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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 1,279 records · Page 71

FTK: A Simplicial Spacetime Meshing Framework for Robust and Scalable Feature Tracking

In this work, we present the Feature Tracking Kit (FTK), a framework that simplifies, scales, and delivers various feature-tracking algorithms for scientific data. The key of FTK is our simplicial spacetime meshing scheme that generalizes both regular and unstructured spatial meshes to spacetime while tessellating spacetime mesh elements into simplices. The benefits of using simplicial spacetime meshes include (1) reducing ambiguity cases for feature extraction and tracking, (2) simplifying the handling of degeneracies using symbolic perturbations, and (3) enabling scalable and parallel processing. The use of simplicial spacetime meshing simplifies and improves the implementation of several feature-tracking algorithms for critical points, quantum vortices, and isosurfaces. As a software framework, FTK provides end users with VTK/ParaView filters, Python bindings, a command line interface, and programming interfaces for feature-tracking applications. We demonstrate use cases as well as scalability studies through both synthetic data and scientific applications including tokamak, fluid dynamics, and superconductivity simulations. We also conduct end-to-end performance studies on the Summit supercomputer. FTK is open sourced under the MIT license: https://github.com/hguo/ftk.

97 MATHEMATICS AND COMPUTING↗

Measurement of flow properties coupled to experimental and numerical analyses of dense, granular flows for solar thermal energy storage

Granular flows of sintered bauxite proppants were researched along an inclined plane for solar thermal energy storage applications. Granular flow properties needed to drive numeric granular models were measured for improved numerical model predictions for Carbobead CP 50/140, 40/100, and 30/60 particles. Particle shape and size distributions were determined by coupling optical microscopy to an in-house image processing algorithm. The impulse excitation technique was used to measure elastic and shear moduli, and compute Poisson’s ratio. The coefficient of static sliding friction was measured using the slip-stick method, and the static rolling friction was determined from measured shear on particles positioned between two hot-pressed plates. The coefficient of restitution was measured by dropping particles on a surface and determining the kinetic energy before and after impact with the surface using high resolution particle tracking velocimetry. Particle size did not significantly impact the coefficients of restitution and static rolling friction, however, particle shape distribution resulted in a large variation in measurements. An inclined flow experiment was performed to characterize granular flows of Carbobead CP 30/60 particles using particle image velocimetry. Numerical models of the experiment using discrete element method were generated with the measured mechanical properties as inputs for comparison with experimental results. A constant directional torque rolling friction model best predicted bulk granular flow behavior. Furthermore, good agreement between the model and experiment was achieved at ambient, steady state conditions, with average velocity differences <10%.

14 SOLAR ENERGY↗

A steering law for a roof-type configuration for a single-gimbal control moment gyro system

Single-Gimbal Control Moment Gyro (SGCMG) systems have been investigated for attitude control of the Large Space Telescope (LST) and the High Energy Astronomy Observatory (HEAO). However, various proposed steering laws for the SGCMG systems thus far have some defects because of singular states of the system. In this report, a steering law for a roof-type SGCMG system is proposed which is based on a new momentum distribution scheme that makes all the singular states unstable. This momentum distribution scheme is formulated by a treatment of the system as a sampled-data system. From analytical considerations, it is shown that this steering law gives control performance which is satisfactory for practical applications. Results of the preliminary computer simulation entirely support this premise.

Yoshikawa, T.↗

The numerical simulation of a high-speed axial flow compressor

The advancement of high-speed axial-flow multistage compressors is impeded by a lack of detailed flow-field information. Recent development in compressor flow modeling and numerical simulation have the potential to provide needed information in a timely manner. The development of a computer program is described to solve the viscous form of the average-passage equation system for multistage turbomachinery. Programming issues such as in-core versus out-of-core data storage and CPU utilization (parallelization, vectorization, and chaining) are addressed. Code performance is evaluated through the simulation of the first four stages of a five-stage, high-speed, axial-flow compressor. The second part addresses the flow physics which can be obtained from the numerical simulation. In particular, an examination of the endwall flow structure is made, and its impact on blockage distribution assessed.

