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DOE OSTI2022

Biolink Model: A universal schema for knowledge graphs in clinical, biomedical, and translational science

Abstract Within clinical, biomedical, and translational science, an increasing number of projects are adopting graphs for knowledge representation. Graph‐based data models elucidate the interconnectedness among core biomedical concepts, enable data structures to be easily updated, and support intuitive queries, visualizations, and inference algorithms. However, knowledge discovery across these “knowledge graphs” (KGs) has remained difficult. Data set heterogeneity and complexity; the proliferation of ad hoc data formats; poor compliance with guidelines on findability, accessibility, interoperability, and reusability; and, in particular, the lack of a universally accepted, open‐access model for standardization across biomedical KGs has left the task of reconciling data sources to downstream consumers. Biolink Model is an open‐source data model that can be used to formalize the relationships between data structures in translational science. It incorporates object‐oriented classification and graph‐oriented features. The core of the model is a set of hierarchical, interconnected classes (or categories) and relationships between them (or predicates) representing biomedical entities such as gene, disease, chemical, anatomic structure, and phenotype. The model provides class and edge attributes and associations that guide how entities should relate to one another. Here, we highlight the need for a standardized data model for KGs, describe Biolink Model, and compare it with other models. We demonstrate the utility of Biolink Model in various initiatives, including the Biomedical Data Translator Consortium and the Monarch Initiative, and show how it has supported easier integration and interoperability of biomedical KGs, bringing together knowledge from multiple sources and helping to realize the goals of translational science.

60 APPLIED LIFE SCIENCES↗

NASA NTRS2003

Effect of Turbulence Models on Two Massively-Separated Benchmark Flow Cases

Two massively-separated flow cases (the 2-D hill and the 3-D Ahmed body) were computed with several different turbulence models in the Reynolds-averaged Navier-Stokes code CFL3D as part of participation in a turbulence modeling workshop held in Poitiers, France in October, 2002. Overall, results were disappointing, but were consistent with results from other RANS codes and other turbulence models at the workshop. For the 2-D hill case, those turbulence models that predicted separation location accurately ended up yielding a too-long separation extent downstream. The one model that predicted a shorter separation extent in better agreement with LES data did so only by coincidence: its prediction of earlier reattachment was due to a too-late prediction of the separation location. For the Ahmed body, two slant angles were computed, and CFD performed fairly well for one of the cases (the larger slant angle). Both turbulence models tested in this case were very similar to each other. For the smaller slant angle, CFD predicted massive separation, whereas the experiment showed reattachment about half-way down the center of the face. These test cases serve as reminders that state- of-the-art CFD is currently not a reliable predictor of massively-separated flow physics, and that further validation studies in this area would be beneficial.

Rumsey, Christopher L.↗

NASA NTRS1983

Modified shielding jet model for twin-jet shielding analysis

An analytical model to estimate the shielding of noise emitted from a point noise source has been developed assuming the shielding jet to be a cylinder of constant radius with uniform flow across the cross section. Comparison to experiment indicated that the model overestimates diffraction of sound around the jet in the far downstream region. The shielding jet model is modified to include widening downstream of the nozzle exit. This not only represents a more realistic model of the jet, but is also expected to improve the shielding estimate downstream. The modified jet model incorporates a Mach number dependent widening rate, a corresponding decrease in flow velocity downstream and an equivalent slug flow evaluation to retain the locally parallel flow approximation of the model development. The shielding analysis with modified jet model is compared to measured data for a subsonic isothermal air jet and a simulated hot subsonic jet. Improvement of the shielding estimate is discussed.

