Search NASA⌕ Search

SEARCH · Search NASA

Results for “application example”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 199 records · Page 11

Simulation of Coupled Processes of Flow, Transport, and Storage of CO 2 in Saline Aquifers

This report is the final scientific one for the award DE- FE0000988 entitled “Simulation of Coupled Processes of Flow, Transport, and Storage of CO 2 in Saline Aquifers.” The work has been divided into six tasks. In task, “Development of a Three-Phase Non-Isothermal CO 2 Flow Module,” we developed a fluid property module for brine-CO 2 mixtures designed to handle all possible phase combinations of aqueous phase, sub-critical liquid and gaseous CO 2 , supercritical CO 2 , and solid salt. The thermodynamic and thermophysical properties of brine-CO 2 mixtures (density, viscosity, and specific enthalpy of fluid phases; partitioning of mass components among the different phases) use the same correlations as an earlier fluid property module that does not distinguish between gaseous and liquid CO 2 -rich phases. We verified the fluid property module using two leakage scenarios, one that involves CO 2 migration up a blind fault and subsequent accumulation in a secondary “parasitic” reservoir at shallower depth, and another investigating leakage of CO 2 from a deep storage reservoir along a vertical fault zone. In task, “Development of a Rock Mechanical Module,” we developed a massively parallel reservoir simulator for modeling THM processes in porous media brine aquifers. We derived, from the fundamental equations describing deformation of porous elastic media, a momentum conservation equation relating mean stress, pressure, and temperature, and incorporated it alongside the mass and energy conservation equations from the TOUGH2 formulation, the starting point for the simulator. In addition, rock properties, namely permeability and porosity, are functions of effective stress and other variables that are obtained from the literature. We verified the simulator formulation and numerical implementation using analytical solutions and example problems from the literature. For the former, we matched a one-dimensional consolidation problem and a two-dimensional simulation of the Mandel-Cryer effect. For the latter, we obtained a good match of temperature and gas saturation profiles, and surface uplift, after injection of hot fluid into a model of a caldera structure. In task, “Incorporation of Geochemical Reactions of Selected Important Species,” we developed a novel mathematical model of THMC processes in porous and fractured saline aquifers, simulating geo-chemical reactions associated with CO 2 sequestration in saline aquifers. Two computational frameworks, sequentially coupled and fully coupled, were used to simulate the reactions and transport. We verified capabilities of the THMC model to treat complex THMC processes during CO 2 sequestration by analytical solutions and we constructed reactive transport models to analyze the THMC process quantitatively. Three of these are 1D reactive transport under chemical equilibrium, a batch reaction model with equilibrium chemical reactions, and a THMC model with CO 2 dissolution. In task “Study of Instability in CO 2 Dissolution-Diffusion-Convection Processes,” We reviewed literature related to the study of density driven convective flows and on the instability of CO 2 dissolution-diffusion-convection processes. We ran simulations that model the density-driven flow instability that would occur during CO 2 sequestration. CO 2 diffused through the top of the system and dissolved in the aqueous phase there, increasing its density. Density fingers formed along the top boundary, and coalesced into a few prominent ones, causing convective flow that forced the fluid to the system bottom. These simulations were in two and three dimensions. We ran additional simulations of convective mixing with density contrast caused by variable dissolved CO 2 concentration in saline water, modeled after laboratory experiments in which supercritical CO2 was circulated in the headspace above a brine saturated packed sand in a pressure vessel. As CO 2 dissolved into the upper part of the saturated sand, liquid phase density increases causing instability and setting off convective mixing. We obtained good agreement with the laboratory experiments, which were characterized by finger development and associated mixing of dissolved CO 2 into the system. We then varied a wide range of parameters and conceptual models in order to analyze the possibility of convective mixing under different conditions, such as various boundary conditions, and chemical reaction conditions. The CO 2 fingers from different simulations showed great differences as time progressed, caused by permeability heterogeneity. The early time diffusive phenomenon was captured by fine grid resolution, and the permeability heterogeneity affected the pattern of the CO 2 fingers. In addition, the fingers from three-dimensional simulations tended to be larger and flatter than the two-dimensional ones. In task “Implementation of Efficient Parallel Computing Technologies,” we made enhancements and modifications to our code in order to substantially increase the grid size that could be run. We installed and ran it on various platforms, including a multi-core PC and a cluster, and verified the numerical implementation and parallel code using an example problem from the literature. This problem, with a grid size of sixty million, utilized the cluster’s entire memory and all of its processors. In task “Implementation of General Fracture Conceptual Models,” we used the MINC approach, a generalization of the double-porosity concept, to model flow through porous and fractured media. In this approach, flow within the matrix is described by subdividing the matrix into nested volumes, with flow occurring between adjacent nested matrix volumes as well as between the fractures and the outer matrix volume. We generalized Hooke’s law to a thermo-multi- poroelastic medium, and derived from the fundamental equations describing deformation of porous and fractured elastic media a momentum conservation equation for thermo-multi- poroelastic media. This equation is a generalization to multi-poroelastic media of the one derived in Task 3.0 for single porosity media. We describe two simulations to provide model verification and application examples. The first, one-dimensional consolidation of a double-porosity medium, is compared to an analytical solution. The second is a match of published results from the literature, a simulation of CO 2 injection into hypothetical aquifer-caprock systems.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Memory and CPU efficient coherent mode decomposition of partially coherent synchrotron radiation with subtraction of common quadratic phase terms

