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At least 433 records · Page 24

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NASA NTRS2003

Finite-Element Methods for Real-Time Simulation of Surgery

Two finite-element methods have been developed for mathematical modeling of the time-dependent behaviors of deformable objects and, more specifically, the mechanical responses of soft tissues and organs in contact with surgical tools. These methods may afford the computational efficiency needed to satisfy the requirement to obtain computational results in real time for simulating surgical procedures as described in Simulation System for Training in Laparoscopic Surgery (NPO-21192) on page 31 in this issue of NASA Tech Briefs. Simulation of the behavior of soft tissue in real time is a challenging problem because of the complexity of soft-tissue mechanics. The responses of soft tissues are characterized by nonlinearities and by spatial inhomogeneities and rate and time dependences of material properties. Finite-element methods seem promising for integrating these characteristics of tissues into computational models of organs, but they demand much central-processing-unit (CPU) time and memory, and the demand increases with the number of nodes and degrees of freedom in a given finite-element model. Hence, as finite-element models become more realistic, it becomes more difficult to compute solutions in real time. In both of the present methods, one uses approximate mathematical models trading some accuracy for computational efficiency and thereby increasing the feasibility of attaining real-time up36 NASA Tech Briefs, October 2003 date rates. The first of these methods is based on modal analysis. In this method, one reduces the number of differential equations by selecting only the most significant vibration modes of an object (typically, a suitable number of the lowest-frequency modes) for computing deformations of the object in response to applied forces.

Basdogan, Cagatay↗

NASA NTRSDate not supplied

Using Thermal Desktop to Model the Effects of Plume Heating on MLI

Gateway draws on experience from International Space Station (ISS) and geostationary satellites for many aspects of design, including Multilayer Insulation (MLI) material selection. MLI is used on many external surfaces, some of which can be exposed to high plume heating from visiting vehicle during docking and undocking. Due to Gateway’s smaller size and closer proximity of sensitive hardware to plumes from visiting vehicles, the expected and contingency plume heating loads are higher than those experienced by the ISS. Because of MLI’s low mass and thermal conductivity between layers, high plume heating loads can potentially heat MLI past its thermal limits. MLI is typically modeled as a single node of insulation with a given effective emissivity. This method is not adequate for modeling plume heating impacts because the temperature of each individual layer cannot be determined. Modeling MLI is complicated because there are several layers and the conduction between each layer is undefined. It is further complicated by the variety of material options for MLI and their respective mass, optics, transmissivity, and temperature limits. This paper shows modeling of a MLI blanket exposed to solar and plume heating loads using Thermal Desktop. Several sensitivity studies were run including examining distance between layers, varying effective emissivity, effects of different MLI materials, and plume heating loads and durations.

MLI↗

NASA NTRSDate not supplied

Using Thermal Desktop to Model the Effects of Plume Heating on MLI

MLI↗

DOE OSTI2024

Communication engine for hybrid interconnect technologies

Systems, apparatuses, and methods for dynamically selecting between wired and wireless interconnects for sending packets are disclosed. A system includes at least a hybrid communication engine and a plurality of interconnects for connecting to various end-points. The communication engine dynamically discovers and utilizes the best interconnect technology available in between given end-points. The communication engine dynamically chooses the physical interconnect that is best suited at any given time to send data from one source to one or multiple destinations. This communication can be either on-chip or across nodes. The communication engine makes a decision based on a set of predetermined parameters that can be re-adjusted by the application layer, such as latency of the transmission, message data size, physical distance from source to destination, the energy cost, and the current congestion on the alternative interconnects.

Blagodurov, Sergey↗

DOE OSTI2021

Engineering Second Sphere Interactions in a Host–Guest Multicomponent Catalyst System for the Hydrogenation of Carbon Dioxide to Methanol

