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Results for “computational complexity”
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Computational modeling of mixed-ligand cobalt complexes with o-quinone derivative of corannulene
The structure and energy characteristics of isomers of electrically neutral adducts of tetracoordinate cobalt complexes with o-quinone derivative of corannulene were studied quantum chemically within the density functional theory (DFT) in the UB3LYP*/6-311++G(d,p) approximation. It was shown that the framework rigidity of the redox-active ligand favors convergence of the energy levels of the high-spin and low-spin isomers of the complexes under study as compared to the o-benzoquinone-containing analogues. At the same time, steric strain in the corannulene moiety causes the stability of the adducts to reduce. A compound characterized by high stabilization energy and the ability to switch its spin states via valence tautomeric rearrangements was found by systematic variation of structural parameters of cobalt bis(chelate).
Formulation and computation of dynamic, interface-compatible Whitney complexes in three dimensions
A discrete De Rham complex enables compatible, structure-preserving discretizations for a broad range of partial differential equations problems. Such discretizations can correctly reproduce the physics of interface problems, provided the grid conforms to the interface. However, large deformations, complex geometries, and evolving interfaces makes generation of such grids difficult. We develop and demonstrate two formally equivalent approaches that, for a given background mesh, dynamically construct an interface-conforming discrete De Rham complex. Both approaches start by dividing cut elements into interface-conforming subelements but differ in how they build the finite element basis on these subelements. The first approach discards the existing non-conforming basis of the parent element and replaces it by a dynamic set of degrees of freedom of the same kind. The second approach defines the interface-conforming degrees of freedom on the subelements as superpositions of the basis functions of the parent element. These approaches generalize the Conformal Decomposition Finite Element Method (CDFEM) and the extended finite element method with algebraic constraints (XFEM-AC), respectively, across the De Rham complex.
Real-Time Stochastic Optimization of Complex Energy Systems on High-Performance Computers
A scalable approach computes in operationally-compatible time the energy dispatch under uncertainty for electrical power grid systems of realistic size with thousands of scenarios. The authors propose several algorithmic and implementation advances in their parallel solver PIPS-IPM for stochastic optimization problems. New developments include a novel, incomplete, augmented, multicore, sparse factorization implemented within the PARDISO linear solver and new multicore- and GPU-based dense matrix implementations. They show improvement on the interprocess communication on Cray XK7 and XC30 systems. PIPS-IPM is used to solve 24-hour horizon power grid problems with up to 1.95 billion decision variables and 1.94 billion constraints on Cray XK7 and Cray XC30, with observed parallel efficiencies and solution times within an operationally defined time interval. To the authors' knowledge, "real-time"-compatible performance on a broad range of architectures for this class of problems hasn't been possible prior to this work
SISGR - A CONCERTED SYNTHETIC, SPECTROSCOPIC, AND COMPUTATIONAL APPROACH TOWARDS WATER SPLITTING BY HETEROMETALLIC COMPLEXES IN SOLUTION AND ON SURFACES
Final Technical Report from September 15, 2009 - September 14, 2016
Automated maintenance for complex hybrid systems
Digital computer, Control Computer Subsystem (CCS), possess high degree of fault tolerance. CCS embodies concepts of self-test and repair. It is capable of monitoring its own performance and of identifying and replacing with standby spare any of its units that fail.
The use of a digital computer for calculation of acoustic fields of complex vibrating structures by the reciprocity principle
A program was compiled for calculating acoustical pressure levels, which might be created by vibrations of complex structures (an assembly of shells and rods), under the influence of a given force, for cases when these fields cannot be measured directly. The acoustical field is determined according to transition frequency and pulse characteristics of the structure in the projection mode. Projection characteristics are equal to the reception characteristics, for vibrating systems in which the reciprocity principle holds true. Characteristics in the receiving mode are calculated on the basis of experimental data on a point pulse space velocity source (input signal) and vibration response of the structure (output signal). The space velocity of a pulse source, set at a point in space r, where it is necessary to calculate the sound field of the structure p(r,t), is determined by measurements of acoustic pressure, created by a point source at a distance R. The vibration response is measured at the point where the forces F and f exciting the system should act.
Fast and stable algorithms for computing the principal square root of a complex matrix
This note presents recursive algorithms that are rapidly convergent and more stable for finding the principal square root of a complex matrix. Also, the developed algorithms are utilized to derive the fast and stable matrix sign algorithms which are useful in developing applications to control system problems.
Towards Computational Study of Flow within Cavities with Complex Geometric Features.
Abstract not provided.
Final Scientific/Technical Report for Phase II SBIR Project - Optimal production planning, sourcing, distribution & routing for complex energy intensive companies using High Performance Computing (HPC)
Explore the source record for details and available documents.
Towards Computational Study of Flow within Cavities with Complex Geometric Features.
Abstract not provided.
