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At least 1,135 records · Page 63

Upscaling Methods Applied to a Fine-Scale Reservoir Model

This study was conducted as part of the Southwest Regional Partnership on Carbon Sequestration (SWP) project to evaluate how upscaling fine-scale simulation models to coarse-scale simulation models impacted the results. The focus was on the Farnsworth Unit (FWU) and its Morrow' B' Sandstone reservoir, specifically the west half of the field. Due to data limitations and the geologic characteristics of the surrounding area, the upscaling was limited to the west half of the FWU rather than a broader basinscale model. The primary aim was to explore how upscaling impacts numerical simulation models, particularly regarding CO 2 -enhanced oil recovery (EOR) and storage capacity predictions. Upscaling was necessary to reduce computational demands when transitioning from high-resolution geological models to coarser grids, as large-scale simulations with finer grids can be computationally prohibitive. This study expands on previous work by the SWP to understand how additional upscaling, applied to already fine-scale numerical simulation models, affects reservoir performance simulations (Ampomah, Balch, & Grigg, 2015). This is key to understanding how loss of resolution can affect coarsescale model results that may be used for large sensitivity analyses, uncertainty quantifications, and training data for machine learning applications.

02 PETROLEUM↗

A low-scale flavon model with a $ {\mathrm{\mathbb{Z}}}_N$ symmetry

We propose a model that explains the fermion mass hierarchy by the Froggatt-Nielsen mechanism with a discrete $ {\mathrm{\mathbb{Z}}}_N^F $ symmetry. As a concrete model, we study a super-symmetric model with a single flavon coupled to the minimal supersymmetric Standard Model. Flavon develops a TeV scale vacuum expectation value for realizing flavor hierarchy, an appropriate μ -term and the electroweak scale, hence the model has a low cutoff scale. We demonstrate how the flavon is successfully stabilized together with the Higgs bosons in the model. The discrete flavor symmetry $ {\mathrm{\mathbb{Z}}}_N^F $ controls not only the Standard Model fermion masses, but also the Higgs potential and a mass of the Higgsino which is a good candidate for dark matter. The hierarchy in the Higgs-flavon sector is determined in order to make the model anomaly-free and realize a stable electroweak vacuum. We show that this model can explain the fermion mass hierarchy, realistic Higgs-flavon potential and thermally produced dark matter at the same time. We discuss flavor violating processes induced by the light flavon which would be detected in future experiments.

Supersymmetric Standard Model↗

Scaling effects in the impact response of graphite-epoxy composite beams

In support of crashworthiness studies on composite airframes and substructure, an experimental and analytical study was conducted to characterize size effects in the large deflection response of scale model graphite-epoxy beams subjected to impact. Scale model beams of 1/2, 2/3, 3/4, 5/6, and full scale were constructed of four different laminate stacking sequences including unidirectional, angle ply, cross ply, and quasi-isotropic. The beam specimens were subjected to eccentric axial impact loads which were scaled to provide homologous beam responses. Comparisons of the load and strain time histories between the scale model beams and the prototype should verify the scale law and demonstrate the use of scale model testing for determining impact behavior of composite structures. The nonlinear structural analysis finite element program DYCAST (DYnamic Crash Analysis of STructures) was used to model the beam response. DYCAST analysis predictions of beam strain response are compared to experimental data and the results are presented.

Jackson, Karen E.↗

The OME Framework for genome-scale systems biology

The life sciences are undergoing continuous and accelerating integration with computational and engineering sciences. The biology that many in the field have been trained on may be hardly recognizable in ten to twenty years. One of the major drivers for this transformation is the blistering pace of advancements in DNA sequencing and synthesis. These advances have resulted in unprecedented amounts of new data, information, and knowledge. Many software tools have been developed to deal with aspects of this transformation and each is sorely needed. However, few of these tools have been forced to deal with the full complexity of genome-scale models along with high throughput genome-scale data. This particular situation represents a unique challenge, as it is simultaneously necessary to deal with the vast breadth of genome-scale models and the dizzying depth of high-throughput datasets. It has been observed time and again that as the pace of data generation continues to accelerate, the pace of analysis significantly lags behind. It is also evident that, given the plethora of databases and software efforts, it is still a significant challenge to work with genome-scale metabolic models, let alone next-generation whole cell models. We work at the forefront of model creation and systems scale data generation. The OME Framework was borne out of a practical need to enable genome-scale modeling and data analysis under a unified framework to drive the next generation of genome-scale biological models. Here we present the OME Framework. It exists as a set of Python classes. However, we want to emphasize the importance of the underlying design as an addition to the discussions on specifications of a digital cell. A great deal of work and valuable progress has been made by a number of communities towards interchange formats and implementations designed to achieve similar goals. While many software tools exist for handling genome-scale metabolic models or for genome-scale data analysis, no implementations exist that explicitly handle data and models concurrently. The OME Framework structures data in a connected loop with models and the components those models are composed of. This results in the first full, practical implementation of a framework that can enable genome-scale design-build-test. Over the coming years many more software packages will be developed and tools will necessarily change. However, we hope that the underlying designs shared here can help to inform the design of future software.