Many enzymes utilize interactions extending beyond the primary coordination sphere to enhance catalyst activity and/or selectivity. Such interactions could improve the efficacy of synthetic catalyst systems, but the supramolecular assemblies employed by biology to incorporate second sphere interactions are challenging to replicate in synthetic catalysts. Herein, a strategy is reported for efficiently manipulating outer sphere influence on catalyst reactivity by modulating host–guest interactions between a noncovalently encapsulated transitionmetal-based catalyst guest and a metal–organic framework (MOF) host. This composite consists of a ruthenium PNP pincer complex encapsulated in the MOF UiO-66 that is used in tandem with the zirconium oxide nodes of UiO-66 and a ruthenium PNN pincer complex to hydrogenate carbon dioxide to methanol. Due to the method used to incorporate the complexes in UiO-66, structure–activity relationships could be efficiently determined using a variety of functionalized UiO-66-X hosts. These investigations uncovered the beneficial effects of the ammonium functional group (i.e., UiO-66-NH 3 + ). Mechanistic experiments revealed that the ammonium functionality improved efficiency in the hydrogenation of carbon dioxide to formic acid, the first step in the cascade. Isotope effects and structure–activity relationships suggested that the primary role of the ammonium functionality is to serve as a general Brønsted acid. Importantly, the cooperative influence from the host was effective only with the functional group in close proximity to the encapsulated catalyst. Here, reactions carried out in the presence of molecular sieves to remove water highlighted the beneficial effects of the ammonium functional group in UiO-66-NH 3 + and resulted in a 4-fold increase in activity. As a result of the modular nature of the catalyst system, the highest reported turnover number (TON) (19 000) and turnover frequency (TOF) (9100 h –1 ) for the hydrogenation of carbon dioxide to methanol are obtained. Moreover, the reaction was readily recyclable, leading to a cumulative TON of 100 000 after 10 reaction cycles.

08 HYDROGEN↗

DOE OSTI2017

Optimal net-load balancing in smart grids with high PV penetration

Mitigating mismatches in supply demand curve is critical for smooth power grid operation. Traditionally, load curtailment techniques such as Demand Response (DR) have been used for this purpose. However, smart grids with high PV penetration sometimes exhibit supply surplus causing over-voltages. Thus, load curtailment techniques cannot be the only component of a net-load balancing framework. Supply curtailment techniques such as Volt-Var Optimizations are complex and computationally expensive. This increases the complexity of net-load balancing systems used by the grid operator and limits their scalability. Recently, new technologies have been developed that enable the rapid and selective connection of PV modules of an installation to the grid. Taking advantage of these advancements, we develop a unified optimal net-load balancing framework which performs both load and solar curtailment. We show that when the available curtailment values are discrete, this problem is NP-hard and develop bounded approximation algorithms for minimizing the curtailment cost. Our algorithms produce fast solutions, given the tight timing constraints required for grid operation. We also incorporate the notion of fairness to ensure that curtailment is evenly distributed among all the nodes. Finally, we develop an online algorithm which performs net-load balancing using only data available for the current interval. Using both theoretical analysis and practical evaluations, we show that our net-load balancing algorithms provide solutions which are close to optimal in a small amount of time.

14 SOLAR ENERGY↗

NASA NTRS1992

Determining Mars parking orbits which ensure in-plane arrival and departure burns

A numerical method to find suitable Mars parking orbits is developed which takes into account geometries associated with the asymptotes, along with the nodal precession caused by the oblateness of Mars. A selected orbital plane which contains the arrival asymptote precesses through the stay time to the plane also containing the departure asymptote. The parking orbit is co-planar with both the arrival and departure asymptotes and only in-plane burns are required at both Mars arrival and departure. The need for a plane change at Mars departure to achieve the proper velocity vector for earth return is eliminated. The method requires very little computation time to determine a set of all possible inclinations and right ascensions of the ascending nodes.

Desai, Prasun N.↗

DOE OSTI2026

Numerical simulation of vortex-induced vibration response of a single IEA 10-MW wind turbine blade

Three-dimensional simulation of vortex-induced vibration (VIV) of a single International Energy Agency (IEA) 10-MW reference wind turbine blade with a length of 97.325 m is performed using the ExaWind stack, an open-source suite of codes. This study aims to illustrate the spanwise VIV response characteristics and cross-validate the results with an existing commercial framework. Five near-body meshes and three time steps are selected for the convergence study. To improve computational efficiency, several VIV triggering methods are also compared to shorten the VIV development period. The ExaWind-based VIV simulation strategy for a single IEA 10-MW blade is determined. First, the modal shape is validated against published results. Then, spanwise VIV responses of four blade configurations under a fixed and varied incoming flow velocity are analyzed. Results show that the VIV response is dominated by the first edgewise (second overall) mode. Little first-mode contributions appear near the second-mode node, producing a pi phase jump, and a higher harmonics response occurs near the blade root. Rotational degrees of freedom are minor compared with translational motion. The response versus reduced velocity is analyzed, showing a two-branch behavior similar to that of VIV for a bluff cylinder. Across all tested cases, the dominant frequency remains locked to the natural frequency of the second mode with no observed desynchronization. A mild deviation is observed for the case of 90-degree pitch and 310-degree azimuth rotation near a reduced velocity of 6, which will be examined with additional cases in future work. These findings indicate that severe VIV responses can arise under specific configurations and flow conditions, thereby increasing the potential for VIV fatigue damage and requiring greater attention during operation.

