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2006-07 Program on Development, Assessment and Utilization of Complex Computer Models
Mathematical models intended for computational simulation of complex real-world processes are a crucial ingredient in virtually every field of science, engineering, medicine, and business, and in everyday life as well. Cellular telephones attempt to meet a caller's needs by optimizing a network model that adapts to local data, and people threatened by hurricanes decide whether to stay or flee depending on the predictions of a continuously updated computational model. Two related but independent phenomena have led to the near-ubiquity of models: the remarkable growth in computing power and the matching gains in algorithmic speed and accuracy. Together, these factors have vastly increased the applicability and reliability of simulation---not only by drastically reducing simulation time, thus permitting solution of larger and larger problems, but also by allowing simulation of previously intractable problems. The intellectual content of computational modeling comes from a variety of disciplines, including statistics and probability, applied mathematics, operations research, and computer science, and the application areas are remarkably diverse. Despite this diversity of methodology and application, there are a variety of common challenges — detailed below — in developing, evaluating and using complex computer models of processes, which directly relate to the mission of SAMSI. Overall Program Leaders Committee (leadership of each of the subprograms is listed below): Susie Bayarri (U. Valencia. Chair), Bruce Pitman (U. Buffalo), Peter Reichert (EAWAG), Tom Santner (Ohio State U.), Darren Wilkinson (U. Newcastle); Dave Higdon (Los Alamos National Lab. Liaison), Scott Mitchell (Sandia Liaison), Derek Bingham (Simon Fraser U., Liaison to the Canadian National Program and Complex Data Structures); James Berger (SAMSI, Directorate Liaison); Mary Wheeler (National Advisory Committee Liaison)
Research FociStudy of computer models needs to take place in the context of actual computer models. But because of the inherent complexity of computer models, and the very different types of such models, it is proposed to have a SAMSI program with sub-programs, focusing on specific computer modeling scenarios. This approach allows in-depth exploration of specific types of computer models, while maintaining an overall 'SAMSI umbrella' that allows quick transfer of techniques developed in one sub-program to another. The following subprograms will be conducted during the year. Environmental/Ecological Models Subprogram The environmental modeling subprogram will deal with 3 problem and research fields at the interface between statistics and environmental modelling: Problems of model calibration in the presence of structural model deficits and input uncertainty, problems of decision-oriented model application under high uncertainty about model structure and parameter values, and problems of universality or transferability of environmental models. Application areas may be hydrological models, climate models and plankton models. Final decisions about contents and application areas will be taken at or after the opening workshop in September. Leaders Committee: Peter Reichert (EAWAG and ETH Zurich, Chair, [email protected]), Douglas Nychka (NCAR), Jonathan Rougier (U. Durham), Ken Reckhow (Duke U., Local Scientific Coordinator), Montse Fuentes (North Carolina State U., Local Scientific Coordinator), Nell Sedransk (SAMSI, Directorate Liaison) Scientific Committee: Jim Clark (Duke U.), Leonard Smith (Oxford U.) Planned Activities: At the opening workshop, there will be talks about problems in all three research fields. This should lead to the formation of working groups which will establish the subprograms in the selected research fields. Establishing the work programs will then need some meetings in the fall of 2006 and will probably lead to intermediate workshops in spring 2007 to support the generation of results for the final program workshop. Subprogram on Uncertainty in Models of Granular Materials: Sources and Consequences The goal of the subprogram is to develop a better understanding of the variability that appears in - indeed, often dominates - the observed behavior of granular materials during flow and deformation. Ultimately, science seeks a description of granular flow, mathematical models that can be used in applications - applications ranging from building hoppers to transporting ore to predicting the path of a landslide. Although these applications are familiar and have existed for generations, there is no full scientific explanation of the fundamental physical processes activated during granular flows. New insights arise in statistics, mathematics, physics, and engineering. This program helps build a tapestry of science that, in the end, will provide the desired description of the flow of granular materials. This program brings together scientists whose specializations including: experimental evidence of the significant role of fluctuations in granular deformation; statistical mechanical models of the underlying microscopic physics of grain flow; bridging micro-scale physics and macroscopic scale modeling; analyzing and computing macro-scale mathematical models in the face of uncertainty in those models. Leaders Committee: Bruce Pitman (U. Buffalo, Chair, [email protected]), Luis Pericchi (U. Puerto Rico); Sorin Mitran (UNC-Chapel Hill, Local Scientific Coordinator); Ralph Smith (SAMSI, Directorate Liaison) The engineering subprogram will study three frequently-occurring problem areas in finite-element and other engineering models. These problems are those of Validation, Calibration, and Combining Data from physical experiments and computer experiments. The emphasis will be on applications where the computer models require substantial running times and the physical models are difficult or expensive, so that, in some