Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “mesh data”

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 901 records · Page 50

High-Fidelity Simulation Aerodynamics Dataset of NACA 0012 and 0021 Airfoils

The repository contains time series data of pressure, viscous and moment forces for the NACA 0012 and 0021 airfoils at angles of attack (AOA), 5, 17, 30, 45, 60 and 90 degrees. The data was generated during the high-fidelity simulations of the airfoils using the open-source CFD code, Nalu-Wind (https://github.com/Exawind/nalu-wind). The research objective was to study the effects of mesh resolution and turbulence model on the three-dimensional deep stall aerodynamics of the airfoils, which has been published in the Journal of Turbulence (https://doi.org/10.1080/14685248.2023.2225141). Several meshes of the O-grid type were generated using the modified Pointwise Glyph script of Carrigan (https://github.com/pointwise/AirfoilMesh) by varying the wall normal and spanwise resolutions. Note that, the geometry was extruded by four chord lengths in the spanwise direction. In the paper, we showed that Improved Delayed Detached Eddy Simulation (IDDES) hybrid RANS/LES turbulence model with a minimum of 24 cells per chord length in the spanwise direction is necessary to correctly predict the loads in the deep stall regime. Under the NACA 0012 airfoil directory, the data for several combinations of wall-normal and spanwise resolutions are presented in each of the AOA subdirectories. The corresponding experimental data for the lift and drag polars can be found in the "exp_data" subdirectory. The directory for the NACA 0021 airfoil consists of CFD force data and airfoil polars for Reynolds numbers 2.7e5 and 2.0e6.

17 WIND ENERGY↗

LC-Opt: Benchmarking Reinforcement Learning and Agentic AI for End-to-End Liquid Cooling Optimization in Data Centers

Liquid cooling is critical for thermal management in high-density data centers with the rising AI workloads. However, machine learning-based controllers are essential to unlock greater energy efficiency and reliability, promoting sustainability. We present LC-Opt, a Sustainable Liquid Cooling (LC) benchmark environment, for reinforcement learning (RL) control strategies in energy-efficient liquid cooling of high-performance computing (HPC) systems. Built on the baseline of a high-fidelity digital twin of Oak Ridge National Lab's Frontier Supercomputer cooling system, LC-Opt provides detailed Modelica-based end-to-end models spanning site-level cooling towers to data center cabinets and server blade groups. RL agents optimize critical thermal controls like liquid supply temperature, flow rate, and granular valve actuation at the IT cabinet level, as well as cooling tower (CT) setpoints through a Gymnasium interface, with dynamic changes in workloads. This environment creates a multi-objective real-time optimization challenge balancing local thermal regulation and global energy efficiency, and also supports additional components like a heat recovery unit (HRU). We benchmark centralized and decentralized multi-agent RL approaches, demonstrate policy distillation into decision and regression trees for interpretable control, and explore LLM-based methods that explain control actions in natural language through an agentic mesh architecture designed to foster user trust and simplify system management. LC-Opt democratizes access to detailed, customizable liquid cooling models, enabling the ML community, operators, and vendors to develop sustainable data center liquid cooling control solutions.