17 WIND ENERGY↗

DOE OSTI2022

Geometric Frustration on the Trillium Lattice in a Magnetic Metal-Organic Framework

In the dense metal-organic framework Na [ Mn ( HCOO ) 3 ] , Mn 2 + ions ( S = 5 2 ) occupy the nodes of a “trillium” net. In this work, we show that the system is strongly magnetically frustrated: the Néel transition is suppressed well below the characteristic magnetic interaction strength; short-range magnetic order persists far above the Néel temperature; and the magnetic susceptibility exhibits a pseudo-plateau at 1 3 -saturation magnetization. A simple model of nearest-neighbor Heisenberg antiferromagnetic and dipolar interactions accounts quantitatively for all observations, including an unusual 2- k magnetic ground state. We show that the relative strength of dipolar interactions is crucial to selecting this particular ground state. Geometric frustration within the classical spin liquid regime gives rise to a large magnetocaloric response at low applied fields that is degraded in powder samples as a consequence of the anisotropy of dipolar interactions.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2025

Development of a River Dynamical Core for E3SM to simulate compound flooding on Exascale-class heterogeneous supercomputers

Flooding events pose significant risk to human life, property, and infrastructure. Physically-consistent quantification of altered flood risks in global models requires hyper-resolution (~1 km) or fine flood simulations using two-dimensional (2D) physics schemes, both of which are unavailable in the current generation Earth System Models. Here, in this work, we have developed the River Dynamical Core (RDycore), which is an open-source, 2D shallow water equation (SWE) library for the U.S. Department of Energy's Energy Exascale Earth System Model (E3SM). RDycore uses PETSc and libCEED libraries that allows it to run efficiently on CPUs and GPUs, as well as select a time-integration algorithm at runtime without requiring any code modifications. RDycore achieves spatial error convergence rates for problems with analytical and manufactured solutions similar to those reported previously in the literature, or consistent with the implemented first-order spatial discretization scheme. RDycore's accuracy in predicting flooding for a well-studied dam break problem is comparable to existing SWE models. For a problem with 471 million grid cells, RDycore achieves a speedup of 6.6x and 7.6x on GPUs compared to CPUs when using 320 compute nodes on DOE's Perlmutter and Frontier supercomputers, respectively. The one-way coupling of the RDycore library within E3SM is demonstrated by performing multiple 5-day flooding simulations during Hurricane Harvey driven by five precipitation datasets. The E3SM--RDycore simulations at 30 m spatial resolution accurately simulate maximum water height during the hurricane when benchmarked against a previously published study and achieve a speedup of 15x (Perlmutter) and 21x (Frontier) on GPUs relative to CPUs. The work presented here is the foundational step in providing hardware and algorithmic portability framework for simulating kilometer-scale river dynamics within E3SM.

Flood Simulation↗

DOE OSTI2023

Photoreactive Carbon Dioxide Capture by a Zirconium–Nanographene Metal–Organic Framework

Here, the mechanism of photochemical CO 2 reduction to formate by PCN-136, a Zr-based metal-organic framework (MOF) that incorporates light-harvesting nanographene ligands, has been investigated using steady-state and time-resolved spectroscopy and density functional theory (DFT) calculations. The catalysis was found to proceed via a "photoreactive capture" mechanism, where Zr-based nodes serve to capture CO 2 in the form of Zr- bicarbonates, while the nanographene ligands have a dual role of absorbing light and storing one-electron equivalents for catalysis. We also find that the process occurs via a "two-for-one" route, where a single photon initiates a cascade of electron/hydrogen atom transfers from the sacrificial donor to the CO 2 -bound MOF. The mechanistic findings obtained here illustrate several advantages of MOF-based architectures in molecular photocatalyst engineering and provide insights on ways to achieve high formate selectivity.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2023

Improving materials property predictions for graph neural networks with minimal feature engineering *

Graph neural networks (GNNs) have been employed in materials research to predict physical and functional properties, and have achieved superior performance in several application domains over prior machine learning approaches. Recent studies incorporate features of increasing complexity such as Gaussian radial functions, plane wave functions, and angular terms to augment the neural network models, with the expectation that these features are critical for achieving a high performance. Here, we propose a GNN that adopts edge convolution where hidden edge features evolve during training and extensive attention mechanisms, and operates on simple graphs with atoms as nodes and distances between them as edges. As a result, the same model can be used for very different tasks as no other domain-specific features are used. With a model that uses no feature engineering, we achieve performance comparable with state-of-the-art models with elaborate features for formation energy and band gap prediction with standard benchmarks; we achieve even better performance when the dataset size increases. Although some domain-specific datasets still require hand-crafted features to achieve state-of-the-art results, our selected architecture choices greatly reduce the need for elaborate feature engineering and still maintain predictive power in comparison.