59 BASIC BIOLOGICAL SCIENCES↗

Microburst modelling and scaling

A microburst can be modeled by releasing a volume of fluid that is slightly heavier than the ambient fluid, allowing it to fall onto a horizontal surface. Vorticity develops on the sides of this parcel as it descends and causes it to roll up into a turbulent vortex ring which impinges on the ground. Such a model exhibits many of the features of naturally occurring microbursts which are a hazard to aviation. In this paper this model is achieved experimentally by releasing a volume of salt water into fresh water from a cylindrical dispenser. When care is taken with the release the spreading rate of the surface outflow is measurable and quite repeatable despite the fact that the flow is turbulent. An elementary numerical approximation to this model, based on inviscid vortex dynamics, has also been developed. A scaling law is proposed which allows experiments with different fluid densities to be compared with each other and with the numerical results. More importantly the scaling law makes it possible to compare the model results with real microbursts.

Lundgren, T. S.↗

The long road to groundwater RODs on the ORR: development of a regional groundwater model - 15632

This paper describes the first year of planning and development for the Oak Ridge Reservation (ORR) regional groundwater flow model (ORGFM). The first stage involved the creation of a groundwater model Technical Advisory Group (TAG), made up of local and national industry experts to support the model development. As a first step in the model development process, a smaller-scale model (a Test Case Model) is being developed to test the modeling tools and approach being considered for the regional model. The Test Case Model is allowing the team to identify and develop work-flow processes on a small scale prior to developing the large, regional-scale model. The modeling team currently is testing the combined use of EarthVision{sup R} and MODFLOW-USG (a modular finite-difference flow model using un-structured grids) to develop the regional-scale model. It is anticipated that the ORGFM will be completed by 2016. This paper presents the progress of the ORGFM model development. (authors)

54 ENVIRONMENTAL SCIENCES↗

Improving the phenotype predictions of a yeast genome‐scale metabolic model by incorporating enzymatic constraints

Abstract Genome‐scale metabolic models ( GEM s) are widely used to calculate metabolic phenotypes. They rely on defining a set of constraints, the most common of which is that the production of metabolites and/or growth are limited by the carbon source uptake rate. However, enzyme abundances and kinetics, which act as limitations on metabolic fluxes, are not taken into account. Here, we present GECKO , a method that enhances a GEM to account for enzymes as part of reactions, thereby ensuring that each metabolic flux does not exceed its maximum capacity, equal to the product of the enzyme's abundance and turnover number. We applied GECKO to a Saccharomyces cerevisiae GEM and demonstrated that the new model could correctly describe phenotypes that the previous model could not, particularly under high enzymatic pressure conditions, such as yeast growing on different carbon sources in excess, coping with stress, or overexpressing a specific pathway. GECKO also allows to directly integrate quantitative proteomics data; by doing so, we significantly reduced flux variability of the model, in over 60% of metabolic reactions. Additionally, the model gives insight into the distribution of enzyme usage between and within metabolic pathways. The developed method and model are expected to increase the use of model‐based design in metabolic engineering.

59 BASIC BIOLOGICAL SCIENCES↗

A Wind Tunnel Investigation of a Small Scale Tiltrotor Model in Descending Flight

A small-scale tiltrotor model was tested in the 7-by 10-foot Wind Tunnel at NASA Ames Research Center, with the goal of better understanding Vortex Ring State (VRS) effects on tiltrotor aircraft. Test objectives were to obtain performance data of a tiltrotor model over a wide range of descent conditions, to explore the effects of sideslip at these descent conditions, and to investigate the validity of using a single-rotor with a physical image plane to simulate dual rotor performance characteristics. The model consisted of a pair of 2-bladed teetering rotors with untwisted, 11.125-inch diameter, rectangular planform blades. Model configuration variations included a dual-rotor, an isolated-rotor, and a single-rotor with a physical image plane. Rotor performance data were obtained for the dual-rotor configuration operating over a wide range of descent and sideslip conditions. Isolated-rotor and single-rotor with image plane configurations were tested over an abbreviated range of descent conditions. Results of this investigation are presented and show mean thrust reductions in the region of VRS for each model configuration. In comparison with the dual-rotor configuration, the isolated-rotor and single-rotor with image plane configurations produced thrust results similar in trend but different in magnitude.

