add to the torrent of data. The sheer magnitude of geospatial imagery has driven the requirements for automated image analysis, and subsequently, driven the development of geospatial image analysis algorithms. As the sophistication of these algorithms has increased, so has the need to verify and validate (V and V) the performance of the algorithms.