Search NASA⌕ Search

SEARCH · Search NASA

Results for “NODES”

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 19 records
All sourcesNASA NTRSDOE OSTI
NASA NTRS2010

Use of a Hybrid Edge Node-Centroid Node Approach to Thermal Modeling

A recent proposal submitted for an ESA mission required that models be delivered in ESARAD/ESATAN formats. ThermalDesktop was the preferable analysis code to be used for model development with a conversion done as the final step before delivery. However, due to some differences between the capabilities of the two codes, a unique approach was developed to take advantage of the edge node capability of ThermalDesktop while maintaining the centroid node approach used by ESARAD. In essence, two separate meshes were used: one for conduction and one for radiation. The conduction calculations were eliminated from the radiation surfaces and the capacitance and radiative calculations were eliminated from the conduction surfaces. The resulting conduction surface nodes were coincident with all nodes of the radiation surface and were subsequently merged, while the nodes along the edges remained free. Merging of nodes on the edges of adjacent surfaces provided the conductive links between surfaces. Lastly, all nodes along edges were placed into the subnetwork and the resulting supernetwork included only the nodes associated with radiation surfaces. This approach had both benefits and disadvantages. The use of centroid, surface based radiation reduces the overall size of the radiation network, which is often the most computationally intensive part of the modeling process. Furthermore, using the conduction surfaces and allowing ThermalDesktop to calculate the conduction network can save significant time by not having to manually generate the couplings. Lastly, the resulting GMM/TMM models can be exported to formats which do not support edge nodes. One drawback, however, is the necessity to maintain two sets of surfaces. This requires additional care on the part of the analyst to ensure communication between the conductive and radiative surfaces in the resulting overall network. However, with more frequent use of this technique, the benefits of this approach can far outweigh the additional effort.

Peabody, Hume L.↗
NASA NTRS2010

Use of a Hybrid Edge Node-Centroid Node Approach to Thermal Modeling

A recent proposal submitted for an ESA mission required that models be delivered in ESARAD/ESAT AN formats. ThermalDesktop was the preferable analysis code to be used for model development with a conversion done as the final step before delivery. However, due to some differences between the capabilities of the two codes, a unique approach was developed to take advantage of the edge node capability of ThermalDesktop while maintaining the centroid node approach used by ESARAD. In essence, two separate meshes were used: one for conduction and one for radiation. The conduction calculations were eliminated from the radiation surfaces and the capacitance and radiative calculations were eliminated from the conduction surfaces. The resulting conduction surface nodes were coincident with all nodes of the radiation surface and were subsequently merged, while the nodes along the edges remained free. Merging of nodes on the edges of adjacent surfaces provided the conductive links between surfaces. Lastly, all nodes along edges were placed into the subnetwork and the resulting supernetwork included only the nodes associated with radiation surfaces. This approach had both benefits and disadvantages. The use of centroid, surface based radiation reduces the overall size of the radiation network, which is often the most computationally intensive part of the modeling process. Furthermore, using the conduction surfaces and allowing ThermalDesktop to calculate the conduction network can save significant time by not having to manually generate the couplings. Lastly, the resulting GMM/TMM models can be exported to formats which do not support edge nodes. One drawback, however, is the necessity to maintain two sets of surfaces. This requires additional care on the part of the analyst to ensure communication between the conductive and radiative surfaces in the resulting overall network. However, with more frequent use of this technique, the benefits of this approach can far outweigh the additional effort.