Application examples of a memory and CPU efficient coherent mode decomposition (CMD) method for wave-optics based simulation of the partially coherent undulator radiation propagation through a hard X-ray beamline in a 3rd generation synchrotron radiation source are presented. The high efficiency of the method is achieved thanks to the analytical treatment of the common quadratic phase terms that are developed in the phase of cross-spectral density (CSD) of partially coherent radiation at a distance from source. This treatment allows for a considerable, several orders of magnitude, reduction of the 4D CSD mesh density (and the memory occupied by the CSD) required for ensuring sufficient accuracies of wavefront propagation simulations with the modes produced by the CMD at a beamline entrance. This method, implemented in the “Synchrotron Radiation Workshop” open-source software, dramatically increases the feasibility of the CMD of 4D CSD for producing 2D coherent modes for a large variety of applications at storage rings and other types of radiation sources.

36 MATERIALS SCIENCE↗

Evaluation of native Earth system model output with ESMValTool v2.6.0

Earth system models (ESMs) are state-of-the-art climate models that allow numerical simulations of the past, present-day, and future climate. To extend our understanding of the Earth system and improve climate change projections, the complexity of ESMs heavily increased over the last decades. As a consequence, the amount and volume of data provided by ESMs has increased considerably. Innovative tools for a comprehensive model evaluation and analysis are required to assess the performance of these increasingly complex ESMs against observations or reanalyses. One of these tools is the Earth System Model Evaluation Tool (ESMValTool), a community diagnostic and performance metrics tool for the evaluation of ESMs. Input data for ESMValTool needs to be formatted according to the CMOR (Climate Model Output Rewriter) standard, a process that is usually referred to as “CMORization”. While this is a quasi-standard for large model intercomparison projects like the Coupled Model Intercomparison Project (CMIP), this complicates the application of ESMValTool to non-CMOR-compliant climate model output. In this paper, we describe an extension of ESMValTool introduced in v2.6.0 that allows seamless reading and processing of “native” climate model output, i.e., operational output produced by running the climate model through the standard workflow of the corresponding modeling institute. This is achieved by an extension of ESMValTool's preprocessing pipeline that performs a CMOR-like reformatting of the native model output during runtime. Thus, the rich collection of diagnostics provided by ESMValTool is now fully available for these models. For models that use unstructured grids, a further preprocessing step required to apply many common diagnostics is regridding to a regular latitude–longitude grid. Extensions to ESMValTool's regridding functions described here allow for more flexible interpolation schemes that can be used on unstructured grids. Currently, ESMValTool supports nearest-neighbor, bilinear, and first-order conservative regridding from unstructured grids to regular grids. Example applications of this new native model support are the evaluation of new model setups against predecessor versions, assessing of the performance of different simulations against observations, CMORization of native model data for contributions to model intercomparison projects, and monitoring of running climate model simulations. For the latter, new general-purpose diagnostics have been added to ESMValTool that are able to plot a wide range of variable types. Currently, five climate models are supported: CESM2 (experimental; at the moment, only surface variables are available), EC-Earth3, EMAC, ICON, and IPSL-CM6. As the framework for the CMOR-like reformatting of native model output described here is implemented in a general way, support for other climate models can be easily added.

