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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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At least 289 records · Page 16

A bidirectional coupling procedure applied to multiscale respiratory modeling

In this study, we present a novel multiscale computational framework for efficiently linking multiple lower-dimensional models describing the distal lung mechanics to imaging-based 3D computational fluid dynamics (CFDs) models of the upper pulmonary airways in order to incorporate physiologically appropriate outlet boundary conditions. The framework is an extension of the modified Newton’s method with nonlinear Krylov accelerator developed by Carlson and Miller [1], Miller [2] and Scott and Fenves [3]. Our extensions include the retention of subspace information over multiple timesteps, and a special correction at the end of a timestep that allows for corrections to be accepted with verified low residual with as little as a single residual evaluation per timestep on average. In the case of a single residual evaluation per timestep, the method has zero additional computational cost compared to uncoupled or unidirectionally coupled simulations. We expect these enhancements to be generally applicable to other multiscale coupling applications where timestepping occurs. In addition we have developed a “pressure-drop” residual which allows for stable coupling of flows between a 3D incompressible CFD application and another (lower-dimensional) fluid system. We expect this residual to also be useful for coupling non-respiratory incompressible fluid applications, such as multiscale simulations involving blood flow. The lower-dimensional models that are considered in this study are sets of simple ordinary differential equations (ODEs) representing the compliant mechanics of symmetric human pulmonary airway trees. To validate the method, we compare the predictions of hybrid CFD–ODE models against an ODE-only model of pulmonary airflow in an idealized geometry. Subsequently, we couple multiple sets of ODEs describing the distal lung to an imaging-based human lung geometry. Boundary conditions in these models consist of atmospheric pressure at the mouth and intrapleural pressure applied to the multiple sets of ODEs. In both the simplified geometry and in the imaging-based geometry, the performance of the method was comparable to that of monolithic schemes, in most cases requiring only a single CFD evaluation per time step. Thus, this new accelerator allows us to begin combining pulmonary CFD models with lower-dimensional models of pulmonary mechanics with little computational overhead. Moreover, because the CFD and lower-dimensional models are totally separate, this framework affords great flexibility in terms of the type and breadth of the adopted lower-dimensional model, allowing the biomedical researcher to appropriately focus on model design. Research funded by the National Heart and Blood Institute Award 1RO1HL073598.

60 APPLIED LIFE SCIENCES↗

Coupled THM Modeling of Hydroshearing Stimulation in Tight Fractured Volcanic Rock

Here, we use the TOUGH-FLAC simulator for coupled thermo–hydro-mechanical modeling of well stimulation for an Enhanced Geothermal System (EGS) project. We also analyze the potential for injection-induced fracturing and reactivation of natural fractures in a porous medium with associated permeability enhancement. Our analysis aims to understand how far the EGS reservoir may grow and how the hydroshearing process relates to system conditions. We analyze the enhanced reservoir, or hydrosheared zone, by studying the extent of the failure zone using an elasto-plastic model, and accounting for permeability changes as a function of the induced stresses. For both fully saturated and unsaturated medium cases, the results demonstrate how EGS reservoir growth depends on the initial fluid phase, and how the reservoir extent changes as a function of two critical parameters: (1) the coefficient of friction, and (2) the permeability-enhancement factor. Furthermore, while well stimulation is driven by pressure exceeding the hydroshearing threshold, the modeling also demonstrates how injection-induced cooling further extends the effects of stimulation.

15 GEOTHERMAL ENERGY↗

Advanced Reactors-Intermediate Heat Exchanger (IHX) Coupling: Theoretical Modeling and Experimental Validation

The overall goal of the research project was to model the behavior of the advanced reactorintermediate heat exchange system and to develop advanced control techniques for off-normal conditions. The specific objectives defined for the project were: 1. To develop the steady-state thermal hydraulic design of the intermediate heat exchanger (IHX); 2. To develop mathematical models to describe the advanced nuclear reactor-IHX-chemical process/power generation coupling during normal and off-normal operations, and to simulate models using multiphysics software; 3. To develop control strategies using genetic algorithm or neural network techniques and couple these techniques with the multiphysics software; 4. To validate the models experimentally The project objectives were accomplished by defining and executing four different tasks corresponding to these specific objectives. The first task involved selection of IHX candidates and developing steady state designs for those. The second task involved modeling of the transient and offnormal operation of the reactor-IHX system. The subsequent task dealt with the development of control strategies and involved algorithm development and simulation. The last task involved experimental validation of the thermal hydraulic performances of the two prototype heat exchangers designed and fabricated for the project at steady state and transient conditions to simulate the coupling of the reactor- IHX-process plant system. The experimental work utilized the two test facilities at The Ohio State University (OSU) including one existing High-Temperature Helium Test Facility (HTHF) and the newly developed high-temperature molten salt facility.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Collective dynamics in atomistic models with coupled translational and spin degrees of freedom

