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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 1,099 records · Page 61
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Immersive Scientific Visualization of Molten-Salt Reactor Waste Characteristics Using Virtual Reality

Immersive visualization is changing how we explore, communicate, and understand complex scientific systems. In nuclear energy, an area in which data are often multidimensional, time-dependent, and difficult to interpret, virtual reality (VR) represents a powerful and intuitive informational medium. This work introduces a VR-based platform that visualizes the post-shutdown behavior and waste management lifecycle of molten-salt reactors (MSRs), a next-generation reactor type with unique operational and safety characteristics. The platform, built in Unity, is streamed on the Meta Quest 3 headset. It transforms high-fidelity simulation data into an interactive, immersive experience. Users can explore time-dependent reactor characteristics such as nuclide decay, which is a key factor for evaluating reactor waste strategies. The datasets were generated using the MOOSE (Multiphysics Object-Oriented Simulation Environment) framework and then processed through ParaView scripting for smooth integration into Unity. From a visualization standpoint, the platform emphasizes spatial storytelling, temporal exploration, and user-centered interaction. Users can navigate 3D reactor geometries, slice through volumetric data, and manipulate time to observe how physical phenomena evolve. Real-scale rendering and embodied interaction make the experience feel tangible. The interface is designed to be accessible, even to those without nuclear or simulation expertise. This lowers the barrier for stakeholders, policymakers, and the general public, while still supporting expert analysis and collaborative decision-making. This work shows how immersive visualization can function as both a scientific tool and a communication interface. By integrating simulation, processing, and visualization into a cohesive workflow, we offer a scalable framework for immersive scientific storytelling. The modular design supports future extensions to other reactor types and lifecycle stages, from shutdown to long-term storage, making the platform adaptable for both research and outreach.

99 - GENERAL AND MISCELLANEOUS↗
DOE OSTI2015

The ensemble switch method for computing interfacial tensions

We present a systematic thermodynamic integration approach to compute interfacial tensions for solid-liquid interfaces, which is based on the ensemble switch method. Applying Monte Carlo simulations and finite-size scaling techniques, we obtain results for hard spheres, which are in agreement with previous computations. The case of solid-liquid interfaces in a variant of the effective Asakura-Oosawa model and of liquid-vapor interfaces in the Lennard-Jones model are discussed as well. We demonstrate that a thorough finite-size analysis of the simulation data is required to obtain precise results for the interfacial tension.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2015

Mass transport and turbulence in gravitationally unstable disk galaxies. I. The case of pure self-gravity

The role of gravitational instability-driven turbulence in determining the structure and evolution of disk galaxies, and the extent to which gravity rather than feedback can explain galaxy properties, remains an open question. To address it, we present high-resolution adaptive mesh refinement simulations of Milky Way-like isolated disk galaxies, including realistic heating and cooling rates and a physically motivated prescription for star formation, but no form of star formation feedback. After an initial transient, our galaxies reach a state of fully nonlinear gravitational instability. In this state, gravity drives turbulence and radial inflow. Despite the lack of feedback, the gas in our galaxy models shows substantial turbulent velocity dispersions, indicating that gravitational instability alone may be able to power the velocity dispersions observed in nearby disk galaxies on 100 pc scales. Moreover, the rate of mass transport produced by this turbulence approaches ∼1 M{sub ⊙} yr{sup −1} for Milky Way-like conditions, sufficient to fully fuel star formation in the inner disks of galaxies. In a companion paper, we add feedback to our models, and use the comparison between the two cases to understand which galaxy properties depend sensitively on feedback and which can be understood as the product of gravity alone. All of the code, initial conditions, and simulation data for our model are publicly available.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2019

Partial molar properties from molecular simulation using multiple linear regression

