Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “Computational Physics”

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 415 records · Page 23
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Diffusion Probabilistic Modeling for Video Generation

Denoising diffusion probabilistic models are a promising new class of generative models that mark a milestone in high-quality image generation. This paper showcases their ability to sequentially generate video, surpassing prior methods in perceptual and probabilistic forecasting metrics. We propose an autoregressive, end-to-end optimized video diffusion model inspired by recent advances in neural video compression. The model successively generates future frames by correcting a deterministic next-frame prediction using a stochastic residual generated by an inverse diffusion process. We compare this approach against six baselines on four datasets involving natural and simulation-based videos. We find significant improvements in terms of perceptual quality and probabilistic frame forecasting ability for all datasets.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Tycho: Realistically Simulating Exoplanets within Stellar Clusters. I. Improving the Monte Carlo Approach

To fully understand the diverse population of exoplanets, we must study their early lives within open clusters, the birthplace of most stars with masses >0.5M {sub ⊙} (including those currently in the field). Indeed, when we observe planets within clustered environments, we notice highly eccentric and odd systems that suggest the importance of dynamical pathways created by interactions with additional bodies (as in the case of HD 285507b). However, it has proven difficult to investigate these effects, as many current numerical solvers for the multi-scale N-body problem are simplified and limited in scope. To remedy this, we aim to create a physically complete computational solution to explore the role of stellar close encounters and interplanetary interactions in producing the observed exoplanet populations for both open cluster stars and field stars. We present a new code, Tycho, which employs a variety of different computational techniques, including multiple N-body integration methods, close encounter handling, modified Monte Carlo scattering experiments, and a variety of empirically informed initial conditions. We discuss the methodology in detail, and its implementation within the AMUSE software framework. Approximately 1% of our systems are promptly disrupted by star-star encounters contributing to the rogue planets occurrence rate. Additionally, we find that close encounters which that perturb long-period planets lead to 38.3% of solar-system-like planetary systems becoming long-term unstable.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

DRAGraces: A Pipeline for the GRACES High-resolution Spectrograph at Gemini

This paper describes the software Data Reduction and Analysis for GRACES (DRAGraces), which is a pipeline reducing spectra from Gemini Remote Access to the CFHT ESPaDOnS Spectrograph (GRACES) at the Gemini North Telescope. The code is written in the IDL language. It is designed to find all the GRACES frames in a given directory, automatically determine the list of bias, flat, arc, and science frames, and perform the whole reduction and extraction within a few minutes. We compare the output from DRAGraces with that of the Open source Pipeline for ESPaDOnS Reduction and Analysis (OPERA), a pipeline developed at the Canada–France–Hawaii Telescope (CFHT) that also can extract GRACES spectra. Both pipelines were developed completely independently, yet they give very similar extracted spectra. They both have their advantages and disadvantages. For instance, DRAGraces is more straightforward and easy to use and is less likely to be derailed by a parameter that needs to be tweaked, while OPERA offers a more careful extraction that can be significantly superior when the highest resolution is required and when the signal-to-noise ratio is low. One should compare both before deciding which one to use for their science. Yet, both pipelines deliver a fairly comparable resolution power (R ~ 52.8k and 36.6k for DRAGraces and R ~ 58k and 40k for OPERA in high- and low-resolution spectral modes, respectively), wavelength solution, and signal-to-noise ratio per resolution element.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2025

A Scalable Gaussian Process Approach to Shear Mapping with MuyGPs

Analysis of cosmic shear is an integral part of understanding structure growth across cosmic time, which in turn provides us with information about the nature of dark energy. Conventional methods generate shear maps from which we can infer the matter distribution in the universe. Current methods (e.g., Kaiser–Squires inversion) for generating these maps, however, are tricky to implement and can introduce bias. Recent alternatives construct a spatial process prior for the lensing potential, which allows for inference of the convergence and shear parameters given lensing shear measurements. Realizing these spatial processes, however, scales cubically in the number of observations—an unacceptable expense as near-term surveys expect billions of correlated measurements. Therefore, we present a linearly scaling shear map construction alternative using a scalable Gaussian process prior called MuyGPs. MuyGPs avoids cubic scaling by conditioning interpolation on only nearest neighbors and fits hyperparameters using batched leave-one-out cross-validation. This work is the first step toward a full, scalable mass mapping method. We work in a simplified regime where we validate our method by interpolating and analyzing maps given noisy point-estimate data from all three shear fields, taken from a suite of N -body ray-tracing simulations. We also show that we can perform these operations at the scale of billions of galaxies on high-performance computing platforms.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