Peabody, Hume L.↗
NASA NTRSDate not supplied

Implementation of a Hybrid Edge Node-Centroid Node Approach for the Generation of Reduced Thermal Models

Reduced thermal models are often required for delivery to organizations that manage observatory or launch models at the highest levels of assembly. However, the effort to generate reduced models, and verify against their detailed counterparts, is a challenge that has not yet been conclusively solved. Higher level organizations often place a limit on the number of nodes for delivered models with the assumption that smaller models generally result in less computation time. However, the burden of producing and verifying the accuracy of the reduced models is placed primarily on the lower-level organizations, which in turn consumes resources needed to produce these models. Limiting the total number of allowable nodes may also prevent users from taking full advantage of software capabilities that allow for faster generation of models, such as finite elements, which generally require more nodes than older centroid based models. A methodology using Thermal Desktop was described in 2010 which used: (1) finite elements and edge nodes for a conduction matrix, (2) centroid nodes for capacitance and radiative computations, and (3) the super network feature to produce a conduction matrix based only on the centroid nodes. At that time, the methodology was clear, but the implementation would have had to be done manually; however, with the inclusion of the OpenTD Application Programming Interface, this methodology can now be implemented programmatically and for the first time, be a viable approach for the generation of reduced models. The approach was implemented and developed at the NASA Goddard Space Flight Center (GSFC) for the Capture, Containment, and Return System (CCRS) payload on the Earth Return Orbiter (ERO) as part of the Mars Sample Return mission, resulting in the TCYEE tool. ERO features a spacecraft bus provided by Airbus through the European Space Agency with node limitations on the delivered CCRS model provided by GSFC. TCYEE was used to generate the reduced model for this delivery and the predictions compared favorably to the detailed model currently in use for the thermal performance evaluation. Furthermore, TCYEE is being explored for potential use on the Roman Space Telescope (RST) for the generation of reduced models for delivery to the launch provider, which also has node limit requirements on the RST observatory model for use in launch simulation analyses. This paper describes the methodology, its implementation, and compares the performance of reduced models generated by TCYEE to their detailed counterparts.

Thermal Desktop↗
NASA NTRSDate not supplied

Implementation of a Hybrid Edge Node-Centroid Node Approach for the Generation of Reduced Thermal Models

Reduced thermal models are often required for delivery to organizations that manage observatory or launch models at the highest levels of assembly. However, the effort to generate reduced models, and verify against their detailed counterparts, is a challenge that has not yet been conclusively solved. Higher level organizations often place a limit on the number of nodes for delivered models with the assumption that smaller models generally result in less computation time. However, the burden of producing and verifying the accuracy of the reduced models is placed primarily on the lower-level organizations, which in turn consumes resources needed to produce these models. Limiting the total number of allowable nodes may also prevent users from taking full advantage of software capabilities that allow for faster generation of models, such as finite elements, which generally require more nodes than older centroid based models. A methodology using Thermal Desktop was described in 2010 which used: (1) finite elements and edge nodes for a conduction matrix, (2) centroid nodes for capacitance and radiative computations, and (3) the super network feature to produce a conduction matrix based only on the centroid nodes. At that time, the methodology was clear, but the implementation would have had to be done manually; however, with the inclusion of the OpenTD API, this methodology can now be implemented programmatically and for the first time, be a viable approach for the generation of reduced models. The approach was implemented and developed at the NASA Goddard Space Flight Center (GSFC) for the Capture, Containment, and Return System (CCRS) payload on the Earth Return Orbiter (ERO) as part of the Mars Sample Return (MSR) mission, resulting in the TCYEE tool. ERO features a spacecraft bus provided by Airbus through the European Space Agency (ESA) with node limitations on the delivered CCRS model provided by GSFC. TCYEE was used to generate the reduced model for this delivery and the predictions compared favorably to the detailed model currently in use for the thermal performance evaluation. Furthermore, TCYEE is being explored for potential use on the Roman Space Telescope (RST) for the generation of reduced models for delivery to the launch provider, which also has node limit requirements on the RST observatory model for use in launch simulation analyses. This paper describes the methodology, its implementation, and compares the performance of reduced models generated by TCYEE to their detailed counterparts.