Partial molar volumes, energies, and enthalpies can be computed from NpT-Gibbs ensemble simulations through a post-processing procedure that leverages fluctuations in composition, total volume, and total energy of a simulation box. By recording the instantaneous box volumes V and instantaneous number of molecules N i of each of n species for M frames, a large M ×n matrix N is constructed, as well as the M × 1 vector V. The 1 × n vector of partial molar volumes V¯ may then be solved using N • V¯=V. A similar construction permits calculation of partial molar energies using M instantaneous measurements of the total energy of the simulation box, and N • U¯=U. Partial molar enthalpies may be derived from U¯, V¯, and pressure p. These properties may be used to calculate enthalpy and entropy of transfer (absorption, extraction, and adsorption) for species in complex mixtures. The method is demonstrated on three systems in the NpT-Gibbs ensemble: a highly compressible natural gas condensate of methane, n-butane, and n-decane, the liquid-phase adsorption of 1,5-pentanediol and ethanol onto the MFI zeolite, and a relatively incompressible mixture of ethanol, n-dodecane, and water at liquid-liquid equilibrium. Property predictions are compared to those from numerical differentiation of simulation data sequentially changing the composition and from equations of state. Here, the method can also be extended to reaction equilibria in a closed system and is applied to a reactive first-principles Monte Carlo simulation of compressed nitrogen/oxygen.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2015

RADIO AND X-RAY SHOCKS IN CLUSTERS OF GALAXIES

Radio relics detected in the outskirts of galaxy clusters are thought to trace radio-emitting relativistic electrons accelerated at cosmological shocks. In this study, using the cosmological hydrodynamic simulation data for the large-scale structure formation and adopting a diffusive shock acceleration (DSA) model for the production of cosmic-ray (CR) electrons, we construct mock radio and X-ray maps of simulated galaxy clusters that are projected in the sky plane. Various properties of shocks and radio relics, including the shock Mach number, radio spectral index, and luminosity, are extracted from the synthetic maps and compared with observations. A substantial fraction of radio and X-ray shocks identified in these maps involve multiple shock surfaces along lines of sight (LOSs), and the morphology of shock distributions in the maps depends on the projection direction. Among multiple shocks in a given LOS, radio observations tend to pick up stronger shocks with flatter radio spectra, while X-ray observations preferentially select weaker shocks with larger kinetic energy flux. As a result, in some cases the shock Mach numbers and locations derived from radio and X-ray observations could differ from each other. We also find that the distributions of the spectral index and radio power of the synthetic radio relics are somewhat inconsistent with those of observed real relics; a bit more radio relics have been observed closer to the cluster core and with steeper spectral indices. We suggest that the inconsistency could be explained if very weak shocks with M{sub s} ≲ 2 accelerate CR electrons more efficiently, compared with the DSA model adopted here.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

Toward flow control: An assessment of the curled wake model in the FLORIS framework

In this work, a new controls-oriented wake model is modified and compared to an analytical Gaussian wake model, high-fidelity simulation data, and experimental wind tunnel campaign. This model, called the curled wake model, captures a wake phenomenon that occurs behind yawed turbines, modeled as a collection of vortices shed from the rotor plane. Through turbine simulations, these vortices are shown to have a significant impact on the prediction of the wake steering's performance. Overall, the results support the concept of secondary steering, or a yawed turbine's ability to deflect the wake of a downstream turbine, and suggest that future turbine wake studies and yaw optimizations should include the curled wake phenomenon.

17 WIND ENERGY↗
DOE OSTI2016

SU-F-T-50: Evaluation of Monte Carlo Simulations Performance for Pediatric Brachytherapy Dosimetry

Purpose: Pediatric tumors are generally treated with multi-modal procedures. Brachytherapy can be used with pediatric tumors, especially given that in this patient population low toxicity on normal tissues is critical as is the suppression of the probability for late malignancies. Our goal is to validate the GATE toolkit on realistic brachytherapy applications, and evaluate brachytherapy plans on pediatrics for accurate dosimetry on sensitive and critical organs of interest. Methods: The GATE Monte Carlo (MC) toolkit was used. Two High Dose Rate (HDR) 192Ir brachytherapy sources were simulated (Nucletron mHDR-v1 and Varian VS2000), and fully validated using the AAPM and ESTRO protocols. A realistic brachytherapy plan was also simulated using the XCAT anthropomorphic computational model .The simulated data were compared to the clinical dose points. Finally, a 14 years old girl with vaginal rhabdomyosarcoma was modelled based on clinical procedures for the calculation of the absorbed dose per organ. Results: The MC simulations resulted in accurate dosimetry in terms of dose rate constant (Λ), radial dose gL(r) and anisotropy function F(r,θ) for both sources.The simulations were executed using ∼1010 number of primaries resulting in statistical uncertainties lower than 2%.The differences between the theoretical values and the simulated ones ranged from 0.01% up to 3.3%, with the largest discrepancy (6%) being observed in the dose rate constant calculation.The simulated DVH using an adult female XCAT model was also compared to a clinical one resulting in differences smaller than 5%. Finally, a realistic pediatric brachytherapy simulation was performed to evaluate the absorbed dose per organ and to calculate DVH with respect to heterogeneities of the human anatomy. Conclusion: GATE is a reliable tool for brachytherapy simulations both for source modeling and for dosimetry in anthropomorphic voxelized models. Our project aims to evaluate a variety of pediatric brachytherapy schemes using a population of pediatric phantoms for several pathological cases. This study is part of a project that has received funding from the European Union Horizon2020 research and innovation programme under the MarieSklodowska-Curiegrantagreement.No691203.The results published in this study reflect only the authors view and the Research Executive Agency (REA) and the European Commission is not responsible for any use that may be madeof the information it contains.