When using an atomistic model that simultaneously treats the dynamics of translational and spin degrees of freedom, we perform combined molecular and spin dynamics simulations to investigate the mutual influence of the phonons and magnons on their respective frequency spectra and lifetimes in ferromagnetic bcc iron. Furthermore, by calculating the Fourier transforms of the space- and time-displaced correlation functions, the characteristic frequencies and the linewidths of the vibrational and magnetic excitation modes were determined. A comparison of the results with that of the stand-alone molecular dynamics and spin dynamics simulations reveals that the dynamic interplay between the phonons and magnons leads to a shift in the respective frequency spectra and a decrease in the lifetimes. Moreover, in the presence of lattice vibrations, additional longitudinal magnetic excitations were observed with the same frequencies as the longitudinal phonons.

74 ATOMIC AND MOLECULAR PHYSICS↗

Understanding Diverse Model Projections of Future Extreme El Niño

The majority of future projections in the Coupled Model Intercomparison Project (CMIP5) show more frequent exceedances of the 5 mm day -1 rainfall threshold in the eastern equatorial Pacific rainfall during El Niño, previously described in the literature as an increase in “extreme El Niño events”; however, these exceedance frequencies vary widely across models, and in some projections actually decrease. Here we combine single-model large ensemble simulations with phase 5 of the Coupled Model Intercomparison Project (CMIP5) to diagnose the mechanisms for these differences. The sensitivity of precipitation to local SST anomalies increases consistently across CMIP-class models, tending to amplify extreme El Niño occurrence; however, changes to the magnitude of ENSO-related SST variability can drastically influence the results, indicating that understanding changes to SST variability remains imperative. Future El Niño rainfall intensifies most in models with 1) larger historical cold SST biases in the central equatorial Pacific, which inhibit future increases in local convective cloud shading, enabling more local warming; and 2) smaller historical warm SST biases in the far eastern equatorial Pacific, which enhance future reductions in stratus cloud, enabling more local warming. Additionally, these competing mechanisms complicate efforts to determine whether CMIP5 models under- or overestimate the future impacts of climate change on El Niño rainfall and its global impacts. However, the relation between future projections and historical biases suggests the possibility of using observable metrics as “emergent constraints” on future extreme El Niño, and a proof of concept using SSTA variance, precipitation sensitivity to SST, and regional SST trends is presented.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Time-Dependent Cryospheric Longwave Surface Emissivity Feedback in the Community Earth System Model

Frozen and unfrozen surfaces exhibit different longwave surface emissivities with different spectral characteristics, and outgoing longwave radiation and cooling rates are reduced for unfrozen scenes relative to frozen ones. In this paper physically realistic modeling of spectrally resolved surface emissivity throughout the coupled model components of the Community Earth System Model (CESM) is advanced, and implications for model high-latitude biases and feedbacks are evaluated. It is shown that despite a surface emissivity feedback amplitude that is, at most, a few percent of the surface albedo feedback amplitude, the inclusion of realistic, harmonized longwave, spectrally resolved emissivity information in CESM1.2.2 reduces wintertime Arctic surface temperature biases from -7.2 ± 0.9 K to -1.1 ± 1.2 K, relative to observations. The bias reduction is most pronounced in the Arctic Ocean, a region for which Coupled Model Intercomparison Project version 5 (CMIP5) models exhibit the largest mean wintertime cold bias, suggesting that persistent polar temperature biases can be lessened by including this physically based process across model components. The ice emissivity feedback of CESM1.2.2 is evaluated under a warming scenario with a kernel-based approach, and it is found that emissivity radiative kernels exhibit water vapor and cloud cover dependence, thereby varying spatially and decreasing in magnitude over the course of the scenario from secular changes in atmospheric thermodynamics and cloud patterns. Finally, accounting for the temporally varying radiative responses can yield diagnosed feedbacks that differ in sign from those obtained from conventional climatological feedback analysis methods.

