35. ADVANCED COMPUTATIONAL METHODS FOR APPLIED SCIENCES AND ENGINEERING

The Office of Science (SC) supports fundamental research programs in basic energy sciences, biological and environmental sciences, and computational science.  SC manages this research portfolio through six interdisciplinary program offices:  Advanced Scientific Computing Research (ASCR), Basic Energy Sciences (BES), Biological and Environmental Research (BER), Fusion Energy Sciences (FES), High Energy Physics (HEP), Nuclear Physics (NP), and Nuclear Energy and Technology (NE).  Researchers in these areas have achieved key scientific insights in a number of areas of national importance; however, many challenges in applied sciences and engineering are now facing DOE programs that require advanced modeling and simulation capabilities on petascale computers.  Another challenge facing DOE programs is driven by the need for capture, storage, transmission, sharing and analysis of large-scale experimental and observational data, as well as data from simulations.  This topic is seeking applications that fully integrate ASCR’s applied mathematics, computer science, and computational science in the areas of physical, biological and environmental sciences, and nuclear energy to solve practical problems at the petascale level, and a new generation of data management and knowledge discovery tools for the large data sets obtained from large experimental facilities and from high end simulations. Grant applications are sought that:  (1) Address obtaining significant insight into, or actually solving challenging problems of national engineering significance related to DOE missions through computational science; and (2) Integrate computational engineering with discipline-driven applications and technologies through teaming and partnerships with computer scientists and applied mathematicians.  These activities are supported by a Scientific Computing Hardware Infrastructure that will evolve to meet the needs of the science programs.  Computing allocation in SC at the National Energy Research Scientific Computing Center (NERSC) and the National Leadership Computing Facilities (NLCF) at Oak Ridge National Laboratory and Argonne National Laboratory could be made available to applications that require stable computing facilities.  Grant applications must clearly identify domain-specific applied science problems and the corresponding computational science tools and methods to be used.  Grant applications are sought only in the following subtopics:

a. Computational Methods for Nuclear Energy and Technology—Nuclear power provides over 20 percent of the U.S. electricity supply without emitting harmful air pollutants, including those that may cause adverse global climate changes.  New advanced computational methods algorithms are needed to address specific modeling and simulation issues that affect the future deployment of nuclear energy in current and future reactor designs.  This subtopic addresses key advanced computational methods needed for nuclear analyses and improvement in nuclear reactor technology.  Grant applications focusing on the application of computational methods to nuclear energy are sought by the Office of Advanced Scientific Computing Research and the Office of Nuclear Energy.  Improvements and advances are needed for simulating reactor systems and component technologies that ultimately would be used in the design, construction, or operation of existing and future nuclear power plants, advanced fast reactors, and Generation IV nuclear power systems [see references].  Grant applications are sought for advanced computational methods that involve advanced reactor/core computer simulations sought for nuclear energy technology including:  (a) reactor/core computer simulation methods for existing light water reactor designs; (b) advanced reactor design model code development; coupled/parallel thermal-hydraulic-reactor physics tools; safety and performance evaluation methods and engineering calculations for new Generation IV reactor designs, reactors, major reactor components, and reactor core and fuel assemblies; (c) ab initio nuclear cross section/ nuclear data development methods, for Generation IV and GNEP reactor designs; and (d) advanced graphic user-interfaces (GUIs) that use existing nuclear computer codes and simulation methods for large-scale and petascale computers.  Grant applications that address the following areas of investigation are NOT of interest and will be declined:  generalized thermal-hydraulics analysis (e.g. CFD or two-fluid codes) and probabilistic risk assessment tools or methods.