cases, physical experiments can be conducted for only subcomponents of the desired system or a physical simulator may only be possible for the desired system. Issues of combining codes from system components to produce valid codes for the entire system can then arise. The design of both the physical and computer experiments will also be of special interest. Leaders Committee: Tom Santner (Ohio State U., Chair, [email protected]), Angela Patterson (General Electric), Mary Fortier (General Motors), Jim Berger (SAMSI, Directorate Liaison) Scientific Committee: Laura Swiler (Sandia National Labs), Dave Higdon (Los Alamos National Labs), Scott Mitchell (Sandia National Labs), Shih-Chung Tsai (General Motors) Planned Activities: A pre-program workshop will be held to sort our issues involving available test-bed problems (including confidentiality issues) and issues of communication with the major engineering subgroups that will not be resident at SAMSI. A later workshop is planned in January to solidify the directions of the working groups and to involve additional people. Biological Modeling Subprogram This program will focus on two types of biological models. The first is models of the impact of drug therapy and resistance on acute viral infections. These models are based on a multi-scale approach,integrating within-host models (i.e. ones that describe infection within a given individual) with between-host (epidemiological) models that describe the spread of infection at the population level. Numerous questions exist in terms of fitting these models to data, validating the models and using them for assessment of the spread of viral infection. A second focus of the program will be on system biological models. Models range from small biochemical networks corresponding to sets of coupled ODEs to large spatio-temporal models requiring advanced numerical methods. The modeling of cells or that of the vascular system and/or subsystems fall under the latter category. Some models are deterministic, while others are intrinsically stochastic, giving different output on each run. All typically contain uncertain parameters that must be estimated from sparse, noisy experimental data. Additionally, there is often uncertainty regarding model structure. Particular problems that arise in the context of systems biology models include: estimating large numbers of parameters from sparse data, parameter estimation using complex multivariate data, simultaneous estimation of model parameters and structure, and estimating parameters of complex stochastic models. Leaders Committee: Darren Wilkinson (U. of Newcastle, Chair, [email protected]), Pierre A. Gremaud (North Carolina State U., Local Scientific Coordinator), Greg Rempala (Univ. of Louisville), Ralph Smith (N.C. State University and SAMSI, Directorate Liaison) Planned Activities: There will be a year-long working group on models of viral infection. From March to May there will be an intensive research session on systems biology models, that will begin with a two-day workshop on calibration of biochemical network models. This Subprogram will engage in an in-depth treatment of methodological issues that arise in the design, analysis and utilization of computer models across many fields of application. This Subprogram will evolve in close collaboration with the four disciplinary subprograms (Environmental/Ecological Models, Engineering Models, Uncertainty in Models of Granular Materials, and Biological Modeling), engaging them in an overall research umbrella. In trying to predict reality (with uncertainty bounds), some of the key issues that have arisen are: use of model approximations (emulators) as surrogates for expensive simulators, for calibration/prediction tasks and in optimization or decision support; dealing with high dimensional input spaces; validation and utilization of computer models in situations with very little data, and/or functional (possibly multivariate) outputs; non-homogeneity, including jumps and phase changes as we move around the input space; implementation and transference methodology to current practice; efficient MCMC algorithms and prior assessments; optimization and design. Leaders Committee: Susie Bayarri (U. Valencia, Chair, [email protected]), Michael Goldstein (U. Durham), Tony O'Hagan (Sheffield Univ.), Jerry Sacks, Henry Wynn (London School of Economics), Robert Wolpert (Duke U., Local Scientific Coordinator), Jim Berger (SAMSI, Directorate Liaison)
Description of ActivitiesSummer School: In summer 2006, there will be a summer school at Simon Fraser University, conducted jointly between SAMSI and the Canadian National Program on Complex Data Structures. This will be an opportunity for students, new researchers, and others interested in becoming involved with the study of computer models to learn many of the latest methodological developments in the area.
Workshops: The Kickoff Workshop, to be held September 10-14, 2006. Its principal
goal will be to engage a broadly representative segment of the statistical, applied mathematical
and computer modeling communities in formulation and pursuit of specific research activities to be
undertaken by the Program Working Groups, which include:
There will also be numerous mid-program workshops organized by the subprograms, and a Transition Workshop, at the end of the program, to disseminate program results and chart a path for future research in the area. Working Groups: The working groups meet regularly throughout the program to pursue particular research topics identified in the kickoff workshop (or subsequently chosen by the working group participants). The working groups consist of SAMSI visitors, postdoctoral fellows, graduate students, and local faculty and scientists. It is not necessary to be continually resident at SAMSI to maintain connection to the working groups.
Air Quality
Further InformationAdditional information about the program and opportunities to participate in it is available:
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