42 ENGINEERING↗

DOE OSTI2023

Identification of genetic and environmental factors influencing aerial root traits that support biological nitrogen fixation in sorghum

Abstract Plant breeding and genetics play a major role in the adaptation of plants to meet human needs. The current requirement to make agriculture more sustainable can be partly met by a greater reliance on biological nitrogen fixation by symbiotic diazotrophic microorganisms that provide crop plants with ammonium. Select accessions of the cereal crop sorghum (Sorghum bicolor (L.) Moench) form mucilage-producing aerial roots that harbor nitrogen-fixing bacteria. Breeding programs aimed at developing sorghum varieties that support diazotrophs will benefit from a detailed understanding of the genetic and environmental factors contributing to aerial root formation. A genome-wide association study of the sorghum minicore, a collection of 242 landraces, and 30 accessions from the sorghum association panel was conducted in Florida and Wisconsin and under 2 fertilizer treatments to identify loci associated with the number of nodes with aerial roots and aerial root diameter. Sequence variation in genes encoding transcription factors that control phytohormone signaling and root system architecture showed significant associations with these traits. In addition, the location had a significant effect on the phenotypes. Concurrently, we developed F2 populations from crosses between bioenergy sorghums and a landrace that produced extensive aerial roots to evaluate the mode of inheritance of the loci identified by the genome-wide association study. Furthermore, the mucilage collected from aerial roots contained polysaccharides rich in galactose, arabinose, and fucose, whose composition displayed minimal variation among 10 genotypes and 2 fertilizer treatments. These combined results support the development of sorghums with the ability to acquire nitrogen via biological nitrogen fixation.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2024

Early experiences on the OLCF Frontier system with AthenaPK and Parthenon–Hydro

The Oak Ridge Leadership Computing Facility (OLCF) has been preparing the nation's first exascale system, Frontier, for production and end users. Frontier is based on HPE Cray's new EX architecture and Slingshot interconnect and features 74 cabinets of optimized 3rd Gen AMD EPYC CPUs for HPC and AI and AMD Instinct 250X accelerators. As a part of this preparation, “real-world” user codes have been selected to help assess the functionality, performance, and usability of the system. This article describes early experiences using the system in collaboration with the Hamburg Observatory for two selected codes, which have since been adopted in the OLCF test harness. Experiences discussed include efforts to resolve performance variability and per-cycle slowdowns. Results are shown for a performance portable astrophysical magnetohydronamics code, AthenaPK, and a mini-application stressing the core functionality of a performance portable block-structured adaptive mesh refinement framework, Parthenon-Hydro. Here, these results show good scaling characteristics to the full system. At the largest scale, the Parthenon-Hydro miniapp reaches a total of $1.7$ $\times$ $10^{13}$ zone-cycles/s on 9216 nodes (73,728 logical GPUs) at ≈92% weak scaling parallel efficiency (starting from a single node using a second-order, finite-volume method).

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2021

Efficient Contingency Analysis in Power Systems via Network Trigger Nodes

Modeling failure dynamics within a power system is a complex and challenging process due to multiple inter-dependencies and convoluted inter-domain relationships. Subject matter experts (SMEs) are interested in understanding these failure dynamics for reducing the impact from future disasters (i.e., losses or failures of power system components, such as transmission lines). Contingency analysis (CA) tools enable such ’what-if’ scenario analyses to evaluate the impacts on the power system. Analyzing all possible contingencies among N system components can be computationally expensive. An important step for performing CA is identifying a set of k ‘trigger’ components, which when failed initially can significantly impact the overall system by causing multiple failures. Currently SMEs focus on identifying these trigger components by running expensive simulations on all possible subsets, which quickly becomes infeasible. Hence finding a relevant set of trigger components (contingencies) rapidly to enable efficient and useful CA is crucial.In a collaboration between computer scientists and power system experts, we propose an efficient method for performing CA by exploiting network inter-dependencies in power system components. First, we construct a network with multiple electric grid infrastructure components and dependencies as connections among them. We reformulate the problem of finding a set of trigger components as a problem of identifying critical nodes in the network, which can cascade power failures through connected nodes and cause significant damage to the network. To guide the practical CA tools, we develop a network-based model with a probabilistic edge-weights setup using intricate domain rules. Then we conduct an empirical study on real power system data in the US for both regional and national levels. Firstly, we use power system datasets for the US to create a national-scale domain-driven model. Secondly, we demonstrate that network-based model outperforms the outputs from a real CA tool and show on average 25 × improved selection of contingencies, thereby showcasing practical benefits to the power experts.