58 GEOSCIENCES↗

Application of Benchmark Examples to Assess the Single and Mixed-Mode Static Delamination Propagation Capabilities in ANSYS

The application of benchmark examples for the assessment of quasi-static delamination propagation capabilities is demonstrated for ANSYS. The examples are independent of the analysis software used and allow the assessment of the automated delamination propagation in commercial finite element codes based on the virtual crack closure technique (VCCT). The examples selected are based on two-dimensional finite element models of Double Cantilever Beam (DCB), End-Notched Flexure (ENF), Mixed-Mode Bending (MMB) and Single Leg Bending (SLB) specimens. First, the quasi-static benchmark examples were recreated for each specimen using the current implementation of VCCT in ANSYS . Second, the delamination was allowed to propagate under quasi-static loading from its initial location using the automated procedure implemented in the finite element software. Third, the load-displacement relationship from a propagation analysis and the benchmark results were compared, and good agreement could be achieved by selecting the appropriate input parameters. The benchmarking procedure proved valuable by highlighting the issues associated with choosing the input parameters of the particular implementation. Overall the results are encouraging, but further assessment for three-dimensional solid models is required.

Krueger, Ronald↗

A Co-design Framework for Online Data Analysis and Reduction

Science applications preparing for the exascale era are increasingly exploring in situ computations comprising of simulation-analysis-reduction pipelines coupled in-memory. Efficient composition and execution of such complex pipelines for a target platform is a codesign process that evaluates the impact and tradeoffs of various application- and system-specific parameters. In this article, we describe a toolset for automating performance studies of composed HPC applications that perform online data reduction and analysis. We describe Cheetah, a new framework for composing parametric studies on coupled applications, and Savanna, a runtime engine for orchestrating and executing campaigns of codesign experiments. Furthermore, this toolset facilitates understanding the impact of various factors such as process placement, synchronicity of algorithms, and storage versus compute requirements for online analysis of large data. Ultimately, we aim to create a catalog of performance results that can help scientists understand tradeoffs when designing next-generation simulations that make use of online processing techniques. We illustrate the design of Cheetah and Savanna, and present application examples that use this framework to conduct codesign studies on small clusters as well as leadership class supercomputers.

97 MATHEMATICS AND COMPUTING↗

Functional prescription for EFT matching

We simplify the one-loop functional matching formalism to develop a streamlined prescription. The functional approach is conceptually appealing: all calculations are performed within the UV theory at the matching scale, and no prior determination of an Effective Field Theory (EFT) operator basis is required. Our prescription accommodates any relativistic UV theory that contains generic interactions (including derivative couplings) among scalar, fermion, and vector fields. As an example application, we match the singlet scalar extended Standard Model (SM) onto SMEFT.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

A semidefinite program solver for the conformal bootstrap

We introduce SDPB: an open-source, parallelized, arbitrary-precision semidefinite program solver, designed for the conformal bootstrap. SDPB significantly outperforms less specialized solvers and should enable many new computations. As an example application, we compute a new rigorous high-precision bound on operator dimensions in the 3d Ising CFT, Δ σ = 0.518151(6), Δ ϵ = 1.41264(6).

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Determination of Ice Characteristics for Marine Hydroengineering Structures

Problems and potential approaches to determining ice characteristics for sea hydroengineering structures design are considered. A system for numerical modeling of ice dynamics is presented. The system may be used to define ice characteristics on approaches to structures with due regard for local hydrometeorological conditions and ice loads on structures. System application examples are presented for determining computational scenarios for ice loads at structures of the Pevek floating nuclear power plant (FNPP), as well as for the breakwater pier under reconstruction in Vanino. A scenario approach is used to determined ice loads.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Algorithmic Patterns for $$\mathcal {H}$$-Matrices on Many-Core Processors

In this work, we consider the reformulation of hierarchical ( \(\mathcal {H}\) ) matrix algorithms for many-core processors with a model implementation on graphics processing units (GPUs). \(\mathcal {H}\) matrices approximate specific dense matrices, e.g., from discretized integral equations or kernel ridge regression, leading to log-linear time complexity in dense matrix–vector products. The parallelization of \(\mathcal {H}\) matrix operations on many-core processors is difficult due to the complex nature of the underlying algorithms. While previous algorithmic advances for many-core hardware focused on accelerating existing \(\mathcal {H}\) matrix CPU implementations by many-core processors, we here aim at totally relying on that processor type. As main contribution, we introduce the necessary parallel algorithmic patterns allowing to map the full \(\mathcal {H}\) matrix construction and the fast matrix–vector product to many-core hardware. In this work, crucial ingredients are space filling curves, parallel tree traversal and batching of linear algebra operations. The resulting model GPU implementation hmglib is the, to the best of the authors knowledge, first entirely GPU-based Open Source \(\mathcal {H}\) matrix library of this kind. We investigate application examples as present in kernel ridge regression, Gaussian Process Regression and kernel-based interpolation. In this context, an in-depth performance analysis and a comparative performance study against a standard multi-core CPU \(\mathcal {H}\) matrix library highlights profound speedups of our many-core parallel approach.