Naug, Avisek [Hewlett Packard Enterprise]↗

CEED-MS8:Initial Integration of CEED Software in ECP Applications

Key components of CEED software development involve fast finite element operator storage and evaluation, architecture optimizations, performant algorithms for all orders, global kernels for finite element operators, efficient use of the memory sub-system, optimal data locality and motion, enhanced scalability and parallelism, and fast tensor contractions. As ultimate goals of the project, CEED is exploring and identifying the best algorithms for the full range of discretizations and applying algorithmic and software development to support ECP applications’ needs. In this milestone we report on the initial integration of CEED software in the selected first-wave ECP/CEED apps and the continued exploration of other ECP applications as second-wave (milestone CEED-MS23) and third-wave (milestone CEED-MS35) ECP/CEED application candidates. An extensive evaluation of various approaches for GPU acceleration of the CEED computational motives is also a major focus of the report, both in the settings of CEED’s Nekbone and Laghos miniapps, as well as versions of CEED’s bake-off problems (introduced in milestone CEED-MS6). The first-wave ECP applications targeted for coupling with CEED software include the ExaSMR and MARBL applications. We also report on near-term collaboration with the seed-funded Urban Systems project, as well as engagements with ACME, ExaAM, GEOS and the Application Assessment and Proxy App projects. The ExaSMR project involves coupled thermal-hydraulics/neutronics, with the latter based on Monte Carlo methods and the former based on high-order discretizations of the Navier-Stokes and energy equations for accurate simulation of turbulent transport. The project requires fast and efficient turbulence simulation capabilities that will scale to exascale platforms. Work within CEED will ensure that all aspects of the Nek5000 workflow scale to the target problem space, which involves > 10 10 degrees of freedom in typical production runs. CEED’s goal is to provide implementations that perform with maximum attainable efficiency and deliver low turn-around times. A deliverable for this milestone is beta-release of the GPU-based variant of Nek5000. MARBL is targeting high-energy-density physics problems, including single fluid multi-material hydrodynamics and radiation/magnetic diffusion simulation, with applications in inertial confined fusion, pulsed power experiments, and equation of state/material strength analysis. The code uses high-order methods based arbitrary Lagrangian-Eulerian, direct Eulerian, and unstructured adaptive mesh refinement. A deliverable for this milestone is collaboration with MARBL for improved performance based on partially-assembled operators. The Urban exascale project is planning to couple real-time data with high performance simulations to study particulate transport in cities. Nek5000 will be used for large eddy and RANS (Reynolds-averaged Navier-Stokes) simulations of turbulent transport in these domains. Areas where the CEED team is aiding the Urban Canyon group include creating high-order meshes for urban geometries and developing boundary conditions appropriate for simulations close to real-life urban conditions. The software artifacts delivered as part of this milestone include GPU-enabled versions of the Nekbone and Laghos miniapps, which are provided through the CEED website, http://ceed.exascaleproject.org and the CEED GitHub organization, http://github.com/ceed. In addition to details and results from the above R&D efforts, in this document we are also reporting on other project-wide activities performed in Q4 of FY17, including: the CEED first annual meeting and participation of CEED researchers in a variety of outreach activities.

97 MATHEMATICS AND COMPUTING↗

FUN3D Analyses in Support of the 1st AIAA Stability and Control Prediction Workshop

The 1st AIAA Stability and Control Prediction Workshop was created to establish best practices for the prediction of stability & control derivatives using computational fluid dynamics and assess the limitations of these computational methods when those best practices are applied. The inaugural workshop considers the ONERA version of the NASA/Boeing Common Research Model(CRM), which includes the wing, body, horizontal tail, and a vertical tail designed by ONERA. Wind tunnel tests have been conducted for this configuration with longitudinal tests having been previously published, in addition to unpublished data at small sideslip angles that will serve as ‘blind’ data for workshop data comparisons. Participants were provided a ‘family’ of unstructured grids for the full-span ONERA CRM model with the wind-tunnel sting included. This family of mixed-element grids consists of 5 levels of refinement (tiny, coarse, medium, fine, and extra fine) with surface and volume mesh scaling, resulting in a size range of 14.6 to 53.4 million nodes. In addition, a medium refinement mesh has been provided for the ONERA CRM configuration without a sting to evaluate the sting’s impact on static longitudinal stability characteristics. In addition to these workshop-provided grids, the present work also considers an equivalent ‘family’ of computational grids generated using Heldenmesh™, a rapid grid generation software by Helden Aerospace Corporation for creating high-quality, three-dimensional, mixed-element unstructured meshes. Because of the authors’ familiarity with this software, these additional grids were generated as a comparison to the workshop-provided grids and to better understand the implications of using volume-mirrored grids for stability and control predictions. The present work will contribute to the workshop with test case data generated using the NASA FUN3D code, a parallelized, unstructured, node-based, finite-volume discretization, Reynolds-averaged Navier-Stokes flow solver. Numerical simulations will be conducted using the Quadratic Constitutive Relationship (QCR) version of the Spalart-Allmaras (SA) turbulence model with negative turbulence variable provisions. Both steady and2nd-order, time-accurate simulation results are to be generated and compared for select test cases, as time permits, to investigate their impact on FUN3D predictions. The present work will consider the three primary workshop test cases: (1) grid convergence study, (2) Mach number effect on static stability, and (3) wind tunnel sting increments. Additionally, data will be provided for the two optional test cases, which include:(1) static stability derivative calculations and (2)sideslip angle sweeps. In each of the test cases, the vehicle is stationary, and the body is assumed to be rigid, where vehicle deformation has been accounted for in the model configuration geometry. For all test cases, longitudinal and lateral force and moment aerodynamic coefficients will be provided for the total configuration, in addition to a component-level breakdown that includes the port wing, starboard wing, fuselage, and tail.