Questions – contact Madeline Feltus, NE Office (Madeline.Feltus@nuclear.energy.gov) or Thomas Ndousse-Fetter, ASCR Office (tndousse@er.doe.gov)

Subtopic a References:

1.      “What’s News,” U.S. DOE Office of Nuclear Energy, home page, at http://www.nuclear.gov

2.      “Generation IV Nuclear Energy Systems,” Office of Nuclear Energy Website, at http://gen-iv.ne.doe.gov/

3.   “Advanced Fuel Cycle Initiative (AFCI),” Annual Report 2003.  (Available at: http://nuclear.gov/reports/AFCIAnnualRpt03.pdf

4.   “Global Nuclear Energy Partnership (GNEP),” U.S. DOE Website, at http://www.gnep.energy.gov

b. Computation Bio-Informatics—The processing of genome scale data sets being generated by experimental groups is a core Genomes to Life (GTL) need.  Software for identifying protein modifications from mass spectra of trypsinized proteomic samples is a current need.  Grant applications are sought to improve one or more of the component software packages that have already been developed by laboratory groups, in order to enhance user friendliness and thereby support their broad export to the biologist community.  Grant applications also are sought to develop novel software in support of cellular modeling tasks.  Of particular interest are approaches related to:  (1) systems biology, (2) the processing of proteomics and metabolomics data sets, (3) improved integration and or querying of heterogenous data sets, and (4) the automated development of cellular metabolic models from data sets on newly studied microbes.

Questions – contact Marvin Stodolsky, BER Office ( Marvin.Stodolsky@science.doe.gov) or Thomas Ndousse-Fetter, ASCR Office (tndousse@er.doe.gov)

Subtopic b References:

1.   “Genomics: GTL—Systems Biology for Energy and Environment,” U.S. DOE Website, at http://doegenomestolife.org/

2.   “Genomics: GTL Roadmap,” U.S. DOE Website, at http://doegenomestolife.org/roadmap/index.shtml

c. Computational Methods for Petascale Physics—The Department of Energy supports the development of computational technologies for the recording, processing, storage, distribution, and analysis of very large experimental data sets collected at current or planned High Energy Physics (HEP) facilities [1, 2, 3].  The international nature of HEP experiments and their large computing resource requirements drive the current HEP paradigm of handling and analyzing experimental data in a highly distributed fashion.  By aggregating world-wide computing resources from HEP and other disciplines, initiatives like the Open Science Grid [4] aim to make idle computing resources available to all participating disciplines.  The Offices of High Energy physics and Advanced Scientific Computing Office seeks grant applications in support of the design, implementation, and operation of distributed computing systems comprising many distributed Teraflops of CPU power and distributed petabytes of data.  Areas of current interest include middleware development for grid-enabled systems, distributed data management and analysis frameworks, distributed system configuration tools, monitoring and accounting tools, and security assurance tools for a distributed environment. 

Questions - contact Saul Gonzalez, HEP Office (Saul.Gonzalez@science.doe.gov) or Thomas Ndousse-Fetter, ASCR Office (tndousse@er.doe.gov)

Subtopic c References:

1.      “High Energy Physics (HEP),” U.S. DOE Office of Science Website, at http://www.science.doe.gov/Program_Offices/HEP.htm

2.      “The ATLAS Experiment,” CERN Website, at http://atlasinfo.cern.ch

3.      “Compact Muon Solenoid,” CERN Website, at http://cmsdoc.cern.ch

4.      “Open Science Grid,” National Science Foundation/U.S.DOE Office of Science Website, at http://opensciencegrid.org

d. Computational Methods for Modeling Subsurface Flow and Transport—The Department of Energy has long-term clean-up and management responsibility for its Cold War era production facilities, and the responsibility for monitoring the behavior of contaminants in the groundwater and vadose zone around existing and future waste disposal and storage areas. Conceptual model development and computer simulation of contaminant transport are important elements of the decision-making process for environmental remediation and monitoring. Simulation of subsurface transport processes on high performance, "leadership class" computers has not been widely utilized by subsurface scientists or environmental managers responsible for remediation decision-making. The intent of this call is to explore what options "leadership class" computing can bring to practical applications of modeling subsurface fluid flow in the context of environmental fate, transport and remediation and to foster collaborations among subsurface scientists within industry, academia and national laboratories in order to facilitate the use of high performance computers for environmental applications.