60 APPLIED LIFE SCIENCES↗
NASA NTRS1973

Reliability of cosmic dust data from Pioneers 8 and 9.

A comprehensive study of the characteristics and capabilities of the Pioneer cosmic dust mission is presented to facilitate accurate astronomical adaptations of the data by independent researchers. The characteristics of the sensor and associated electronics as they relate to dynamic range, field of view, and penetration effects in the film are discussed, comparisons are made between flight and simulation data, and statistical analyses are made of the reliability of the flight data. It is shown that the measurements from the Pioneer experiment are highly reliable and provide a valuable contribution to man's knowledge of the meteoroid environment of the solar system.

Gruen, E.↗
DOE OSTI2023

Impact of genotype‐calling methodologies on genome‐wide association and genomic prediction in polyploids

Abstract Discovery and analysis of genetic variants underlying agriculturally important traits are key to molecular breeding of crops. Reduced representation approaches have provided cost‐efficient genotyping using next‐generation sequencing. However, accurate genotype calling from next‐generation sequencing data is challenging, particularly in polyploid species due to their genome complexity. Recently developed Bayesian statistical methods implemented in available software packages, polyRAD, EBG, and updog, incorporate error rates and population parameters to accurately estimate allelic dosage across any ploidy. We used empirical and simulated data to evaluate the three Bayesian algorithms and demonstrated their impact on the power of genome‐wide association study (GWAS) analysis and the accuracy of genomic prediction. We further incorporated uncertainty in allelic dosage estimation by testing continuous genotype calls and comparing their performance to discrete genotypes in GWAS and genomic prediction. We tested the genotype‐calling methods using data from two autotetraploid species, Miscanthus sacchariflorus and Vaccinium corymbosum , and performed GWAS and genomic prediction. In the empirical study, the tested Bayesian genotype‐calling algorithms differed in their downstream effects on GWAS and genomic prediction, with some showing advantages over others. Through subsequent simulation studies, we observed that at low read depth, polyRAD was advantageous in its effect on GWAS power and limit of false positives. Additionally, we found that continuous genotypes increased the accuracy of genomic prediction, by reducing genotyping error, particularly at low sequencing depth. Our results indicate that by using the Bayesian algorithm implemented in polyRAD and continuous genotypes, we can accurately and cost‐efficiently implement GWAS and genomic prediction in polyploid crops.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

DeFault: DEep‐Learning‐Based FAULT Delineation Using the IBDP Passive Seismic Data at the Decatur CO2 Storage Site