CFD↗

Notified access in coarray-based hydrodynamics applications on many-core architectures: Design and performance

With the increasing availability of the Remote Direct Memory Access (RDMA) support in computer networks, the so called Partitioned Global Address Space (PGAS) model has evolved in the last few years. Although there are several cases where a PGAS approach can easily solve difficult message passing situations, like in particle tracking and adaptive mesh refinement applications, the producer-consumer pattern, usually adopted in task-based parallelism, can only be implemented inefficiently because of the separation between data transfer and synchronization (which is usually unified in message passing programming models). Here, in this paper, we provide two contributions: (1) we propose an extension for the Fortran language that provides the concept of Notified Access by associating regular coarray variables with event variables. (2) We demonstrate that the MPI extension proposed by foMPI for Notified Access can be used effectively to implement the same concept in a PGAS run-time library like OpenCoarrays. Moreover, for a hydrodynamics mini-application, we found that Fortran 2018 events perform always better than Fortran 2008 sync statements on many-core processors. We finally show how the proposed Notified Access can improve the performance even more.

97 MATHEMATICS AND COMPUTING↗

3D numerical simulation of the long range propagation of acoustical shock waves through a heterogeneous and moving medium

Many situations involve the propagation of acoustical shock waves through flows. Natural sources such as lightning, volcano explosions, or meteoroid atmospheric entries, emit loud, low frequency, and impulsive sound that is influenced by atmospheric wind and turbulence. The sonic boom produced by a supersonic aircraft and explosion noises are examples of intense anthropogenic sources in the atmosphere. The Buzz-Saw-Noise produced by turbo-engine fan blades rotating at supersonic speed also propagates in a fast flow within the engine nacelle. Simulating these situations is challenging, given the 3D nature of the problem, the long range propagation distances relative to the central wavelength, the strongly nonlinear behavior of shocks associated to a wide-band spectrum, and finally the key role of the flow motion. With this in view, the so-called FLHOWARD (acronym for FLow and Heterogeneous One-Way Approximation for Resolution of Diffraction) method is presented with three-dimensional applications. A scalar nonlinear wave equation is established in the framework of atmospheric applications, assuming weak heterogeneities and a slow wind. It takes into account diffraction, absorption and relaxation properties of the atmosphere, quadratic nonlinearities including weak shock waves, heterogeneities of the medium in sound speed and density, and presence of a flow (assuming a mean stratified wind and 3D turbulent ? flow fluctuations of smaller amplitude). This equation is solved in the framework of the one-way method. A split-step technique allows the splitting of the non-linear wave equation into simpler equations, each corresponding to a physical effect. Each sub-equation is solved using an analytical method if possible, and finite-differences otherwise. Nonlinear effects are solved in the time domain, and others in the frequency domain. Homogeneous diffraction is handled by means of the angular spectrum method. Ground is assumed perfectly flat and rigid. Due to the 3D aspect, the code was massively parallelized using the single program, multiple data paradigm with the Message Passing Interfaces (MPI) for distributed memory architectures. This allows us to handle problems in the order of a thousand billion mesh points in the four dimensions (3 dimensions of space plus time). The validity of the method has been thoroughly evaluated on many cases with known solutions: linear piston, scattering of plane wave by a heterogeneous sphere, propagation in a waveguide with a shear flow, scattering by a finite amplitude vortex and nonlinear propagation in a thermoviscous medium. This validation process allows for a detailed assessment of the advantages and limitations of the method. Finally, applications to atmospheric propagation of shock waves will be presented.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DS-GL: Advancing Graph Learning via Harnessing the Power of Nature within Dynamic Systems