97 MATHEMATICS AND COMPUTING↗

Thermomechanical Processing of Metal Feedstock for Semisolid Forming: A Review

Thermomechanical processing of cast structures is an effective solid working route of generating thixotropic morphologies after subsequent partial melting and is in use for decades to manufacture the bulk billet feedstock for thixoforming from a variety of alloys. The solid-state deformation is also critical for coarse particulate feedstock, utilized for semisolid forming either directly or after compaction into billets. Although the original concept, called strain-induced melt activation (SIMA), defined the specific procedure, the term became generally recognized synonym for a variety of thermomechanical treatments offering an opportunity of controlling the solidification microstructure. This review covers transformations during solid-state deformation, reheating to semisolid state and isothermal holding within solidus–liquidus range, and solidification of thixotropic slurries. Essentials of semisolid metal processing, necessary to understand the subject, are supported by details related to specific implementation techniques and alloys. Application examples at laboratory and commercial levels and properties achieved with conventional and severe plastic deformation techniques, for different alloys along with present limitations, are described. The link between solid-state deformation-enhanced melting and liquid metal engineering is emphasized throughout the paper in terms of the common goal of controlling the solidification outcome in order to develop technology for mass-scale production of net-shape components having performance characteristics superior to conventional castings.

36 MATERIALS SCIENCE↗

Generalization of a stability domain estimation method for nonlinear discrete systems

In this paper, we present a generalization approach of an algebraic existing method to estimate stability regions for discrete nonlinear polynomial systems of degree 3. The existing method is based on the enlargement of a guaranteed stability region by applying various steps of a proposed algorithm. Its main limitation is that the initial result has only been subsequently developed in a particular case of a single iteration. The stability domain obtained is consequently not the widest one. Our main contribution in this paper is to develop generalized functions that allow the enlargement of the guaranteed stability region after k iterations, for any value of k. A required fundamental tool is developed and consists in a general formula allowing to give the result of the Kronecker power calculation of two matrices sum. The advantages of this generalization are to reach a larger region of asymptotic stability and to improve the existing methods results. Two application examples illustrate the proposed method.

97 MATHEMATICS AND COMPUTING↗

Standard operating procedures for the comprehensive and reliable analysis of cannabis terpenes

Terpenes are the primary determinants of cannabis flower aroma, and ongoing research tests their potential for impacting the overall experience. Frustratingly, despite the importance of terpenes in cannabis physiology and commercial uses, literature reports vary widely regarding the major constituents of volatile blends and the concentrations of individual terpenes. Here, in this article, we provide detailed descriptions of complementary approaches that will allow researchers to determine the identity and quantity of cannabis terpenes unequivocally and reliably. These standard operating procedures will guide decisions about which method to employ to address specific analytical goals. We are including two application examples to illustrate the utility of different approaches for tackling the analysis of terpenes in cannabis flower samples.

Polito, Joshua↗

Predicting the impact of land management decisions on overland flow generation: Implications for cesium migration in forested Fukushima watersheds

The effects of land use and land cover (LULC) change on environmental systems across the land surface's “critical zone” are highly uncertain, often making prediction and risk management decision difficult. In a series of numerical experiments with an integrated hydrologic model, overland flow generation is quantified for both present day and forest thinning scenarios. A typhoon storm event in a watershed near the Fukushima Dai-ichi Nuclear Power Plant is used as an example application in which the interplay between LULC change and overland flow generation is important given that sediment-bound radionuclides may cause secondary contamination via surface water transport. Results illustrate the nonlinearity of the integrated system spanning from the deep groundwater to the atmosphere, and provide quantitative tools when determining the tradeoffs of different risk-mitigation strategies.

54 ENVIRONMENTAL SCIENCES↗

Mapping use cases and dataset needs for benchmarking buildings data

A perennial challenge in buildings research is the lack of high-quality datasets that can be relied upon for a wide array of tasks, including model calibration and improving energy efficiency and load flexibility. Instrumenting a building for data collection is resource intensive, so it is important to be methodical in the approach and ensure that resulting data are flexible and useful for a broad range of analyses. This study aims to fill the gaps in characterizing potential use cases for buildings datasets and mapping them to dataset needs using a well-defined data infrastructure. Here, we have developed a systematic mapping strategy between buildings dataset needs and use cases to help streamline the processes of efficiently targeting datasets, designing building sensing systems, and determining buildings research use cases. We selected 14 prospective use cases and 11 refined buildings data categories for developing the preliminary dataset-needs-to-use-cases mapping matrix (‘DN-UC mapping matrix’) with generic ‘Tags’—a detailed sub-level of data categories extracted by justifying the needs of an aspect of the datasets to use cases. We present two example applications of the developed mapping matrix to demonstrate use of the mapping matrix and its effectiveness.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

dfnWorks: A discrete fracture network framework for modeling subsurface flow and transport