Mulac, Richard A.↗

An Experimental and Computational Study on Soot Formation in a Coflow Jet Flame Under Microgravity and Normal Gravity

Upon the completion of the Structure and Liftoff in Combustion Experiment (SLICE) in March 2012, a comprehensive and unique set of microgravity coflow diffusion flame data was obtained. This data covers a range of conditions from weak flames near extinction to strong, highly sooting flames, and enabled the study of gravitational effects on phenomena such as liftoff, blowout and soot formation. The microgravity experiment was carried out in the Microgravity Science Glovebox (MSG) on board the International Space Station (ISS), while the normal gravity experiment was performed at Yale utilizing a copy of the flight hardware. Computational simulations of microgravity and normal gravity flames were also carried out to facilitate understanding of the experimental observations. This paper focuses on the different sooting behaviors of CH4 coflow jet flames in microgravity and normal gravity. The unique set of data serves as an excellent test case for developing more accurate computational models.Experimentally, the flame shape and size, lift-off height, and soot temperature were determined from line-of-sight flame emission images taken with a color digital camera. Soot volume fraction was determined by performing an absolute light calibration using the incandescence from a flame-heated thermocouple. Computationally, the MC-Smooth vorticity-velocity formulation was employed to describe the chemically reacting flow, and the soot evolution was modeled by the sectional aerosol equations. The governing equations and boundary conditions were discretized on an axisymmetric computational domain by finite differences, and the resulting system of fully coupled, highly nonlinear equations was solved by a damped, modified Newtons method. The microgravity sooting flames were found to have lower soot temperatures and higher volume fraction than their normal gravity counterparts. The soot distribution tends to shift from the centerline of the flame to the wings from normal gravity to microgravity.

microgravity↗

Impact of Satellite Viewing-Swath Width on Global and Regional Aerosol Optical Thickness Statistics and Trends

We use the Moderate Resolution Imaging Spectroradiometer (MODIS) satellite aerosol optical thickness (AOT) product to assess the impact of reduced swath width on global and regional AOT statistics and trends. Alongtrack and across-track sampling strategies are employed, in which the full MODIS data set is sub-sampled with various narrow-swath (approximately 400-800 km) and single pixel width (approximately 10 km) configurations. Although view-angle artifacts in the MODIS AOT retrieval confound direct comparisons between averages derived from different sub-samples, careful analysis shows that with many portions of the Earth essentially unobserved, spatial sampling introduces uncertainty in the derived seasonal-regional mean AOT. These AOT spatial sampling artifacts comprise up to 60%of the full-swath AOT value under moderate aerosol loading, and can be as large as 0.1 in some regions under high aerosol loading. Compared to full-swath observations, narrower swath and single pixel width sampling exhibits a reduced ability to detect AOT trends with statistical significance. On the other hand, estimates of the global, annual mean AOT do not vary significantly from the full-swath values as spatial sampling is reduced. Aggregation of the MODIS data at coarse grid scales (10 deg) shows consistency in the aerosol trends across sampling strategies, with increased statistical confidence, but quantitative errors in the derived trends are found even for the full-swath data when compared to high spatial resolution (0.5 deg) aggregations. Using results of a model-derived aerosol reanalysis, we find consistency in our conclusions about a seasonal-regional spatial sampling artifact in AOT Furthermore, the model shows that reduced spatial sampling can amount to uncertainty in computed shortwave top-ofatmosphere aerosol radiative forcing of 2-3 W m(sup−2). These artifacts are lower bounds, as possibly other unconsidered sampling strategies would perform less well. These results suggest that future aerosol satellite missions having significantly less than full-swath viewing are unlikely to sample the true AOT distribution well enough to obtain the statistics needed to reduce uncertainty in aerosol direct forcing of climate.