Thermal desktop↗
NASA NTRSDate not supplied

Implementation of a Hybrid Edge Node-Centroid Node Approach for the Generation of Reduced Thermal Models

Reduced thermal models are often required for delivery to organizations that manage observatory or launch models at the highest levels of assembly. However, the effort to generate reduced models, and verify against their detailed counterparts, is a challenge that has not yet been conclusively solved. Higher level organizations often place a limit on the number of nodes for delivered models with the assumption that smaller models generally result in less computation time. However, the burden of producing and verifying the accuracy of the reduced models is placed primarily on the lower-level organizations, which in turn consumes resources needed to produce these models. Limiting the total number of allowable nodes may also prevent users from taking full advantage of software capabilities that allow for faster generation of models, such as finite elements, which generally require more nodes than older centroid based models. A methodology using Thermal Desktop was described in 2010 which used: (1) finite elements and edge nodes for a conduction matrix, (2) centroid nodes for capacitance and radiative computations, and (3) the super network feature to produce a conduction matrix based only on the centroid nodes. At that time, the methodology was clear, but the implementation would have had to be done manually; however, with the inclusion of the OpenTD API, this methodology can now be implemented programmatically and for the first time, be a viable approach for the generation of reduced models. The approach was implemented and developed at the NASA Goddard Space Flight Center (GSFC) for the Capture, Containment, and Return System (CCRS) payload on the Earth Return Orbiter (ERO) as part of the Mars Sample Return (MSR) mission, resulting in the TCYEE tool. ERO features a spacecraft bus provided by Airbus through the European Space Agency (ESA) with node limitations on the delivered CCRS model provided by GSFC. TCYEE was used to generate the reduced model for this delivery and the predictions compared favorably to the detailed model currently in use for the thermal performance evaluation. Furthermore, TCYEE is being explored for potential use on the Roman Space Telescope (RST) for the generation of reduced models for delivery to the launch provider, which also has node limit requirements on the RST observatory model for use in launch simulation analyses. This paper describes the methodology, its implementation, and compares the performance of reduced models generated by TCYEE to their detailed counterparts.

Hume L. Peabody↗
NASA NTRSDate not supplied

Implementation of a Hybrid Edge Node-Centroid Node Approach for the Generation of Reduced Thermal Models

Reduced thermal models are often required for delivery to organizations that manage models at the highest levels of assembly. The effort to generate/verify these models against their detailed counterparts is a challenge not yet conclusively solved. Higher level organizations often place a limit on the node count for delivered models, assuming smaller models result in faster computation. The burden of producing and verifying the accuracy of reduced models is primarily on the lower-level organizations, which consumes resources to produce these models. Limiting the number of allowable nodes may prevent users from taking full advantage of software capabilities that allow for faster generation of models, such as finite elements, which require more nodes than centroid based models. A methodology using Thermal Desktop was described in 2010 using: (1) finite elements and edge nodes for the conduction matrix, (2) centroid nodes for capacitance and radiative computations, and (3) the super network feature to produce a conduction matrix based only on the centroid nodes. While the methodology was clear, the implementation would have had to be done manually; with the inclusion of the OpenTD Application Programming Interface, this methodology can now be implemented programmatically and be a viable approach for the generation of reduced models. The approach was implemented at NASA-Goddard for the Capture-Containment-and-Return-System (CCRS) payload, resulting in the TCYEE tool. CCRS requires delivery with node limitations through the European Space Agency to its contractors. TCYEE generated the reduced model for delivery and the predictions compared favorably to the detailed model. Furthermore, TCYEE is being explored for potential use on the Roman Space Telescope (RST) for the generation of reduced models for delivery to the launch provider, which also has node limit requirements. This paper describes the methodology, implementation, and the performance of reduced models compared to their detailed counterparts.