Tabassum, Anika↗

NASA NTRSDate not supplied

Recent Advances in Discrete Crack Modeling Applied to Laminated Composites with Emphasis on: Floating Node Method, VCCT and Cohesive Zone Modeling

The present talk will provide an overview of the work performed during the Advanced Composites Project (ACP) on the development, and verification and validation of the Floating Node Method (FNM) as well as the Virtual Crack Closure Technique (VCCT) and cohesive zone modeling (CZM). The FNM is a finite element-based technique to represent crack networks. The complex nature of matrix crack-delamination interactions observed in unidirectional (UD) tape laminates suggests that a methodology such as the FNM method may be required to be able to accurately simulate damage progression in these laminates. Simulating crack onset and growth within the context of the FNM relies on techniques such as VCCT and CZM. The talk is organized to provide, via select examples, an overview of the breadth of the Verification & Validation (V&V) exercises performed during the ACP, and how these challenged the state-of-the art and guided further developments in discrete crack modeling, while helping to establish confidence in the progress made and map the challenges ahead. The performance of the VCCT and CZM individually, and in combination with the FNM can be assessed through verification exercises. These exercises typically consist of a comparison of simulation results to known numerical or analytical solutions. Verification is key to identify implementation issues and limitations that, otherwise, may remain undetected and cloud any subsequent validation efforts. Indeed, a subset of these numerical exercises led to further developments of the VCCT and the FNM method as will be illustrated. Before embarking on the subsequent validation of the framework, it is critical to have adequate characterization data. However, the testing campaign conducted revealed material responses that challenged the state-of-the-art and required further developments. The developments in CZM technology associated with the modeling of the responses of hybrid interfaces (fabric/UD) will be given as an example. Finally, the talk will conclude with a summary of the validation exercises performed under quasi-static and fatigue loadings, highlighting some of the key achievements, outstanding challenges and lessons learned.

finite elements↗

DOE OSTI2020

Guest-Controlled Incommensurate Modulation in a Meta-Rigid Metal–Organic Framework Material

Structural transitions of host systems in response to guest binding dominate many chemical processes. We report an unprecedented type of structural flexibility within a meta-rigid material, MFM-520, which exhibits a reversible periodic-to-aperiodic structural transition resulting from a drastic distortion of a [ZnO 4 N] node controlled by the specific host–guest interactions. The aperiodic crystal structure of MFM-520 has no three-dimensional (3D) lattice periodicity but shows translational symmetry in higher-dimensional (3 + 2)D space. In this work, we have directly visualized the aperiodic state which is induced by incommensurate modulation of the periodic framework of MFM-520·H 2 O upon dehydration to give MFM-520. Filling MFM-520 with CO 2 and SO 2 reveals that, while CO 2 has a minimal structural influence, SO 2 can further modulate the structure incommensurately. MFM-520 shows exceptional selectivity for SO 2 under flue-gas desulfurization conditions, and the facile release of captured SO 2 from MFM-520 enabled the conversion to valuable sulfonamide products. MFM-520 can thus be used as a highly efficient capture and delivery system for SO 2 .

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2021

Efficient Sampling of Complex Interdependent and Multiplex Networks

Efficient sampling of interdependent and multiplex infrastructure networks is critical for effectively applying failure and recovery algorithms in real-world settings, as well as to generate property-preserving reduced-order graph-based ensembles that address topological uncertainties. In this paper, we first explore the performance, i.e. the success in preserving graph properties, of graph sampling algorithms for interdependent and multiplex networks with synthetic and real-world graphs. We simulate sampling algorithms under different parameter settings. These settings include probabilistic graph generators, coupling patterns, and various performance metrics. Our results show that while Random Node and Random Walk sampling algorithms perform best for interdependent networks, Random Edge and Forest Fire sampling algorithms perform best for multiplex networks. Second, we propose and implement a novel similarity-based sampling algorithm for multiplex networks that samples only log(N) number of layers of an N-layer multiplex network while yielding computational savings with performance guarantees. Experimental results show that similarity sampling outperforms complete sampling of all layers while decreasing performance costs from a linear scale to a logarithmic one. Our results also indicate that similarity-based sampling outperforms complete sampling and random selection in nearly all scenarios when tested with real-world data.

Subasi, Omer↗