54 ENVIRONMENTAL SCIENCES↗

Impact of Lateral Mixing in the Ocean on El Nino in a Suite of Fully Coupled Climate Models

Abstract We examine the dependence of the amplitude of the El Nino‐Southern Oscillation (ENSO) on the mixing coefficient parameterizing the lateral mixing of tracers (A Redi ) The value of this coefficient is very uncertain, ranging in Earth System Models between a few hundred and a few thousand m 2 s −1 , with some observational estimates showing even higher values. A suite of simulations is made with two spatially varying distributions of A Redi derived from satellite observations as well as four simulations where a spatially constant A Redi is varied over a factor of 6. Surprisingly, larger values of A Redi result in stronger ENSO variability despite the higher mixing coefficients producing more efficient lateral diffusive damping of anomalies. This is because lateral mixing also warms the cold tongue, increasing vertical temperature gradients and decreasing horizontal temperature gradients. Larger vertical temperature gradients make sea surface temperatures more responsive to atmospheric forcing, while smaller horizontal temperature gradients shift the location of convection and make the atmosphere more responsive to sea surface temperature anomalies. The last effect holds across simulations as well as within individual simulations and thus also helps to explain interdecadal variability in ENSO amplitude. By contrast, a previously proposed anticorrelation between the amplitude interannual and annual variability does not hold across simulations, although it does hold within simulations. The propagation of thermocline depth anomalies is relatively insensitive to the value of A Redi . Properly specifying the lateral mixing along the equator (including distinguishing the impacts of subgridscale turbulence and tropical instability waves) appears essential to simulating ENSO.

54 ENVIRONMENTAL SCIENCES↗

The Community Earth System Model: A Framework for Collaborative Research

The Community Earth System Model (CESM) is a flexible and extensible community tool used to investigate a diverse set of earth system interactions across multiple time and space scales. This global coupled model is a natural evolution from its predecessor, the Community Climate System Model, following the incorporation of new earth system capabilities. These include the ability to simulate biogeochemical cycles, atmospheric chemistry, ice sheets, and a high-top atmosphere. These and other new model capabilities are enabling investigations into a wide range of pressing scientific questions, providing new predictive capabilities and increasing our collective knowledge about the behavior and interactions of the earth system. Simulations with numerous configurations of the CESM have been provided to the Coupled Model Intercomparison Project Phase 5 (CMIP5) and are being analyzed by the broader community of scientists. Additionally, the model source code and associated documentation are freely available to the scientific community to use for earth system studies, making it a true community tool. Here we describe this earth modeling system, its various possible configurations, and illustrate its capabilities with a few science highlights.

atmosperic chemistry↗

Machine learning coupled multi-scale modeling for redox flow batteries

The reaction distribution in macro or device-scale has been studied for redox flow batteries. The reaction distribution on electrode pore-scale structure however is not well understood, lacking especially on how the reaction distribution on the pore-scale may impact the overall performance of a flow battery. This study introduces for the first time a framework of a multi-scale model that provides understanding of the relationship between the pore-scale electrode structure reaction and the device-scale electrochemical reaction uniformity within the flow battery. A reduced order model is constructed based on 128 pore-scale simulations, which provide a quantitative relationship between the battery operation conditions (inlet velocity, current density, inlet concentration) and the surface reaction uniformity for the pore-scale sample. The multi-scale framework upscales this pore-scale surface reaction uniformity to device-scale combined uniformity. Based on the multi-scale model, a time-varying optimization of the inlet velocity is established, leading to significant reduction on pump power consumption with targeted surface reaction uniformity. The multi-scale model establishes the critical link between the micro-structure of a flow battery component and its performance at the macro-scale, therefore providing rationale for further operational or material optimization.

flow batteries, machine learning, multi-scale mode↗

Climate Change Projections in CESM1(CAM5) Compared to CCSM4

Future climate change projections for phase 5 of the Coupled Model Intercomparison Project (CMIP5) are introduced for the Community Earth System Model version 1 that includes the Community Atmospheric Model version 5 [CESM1(CAM5)]. These findings are compared to the Community Climate System Model, version 4 (CCSM4) and include simulations using the representative concentration pathway (RCP) mitigation scenarios, and extensions for those scenarios beyond 2100 to 2300. Equilibrium climate sensitivity of CESM1(CAM5) is 4.10°C, which is higher than the CCSM4 value of 3.20°C. The transient climate response is 2.33°C, compared to the CCSM4 value of 1.73°C. Thus, even though CESM1(CAM5) includes both the direct and indirect effects of aerosols (CCSM4 had only the direct effect), the overall climate system response including forcing and feedbacks is greater in CESM1(CAM5) compared to CCSM4. The Atlantic Ocean meridional overturning circulation (AMOC) in CESM1(CAM5) weakens considerably in the twenty-first century in all the RCP scenarios, and recovers more slowly in the lower forcing scenarios. The total aerosol optical depth (AOD) changes from ~0.12 in 2006 to ~0.10 in 2100, compared to a preindustrial 1850 value of 0.08, so there is less negative forcing (a net positive forcing) from that source during the twenty-first century. As a result, the change from 2006 to 2100 in aerosol direct forcing in CESM1(CAM5) contributes to greater twenty-first century warming relative to CCSM4. There is greater Arctic warming and sea ice loss in CESM1(CAM5), with an ice-free summer Arctic occurring by about 2060 in RCP8.5 (2040s in September) as opposed to about 2100 in CCSM4 (2060s in September).