Abrego, Anita I.↗

On the Scaling Laws for Jet Noise in Subsonic and Supersonic Flow

The scaling laws for the simulation of noise from subsonic and ideally expanded supersonic jets are examined with regard to their applicability to deduce full scale conditions from small-scale model testing. Important parameters of scale model testing for the simulation of jet noise are identified, and the methods of estimating full-scale noise levels from simulated scale model data are addressed. The limitations of cold-jet data in estimating high-temperature supersonic jet noise levels are discussed. It is shown that the jet Mach number (jet exit velocity/sound speed at jet exit) is a more general and convenient parameter for noise scaling purposes than the ratio of jet exit velocity to ambient speed of sound. A similarity spectrum is also proposed, which accounts for jet Mach number, angle to the jet axis, and jet density ratio. The proposed spectrum reduces nearly to the well-known similarity spectra proposed by Tam for the large-scale and the fine-scale turbulence noise in the appropriate limit.

Vu, Bruce↗

Modeling of the Molten Salt Reactor Experiment with SCALE

A SCALE model was developed for the Molten Salt Reactor Experiment (MSRE) benchmark that was recently added to the International Handbook of Evaluated Reactor Physics Benchmark Experiments. This SCALE model served as a basis for criticality calculations and nuclear data sensitivity and uncertainty analyses with the Monte Carlo code Shift and the TSUNAMI computational capabilities in the SCALE code system. The focus of this work is the assessment of the impact of nuclear data on the calculated eigenvalue results in support of the discussion of differences between the calculated and the experimental eigenvalue result. The differences in the eigenvalues obtained using the ENDF/B-VII.0, ENDF/B-VII.1, and ENDF/B-VIII.0 nuclear data libraries cover a relatively small range of ~230 pcm. Since eigenvalue sensitivity of the MSRE is dominated by the neutron multiplicity and neutron capture of 235 U and elastic scattering in graphite, relevant changes in the ENDF/B libraries for nuclear reactions (such as carbon capture) that caused large differences in other graphite-moderated systems did not have a significant impact. Propagation of nuclear data uncertainty results in an eigenvalue uncertainty of ~700 pcm with the major contributors being 235 U neutron multiplicity, graphite elastic scattering, and 7Li neutron capture. All calculations resulted in large differences of ~2000 pcm in eigenvalue compared to the benchmark experimental value. Several potential contributors to this difference—including uncertainties and gaps in the knowledge of the material, geometry, and nuclear data—were identified. Simplified models of the full MSRE core were developed, and similarity assessments were conduced with the full MSRE core model. It was found that simplified models can serve as adequate surrogates of the full-core model such that they can be used for performing selected nuclear data performance assessments with a lower computational burden.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

On the Scaling Laws and Similarity Spectra for Jet Noise in Subsonic and Supersonic Flow

The scaling laws for the simulation of noise from subsonic and ideally expanded supersonic jets are reviewed with regard to their applicability to deduce full-scale conditions from small-scale model testing. Important parameters of scale model testing for the simulation of jet noise are identified, and the methods of estimating full- scale noise levels from simulated scale model data are addressed. The limitations of cold-jet data in estimating high-temperature supersonic jet noise levels are discussed. New results are presented showing the dependence of overall sound power level on the jet temperature ratio at various jet Mach numbers. A generalized similarity spectrum is also proposed, which accounts for convective Mach number and angle to the jet axis.

Kandula, Max↗

Wind tunnel and ground static tests of a .094 scale powered model of a modified T-39 lift/cruise fan V/STOL research airplane

Ground static and wind tunnel test of a scale model modified T-39 airplane are reported. The configuration in the nose and replacement of the existing nacelles with tilting lift/cruise fans. The model was powered with three 14 cm diameter tip driven turbopowered simulators. Forces and moments were measured by an internal strain guage balance. Engine simulator thrust and mass flow were measured by calibrated pressure and temperature instrumentation mounted downstream of the fans. The low speed handling qualities and general aerodynamic characteristics of the modified T-39 were defined. Test variables include thrust level and thrust balance, forward speed, model pitch and sideslip angle at forward speeds, model pitch, roll, and ground height during static tests, lift/cruise fan tilt angle, flap and aileron deflection angle, and horizonal stabilizer angle. The effects of removing the landing gear, the lift/cruise fans, and the tail surfaces were also investigated.