Gerhold, C. H.↗

NASA NTRS2004

Interaction of Strong Transient Interplanetary Disturbances with the Dayside Magnetosphere

The objective of the investigation was to gain an understanding of the complex response of the magnetosphere to strong transient interplanetary disturbances. Because the project was only funded for a year, the investigation focused on only one of the three topics proposed in the original three year proposal. We investigated the response of the dayside auroral region to strong transient interplanetary disturbances. The method of the investigation was to use three-dimensional magnetohydrodynamic (MHD) simulations that employ measurements of the solar wind conditions upstream the bow shock to model actual events and then to compare the simulation results with observations from spacecraft located at downstream locations. We modeled an event that occurred on July 14,2000, for which both CLUSTER and IMAGE simultaneous observations were available. The event was marked by high solar wind dynamic pressure and a strong IMF By component. Comparisons showed a very good agreement between intensifications in the auroral emissions measured by IMAGE

Berchem, Jean↗

NASA NTRS1970

A model for analysis of the temperature distribution with injection of a heated jet into an isothermal flow

Heated jet injection into isothermal turbulent boundary layer, investigating temperature distribution downstream with conduction model

Eckert, E. R. G.↗

NASA NTRSDate not supplied

WMLES of Boundary-Layer Transition

The potential for the accurate prediction of laminar-turbulent transition by Wall-Modeled Large-Eddy Simulation (WMLES) is investigated through analysis of Direct Numerical Simulation (DNS) and WMLES results. The analysis indicates satisfactory prediction of transition by WMLES is possible, provided a) a sufficiently accurate wall model for the initial stage of transition is employed, b) a satisfactory transition is made between this initial-stage wall model and the wall model for the downstream fully-developed turbulence, and c) limitations on temporal and spatial resolution, and on the thickness of the wall-modeled region, imposed by the need to accurately resolve the disturbance waves and the transition region are observed. This is illustrated with a WMLES computation that yields reasonable agreement with DNS results; however, the wall-modeled region thickness, and thus the cost savings, is less than is typical for WMLES of fully developed turbulence.

wall-modeled large-eddy simulation, boundary-layer↗

NASA NTRSDate not supplied

WMLES of Boundary-Layer Transition

An analysis of the potential for the accurate prediction of laminar-turbulent transition by Wall-Modeled Large-Eddy Simulation (WMLES) indicates that satisfactory prediction of transition by WMLES is possible, provided a) a sufficiently accurate wall model for the initial stage of transition is employed, b) a satisfactory transition is made between this initial-stage wall model and the wall model for the downstream fully-developed turbulence, and c) limitations on temporal and spatial resolution, and on the thickness of the wall-modeled region, imposed by the need to accurately resolve the disturbance waves and the transition region are observed. This is illustrated with WMLES computations of subharmonic transition in a flat-plate boundary layer that yield reasonable agreement with DNS results. However, the wall-modeled region thickness, and thus the cost savings, is less than is typical for WMLES of fully developed turbulence.

wall-modeled large-eddy simulation↗

NASA NTRSDate not supplied

WMLES of Boundary-Layer Transition

Wall-modeled large-eddy simulation↗

DOE OSTI2021

Biological Response Models: Predicting Injury and Mortality of Fish During Downstream Passage through Hydropower Facilities

This report describes the U.S. Department of Energy’s HydroPASSAGE project efforts to develop and collect biological response models for integration into the Biological Performance Assessment (BioPA) toolset and the Hydropower Biological Evaluation Toolset (HBET). These models help understand how fish are likely to respond during dam passage when exposed to hydraulic and physical stressors associated with turbines and other hydropower structures. When fish pass through hydropower facilities, they may encounter several stressors, of which the three most common are collision, rapid decompression, and fluid shear. Specialized equipment has been used to develop 99 biological response models for exposure to blade strike, rapid decompression, or fluid shear. The models were gathered from the literature or developed as part of this effort and include models for 31 different species of fish that have various predicted endpoints (i.e., injury or mortality). Among these models, considerable variation in susceptibility to the stressors has been observed from one species to another, and a species’ susceptibility to one stressor does not necessarily indicate similar susceptibility to another. Although several species have been examined, it is still unclear how many other species, which may have different morphological traits, may respond to these stressors, so further examination of the different species is needed. These models can and have been applied in several different cases, often using the BioPA toolset and HBET, to better understand the potential for injury and mortality that may occur during fish passage at hydropower facilities, including specific applications, such as turbine replacement, the installation of new turbines, or changing operations of currently installed turbines. As hydropower is continually developed to meet the electricity needs of society, tools such as HBET and BioPA, used with the integrated biological response models, will aid in the development of technologies and strategies that avoid, minimize, mitigate, or manage environmental effects.