Computer Programming and Software↗
NASA NTRS2004

A Six-Node Curved Triangular Element and a Four-Node Quadrilateral Element for Analysis of Laminated Composite Aerospace Structures

Mathematical development and some computed results are presented for Mindlin plate and shell elements, suitable for analysis of laminated composite and sandwich structures. These elements use the conventional 3 (plate) or 5 (shell) nodal degrees of freedom, have no communicable mechanisms, have no spurious shear energy (no shear locking), have no spurious membrane energy (no membrane locking) and do not require arbitrary reduction of out-of-plane shear moduli or under-integration. Artificial out-of-plane rotational stiffnesses are added at the element level to avoid convergence problems or singularity due to flat spots in shells. This report discusses a 6-node curved triangular element and a 4-node quadrilateral element. Findings show that in regular rectangular meshes, the Martin-Breiner 6-node triangular curved shell (MB6) is approximately equivalent to the conventional 8-node quadrilateral with integration. The 4-node quadrilateral (MB4) has very good accuracy for a 4-node element, and may be preferred in vibration analysis because of narrower bandwidth. The mathematical developments used in these elements, those discussed in the seven appendices, have been applied to elements with 3, 4, 6, and 10 nodes and can be applied to other nodal configurations.

Martin, C. Wayne↗
DOE OSTI2019

Indocyanine Green Fluorescence Imaging with Lymphoscintigraphy for Sentinel Node Biopsy in Melanoma: Increasing the Sentinel Lymph Node-Positive Rate

Introduction: The goal of this study was to analyze patients who underwent a sentinel lymph node biopsy (SLNB) in melanoma with the combination of radioisotope lymphoscintigraphy and indocyanine green (ICG) fluorescence imaging to compare our true positive (TP) rate, a means to perform immediate analysis of the SLNB, with that of the literature. Methods: Consecutive cutaneous melanoma patients who underwent SLNB with lymphoscintigraphy and ICG-based fluorescence imaging by the senior author (BG) from 2012 to 2018 were prospectively enrolled. The average expected SLN-positive rate per T stage was calculated based on three studies and compared with our SLN-positive rate. Results: Overall, 574 consecutive patients were analyzed. Average Breslow thickness was 1.9 mm. A total of 1754 sentinel nodes were sampled; 1497 were identified by gamma probe signaling and ICG, 241 were identified by gamma probe signaling only, and 16 were identified by ICG only. There were 123 (21.4%) patients with at least one positive SLN; 113 (91.9%) had at least one positive node identified with both gamma probe signaling and ICG, 8 (6.5%) had positive node(s) identified with gamma probe signaling only, and 2 (1.6%) had positive node(s) identified with ICG only. There was an overall 21.4% SLN-positive rate, with 8% T1, 18.5% T2, 41.1% T3, and 52.4% T4, which is higher than the predicted rates for each stage. Conclusions: With the largest cohort of patients reported who underwent a melanoma SLNB with lymphoscintigraphy and ICG, we demonstrated that this technique results in higher SLN-positive rates than predicted. Patients are being followed but, given the TP data, knowledge of our results may foster the use of this modality to improve staging and treatment options.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2020

Taming the fixed-node error in diffusion Monte Carlo via range separation

By combining density-functional theory (DFT) and wave function theory via the range separation (RS) of the interelectronic Coulomb operator, we obtain accurate fixed-node diffusion Monte Carlo (FN-DMC) energies with compact multi-determinant trial wave functions. In particular, we combine here short-range exchange-correlation functionals with a flavor of selected configuration interaction known as configuration interaction using a perturbative selection made iteratively (CIPSI), a scheme that we label RS-DFT-CIPSI. One of the take-home messages of the present study is that RS-DFT-CIPSI trial wave functions yield lower fixed-node energies with more compact multi-determinant expansions than CIPSI, especially for small basis sets. Indeed, as the CIPSI component of RS-DFT-CIPSI is relieved from describing the short-range part of the correlation hole around the electron-electron coalescence points, the number of determinants in the trial wave function required to reach a given accuracy is significantly reduced as compared to a conventional CIPSI calculation. Importantly, by performing various numerical experiments, we evidence that the RS-DFT scheme essentially plays the role of a simple Jastrow factor by mimicking short-range correlation effects, hence avoiding the burden of performing a stochastic optimization. Considering the 55 atomization energies of the Gaussian-1 benchmark set of molecules, we show that using a fixed value of mu = 0.5 bohr(-1) provides effective error cancellations as well as compact trial wave functions, making the present method a good candidate for the accurate description of large chemical systems.

