Regional Climate Simulations With the Community Earth System Model
Not Available
54 ENVIRONMENTAL SCIENCES↗
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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.
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GloudSim: Google trace based cloud simulator with virtual machines: GloudSim: Google trace based cloud simulator with virtual machines
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97 MATHEMATICS AND COMPUTING↗
XScan: An Integrated Tool for Understanding Open Source Community-Based Scientific Code
Many scientific communities have adopted community-based models that integrate multiple components to simulate whole system dynamics. The community software projects’ complexity, stems from the integration of multiple individual software components that were developed under different application requirements and various machine architectures, has become a challenge for effective software system understanding and continuous software development. The paper presents an integrated software toolkit called X-ray Software Scanner (in abbreviation, XScan) for a better understanding of large-scale community-based scientific codes. Our software tool provides support to quickly summarize the overall information of scientific codes, including the number of lines of code, programming languages, external library dependencies, as well as architecture-dependent parallel software features. The XScan toolkit also realizes a static software analysis component to collect detailed structural information and provides an interactive visualization and analysis of the functions. We use a large-scale community-based Earth System Model to demonstrate the workflow, functions and visualization of the toolkit. We also discuss the application of advanced graph analytics techniques to assist software modular design and component refactoring.
Zheng, Weijian↗
Performance and Energy Usage of Workloads on KNL and Haswell Architectures. In: High Performance Computing Systems. Performance Modeling, Benchmarking, and Simulation
Manycore architectures are an energy-efficient step towards exascale computing within a constrained power budget. The Intel Knights Landing (KNL) manycore chip is a specific example of this and has seen early adoption by a number of HPC facilities. It is therefore important to understand the performance and energy usage characteristics of KNL. In this paper, we evaluate the performance and energy efficiency of KNL in contrast to the Xeon (Haswell) architecture for applications representative of the workload of users at NERSC. We consider the optimal MPI/OpenMP configuration of each application and use the results to characterize KNL in contrast to Haswell. As well as traditional DDR memory, KNL contains MCDRAM and we also evaluate its efficacy. Our results show that, averaged over our benchmarks, KNL is 1.84 × more energy efficient than Haswell and has 1.27 × greater performance.
Benchmarking↗
Chapter 8: Planning Tools to Simulate and Optimize Neighborhood Energy Systems
This section introduces different energy modeling tools available in Europe and the USA for community energy master planning process varying from strategic Urban Energy Planning to more detailed Local Energy Planning. Two modeling tools used for Energy Master Planning of primarily residential communities, the 3D city model with CityGML, and the Net Zero Planner tool developed for the US Department of Defense installations are described in more details.
29 ENERGY PLANNING, POLICY, AND ECONOMY↗
Sensitivity of Numerical Simulations of a Mesoscale Convective System to Ice Hydrometeors in Bulk Microphysical Parameterization
Not provided.
Geochemistry & Geophysics↗
Parameterization and Explicit Modeling of Cloud Microphysics: Approaches, Challenges, and Future Directions
Cloud microphysical processes occur at the smallest end of scales among cloud-related processes and thus must be parameterized not only in large-scale global circulation models (GCMs) but also in various higher-resolution limited-area models such as cloud-resolving models (CRMs) and large-eddy simulation (LES) models. Instead of giving a comprehensive review of existing microphysical parameterizations that have been developed over the years, this study concentrates purposely on several topics that we believe are understudied but hold great potential for further advancing bulk microphysics parameterizations: multi-moment bulk microphysics parameterizations and the role of the spectral shape of hydrometeor size distributions; discrete vs “continuous” representation of hydrometeor types; turbulence-microphysics interactions including turbulent entrainment-mixing processes and stochastic condensation; theoretical foundations for the mathematical expressions used to describe hydrometeor size distributions and hydrometeor morphology; and approaches for developing bulk microphysics parameterizations. Also presented are the spectral bin scheme and particle-based scheme (especially, super-droplet method) for representing explicit microphysics. Their advantages and disadvantages are elucidated for constructing cloud models with detailed microphysics that are essential to developing processes understanding and bulk microphysics parameterizations. Particle-resolved direct numerical simulation (DNS) models are described as an emerging technique to investigate turbulence-microphysics interactions at the most fundamental level by tracking individual particles and resolving the smallest turbulent eddies in turbulent clouds. Outstanding challenges and future research directions are explored as well.
54 ENVIRONMENTAL SCIENCES↗
Plasticity-mediated deformation instabilities in thin film-compliant substrate systems: direct three-dimensional simulations
Abstract Surface wrinkles driven by mechanical instability commonly form in thin-film structures attached to a compliant substrate. In this study, a recently developed computational approach is employed to simulate the formation and transformation of wrinkles involving plastic yielding of the thin film. The three-dimensional (3D) finite element models contain an embedded imperfection at the film-substrate interface, serving to trigger the bifurcation modes. Successful application of this technique to allow for film plasticity is demonstrated, including the evolution of 3D surface patterns and their correlation with the overall load–displacement response. The simulations reveal that plastic yielding transforms the surface instability patterns into more localized forms. Under uniaxial loading, the sinusoidal elastic wrinkles undergo the wrinkle-to-fold transition. With equi-biaxial loading, the initial square-checkerboard array turns into continuous tall ridges along the 45° directions. In both loading modes, the plasticity-induced instability patterns are only partially relieved upon unloading, leaving permanent features on the surface.