remote sensing↗

Computational Math Problems for a Clean Energy Future

Cutting edge computational mathematics are ubiquitous in renewable energy research. Problems in resilient and reliable electric grid operations, infrastructure planning, wind farm yaw control, and more demand sophisticated and scalable computational tools that enable the transition of renewable energy technologies from proof of concept to deployment into our energy system. The mission of the Computational Science Center at NREL is to lead the lab's efforts to solve energy challenges using high-performance computing (HPC), computational science, applied mathematics, scientific data management, visualization, and informatics. In this poster, we provide a short overview of three areas of computational mathematics research at NREL: wind power scenario generation for stochastic grid operations and infrastructure planning, improved rational function approximations for electromagnetic transients codes, and wind farm yaw control using a combination of the Alternating Direction Method of Multipliers (ADMM) and reinforcement learning (RL). Increasing penetrations of renewable energy into power grids motivate the investigation of new approaches to characterizing uncertainty for five-minute economic dispatch problems. Similarly, as the penetration of distributed energy resources on power grids increases, it becomes important to revisit our methods of modelling transient phenomena, i.e. electromagnetic transients programs. Finally, the combination of ADMM and RL for wind farm yaw control presented here can potentially increase the efficiency of the deployed distributed controllers by orders of magnitude.

ADMM↗

Numerical study of proppant transport and settling processes in fractures

Reservoir stimulation by creating hydraulically conductive fractures is the key step for enabling enhanced geothermal systems (EGS). The effectiveness of stimulation is significantly influenced by the deposition of proppant inside induced fractures. The transportation and settling of proppant in a propagating fracture is controlled by a multitude of operational and physical parameters, including the fracturing fluid rheology, injection rate, proppant concentration, fracture length/aperture evolution, proppant size/density/shape, etc. A numerical tool that robustly and efficiently accounts for all important attributes can facilitate the design and optimization of reservoir stimulation. This study presents the novel computational tool ELK (ELectrical fracKing) developed for the numerical simulation of proppant-fluid mixture circulation in a fractured geothermal reservoir. We enriched the MOOSE-based PorousFlow module with a suite of equations to consider the fluid-proppant mixture with particle-particle/fluid interactions, which include gravitational settling, particle convection, particle hampering, and strong density and viscosity contrasts. The computational tool is validated by comparing the predicted proppant bed evolution against two different laboratory scale experiments of proppant transport in a fixed aperture channel. Further parameter studies were performed, and the modeling results show that the proppant deposition is determined by the mixing characteristics and settling of the particles from the slurry. Concentration-dependent density and viscosity lead to an inhomogeneous distribution of the proppant, particle collision, and enhanced settling at the bottom of the fractures. Preliminary coupling with dynamic fracture propagation shows promising results and will be further developed to simulate hydraulic stimulation at high fidelity.

15 GEOTHERMAL ENERGY↗

Rapid Spacecraft Payload Development: In-Orbit Demonstration of Flight Software Reuse, Scalability, and Dependability

As space mission design trends towards shared, multi-mission platforms and high-performance onboard computing architectures, the number of spacecraft launched into operation is also steadily rising. Through ridesharing, spacecraft miniaturization, and other cost-reduction measures, the barriers to space are lowering, resulting in compounded growth in the amount of flight software being deployed. To meet the needs of both the growing quantity and evolving nature of spacecraft, flight software design must accordingly adapt to support more efficient development, solutions to computational resource-sharing, and software reusability. This paper focuses on a software payload demonstrating several core technologies that improve the state-of-the-art in these identified areas. Launched into low-earth orbit in January 2022, our software payload was conceived, designed, and delivered in a span of merely two months. It was developed on top of the NASA core Flight System (cFS) framework and the Distributed Spacecraft Autonomy (DSA) Comm cFS application, which translates cFS software bus messages across a Data Distribution Service (DDS) network. The flight software, packaged in Linux container images, was deployed as one of 18 flight applications managed through the Unibap SpaceCloud Framework. The applications were run on a Unibap iX5-102 radiation-tolerant payload computer, hosted on the D-Orbit SCV-004 spacecraft as part of an ESA-sponsored in-orbit technology test. Our payload, referred to as the DSA D-Orbit software, demonstrates the reusability of the DSA Comm app in a substantially different context and purpose as its original mission. Comm’s original design goal was to reliably distribute messages between spacecraft swarms of arbitrary size and dynamic network topology. However, we leverage this same functionality to introduce redundancy and opportunistic parallel data processing in the context of a representative onboard image processing workload. This adaptive mission architecture was enabled in part by the SpaceCloud Framework’s use of container virtualization as the payload integration interface. By using a base container image with common high-level language runtimes and libraries, we were able to rapidly design, develop, and validate our image processing application without many of the technological barriers common to flight software development. We present details the goals, approach, results, and lessons learned through this technology demonstration experiment and contextualize those observations against present and future challenges in spacecraft software development.