13 HYDRO ENERGY↗

NASA NTRSDate not supplied

Comparison of Ice Shapes on Full-Chord and Truncated Swept Wing Models

A research program was conducted to evaluate the effectiveness of icing tunnel hybrid model design. A hybrid design is where the full-scale leading edge of a wing section is maintained only to a certain percentage of the local chord, while the aft section of the model is redesigned into a shortened or truncated planform. Ice shape geometries on a full-chord length and hybrid versions of the swept CRM65 wing model were obtained in NASA Icing Research Tunnel and compared. For most test conditions, the overall size and shape of the ice shapes compared well. On the main part of the ice shape, the hybrid model had larger chordwise extent, resulting in wider ice shape. For the scallop ice shapes, the ice shape heights at attachment line location were identical. For conditions that produced rime shape, hybrid model ice shapes were larger overall, even at the attachment line location. The only location where there was more ice on the full chord model was on the lower surface, downstream of where the hybrid model no longer had full-scale leading edge. For the test conditions where ice mass measurements were acquired for both models, the full-chord models had 11-22% less ice mass than on the hybrid wing. These differences were larger and opposite of those predicted from LEWICE 3D ice prediction calculations. Further investigation is needed in order determine the cause of the differences between the full-chord and hybrid models.

Icing↗

NASA NTRSDate not supplied

Comparison of Ice Shapes on Full-Chord and Truncated Swept Wing Models

Icing↗

NASA NTRS1997

Comparison of Two-Equation Turbulence Models for Prediction of Heat Transfer on Film-Cooled Turbine Blades

A three-dimensional Navier-Stokes code has been used to compute the heat transfer coefficient on two film-cooled turbine blades, namely, the VKI rotor with six rows of cooling holes, including three rows on the shower head and the C3X vane with nine rows of holes, including five rows on the shower head. Predictions of heat transfer coefficient at the blade surface using three two-equation turbulence model specifically, Coakley's q-omega model, Chien's k-epsilon model and Wilcox's k-omega model with Menter's modifications, have been compared with the experimental data of Camci and Arts for the VKI rotor, and of Hylton et al. for the C3X vane along with predictions using the Baldwin-Lomar (B-L) model taken from Garg and Gaugler. It is found that for the cases considered here the two equation models predict the blade heat transfer somewhat better than the B-L model except immediately downstream of the film-cooled holes on the suction surface of the VKI rotor, and over most of the suction surface of the C3X vane. However, all two-equation models require 40% more computer core than the B-L model for solution, and while the q-omega and k-epsilon models need 40% more computer time than the B-L model the k-omega model requires at least 65% more time because of the slower rate of convergence. It is found that the heat transfer coefficient exhibit a strong spanwise as well as streamwise variation for both blades and all turbulence models.