Abstract The carbon capture, utilization, and storage (CCUS) framework is an essential component in reducing greenhouse gas emissions, with its success hinging on the comprehensive knowledge of subsurface geology and geomechanics. Passive seismic event relocation and fault detection offer vital insights into subsurface structures and the ability to monitor fluid migration pathways. Accurate identification and localization of seismic events, however, face significant challenges, including the necessity for high‐quality seismic data and advanced computational methods. To address these challenges, we introduce a novel deep learning method, , specifically designed for passive seismic source relocation and fault delineating for passive seismic monitoring projects. By leveraging data domain‐adaptation, allows us to train a neural network with labeled synthetic data and apply it directly to field data. Using , the passive seismic sources are automatically clustered based on their recording time and spatial locations, and subsequently, faults and fractures are delineated accordingly. We demonstrate the efficacy of on a field case study involving injection related microseismic data from Decatur, Illinois area. Our approach accurately and efficiently relocated passive seismic events, identified faults and could aid in potential damage induced by seismicity. Our results highlight the potential of as a valuable tool for passive seismic monitoring, emphasizing its role in ensuring CCUS project safety. This research bolsters the understanding of subsurface characterization in CCUS, illustrating machine learning’s capacity to refine these methods. Ultimately, our work has significant implications for CCUS technology deployment, an essential strategy in combating climate change. Plain Language Summary In our quest to tackle climate change, we use a strategy known as carbon capture, utilization, and storage (CCUS) to keep greenhouse gases out of the atmosphere. This strategy relies heavily on our ability to understand what's happening deep under the earth's surface. To make sure we store super critical safely, we need to accurately map out the geological structure, especially faults, but this is tough without high‐quality data and complex computer programs. We've developed a new tool called “DeFault,” which uses advanced machine learning to improve how we find and map these underground features. “DeFault” is smart enough to learn from numerically simulated data and then apply what it’s learned to real‐world situations. It groups together seismic activity—tiny tremors and shifts in the earth—based on when and where they happen, which helps us spot where there might be cracks or faults. We tested “DeFault” in Illinois, where CO 2 is injected underground, and it successfully pinpointed where these tremors occurred and mapped out the faults, helping to prevent accidents accurately in the future. Our study shows that “DeFault” will be a powerful ally in making CCUS safer and more effective, especially for the Illinois Basin Decatur Project. Key Points Faults and fractures introduced by carbon storage can be monitored by passive seismicity DeFault algorithm enables an automatic process for accurate and efficient passive seismic event locating and clustering

58 GEOSCIENCES↗
DOE OSTI2015

The structure and IR signatures of the arginine-glutamate salt bridge. Insights from the classical MD simulations

Salt bridges and ionic interactions play an important role in protein stability, protein-protein interactions, and protein folding. Here, we provide the classical MD simulations of the structure and IR signatures of the arginine (Arg)–glutamate (Glu) salt bridge. The Arg-Glu model is based on the infinite polyalanine antiparallel two-stranded β-sheet structure. The 1 μs NPT simulations show that it preferably exists as a salt bridge (a contact ion pair). Bidentate (the end-on and side-on structures) and monodentate (the backside structure) configurations are localized [Donald et al., Proteins 79, 898–915 (2011)]. These structures are stabilized by the short {sup +}N–H⋯O{sup −} bonds. Their relative stability depends on a force field used in the MD simulations. The side-on structure is the most stable in terms of the OPLS-AA force field. If AMBER ff99SB-ILDN is used, the backside structure is the most stable. Compared with experimental data, simulations using the OPLS all-atom (OPLS-AA) force field describe the stability of the salt bridge structures quite realistically. It decreases in the following order: side-on > end-on > backside. The most stable side-on structure lives several nanoseconds. The less stable backside structure exists a few tenth of a nanosecond. Several short-living species (solvent shared, completely separately solvated ionic groups ion pairs, etc.) are also localized. Their lifetime is a few tens of picoseconds or less. Conformational flexibility of amino acids forming the salt bridge is investigated. The spectral signature of the Arg-Glu salt bridge is the IR-intensive band around 2200 cm{sup −1}. It is caused by the asymmetric stretching vibrations of the {sup +}N–H⋯O{sup −} fragment. Result of the present paper suggests that infrared spectroscopy in the 2000–2800 frequency region may be a rapid and quantitative method for the study of salt bridges in peptides and ionic interactions between proteins. This region is usually not considered in spectroscopic studies of peptides and proteins.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS1977

The epoch state navigation filter

The formulation of a recursive maximum likelihood navigation system employing reference position and velocity vectors as state variables is presented. Convenient forms of the required variational equations of motion are developed together with an explicit form of the associated state transition matrix needed to refer measurement data from the measurement time to the epoch time. Computational advantages accrue from this design in that the usual forward extrapolation of the covariance matrix of estimation errors can be avoided without incurring unacceptable system errors. Simulation data for earth orbiting satellites are provided to substantiate this assertion.