36 MATERIALS SCIENCE↗
Non-reciprocal Interferometers for Matter Waves
We propose non-reciprocal interferometers for matter waves and explore them by means of modeling. These interferometers may be implemented as asymmetric quantum rings with broken time-inversion symmetry. Our preliminary analyses lead us to predict that these devices will feature asymmetric transport properties for particles such as electrons, for which the interferometers’ ground states act as directional filters. As a function of the electron velocity, the filters seem to let electrons preferentially pass in one direction rather than in the reverse, thereby reducing the entropy of the electron systems in the contacts. Mechanisms are discussed that are candidates to prevent directional filtering if the filters are operating in thermal equilibrium with incoherent electron reservoirs.
75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
Theoretical Study of Mechanical Stability and Physical Properties of Co{sub 2}V{sub 1−x}Zr{sub x}Ga
The mechanical stability and physical properties of Co{sub 2}V{sub 1−x}Zr{sub x}Ga (x = 0, 0.25, 0.50, 0.75, 1) have been predicted by using ab initio calculations based on density functional theory. The exchange-correlation potentials are treated within the generalized gradient approximation-Perdew-Burke and Ernzerhhof (GGA-PBE) and Hubbard coefficient (GGA+U). The investigated minimum lattice parameter of Co{sub 2}VGa is 5.8030 Å, which is in excellent agreement with available experimental and theoretical data and for Co{sub 2}V{sub 1−x}Zr{sub x}Ga (x = 0.25, 0.50, 0.75, 1) are 5.9026, 5.9625, 6.0060 and 6.0021 Å, respectively, which are predicted for the very first time. The total magnetic moments decrease with increasing concentration of x in Co{sub 2}V{sub 1−x}Zr{sub x}Ga, in agreement with the Slater-Pauling rule. Band structure and density of states calculations show that the minority spin channel exhibits band gaps of 0.43, 0.46, 0.52, 0.54 and 1.01 eV for GGA+U scheme around the Fermi level confirming that all the studied composites are half-metallic in nature. In this study, we also studied the elastic constant and it is established that all the materials are mechanically stable and ductile in nature. The Co{sub 2}VGa is stiffer than other materials and all the studied composites have anisotropic behaviour. Moreover, by using a quasi-harmonic Debye model and calculated elastic constant, the Debye temperature and temperature-dependent constant volume heat capacity have been investigated.
75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
Sensitivity Analysis of Material Model Parameters to Reproduce Crushing of Composite Tubes
The ability to predict the behavior of composite structures under impact conditions is an important challenge for engineering analysis since it requires modeling beyond the elasticity and into failure initiation and propagation. Crushing of laminate composites is the result of a combination of several and complex failure mechanisms, which are not always possible to reproduce together in a single finite element analysis (FEA). In this paper, models based on lamina-level failure criteria have been used to predict the onset of damage; once failure initiates, the mechanisms of failure propagation require reducing the material properties using several degradation schemes. Among the composite material models available in LS-DYNA, MAT-ENHANCED-COMPOSITE-DAMAGE (MAT-54) has been chosen for modeling the axial crushing of composite tubes with various resistant sections and wall slope, given the reduced experimental input parameters to insert into the card definition. Comparison with experimental data shows that such material model is able to successfully reproduce the crushing behavior, even if the numerical results are strictly correlated with some model parameters which cannot be measured experimentally or are purely mathematical expedients. Therefore, extensive calibration of these parameters by trial-and-error is necessary to achieve successful simulation results. Once done it for a structure made of the same composite material, it is possible to adopt the same card configuration for all the other cases, obtaining good agreement between numerical and experimental results. After, the attempt to model the same geometries using the MAT-LAMINATED-COMPOSITE-FABRIC (MAT-58) card with the same parameter values previously calibrated has been done obtaining results comparable with the experimental data.
36 MATERIALS SCIENCE↗
New approach for stability and bifurcation analysis on predator–prey harvesting model for interval biological parameters with time delays
This paper presents a prey–predator harvesting model with time delay for bifurcation analysis. We consider the parameters of the proposed model with imprecise data as form of interval in nature, due to the lack of precise numerical information of the biological parameters such as prey population growth rate and predator population decay rate. The interaction between prey and predator is assumed to be governed by a Holling type II functional response and discrete type gestation delay of the predator for consumption of the prey under impreciseness of the biological parameters. Parametric functional form of interval number with two parameters is introduced. This study reveals that not only delay and harvesting effort play a significant role on the stability on the system but also interval parameters play a crucial role on the stability of the system. Computer simulations of numerical examples are given to explain our proposed imprecise model. We also address critically the biological implications of our analytical findings with proper numerical example.