Scemama, Anthony↗
DOE OSTI2020

Reducing communication in algebraic multigrid with multi-step node aware communication

Algebraic multigrid (AMG) is often viewed as a scalable [Formula: see text] solver for sparse linear systems. Yet, AMG lacks parallel scalability due to increasingly large costs associated with communication, both in the initial construction of a multigrid hierarchy and in the iterative solve phase. This work introduces a parallel implementation of AMG that reduces the cost of communication, yielding improved parallel scalability. It is common in Message Passing Interface (MPI), particularly in the MPI-everywhere approach, to arrange inter-process communication, so that communication is transported regardless of the location of the send and receive processes. Performance tests show notable differences in the cost of intra- and internode communication, motivating a restructuring of communication. In this case, the communication schedule takes advantage of the less costly intra-node communication, reducing both the number and the size of internode messages. Node-centric communication extends to the range of components in both the setup and solve phase of AMG, yielding an increase in the weak and strong scaling of the entire method.

Computer Science↗
NASA NTRS2011

Connecting node and method for constructing a connecting node

A connecting node comprises a polyhedral structure comprising a plurality of panels joined together at its side edges to form a spherical approximation, wherein at least one of the plurality of panels comprises a faceted surface being constructed with a passage for integrating with one of a plurality of elements comprising a docking port, a hatch, and a window that is attached to the connecting node. A method for manufacturing a connecting node comprises the steps of providing a plurality of panels, connecting the plurality of panels to form a spherical approximation, wherein each edge of each panel of the plurality is joined to another edge of another panel, and constructing at least one of the plurality of panels to include a passage for integrating at least one of a plurality of elements that may be attached to the connecting node.

Johnson, Christopher J.↗
DOE OSTI2019

Risk of Positive Sentinel Lymph Node After Neoadjuvant Systemic Therapy in Clinically Node-Negative Breast Cancer: Implications for Postmastectomy Radiation Therapy and Immediate Breast Reconstruction

Background: Residual axillary lymph node involvement after neoadjuvant systemic therapy (NST) is the determining factor for postmastectomy radiation therapy (PMRT). Preoperative identification of patients needing PMRT is essential to enable shared decision-making when choosing the optimal timing of breast reconstruction. We determined the risk of positive sentinel lymph node (SLN) after NST in clinically node-negative (cN0) breast cancer. Methods: All cT1-3N0 patients treated with NST followed by mastectomy and SLNB between 2010 and 2016 were identified from the Netherlands Cancer Registry. Rate of positive SLN for different breast cancer subtypes was determined. Logistic regression analysis was performed to determine correlated clinicopathological variables with positive SLN. Results: In total 788 patients were included, of whom 25.0% (197/788) had positive SLN. cT1-3N0 ER+HER2+, cT1-3N0 ER−HER2+ , and cT1-2N0 triple-negative patients had the lowest rate of positive SLN: 7.2–11.5%, 0–6.3%, and 2.9–6.2%, respectively. cT1-3N0 ER+HER2− and cT3N0 triple-negative patients had the highest rate of positive SLN: 23.8–41.7% and 30.4%, respectively. Multivariable regression analysis showed that cT2 (odds ratio [OR] 1.93; 95% confidence interval [CI] 1.01–3.96), cT3 (OR 2.56; 95% CI 1.30–5.38), grade 3 (OR 0.44; 95% CI 0.21–0.91), and ER+HER2− subtype (OR 3.94; 95% CI 1.77–8.74) were correlated with positive SLN. Conclusions: In cT1-3N0 ER+HER2+, cT1-3N0 ER−HER2+, and cT1-2N0 triple-negative patients treated with NST, immediate reconstruction can be considered an acceptable option due to low risk of positive SLN. In cT1-3N0 ER+HER2− and cT3N0 triple-negative patients treated with NST, risks and benefits of immediate reconstruction should be discussed with patients due to the relatively high risk of positive SLN.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2019