54 ENVIRONMENTAL SCIENCES↗

Shell-model coupled-cluster method for open-shell nuclei

An approach to derive effective shell-model interactions from microscopic nuclear forces is introduced here. The similarity transformed coupled-cluster Hamiltonian decouples the single-reference state of a closed-shell nucleus and provides us with a core for the shell model. We use a second similarity transformation to decouple a shell-model space from the excluded space. We show that the three-body terms induced by both similarity transformations are crucial for an accurate computation of ground and excited states. As a proof of principle we use a nucleon-nucleon interaction from chiral effective field theory, employ a 4 He core, and compute low-lying states of 6–8 He and 6–8 Li in p -shell model spaces. Our conclusions agree with benchmarks from full configuration interaction.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Multi-decadal variation of ENSO forecast skill since the late 1800s

Diagnosing El Niño-Southern Oscillation (ENSO) predictability within operational forecast models is hindered by computational expense and the need for initialization with three-dimensional fields generated by global data assimilation. We instead examine multi-year ENSO predictability since the late 1800s using the model-analog technique, which has neither limitation. We first draw global coupled model states from pre-industrial control simulations, from the Coupled Model Intercomparison Project Phase 6, that are chosen to initially match observed monthly sea surface temperature and height anomalies in the Tropics. Their subsequent 36-month model evolution are the hindcasts, whose 20th century ENSO skill is comparable to twice-yearly hindcasts generated by a state-of-the-art European operational forecasting system. Despite the so-called spring predictability barrier, present throughout the record, there is substantial second-year ENSO skill, especially after 1960. Overall, ENSO exhibited notably high values of both amplitude and skill towards the end of the 19th century, and again in recent decades.

54 ENVIRONMENTAL SCIENCES↗

Natural Fracture Pattern Development Using 3D Coupled Numerical Model: Mechanics and Diagenesis

In the earth's crust, while tectonic processes can mechanically create natural fractures, cementation can simultaneously grow on the surfaces of the fractures. This crystallization can affect the growth of the fractures. To more accurately address the modeling of natural fracture development, both mechanical deformation and chemical diagenesis should be carried out in an integrated manner. Here, we achieve this with a three-dimensional (3D) simulator that couples mechanical and chemical processes for natural fracture pattern development in layer confined situations. Tectonic loading over geologic time is mimicked by displacement driven boundary conditions in a 3D displacement discontinuity method (DDM) scheme. Quartz diagenesis competes with mechanical fracture opening, resulting in three different cementation conditions - open, bridging or fully infilled – which define fracture element stiffness that is used as feedback within the 3D-DDM code during propagation. An important milestone of this work is that this coupled structural diagenetic model can reproduce power-law aperture population statistics which cannot be generated using mechanics alone. More accurately estimated mechanical fracture apertures and their cementation condition is a critical step toward better permeability estimation and fluid path analysis for subsurface reservoirs.

58 GEOSCIENCES↗

An automatic performance model-based scheduling tool for coupled climate system models

The prediction of the climate system is highly depended on the efficient integration of observations and simulations of the Earth. This is regarded as a canonical example of the cyber-physical system. The climate system model, the simulation engine in this cyber-physical system, is one of most challenging applications in scientific computing. It utilizes the multi-physics simulation that couples multiple components, conducts decadal to millennium simulations, and has long been an important application on supercomputers. However, current climate system models suffer from the inefficient task scheduling methods resulting in an intolerable simulation time. Take the Community Earth System Model (CESM), the most widely used climate system model, as an example, one major reason that CESM suffers from bad performances is the huge overhead to rationally distribute processes among the coupled heterogeneous components. According to the report of NCAR, every percent improvement in CESM performance frees up to the equivalent of $250,000 in computing resources in their scientific experiments. To address such challenge, our paper firstly constructs a lightweight and accurate performance model for effectively capturing and predicting the heterogeneous time-to-solution performance of end-to-end CESM components with a given simulation configuration. Then, based on the performance model, we further propose an efficient scheduling strategy based on rectangular packing method to determine the best process layout among different components, and the process numbers assigned to each component. Our evaluations show that we can achieve 58% average run time reductions on CESM comparing to the widely used sequential process layout for a scale of 144 to 480 cores on typical CPU clusters. And we can save 4 million CPU hours when we conduct one standard scientific experiment (a 2870-year simulation), which equals to save $40,089 with a charge of $0.01 per CPU hour. Meanwhile, 26% extra performance improvements could also be gained in our methods comparing to the heuristic branch and bound algorithm with the guidance of the known curve-fitting performance model.