PATOKA: Simulating Electromagnetic Observables of Black Hole Accretion

Abstract The Event Horizon Telescope (EHT) has released analyses of reconstructed images of horizon-scale millimeter emission near the supermassive black hole at the center of the M87 galaxy. Parts of the analyses made use of a large library of synthetic black hole images and spectra, which were produced using numerical general relativistic magnetohydrodynamics fluid simulations and polarized ray tracing. In this article, we describe the PATOKA pipeline, which was used to generate the Illinois contribution to the EHT simulation library. We begin by describing the relevant accretion systems and radiative processes. We then describe the details of the three numerical codes we use, iharm , ipole , and igrmonty , paying particular attention to differences between the current generation of the codes and the originally published versions. Finally, we provide a brief overview of simulated data as produced by PATOKA and conclude with a discussion of limitations and future directions.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

Uncertainty Propagation within Chained Models for Machine Learning Reconstruction of Neutrino-LAr Interactions

Sequential or chained models are increasingly prevalent in machine learning for scientific applications, due to their flexibility and ease of development. Chained models are particularly useful when a task is separable into distinct steps with a hierarchy of meaningful intermediate representations. In reliability-critical tasks, it is important to quantify the confidence of model inferences. However, chained models pose an additional challenge for uncertainty quantification, especially when input uncertainties need to be propagated. In such cases, a fully uncertainty-aware chain of models is required, where each step accepts a probability distribution over the input space, and produces a probability distribution over the output space. In this work, we present a case study for adapting a single model within an existing chain, designed for reconstruction within neutrino-Argon interactions, developed for neutrino oscillation experiments such as MicroBooNE, ICARUS, and the future DUNE experiment. We test the performance of an input uncertainty-enabled model against an uncertainty-blinded model using a method for generating synthetic noise. By comparing these two, we assess the increase in inference quality achieved by exposing models to upstream uncertainty estimates.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Glassy interphases reinforce elastomeric nanocomposites by enhancing percolation-driven volume expansion under strain

For nearly a century, introduction of nanoparticles to elastomers has yielded extraordinarily tough nanocomposites that are critical to technologies from actuators to tires. The mechanisms by which this reinforcement occurs have nevertheless remained a central open question in material science. One widely debated hypothesis posits that strong interactions between polymer and particles induce "glassy bridges" that cement particles into a cohesive percolating network that resists elongation. Here, molecular dynamics simulations show that glassy particle shells do not primarily provide elongational cohesion. Instead, they amplify an underlying mechanism wherein competition between filler and elastomer networks causes the elastomer's volume to increase on deformation. This induces contributions from the elastomer's bulk modulus, which is of order 1000 times larger than its Young's modulus. These findings establish a unified understanding of low-strain reinforcement in filled elastomers as emanating from volumetric competition between coexisting particulate and elastomeric networks. This reframes and unifies our understanding of low-strain reinforcement, provides a clear-cut diagnostic for the presence of glassy bridging, and offers a new design principle for tough elastomeric nanocomposites.

Computational Physics (physics.comp-ph)↗
DOE OSTI2021

Coupled Microbial-Conversion and Computational-Fluid-Dynamics (CFD) Models for Butanediol Production in Micro-Aerated Reactors