97 MATHEMATICS AND COMPUTING↗
Enhanced accuracy through ensembling of randomly initialized auto-regressive models for dynamical systems
Computational mechanics simulations using traditional finite element methods (FEM) require prohibitively expensive computational resources for real-time engineering applications, design optimization, and digital twin implementations. While machine learning (ML) surrogate models offer significant computational speedups, autoregressive ML models for time-dependent mechanical systems suffer from error accumulation that compromises long-term prediction reliability - a critical concern for engineering applications where accuracy over extended time horizons is essential for safety and performance assessments. Here, we propose a deep ensemble framework specifically designed to address this challenge in computational mechanics applications, where multiple ML surrogate models with random weight initializations are trained in parallel and their predictions aggregated during inference. This approach leverages statistical diversity to maximize information gain from a fixed set of training data and to mitigate error propagation, while maintaining the computational efficiency that makes ML surrogates attractive for engineering practice. We validate the framework on three representative problems spanning critical areas of computational mechanics: stress field evolution in heterogeneous microstructures under complex loading (relevant to advanced materials design and composite analysis), planetary-scale shallow water dynamics (applicable to environmental and geotechnical engineering), and Gray-Scott reaction-diffusion systems (relevant to mass transport and chemical process engineering). Across all test cases, the ensemble approach demonstrates consistent error reduction of 15-33% compared to individual models. The codes for this work are available on GitHub (https://github.com/Graham-Brady-Research-Group/AutoregressiveEnsemble_SpatioTemporal_Evolution).
autoregressive prediction↗
A learning-based data-driven forecast approach for predicting future reservoir performance
Quantification of the predictive uncertainty of subsurface models has long been investigated. The traditional workflow is to calibrate prior models to match observed data, and then use the posterior models to simulate future system performance. Not only are these procedures computationally expensive, but they also have issues in maintaining geological model constraints during the calibration step. Data space inversion (DSI) was introduced recently to predict future system performance without the iterative history matching or model calibration step. In general, DSI approaches seek to establish a statistical relationship between the observed and forecast variables, as well as to quantify the predictive uncertainty of the forecast variables, by using an ensemble of uncalibrated prior models. Existing DSI approaches all require a number of complex transformation and mapping operations, which may deter their widespread use. Here in this study, we introduce a new and simpler DSI approach, the learning-based, data-driven forecast approach (LDFA), by combining dimension reduction and machine learning techniques to quickly provide accurate forecast results and reliably quantify corresponding uncertainty in the results. Our LDFA framework is demonstrated using two supervised learning algorithms, artificial neural network (ANN) and support vector regression (SVR), on two representative examples from reservoir engineering and geological carbon storage. Results suggest that our approach provides accurate forecast results (e.g., future oil production rate or cumulative injected CO 2 ) and reasonable predictive uncertainty intervals. Our framework is generic and may be applied to other surface and subsurface problems.
42 ENGINEERING↗
A domain-specific analysis system for examining nuclear reactor simulation data for light-water and sodium-cooled fast reactors
Not Available
43 PARTICLE ACCELERATORS↗
Low depth quantum circuits for Ising models
A scheme for measuring complex temperature partition functions of Ising models is introduced. Two applications of this scheme are presented. First, through appropriate Wick rotations, those amplitudes can be analytically continued to yield estimates for partition functions of Ising models. Bounds on the estimated error are provided through a central-limit theorem whose validity extends beyond the present context; it holds for example for estimations of the Jones polynomial. The kind of state preparations and measurements involved in this application can be made independent of the system size or the parameters of the system being simulated. Second, the scheme allows to accurately estimate non-trivial invariants of links. Another result concerns the computational power of estimations of partition functions for real temperature classical ferromagnetic Ising models. We provide conditions under which estimating such partition functions allows to reconstruct scattering amplitudes of quantum circuits, making the problem BQP-hard. We also show fidelity overlaps for ground states of quantum Hamiltonians, which serve as a witness to quantum phase transitions, can be estimated from classical Ising model partition functions. Finally, we discuss how accurate corner magnetisation measurements on thermal states of two-dimensional Ising models lead to fully polynomial random approximation schemes (FPRAS) for the partition function.
71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
Action principles for quantum automata and Lorentz invariance of discrete time quantum walks
A discrete action principle for general quantum automata is proposed. This action principle is particularized to Discrete Time Quantum Walks (DTQWs) and then extended into an energy and momentum preserving, manifestly covariant formulation. Space–time coordinates are introduced as new variables of the action and their equations of motion enforce energy and momentum conservation. This guarantees that the proposed action can be used to build future, DTQW-based self-consistent models of spinors interacting with gauge fields. A discrete stress–energy tensor for the DTQW is also obtained. The manifest covariance of the formulation highlights the special role played by the grid reference frame in the DTQW dynamics. The main discussion is complemented by three appendices.
71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