computer programming↗

A Cellular Automaton Simulation for Predicting Phase Evolution in Solid-State Reactions

New computational tools for solid-state synthesis recipe design are needed in order to accelerate the experimental realization of novel functional materials proposed by high-throughput materials discovery workflows. This work contributes a cellular automaton simulation framework for predicting the time-dependent evolution of intermediate and product phases during solid-state reactions as a function of precursor choice and amount, reaction atmosphere, and heating profile. The simulation captures the effects of reactant particle spatial distribution, particle melting, and reaction atmosphere. Reaction rates based on rudimentary kinetics are estimated using density functional theory data from the Materials Project and machine learning estimators for the melting point and the vibrational entropy component of the Gibbs free energy. The resulting simulation framework allows for the prediction of the likely outcome of a reaction recipe before any experiments are performed. We analyze five experimental solid-state recipes for BaTiO 3 , CaZrN 2 , and YMnO 3 found in the literature to illustrate the performance of the model in capturing reaction selectivity and reaction pathways as a function of temperature and precursor choice. This simulation framework offers an easier way to optimize existing recipes, aid in the identification of intermediates, and design effective recipes for yet unrealized inorganic solids in silico .

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

ARCADIA and advanced methods licensing and implementation update

AREVA NP is implementing a consistent code and methodology suite for core design and safety analysis, based on first principles modeling with an extremely broad verification and validation data base. Thanks to the high computational power increase in the last decades methods' development and application now include capabilities that were not available in the past. An example is the 3D coupled transient core power distribution characterization, which allows more realistic modeling of plant behavior, removal of inaccuracies by high resolution and access to local information. Another one is the progressive replacement, respectively complement of old deterministic methods by order statistics. This paper provides an update of the current licensing and implementation status of the main AREVA NP new codes (ARCADIA, GALILEO, S-RELAP5) and their associated advanced methods for PWR applications. ARCADIA is the state-of-the-art neutron transport/ thermal-hydraulics (TH)/ thermal-mechanics (TM) code system for PWR applications. Development is completed, implementation started in France, the Netherlands, the U.S.A. and other countries. The extension to BWR applications is on-going. GALILEO is the state-of-the-art fuel rod performance code for PWR and BWR applications. Development is completed, implementation started in France and the U.S.A. S-RELAP5 is a thermal-hydraulic code that has been completely re-coded and modernized in terms of software architecture. S-RELAP5 has been successfully coupled with ARCADIA. It is shown that advanced codes and integrated methods for accident analysis are keys for extending the fuel cycle design space.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Modeling Distributed Computing Infrastructures for HEP Applications

Predicting the performance of various infrastructure design options in complex federated infrastructures with computing sites distributed over a wide area network that support a plethora of users and workflows, such as the Worldwide LHC Computing Grid (WLCG), is not trivial. Due to the complexity and size of these infrastructures, it is not feasible to deploy experimental test-beds at large scales merely for the purpose of comparing and evaluating alternate designs. An alternative is to study the behaviours of these systems using simulation. This approach has been used successfully in the past to identify efficient and practical infrastructure designs for High Energy Physics (HEP). A prominent example is the Monarc simulation framework, which was used to study the initial structure of the WLCG. New simulation capabilities are needed to simulate large-scale heterogeneous computing systems with complex networks, data access and caching patterns. A modern tool to simulate HEP workloads that execute on distributed computing infrastructures based on the SimGrid and WRENCH simulation frameworks is outlined. Studies of its accuracy and scalability are presented using HEP as a case-study. Hypothetical adjustments to prevailing computing architectures in HEP are studied providing insights into the dynamics of a part of the WLCG and candidates for improvements.