DFNWORKS is a parallelized computational suite to generate three-dimensional discrete fracture networks (DFN) and simulate flow and transport. Developed at Los Alamos National Laboratory over the past five years, it has been used to study flow and transport in fractured media at scales ranging from millimeters to kilometers. The networks are created and meshed using DFNGEN, which combines FRAM (the feature rejection algorithm for meshing) methodology to stochastically generate three-dimensional DFNs with the LaGriT meshing toolbox to create a high-quality computational mesh representation. The representation produces a conforming Delaunay triangulation suitable for high performance computing finite volume solvers in an intrinsically parallel fashion. Flow through the network is simulated in dfnFlow, which utilizes the massively parallel subsurface flow and reactive transport finite volume code PFLOTRAN. A Lagrangian approach to simulating transport through the DFN is adopted within DFNTRANS to determine pathlines and solute transport through the DFN. Example applications of this suite in the areas of nuclear waste repository science, hydraulic fracturing and CO 2 sequestration are also included.

42 ENGINEERING↗

Prediction of local concentration fields in porous media with chemical reaction using a multi scale convolutional neural network

The study of solute transport in porous media is of interest in many chemical engineering systems. Some example applications include packed bed catalytic reactors, filtration devices, and batteries. The pore scale modeling of these systems is time consuming and may require large computing resources, for this reason computational fluid dynamics (CFD) simulations are not practical if a large number of simulations is required, like in multiscale modeling, where a model at a large scale calls for pore scale simulations. It has been shown that neural networks can be trained with a dataset of flow simulations and then predict fields orders of magnitude faster, and with less computational resources, in new domains. However, it is crucial to provide the neural network with an effective description of the domain and the undergoing operating conditions to be able to train models that generalize accurately in unseen samples. Therefore, research is needed to employ neural networks in new complex systems. The appropriate training of a network for predicting coupled flow and solute transport processes is an outstanding problem due to the complex interplay between geometry and operating conditions. In this work, we train a multi scale convolutional neural network (MSNet) with a diverse dataset of simulations of transport and chemical reaction in porous media to predict the local concentration fields in images of porous media. Our dataset contains a wide diversity of sphere pack arrangements under different operating conditions (Péclet and Reynolds numbers). Further, we train a robust model by employing different input descriptors that represent the medium and the different operating conditions of each system. Our trained model is able to provide nearly instantaneous predictions, compared to around twenty hours of the CFD workflow, with less than 3.5% error on new geometries and transport conditions. Thus the model could be easily integrated in a multiscale workflow where fast response is needed.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Dynamic beam shaping—Improving laser materials processing via feature synchronous energy coupling

Today, tailored laser beams are rarely used and thus an opportunity to optimize existing or introduce new processes is missed. New methods of dynamic beam shaping have the potential to change that in future. This keynote paper deals with methods allowing a transient energy input into the workpiece at such time scales that the underlying interaction processes are guided towards the desired result. It shows principles, categorizes necessary system technology, and gives application examples to familiarize the reader with the topic. It postulates that time-scale-dependent coupling between transient energy input and addressed process features is key for achieving the optimum.

36 MATERIALS SCIENCE↗

ADAM: A web platform for graph-based modeling and optimization of supply chains

Modeling and optimization are essential tasks that arise in the analysis and design of supply chains (SCs). SC models are essential for understanding emergent behavior such as transactions between participants, inherent value of products exchanged, as well as impact of externalities (e.g., policy and climate) and of constraints. Unfortunately, most users of SC models have limited expertise in mathematical optimization, and this hinders the adoption of advanced decision-making tools. Here, in this work, we present ADAM, a web platform that enables the modeling and optimization of SCs. ADAM facilitates modeling by leveraging intuitive and compact graph-based abstractions that allow the user to express dependencies between locations, products, and participants. ADAM model objects serve as repositories of experimental, technology, and socio-economic data; moreover, the graph abstractions facilitate the organization and exchange of models and provides a natural framework for education and outreach. Here, we discuss the graph abstractions and software design principles behind ADAM, its key functional features and workflows, and application examples.

97 MATHEMATICS AND COMPUTING↗