Specific areas of potential interest include:

• Incorporation of methods of model abstraction, parameter sensitivity and uncertainty analyses into computer simulations of subsurface transport.
• Methods exploring optimal conceptual and computational model complexity for subsurface transport simulation.
• Development of robust methodologies for the joint inversion of geophysical, hydrological, and biogeochemical data.
• Computational methods examining the scalability ("upscaling"), spatial variability and temporal variability of geochemical and biologically mediated reactions occurring at the molecular level to the field scale.
• Computational methods exploring efficient means of solving very large systems of nonlinear equations, inherent in subsurface transport modeling, on high performance computers.
• Development of parallel programming and output visualization tools enabling subsurface scientists to more easily access and utilize the high performance computing assets within DOE.
• Incorporation of process modeling capabilities into system-modeling tools for the design, analysis, and optimization of complex engineering projects.
• Development of advanced mesh generation and adaptive gridding techniques for the accurate representation of complex hydrostratigraphy, multiscale heterogeneity, and advancing saturation and reaction fronts.
• Development of robust and efficient strategies for the coupling of disparate processes with different inherent time constants.

Questions – contact David Lesmes, BER Office (David.Lesmes@science.doe.gov) or Thomas Ndousse-Fetter, ASCR Office (tndousse@er.doe.gov)

Subtopic d References:
 

1.      Steefel, C. I., et al., “Reactive Transport Modeling:  Essential Tool and a New Research Approach for the Earth Sciences,” Earth and Planetary Sciences Letters, 240: 539-558, December 2005.  (ISSN: 0022-3530 print) (Abstract and ordering information available at:  http://www.elsevier.com/wps/find/journaldescription.cws_home/503328/description#description)

2.      Davis, J. A., et al., “Assessing Conceptual Models for Subsurface Reactive Transport of Inorganic Contaminants,” EOS [Earth, Oceans, Space] Transactions, 85(44): 449-455, November 4, 2004.  (Full text available at:  http://www.iscmem.org/Documents/Publication_Davis2004Eos.pdf)

3.      Finsterle, S., “Demonstration of Optimization Techniques for Groundwater Plume Remediation Using iTOUGH2,” Lawrence Berkeley National Laboratory, November 11, 2004.  (Paper LBNL-56624) (Full text available at:  http://repositories.cdlib.org/lbnl/LBNL-56624 )

4.      Kowalsky, M., et al., “Estimation of Field-Scale Soil Hydraulic Parameters and Dielectric Parameters Through Joint Inversion of GPR/Hydrological Data,” Water Resource Research., 41:W11425, November 2005.  (doi:10.1029/2005WR004237) (ISSN:  00431397) (Full text available from American Geophysical Union.  See: http://www.agu.org/pubs/crossref/2005/2005WR004237.shtml)

5.      Singleton, M., J., et al., “Multiphase Reactive Transport Modeling of Seasonal Infiltration Events and Stable Isotope Fractionation in Unsaturated Zone Pore Water and Vapor at the Hanford Site,” Vadose Zone Journal, 3: 775–785, 2004.  (ISSN: 1539-1663) (Abstract only available at:  http://vzj.geoscienceworld.org/cgi/content/abstract/3/3/775)  

6.      Wu, Y. S., et al., “An Efficient Parallel-Computing Method for Modeling Nonisothermal Multiphase Flow and Multicomponent Transport in Porous and Fractured Media,” Advances in Water Resources, 25: 243–261, March 2002.  (Abstract and ordering information available at:  http://www.sciencedirect.com/science/journal/03091708.  Search by volume and page number.)

7.      Zhang, K., Y. S. Wu and Bodvarsson, G. S., “Massively Parallel Computing Simulation of Fluid Flow in the Unsaturated Zone of Yucca Mountain, Nevada,” Journal of Contaminant Hydrology, 62–63: 381–399, 2003. (Abstract and ordering information available at:  http://www.sciencedirect.com/science/journal/01697722.  Search by volume and page number.)

8.      National Research Council, Science and Technology for Environmental Cleanup at Hanford, National Academy Press, 2001.  (Full text available at:  http://books.nap.edu/openbook/0309075963/html/index.html).

9.      U.S. DOE Environmental Management Science Program, Research Needs in Subsurface Science, National Academy Press, 2000. (ISBN:  0309066468) (Full text available at:  http://books.nap.edu/openbook/0309066468/html/index.html)

10.  A Report to Congress on Long-Term Stewardship, Washington, DC:  U.S. DOE Office of Environmental Management, January 2001.  (Full text available at:  http://lts.apps.em.doe.gov/center/stewlink2.asp)

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