Horzela, Maximilian↗

A Runtime Environment for Supporting Research in Resilient HPC System Software &amp; Tools

The high-performance computing (HPC) community continues to increase the size and complexity of hardware platforms that support advanced scientific workloads. The runtime environment (RTE) is a crucial layer in the software stack for these large-scale systems. The RTE manages the interface between the operating system and the application running in parallel on the machine. The deployment of applications and tools on large-scale HPC computing systems requires the RTE to manage process creation in a scalable manner, support sparse connectivity, and provide fault tolerance. We have developed a new RTE that provides a basis for building distributed execution environments and developing tools for HPC to aid research in system software and resilience. This paper describes the software architecture of the Scalable runTime Component Infrastructure (STCI), which is intended to provide a complete infrastructure for scalable start-up and management of many processes in large-scale HPC systems. We highlight features of the current implementation, which is provided as a system library that allows developers to easily use and integrate STCI in their tools and/or applications. The motivation for this work has been to support ongoing research activities in fault-tolerance for large-scale systems. We discuss the advantages of the modular framework employed and describe two use cases that demonstrate its capabilities: (i) an alternate runtime for a Message Passing Interface (MPI) stack, and (ii) a distributed control and communication substrate for a fault-injection tool.

Computer Science↗

Regularizing INR with Diffusion Prior for Self-Supervised 3D Reconstruction OF Neutron Computed Tomography Data

Recently, generative diffusion priors have made huge strides as inverse problem solvers, including the ability to be adapted for inference on out-of-distribution data. Concurrently, implicit neural representations (INRs) have emerged as fast and lightweight inverse imaging solvers that are amenable to hybrid approaches that combine learned priors with traditional inverse problem formulations. In this paper, we present a diffusive computed tomography (CT) inversion framework for regularizing INRs called Diffusive INR (DINR), designed to enable high-quality reconstruction from sparse-view neutron CT. Pretrained purely on synthetic data, DINR is evaluated on simulated and experimentally obtained observations of concrete microstructures, where traditional reconstruction methods suffer substantial degradation when the number of views is reduced. Our approach delivers superior performance, reduces reconstruction artifacts, and achieves gains in PSNR and SSIM, enabling accurate micro-structural characterization even under extreme data limitations compared to state-of-the-art sparse-view reconstruction techniques.

Hossain, Maliha [ORNL]↗

Implementing High-Performance Geometric Multigrid Solver with Naturally Grained Messages

Structured-grid linear solvers often require manually packing and unpacking of communication data to achieve high performance.Orchestrating this process efficiently is challenging, labor-intensive, and potentially error-prone.In this paper, we explore an alternative approach that communicates the data with naturally grained messagesizes without manual packing and unpacking. This approach is the distributed analogue of shared-memory programming, taking advantage of the global addressspace in PGAS languages to provide substantial programming ease. However, its performance may suffer from the large number of small messages. We investigate theruntime support required in the UPC ++ library for this naturally grained version to close the performance gap between the two approaches and attain comparable performance at scale using the High-Performance Geometric Multgrid (HPGMG-FV) benchmark as a driver.