Hunt, D.↗

Unraveling fundamental mechanisms of silicon nitride crystallization in microelectronics manufacturing

This research project investigates the fundamental mechanisms of silicon nitride (SiN) crystallization, aiming to enhance the understanding of this critical material in microelectronics manufacturing. Through a collaborative effort between Sandia National Laboratories, the University of Tennessee, and the University of Florida, we developed a comprehensive framework that integrates experimental techniques, atomistic modeling, meso-scale simulations, and an integrated multi-scale model to capture this physical phenomenon on multiple time and length scales . The project developed a new machine learning based atomistic potential and utilized advanced phase field modeling to capture the complexities of polycrystalline growth and the influence of mechanical stresses on crystallization dynamics. By employing a grain tracker algorithm, the meso-scale model effectively identified and tracked individual crystal grains, enabling the simulation of anisotropic growth behaviors reflective of SiN’s physical properties. The integration of atomistic simulations with meso-scale modeling created a powerful multi-scale framework that validated atomistic inputs and enhanced predictive accuracy for crystallization dynamics at larger scales, validated experimentally. This adaptable modeling capability not only accelerates development times by informing manufacturing processes but also serves as a valuable starting point for understanding crystallization physics in similar materials. The insights gained from this research unlock new opportunities for the development of advanced materials tailored for future microelectronics and photonics applications. Overall, this project represents a significant advancement in understanding of fundamental physics of SiN and establishes a foundation for future research in material science, bridging the gap between atomic-level phenomena and macroscopic material behaviors for practical applications.

36 MATERIALS SCIENCE↗

Wake Geometry Measurements and Analytical Calculations on a Small-Scale Rotor Model

An experimental investigation was conducted in the Langley 14- by 22-Foot Subsonic Tunnel to quantify the rotor wake behind a scale model helicopter rotor in forward level flight at one thrust level. The rotor system in this test consisted of a four-bladed fully articulated hub with blades of rectangular planform and an NACA 0012 airfoil section. A laser light sheet, seeded with propylene glycol smoke, was used to visualize the vortex geometry in the flow in planes parallel and perpendicular to the free-stream flow. Quantitative measurements of wake geometric proper- ties, such as vortex location, vertical skew angle, and vortex particle void radius, were obtained as well as convective velocities for blade tip vortices. Comparisons were made between experimental data and four computational method predictions of experimental tip vortex locations, vortex vertical skew angles, and wake geometries. The results of these comparisons highlight difficulties of accurate wake geometry predictions.

Ghee, Terence A.↗

Acoustic characteristics of 1/20-scale model helicopter rotors

A wind tunnel test to study the effects of geometric scale on acoustics and to investigate the applicability of very small scale models for the study of acoustic characteristics of helicopter rotors was conducted in the United Technologies Research Center Acoustic Research Tunnel. The results show that the Reynolds number effects significantly alter the Blade-Vortex-Interaction (BVI) Noise characteristics by enhancing the lower frequency content and suppressing the higher frequency content. In the time domain this is observed as an inverted thickness noise impulse rather than the typical positive-negative impulse of BVI noise. At higher advance ratio conditions, in the absence of BVI, the 1/20 scale model acoustic trends with Mach number follow those of larger scale models. However, the 1/20 scale model acoustic trends appear to indicate stall at higher thrust and advance ratio conditions.

Shenoy, Rajarama K.↗

GenSLMs: Genome-scale language models reveal SARS-CoV-2 evolutionary dynamics

We seek to transform how new and emergent variants of pandemic-causing viruses, specifically SARS-CoV-2, are identified and classified. By adapting large language models (LLMs) for genomic data, we build genome-scale language models (GenSLMs) which can learn the evolutionary landscape of SARS-CoV-2 genomes. By pre-training on over 110 million prokaryotic gene sequences and fine-tuning a SARS-CoV-2-specific model on 1.5 million genomes, we show that GenSLMs can accurately and rapidly identify variants of concern. Thus, to our knowledge, GenSLMs represents one of the first whole-genome scale foundation models which can generalize to other prediction tasks. We demonstrate scaling of GenSLMs on GPU-based supercomputers and AI-hardware accelerators utilizing 1.63 Zettaflops in training runs with a sustained performance of 121 PFLOPS in mixed precision and peak of 850 PFLOPS. We present initial scientific insights from examining GenSLMs in tracking evolutionary dynamics of SARS-CoV-2, paving the path to realizing this on large biological data.

Zvyagin, Maxim↗