Combining multiple lower-fidelity models for emulating complex model responses for CCS environmental risk assessment
Numerical modeling is essential to support natural resource management and environmental policy-making. In the context of CO 2 geological sequestration, these models are indispensible parts of risk assessment tools. However, because of increasing complexity, modern numerical models require a great computational effort, which in some cases may be infeasible. An increasingly popular approach to overcome computational limitations is the use of surrogate models. This paper presents a new surrogate modeling approach to reduce the computational cost of running a complex, high-fidelity model. The approach is based on the simplification the high-fidelity model into computationally efficient, lower-fidelity models and on linking them with a mathematical function (linking function) that addresses the discrepancies between outputs from models with different levels of fidelity. The resulting linking function model, which can be developed with small computational effort, can be efficiently used in numerical applications where multiple runs of the original high-fidelity model are required, such as for uncertainty quantification or sensitivity analysis. The proposed approach was then applied to the development of a reduced order model for the prediction of groundwater quality impacts from CO 2 and brine leakage for the National Risk Assessment Partnership (NRAP) project.
Unstructured finite element mesh generation and adaptive procedures for CFD
A method is described for generating unstructured meshes of triangles or tetrahedra for computational domains of complex geometrical shape. To illustrate the power of the approach, it is applied to the solution of flows past several complete aircraft configurations. The advocated approach allows for the natural incorporation of mesh adaptivity and this is demonstrated for both inviscid and viscous computations in two and three dimensions.
Tuning and Verification of an Internal Flooding Model for Dynamic PRA
In probabilistic risk assessment (PRA), the likelihoods and consequences of basic events are combined to determine possible system level outcomes and the likelihood of each outcome given an initial event. Both the consequences and likelihoods of basic events may be informed by the use of mathematical models or experimental data regarding the phenomena of interest. In either case, the impact of uncertainties on the results need to be evaluated. If a model is used to predict the evolution of an initiating event, uncertainty quantification can be computationally challenging for complex phenomena with many epistemic (e.g., model) uncertainties. In this work, a reduced order model is introduced for the flooding analysis of a multi-room building at a nuclear power plant under uncertainties which can require long run times using high fidelity computer models. The reduced order model focuses on macro-level transfer of water between rooms and tracks the water level within each room. In order to verify the model's fidelity, its results for the phenomena involved in a scenario of interest are compared to those of a computational fluid dynamics (CFD) code, which are taken to represent reality. This work does not focus on the overall fidelity of the flooding model, as the goal of the project for which it was developed is to develop a methodology rather than to analyze a particular case. The focus instead is on the tunability and verifiability of the reduced order model for relevant physical measures. In analyzing a particular case, the model may be required to incorporate more realistic description of phenomena; however, the procedure described in this work may be used to verify its performance as well. (authors)
Cross-source sensing data fusion for building occupancy prediction with adaptive lasso feature filtering
Fusing various sensing data sources can significantly improve the accuracy and reliability of building occupancy detection. Fusing environmental sensors and wireless network signals are seldom studied for its computational and technical complexity. Here, this study aims to propose an integrated adaptive lasso model that is able to extract critical data features for environmental and Wi-Fi probe dual sensing sources. Through rapid feature extraction and process simplification, the proposed method aims to improve the computational efficiency of occupancy detecting models. To validate the proposed model, an onsite experiment was conducted to examine two occupancy data resolutions, (real-time and four-level occupancy resolutions). The results suggested that, among all twelve features, eight features are most relevant. The mean absolute error of the real-time occupancy can be reduced to 2.18 and F1_accuracy is about 84.36% for the four-level occupancy.
2016 High Performance Computing Annual Report
Sandia National Laboratories’ California site is celebrating its 60th anniversary (1956 to 2016), and high performance computing has been a key enabler for its scientists and engineers throughout much of its history. Since its founding, Sandia California has helped pioneer the use of HPC platforms including hosting Sandia’s first Cray-1 supercomputer in the 1970s and supporting development of scalable cluster computing platforms to create a new paradigm for cost-effective supercomputing in the 1990s. Recent decades of investment in creation of scalable application frameworks for scientific computing have also enabled new generations of modeling and simulation codes. These resources have facilitated computational analysis of complex phenomena in diverse applications spanning national defense, energy, and homeland security. Today, Sandia California researchers work with partners in academia, industry, and national labs to evolve the state-of-the-art in HPC, modeling, and data analysis (including foundational capabilities for exascale computing platforms) and apply them in transformational ways. Research efforts include mitigating the effects of silent hardware failures that can jeopardize the results of large-scale computations, developing exascale-capable asynchronous task-parallel programming models and runtime systems, formulating new techniques to better explore and analyze extreme-scale data sets, and increasing our understanding of materials and chemical sciences which has applications spanning nuclear weapons stockpile stewardship to more efficient automobile engines. The following section highlights some of these research and applications projects and further illustrates the breadth of our HPC capabilities.
Conservative zonal schemes for patched grids in 2 and 3 dimensions
The computation of flow over complex geometries, such as realistic aircraft configurations, poses difficult grid generation problems for computational aerodynamicists. The creation of a traditional, single-module grid of acceptable quality about an entire configuration may be impossible even with the most sophisticated of grid generation techniques. A zonal approach, wherein the flow field is partitioned into several regions within which grids are independently generated, is a practical alternative for treating complicated geometries. This technique not only alleviates the problems of discretizing a complex region, but also facilitates a block processing approach to computation thereby circumventing computer memory limitations. The use of such a zonal scheme, however, requires the development of an interfacing procedure that ensures a stable, accurate, and conservative calculation for the transfer of information across the zonal borders.