Structure, Dynamics, and Reactivity for Light Alkane Oxidation of Fe(II) Sites Situated in the Nodes of a Metal–Organic Framework

Metal organic frameworks (MOFs), with their crystalline, porous structures, can be synthesized to incorporate a wide range of catalytically active metals in tailored surroundings. These materials have potential as catalysts for conversion of light alkanes, feedstocks available in large quantities from shale gas that are changing the economics of manufacturing commodity chemicals. Mononuclear high-spin (S = 2) Fe(II) sites situated in the nodes of the MOF MIL-100(Fe) convert propane via dehydrogenation, hydroxylation, and overoxidation pathways in reactions with the atomic oxidant N 2 O. Pair distribution function analysis, N 2 adsorption isotherms, X-ray diffraction patterns, and infrared and Raman spectra confirm the single-phase crystallinity and stability of MIL-100(Fe) under reaction conditions (523 K in vacuo, 378–408 K C 3 H 8 + N 2 O). Density functional theory (DFT) calculations illustrate a reaction mechanism for the formation of 2-propanol, propylene, and 1-propanol involving the oxidation of Fe(II) to Fe(III) via a high-spin Fe(IV)$=$O intermediate. The speciation of Fe(II) and Fe(III) in the nodes and their dynamic interchange was characterized by in situ X-ray absorption spectroscopy and ex situ Mössbauer spectroscopy. Furthermore, the catalytic relevance of Fe(II) sites and the number of such sites were determined using in situ chemical titrations with NO. N 2 and C 3 H 6 production rates were found to be first-order in N 2 O partial pressure and zero-order in C3H8 partial pressure, consistent with DFT calculations that predict the reaction of Fe(II) with N 2 O to be rate determining. DFT calculations using a broken symmetry method show that Fe-trimer nodes affecting reaction contain antiferromagnetically coupled iron species, and highlight the importance of stabilizing high-spin (S = 2) Fe(II) species for effecting alkane oxidation at low temperatures (<408 K).

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Comparing cross-platform performance via node-to-node scaling studies

Due to the increasing diversity of high-performance computing architectures, researchers and practitioners are increasingly interested in comparing a code’s performance and scalability across different platforms. However, there is a lack of available guidance on how to actually set up and analyze such cross-platform studies. In this paper, we contend that the natural base unit of computing for such studies is a single compute node on each platform and offer guidance in setting up, running, and analyzing node-to-node scaling studies. In conclusion, we propose templates for presenting scaling results of these studies and provide several case studies highlighting the benefits of this approach.

cross-platform studies↗
DOE OSTI2024

Generic and ML Workloads in an HPC Datacenter: Node Energy, Job Failures, and Node-Job Analysis

HPC datacenters offer a backbone to the modern digital society. Increasingly, they run Machine Learning (ML) jobs next to generic, compute-intensive workloads, supporting science, business, and other decision-making processes. However, understanding how ML jobs impact the operation of HPC datacenters, relative to generic jobs, remains desirable but understudied. In this work, we leverage long-term operational data, collected from a national-scale production HPC datacenter, and statistically compare how ML and generic jobs can impact the performance, failures, resource utilization, and energy consumption of HPC datacenters. Our study provides key insights, e.g., ML-related power usage causes GPU nodes to run into temperature limitations, median/mean runtime and failure rates are higher for ML jobs than for generic jobs, both ML and generic jobs exhibit highly variable arrival processes and resource demands, significant amounts of energy are spent on unsuccessfully terminating jobs, and concurrent jobs tend to terminate in the same state. We open-source our cleaned-up data traces on Zenodo (https://doi. org/10.5281/zenodo.13685426), and provide our analysis toolkit as software hosted on GitHub (https://github.com/atlarge-research/2024-icpads-hpc-workload-characterization). This study offers multiple benefits for data center administrators, who can improve operational efficiency, and for researchers, who can further improve system designs, scheduling techniques, etc.

crossanalysis↗