Garg, Vijay K.↗

NASA NTRS2023

EVA Task and 3D Pose Recognition from Video

Extravehicular Activity (EVA) has been known to involve potential risks of biomechanical stresses and injuries to crewmembers. Gathering of EVA motion patterns is necessary for risk analysis and mitigation. However, many existing techniques, such as motion capture systems, are not only cost-prohibitive but are impractical for retrospective analysis of past missions. In this work, a software tool was developed, which can estimate the 3D poses of a spacesuit from photographs or videos, without using special sensors or equipment. The tool is based on the state-of-the-art artificial intelligence and machine learning (AI/ML) system, which was trained by studying and capturing motion patterns of past and current spacesuit test data. The AI/ML tool was further enhanced using synthetically generated data, in which the suit postures, backgrounds, camera angles and illumination conditions were parametrically adjusted and rendered for training. The tool, incorporated the methodologies of Convolutional Neural Network (CNN), was trained, and tested in the cloud computing environment. The trained model was then applied on new imagery and video to extract estimated joint positions and suit outlines. The joint positions were further processed to capture activity (“digging”), pose labels (“bending”), and other useful downstream information. The model performance on new imagery and video was successfully assessed for accuracy and reliability. This AI/ML based posture recognition tool thus allows for the quantification of injury risk and task performance characterization for both current and past missions and training, which can immensely help to improve EVA task and suit design.

Kyung Han Kim↗

NASA NTRS2013

Acoustic Performance of Drive Rig Mufflers for Model Scale Engine Testing

Aircraft engine component testing at the NASA Glenn Research Center (GRC) includes acoustic testing of scale model fans and propellers in the 9- by15-Foot Low Speed Wind Tunnel (LSWT). This testing utilizes air driven turbines to deliver power to the article being studied. These air turbines exhaust directly downstream of the model in the wind tunnel test section and have been found to produce significant unwanted noise that reduces the quality of the acoustic measurements of the engine model being tested. This report describes an acoustic test of a muffler designed to mitigate the extraneous turbine noise. The muffler was found to provide acoustic attenuation of at least 8 dB between 700 Hz and 20 kHz which significantly improves the quality of acoustic measurements in the facility.

Stephens, David, B.↗

NASA NTRS1976

Re-examination of compliant wall experiments in air with water substrates

A possible alternative explanation is proposed for compliant wall drag reductions measured in previous investigations. Standing waves were observed to form on the surfaces of compliant wall models in air with water substrates as the freestream velocity was increased from 15 to 30 m/s. These waves resembled sine waves with half of the wave protruding over the upstream portion of the model and the other half being recessed over the downstream end of the model. These data coupled with results of recent drag reduction experiments suggest that standing waves could have caused a shift in the model center of gravity creating a bending moment that was interpreted as a reduction in the skin friction drag.

Hefner, J. N.↗

DOE OSTI2021

Tritium Transport Phenomena in Molten-Salt Reactors: Molten Salt Tritium Transport Experiment Design

Tritium is produced from neutron interactions with both lithium and beryllium. Large quantities of tritium are generated in Molten Salt Reactors (MSRs) which use LiF/BeF2 (FLiBe) as the fuel salt. Tritium is unique among the radionuclide hazards as it readily permeates through metal structural materials at high temperatures. All metal surfaces are potential release paths for tritium. For adequate safety analysis and eventual licensing of new reactors, predictive models for tritium transport and release from MSRs must be developed. These models must account for the multiple transport phenomena involved with tritium: fuel salt phase mass transport, dissociation/recombination reactions on metal surfaces, interstitial diffusion through the metal structure, and salt or gas phase mass transport in the downstream fluid. These models also must also be validated with representative experiments. Our previous report outlined tritium transport phenomena involved in MSRs, made suggestions on gaps in the transport dataset, and proposed an experimental test stand to test combined transport effects – tritium transport through pipe walls in a convective salt flow. In this report, we summarize an updated analysis framework for tritium transport in MSRs, report our results on hydrogen and deuterium permeation through Hastelloy N, and describe the final design of the Molten Salt Tritium Transport Experiment (MSTTE, pronounced “misty”). The MSRE provides the only wholistic experimental data set for tritium transport in MSRs and understanding the transport phenomena involved in the MSRE is crucial for future model development. One set of parameters in our analysis framework was unknown for the MSRE—surface reaction rates for tritium on Hastelloy N. This warranted our hydrogen and deuterium permeation campaign to assess the permeability, diffusivity, and solubility of hydrogen isotopes in clean Hastelloy N. Surface reaction rate constants were probed by low pressure measurements, however, no surface effects were observed in the limits of our permeation apparatus. Permeation experiments on oxidized Hastelloy N were not performed for this report but are planned in future work. The experimental test stand, MSTTE, measures combined transport properties of the salt-metal system. MSTTE is a forced convection FLiBe loop with custom designed test section to measure tritium transport through candidate structural materials. We use MSRE relevant dimensionless numbers to design and scale the test section. Hastelloy N is a candidate loop and test section material due to the relevance for the MSRE and related designs, however, other metals are being considered (e.g. 316H SS) which may better align with current vendor concepts.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2026