Battin, R. H.↗
NASA NTRS2001

Latitudinal Transport of Angular Momentum by Cellular Flows Observed with MDI

We have analyzed Doppler velocity images from the MDI instrument on SOHO to determine the latitudinal transport of angular momentum by the cellular photospheric flows. Doppler velocity images from 60-days in May to July of 1996 were processed to remove the p-mode oscillations, the convective blue shift, the axisymmetric flows, and any instrumental artifacts. The remaining cellular flows were examined for evidence of latitudinal angular momentum transport. Small cells show no evidence of any such transport. Cells the size of supergranules (30,000 km in diameter) show strong evidence for a poleward transport of angular momentum. This would be expected if supergranules are influenced by the Coriolis force, and if the cells are elongated in an east-west direction. We find good evidence for just such an east-west elongation of the supergranules. This elongation may be the result of differential rotation shearing the cellular structures. Data simulations of this effect support the conclusion that elongated supergranules transport angular momentum from the equator toward the poles, Cells somewhat larger than supergranules do not show evidence for this poleward transport. Further analysis of the data is planned to determine if the direction of angular momentum transport reverses for even larger cellular structures. The Sun's rapidly rotating equator must be maintained by such transport somewhere within the convection zone.

Hathaway, David H.↗
NASA NTRSDate not supplied

Method for Real-Time State Estimation of Structural Modes for an Aeroelastic Wind Tunnel Model

A method for estimating displacements, velocities, and accelerations of structural modes in generalized coordinates from measured sensor data in real time is developed and demonstrated. Data from conventional strain gauges and fiber optic strain sensors (FOSS) were combined with strain mode shapes to produce least-squares estimates of the structural mode displacements. Similarly, accelerometer data were combined with displacement mode shapes to estimate structural mode accelerations. Estimates were then combined using a Kalman filter to refine the displacement estimates and produce structural mode velocity estimates. The approach was demonstrated using simulation data for the NASA-Boeing collaboration called the Integrated Adaptive Wing Technology Maturation (IAWTM) project in both a stable open-loop condition and an unstable condition where estimated displacement and velocity states were used for feedback control. Results supported the feasibility of using this approach for feedback control and system identification applications for wind tunnel tests.

Aeroservoelasticity↗
DOE OSTI2024

Toward Accelerating Discovery via Physics-Driven and Interactive Multifidelity Bayesian Optimization

Both computational and experimental material discovery bring forth the challenge of exploring multidimensional and often nondifferentiable parameter spaces, such as phase diagrams of Hamiltonians with multiple interactions, composition spaces of combinatorial libraries, processing spaces, and molecular embedding spaces. Often these systems are expensive or time consuming to evaluate a single instance, and hence classical approaches based on exhaustive grid or random search are too data intensive. This resulted in strong interest toward active learning methods such as Bayesian optimization (BO) where the adaptive exploration occurs based on human learning (discovery) objective. However, classical BO is based on a predefined optimization target, and policies balancing exploration and exploitation are purely data driven. In practical settings, the domain expert can pose prior knowledge of the system in the form of partially known physics laws and exploration policies often vary during the experiment. Here, we propose an interactive workflow building on multifidelity BO (MFBO), starting with classical (data-driven) MFBO, then expand to a proposed structured (physics-driven) structured MFBO (sMFBO), and finally extend it to allow human-in-the-loop interactive interactive MFBO (iMFBO) workflows for adaptive and domain expert aligned exploration. These approaches are demonstrated over highly nonsmooth multifidelity simulation data generated from an Ising model, considering spin–spin interaction as parameter space, lattice sizes as fidelity spaces, and the objective as maximizing heat capacity. Detailed analysis and comparison show the impact of physics knowledge injection and real-time human decisions for improved exploration with increased alignment to ground truth. Here, the associated notebooks allow to reproduce the reported analyses and apply them to other systems.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1990

Ionospheric refraction effects on orbit determination using the orbit determination error analysis system