Microbial conversion of substrates to macromolecules has been widely used in the synthesis of value-added products in pharmaceutical and biotechnology industries. These bioreactions are also being investigated in the production of low-value commodities such as biofuels [1]. Gas-liquid mass-transfer and transport-reaction coupling are important challenges when designing and scaling up these reactor systems. Experiments in wellmixed small-scale reactors have enabled characterization of microbial reactivity, while their coupling with macroscale transport remains relatively unexplored. In this work, we use a coupled metabolic-CFD model to study the action of a genetically engineered microbe Zymomonas mobilis [2] on sugars to produce 2,3-Butanediol (BDO). BDO is an important hydrocarbon intermediate that can be catalytically upgraded to several fuels and chemicals [3]. An important aspect to this particular microbial conversion is the need for micro-aerated environments as opposed to traditional aerobic fermentation. Slight variations in oxygen concentration can result in competing reaction pathways that disable BDO production. Hence, gas-liquid mass transfer and transport need to be optimized in large-scale reactors to maximize BDO production, for which CFD is a valuable tool. The aerobic-fermentation CFD model previously developed by the authors [5] for simulating bubble-column and airlift reactors at scale was used in this study. The Reynolds-averaged mass, momentum and energy transport equations for interpenetrating gas and liquid phase are solved in this model along with the transport and interphase mass transfer of oxygen. Our previous work used a phenomenological model for microbial oxygen uptake that neglected microbial growth and other reaction pathways. In this work, a detailed metabolic model enabled prediction of product formation and inhibition pathways. In order to manage computational cost, we used a subcycling technique [6] that takes advantage of the clear separation in transport (~ 200 sec) and reaction (~ 2-3 hours) timescales. The CFD model is first solved to steady state, after which the metabolic model is advanced at every cell in the computational domain using the local oxygen concentration. The CFD model is then run to achieve a new steady state that provides a new oxygen distribution for the metabolic model. This process, where reaction and fluid updates are interleaved together, is iterated until reactants are completely exhausted. This work will examine the performance of different reactor designs such as bubble column and airlift reactors at scale (250-500 m3). Oxygen mass-transfer coefficient and distribution are critically analyzed among reactors, and optimization studies pertaining to aeration is presented. Furthermore, it has been observed in experiments that high BDO production may be achieved by manipulating the aerobic environment over the course of reaction, such that oxygen concentration is high during the growth phase, and very low as sugar is depleted. This characteristic will be addressed by our simulations for which a timedependent scheduling strategy for aeration is presented that maximizes BDO production. [1] Humbird, D., Davis, R., and McMillan, J., Aeration costs in stirred-tank and bubble column bioreactors, Biochemical Engineering Journal, 127, 161—166, 2017 [2] Yang, S., Mohagheghi, A., Franden, M. A., Chou, Y.-C., Chen, X., Dowe, N., Himmel, M. E., and Zhang, M., Metabolic engineering of zymomonas mobilis for 2, 3-butanediol production from lignocellulosic biomass sugars. Biotechnology for biofuels, 9(1):189, 2016 [3] Kim, S. J., Sim, H. J., Kim, J. W., Lee, Y. G., Park, Y. C., and Seo, J. H., Enhanced production of 2,3-butanediol from xylose by combinatorial engineering of xylose metabolic pathway and cofactor regeneration in pyruvate decarboxylase-deficient Saccharomyces cerevisiae. Bioresource Technology, 245:1551–1557, 2017 [4] Weller, H., Tabor, G., Jasak, H. and Fureby, C., A tensorial approach to computational continuum mechanics using object-oriented techniques, Computers in physics, 12, 6, 620--631, 1998

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2022

Component-wise reduced-order model design optimization such as for lattice design optimization

Systems and methods for optimizing a lattice structure design are disclosed herein. In some embodiments, a method for optimizing a lattice structure design can include (i) modeling the lattice structure with a component-wise reduced-order model (CWROM) and (ii) optimizing the CWROM based on a selected criterion using a topology optimization algorithm for lattice design. The selected criterion can include a boundary condition and a load applied to the lattice structure. By modeling the lattice structure as a CWROM, the optimization process can be very fast while still permitting the accurate computation of physical quantities of the lattice structure.

Choi, Youngsoo↗
DOE OSTI2023

Topological terms with qubit regularization and relativistic quantum circuits

Qubit regularization provides a rich framework to explore quantum field theories. The freedom to choose how the important symmetries of the theory are embedded in the qubit regularization scheme allows us to construct new lattice models with rich phase diagrams. Some of the phases can contain topological terms which lead to critical phases. In this work we introduce and study the SU(3)-F qubit regularization scheme to embed the SO(3) spin-symmetry. We argue that qubit models in this regularization scheme contain several phases including a critical phase which describes the k = 1 Wess-Zumino-Witten (WZW) conformal field theory (CFT) at long distances, and two massive phases one of which is trvially gapped and the other which breaks the lattice translation symmetry. We construct a simple space-time Euclidean lattice model with a single coupling U and study it using the Monte Carlo method. We show the model has a critical phase at small U and a trivially massive phase at large U with a first order transition separating the two. Another feature of our model is that it is symmetric under space-time rotations, which means the temporal and spatial lattice spacing are connected to each other. The unitary time evolution operator obtained by a Wick rotation of the transfer matrix of our model can help us compute the physics of the k = 1 WZW CFT in real time without the need for tuning the temporal lattice spacing to zero. We use this idea to introduce the concept of a relativistic quantum circuit on a discrete space-time lattice.

Bhattacharya, Tanmoy↗