Development of physics-consistent conditional diffusion model to overcome data scarcity in critical heat flux

Deep generative modeling provides a powerful pathway to overcome data scarcity in energy-related applications where experimental data are often limited. By learning the underlying probability distribution of the training dataset, deep generative models, such as the diffusion model, can generate high-fidelity synthetic samples that statistically resemble the training data. Such synthetic data generation can significantly enrich the size and diversity of the available training data, and more importantly, improve the robustness of downstream machine learning models in predictive tasks. The objective of this paper is to investigate the effectiveness of diffusion models for overcoming data scarcity in nuclear energy applications. By leveraging a public dataset on critical heat flux which covers a wide range of commercial nuclear reactor operational conditions, we developed a diffusion model that can generate an arbitrary amount of synthetic samples. Since a vanilla diffusion model can only generate samples randomly, we also developed a conditional diffusion model capable of generating targeted critical heat flux data under user-specified thermal-hydraulic conditions. The performance of the diffusion model was evaluated based on its ability to capture empirical feature distributions and pair-wise correlations, as well as to maintain physical consistency. The results showed that both the diffusion model and conditional diffusion model can successfully generate realistic and physics-consistent critical heat flux data. Furthermore, uncertainty quantification results demonstrate that the conditional diffusion model is highly effective in augmenting critical heat flux data while maintaining acceptable levels of uncertainty.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2024

A Framework for Identifying Building Energy Models of Localized Utility Service Areas Using Smart Meter Data

Bottom-up load modeling of buildings offers a versatile approach to simulating baseline demand and scenarios of future technology evolution and adoption at the individual building level. This capability is essential to understanding how future load shapes may change with the adoption of electric equipment and vehicles, particularly as it relates to grid planning and infrastructure investments. Traditionally, grid planning techniques have used historical load data to predict future load and infrastructure needs. However, with the anticipated rise in adoption of electrification technologies such as heat pumps and electric vehicles, historical data become less reliable predictors of the future. By employing ResStock, a high-fidelity building stock modeling tool, we can fine-tune electrification scenarios and aggregate models to represent varying geographic resolutions of the grid system, while considering the underlying features of homes. This may enable a more accurate and responsive approach to anticipate and plan for the evolving landscape of energy demands. We present a new framework that leverages building stock energy modeling to identify building models that align with the load shapes and housing attributes of buildings with AMI data. This approach applies two model layers: (1) a classification step that identifies the presence of air conditioning, electric heating, and electric water heating, and (2) an optimization routine that identifies building energy models aligning with load profile data from advanced metering infrastructure meters. This report demonstrates one approach to deploying this framework, and presents results for three test cases that use both modeled and AMI data to assess performance. For a test case using AMI data in Fort Collins, Colorado, we observed a median monthly electricity load CV-RMSE of 16.6%, and a top ten daily heating and cooling median absolute percent error of 7.7% and 8.3%, respectively. For each AMI meter, we identify a set of potential energy models so that downstream use-cases can account for uncertainty driven by variability of baseline technologies and occupant behavior, which impact the response to electrification and energy efficiency scenarios. Our results indicate that ResStock has potential as a scalable solution for modeling residential energy demand at local grid resolutions. Its performance depends on location-specific factors, underlying building characteristics, and the level of aggregation, offering a path towards more precise and adaptive distribution grid planning for the evolving energy landscape.

24 POWER TRANSMISSION AND DISTRIBUTION↗