97 MATHEMATICS AND COMPUTING↗

Modeling and Simulation Tool to Improve Urban Search Planning (NA22 Final Report)

The venture project Tool to Improve Urban Search Planning (LL14-V-Urban Search Planning ToolPD3RS) supported two major types of effort: 1) development of a software prototype search planning tool, with the goal of transitioning the tool to operational users for evaluation and possible adoption; 2) enabling research to better understand the radiation characteristics of an urban environment, with implications for deployment of radiation detection systems in that environment. The first effort has resulted in prototype software, Optimization Planning Tool for Urban Search (OPTUS), that has been distributed to a limited set of potential users, including users within the NNSA emergency response community. The second effort supported various research topics including high fidelity radiation transport modeling in urban environments, measurement campaigns for model validation, development of vehicle-based high purity germanium (HPGe) detector systems and supporting data analysis, and computational capabilities for archiving and managing large data sets. While some of these related efforts have informed the models and software design of the OPTUS tool, in large part they pursued more basic research, some of which has evolved into separate DNN R&D projects. Project performers included Oak Ridge National Laboratory (ORNL), Lawrence Berkeley National Laboratory (LBNL) and the Remote Sensing Laboratory (RSL), in addition to Lawrence Livermore Laboratory (LLNL), the project lead. The project also supported university research, including several internships at the laboratories.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Inverse design of a proper number, shapes, sizes, and locations of coolant flow passages

During the past several years we have developed an inverse method that allows a thermal cooling system designer to determine proper sizes, shapes, and locations of coolant passages (holes) in, say, an internally cooled turbine blade, a scram jet strut, a rocket chamber wall, etc. Using this method the designer can enforce a desired heat flux distribution on the hot outer surface of the object, while simultaneously enforcing desired temperature distributions on the same hot outer surface as well as on the cooled interior surfaces of each of the coolant passages. This constitutes an over-specified problem which is solved by allowing the number, sizes, locations and shapes of the holes to adjust iteratively until the final internally cooled configuration satisfies the over-specified surface thermal conditions and the governing equation for the steady temperature field. The problem is solved by minimizing an error function expressing the difference between the specified and the computed hot surface heat fluxes. The temperature field analysis was performed using our highly accurate boundary integral element code with linearly varying temperature along straight surface panels. Examples of the inverse design applied to internally cooled turbine blades and scram jet struts (coated and non-coated) having circular and non-circular coolant flow passages will be shown.

George S. Dulikravich↗

X-57 “Maxwell” High-Lift Propeller Testing and Model Development

NASA’s X-57 “Maxwell” distributed electric propulsion flight demonstrator has a high-lift system that includes 12 fixed-pitch high-lift propellers located upstream of the wing leading edge for lift augmentation at low speeds. These high-lift propellers are not required at higher speeds and are folded conformally along the nacelles to reduce drag when not in operation. Aircraft performance models and flight simulations incorporate propeller performance to predict thrust, moments, and power consumption and propeller model accuracy is important in identifying safe operating regimes for this aircraft. Current high-lift propeller performance models have been verified and calibrated against numerous computational fluid dynamics analyses under a variety of flight conditions. We performed a series of full-scale wind tunnel tests at the NASA Langley Research Center Low Speed Aeroacoustic Wind Tunnel to further validate these models, to identify any adverse operating conditions for these propellers, and to assess the accuracy of the facility’s new Propeller Test Stand. The results indicate that the models accurately predicted performance and that the right-handed propeller showed lower torque and thrust for a given propeller speed compared to the left-handed version. Acoustic data support these measurements, showing higher tonal noise for the left versus right propeller. We suspect this is due to slight differences in the material properties between the early production (right) and more recent (left) blade sets leading to greater detwisting in the right-handed blades under load. Both propellers demonstrated very stable operation throughout the test including during deployment, stowing, and windmilling. Furthermore, high-speed imagery of the spinning propeller indicated no blade oscillations or instabilities for any test case. We also leveraged these images to analyze the effects of propeller loading on blade detwisting and tip position. Unfortunately, the thrust measurements varied significantly during the test due to cross-loading of the Propeller Test Stand load cell, though trends in the thrust data were still observable. The torque measurement, however, remained very precise for all test points and was used for performance comparisons. As a result of this test, we validated and improved the X-57 high-lift propeller performance models, obtained detailed propeller acoustic data and high-speed imagery, observed the propeller operating safely during a variety of dynamic events, and identified two potentially adverse, low-propeller-speed conditions which will be avoided during normal aircraft operation.

X-57↗