58 GEOSCIENCES↗

Understanding the Biases in Global Monsoon Simulations from the Perspective of Atmospheric Energy Transport

Understanding global monsoon (GM) variability and projecting its future changes rely heavily on climate models. However, climate models generally show pronounced biases in GM simulations, and the reasons for this remain unclear. Here, in this study, we evaluate the performance of 20 pairs of climate models that participated in both phase 5 of the Coupled Model Intercomparison Project (CMIP5) and phase 6 of CMIP (CMIP6) and identify the sources of their GM simulation biases from an energy transport perspective. The multimodel mean improvement in CMIP6 compared to CMIP5 is demonstrated by the increasing skill scores for various GM metrics from 0.20–0.79 to 0.48–0.83. More specifically, the dry biases in the Northern Hemisphere Summer Monsoon (NHSM) precipitation in CMIP5 [root-mean-square error (RMSE): 1.85 mm day −1 ] are reduced in CMIP6 (RMSE: 1.66 mm day −1 ). This higher simulation skill is associated with higher skill in simulating the precipitation-solstitial mode, monsoon intensity, and monsoon domains. The improvement in the NHSM precipitation simulation results from that in the meridional transport of atmospheric energy. Atmospheric energy budget analysis shows that the negative biases in downward surface longwave radiation and northward energy transport are smaller in CMIP6 than in CMIP5 in the boreal summer, resulting in a more realistic interhemispheric thermal contrast and meridional gradient of moist static energy. However, a major weakness of the CMIP6 models is found in the Southern Hemisphere Summer Monsoon precipitation simulation due to the positive bias in the top-of-the-atmosphere downward longwave radiation. This study shows that reasonably reproducing the meridional global atmospheric energy transportation is necessary for skillful GM simulation.

54 ENVIRONMENTAL SCIENCES↗

Integrated Cyber/Physical Grid Resiliency Modeling

This project explored coupling modeling and analysis methods from multiple domains to address complex hybrid (cyber and physical) attacks on mission critical infrastructure. Robust methods to integrate these complex systems are necessary to enable large trade-space exploration including dynamic and evolving cyber threats and mitigations. Reinforcement learning employing deep neural networks, as in the AlphaGo Zero solution, was used to identify "best" (or approximately optimal) resilience strategies for operation of a cyber/physical grid model. A prototype platform was developed and the machine learning (ML) algorithm was made to play itself in a game of 'Hurt the Grid'. This proof of concept shows that machine learning optimization can help us understand and control complex, multi-dimensional grid space. A simple, yet high-fidelity model proves that the data have spatial correlation which is necessary for any optimization or control. Our prototype analysis showed that the reinforcement learning successfully improved adversary and defender knowledge to manipulate the grid. When expanded to more representative models, this exact type of machine learning will inform grid operations and defense - supporting mitigation development to defend the grid from complex cyber attacks! This same research can be expanded to similar complex domains.

97 MATHEMATICS AND COMPUTING↗

Earth's energy imbalance since 1960 in observations and CMIP5 models: Earth's energy imbalance since 1960

Observational analyses of running 5 year ocean heat content trends (Ht) and net downward top of atmosphere radiation (N) are significantly correlated (r ~ 0.6) from 1960 to 1999, but a spike in Ht in the early 2000s is likely spurious since it is inconsistent with estimates of N from both satellite observations and climate model simulations. Variations in N between 1960 and 2000 were dominated by volcanic eruptions and are well simulated by the ensemble mean of coupled models from the Fifth Coupled Model Intercomparison Project (CMIP5). Here, we find an observation-based reduction in N of -0.31 ± 0.21 W m -2 between 1999 and 2005 that potentially contributed to the recent warming slowdown, but the relative roles of external forcing and internal variability remain unclear. Finally, while present-day anomalies of N in the CMIP5 ensemble mean and observations agree, this may be due to a cancelation of errors in outgoing longwave and absorbed solar radiation.

58 GEOSCIENCES↗