The influence of ionospheric refraction on orbit determination was studied through the use of the Orbit Determination Error Analysis System (ODEAS). The results of a study of the orbital state estimate errors due to the ionospheric refraction corrections, particularly for measurements involving spacecraft-to-spacecraft tracking links, are presented. In current operational practice at the Goddard Space Flight Center (GSFC) Flight Dynamics Facility (FDF), the ionospheric refraction effects on the tracking measurements are modeled in the Goddard Trajectory Determination System (GTDS) using the Bent ionospheric model. While GTDS has the capability of incorporating the ionospheric refraction effects for measurements involving ground-to-spacecraft tracking links, such as those generated by the Ground Spaceflight Tracking and Data Network (GSTDN), it does not have the capability to incorporate the refraction effects for spacecraft-to-spacecraft tracking links for measurements generated by the Tracking and Data Relay Satellite System (TDRSS). The lack of this particular capability in GTDS raised some concern about the achievable accuracy of the estimated orbit for certain classes of spacecraft missions that require high-precision orbits. Using an enhanced research version of GTDS, some efforts have already been made to assess the importance of the spacecraft-to-spacecraft ionospheric refraction corrections in an orbit determination process. While these studies were performed using simulated data or real tracking data in definitive orbit determination modes, the study results presented here were obtained by means of covariance analysis simulating the weighted least-squares method used in orbit determination.

Yee, C. P.↗
DOE OSTI2019

Yearly report for the period Jan. 2018 – Feb. 2019 IC Project: w17_faultprediction “Critical Stress in Earth”

The consequence of earthquake is usually catastrophic. Currently, we cannot determine when a fault is approaching failure due to either anthropogenic activities or tectonic movement. In an anthropogenically perturbed setting, the rate of physical changes on faults far exceeds most natural processes with currently unpredictable and unmeasurable results. In a tectonic setting we generally do not know where a fault is in the earthquake cycle beyond noting how long has passed since the last rupture, which is itself sometimes unknown. The Laboratory has therefore funded a multi million multi-year LDRD-DR program that comprises experiments, numerical modeling, and machine learning in order to develop and test a highly novel approach to probe the earthquake cycle and in particular, to detect and locate stressed faults that are approaching failure. For this program, modeling of a series of sheared granular layers undergoing stick-slip behavior using the EES-17’s Combined Finite-Discrete Element Method (FDEM) based code HOSS (Hybrid Optimization Software Suite) plays a pivotal role since numerical simulations of granular fault gouge allow for analysis of the mechanical behavior of the system at a level of spatial and temporal resolution not accessible experimentally, and also offer the possibility of identifying the most important parameters governing earthquake dynamics. The simulated data also provide very detailed stress, strain and motion information for machine learning purpose to predict earthquake. The code – HOSS – has been developed in Geophysics Group in LANL during the past ten years and is used to simulate the stick-slip behavior of granular fault gouge. One of the key feature of HOSS is that it is superior to pure finite element method and discrete element method and can provide very detailed evolvement information of granular fault gouge. Additionally, its parallel computing capability makes large scale earthquake gouge simulation possible. Taking these facts into account, and also because few other fully parallel FDEM code exists, this IC project allows LANL to stay at the forefront of earthquake gouge and granular material simulation in the world.

42 ENGINEERING↗
DOE OSTI2022

Challenge Problem 1: Preliminary Model Development and Assessment of Flexible Heat Transfer Modeling Approaches

This report presents the modeling progress of a university consortium studying flexible modeling for turbulent heat transfer. In the context of advanced nuclear reactor design, where challenges include non-unity Prandtl fluids, free and mixed convection, and transitional flow, computational fluid dynamics methods are underutilized due to low confidence in modeling approaches and high computational cost. This report evaluates the performance of engineering CFD models in diabatic, buoyant turbulent flow. It finds that all turbulence models including several variants of the k-ε and k-ω models struggle to predict accurate turbulent momentum and heat transfer in such flows. The Nusselt numbers have been compared between the models and the DNS data, where calculations have been performed for each case and trends have shown a good agreement between DNS estimated Nusselt numbers and available correlations as well as experimental data. A novel DNS correlation for high Pr cases as they are transitioning from mixed convection to natural convection has been proposed. While Nusselt number errors relative to DNS range from 20% to 50%, the models capture similar trends to DNS with respect to Nusselt suppression and amplification under varying levels of buoyancy effect. This report also highlights model form error as a significant contributor to CFD predictions and proposes a framework for quantifying model error and improving confidence in CFD calculations. To improve the predictive capability of engineering CFD models, data-driven approaches for turbulence models are investigated. Theoretical frameworks based on the invariant tensor / vector basis neural networks for prediction of Reynolds stresses and turbulent heat fluxes are employed. The models are developed using direct numerical simulations data for forced convection flows of different fluids in vertical planar channel domain. The framework is implemented in spectral element solvers Nek5000 / nekRS and has shown a potential for future development and consideration of mixed convection flows.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