With the rapid digitization of the world, an increasing number of real-world applications are turning to nonEuclidean data, modeled as graphs. Due to their intrinsic high complexity and irregularity, learning from graph data demands tremendous computational power. Recently, CMOS-compatible Ising machines, i.e., dynamic systems composed of CMOS components, have emerged as a new approach that harnesses the inherent power of natural annealing within dynamic systems to efficiently resolve binary optimization problems and have been adopted for traditional graph computation, such as max-cut. However, when performing complex Graph Learning (GL) tasks, Ising machines face significant hurdles: (i) they are inherently binary and thus ill-suited for real-valued problems; (ii) their expensive all-to-all coupling network that guarantees effective natural annealing poses daunting scalability concerns. To address these challenges, this paper proposes a nature-powered graph learning framework dubbed DS-GL, which is the first effort to transform the process of solving graph learning problems into the natural annealing process within a parameterized dynamic system embodied as a CMOS chip. To tackle the two major hurdles, DS-GL first augments the Ising machine architecture to modify the self-reaction term of its Hamiltonian function from linear to quadratic, effectively serving as an energy regulator. This adjustment maintains the system’s original physical interpretation while enabling it to process continuous, real-valued data. Second, to address the scaling issue, DS-GL further upgrades the real-valued dense Ising machine by decomposing it into a mesh-based multi-PE dynamic system that supports efficient distributed spatial-temporal co-annealing across different PEs through sparse interconnects. By exploiting the inherent sparsity and component structures in real-world graphs, DS-GL is able to map complex graph learning tasks onto the scalable dynamic system while maintaining high accuracy. Evaluations with three diverse GL applications across six real-world datasets, including traffic flow and COVID-19 prediction, show that DS-GL can deliver from 102× to 106× speedups and 500× energy reduction over Graph Neural Networks on GPUs, with 5% - 20% accuracy enhancement.

Song, Ruibing↗

Panel-Segmentation [SWR-21-18]

Panel-Segmentation contains the scripts for automated metadata extraction of solar PV installations, using satellite imagery coupled with computer vision techniques. In this package, the user can perform the following actions: *Automatically generate a satellite image using a set of lat-long coordinates, and a Google Maps API key. Users would need to set up a Google Cloud account and get a Maps Static API key. Please refer to Setting Up Google Maps Static API Key section for this process. *Perform image segmentation on the satellite image, to locate the solar array(s) in the image on a pixel-by-pixel basis, using an image segmentation model (panel_detection_model.pth). Get classification of the installation (rooftop, ground mounted fixed-tilt or tracking, carport, etc). *Perform azimuth estimation on each solar array cluster in the masked image. *Detect solar panels and get its latitude, longitude, and address within a geographic bounding box through the SOL-Searcher Pipeline. *Detect and calculate hurricane damage on solar installations given pre-hurricane and post-hurricane satellite imagery through the Hurricane Detection Pipeline. *Detect and calculate hail damage on solar installations given satellite imagery through the Hail Detection pipeline. *Convert NOAA MESH (Maximum Estimated Size of Hail) grib2 files into kml or geojson files. *Estimate tilt and azimuth of a solar array by processing USGS LiDAR data for the array’s location.

Edun, Ayobami↗

Combined Near and Far Field High Energy Diffraction Microscopy Dataset for Ti-7Al Tensile Specimen Elastically Loaded In Situ

We present both near-field HEDM data that maps out the grain morphology and intragranular crystallographic orientations and far-field HEDM data that provides the grain centroid, grain average crystallographic orientation, and grain average elastic strain tensor for each grain. Finally, we provide a finite element mesh that can be utilized to simulate deformation in the volume of this Ti-7Al specimen.

Turner, Todd J.↗

Challenges of Monte Carlo Transport

These are slides from a presentation for Parallel Summer School at Los Alamos National Laboratory. Solving discretized partial differential equations (PDEs) of interest can require a large number of computations. We can identify concurrency to allow parallel solution of discrete PDEs. Simulated particles histories can be used to solve the Boltzmann transport equation. Particle histories are independent in neutral particle transport, making them amenable to parallel computation. Physical parameters and method type determine the data dependencies of particle histories. Data requirements shape parallel algorithms for Monte Carlo. Then, Parallel Computational Physics and Parallel Monte Carlo are discussed and, finally, the results are given. The mesh passing method greatly simplifies the IMC implementation and allows simple load-balancing. Using MPI windows and passive, one-sided RMA further simplifies the implementation by removing target synchronization. The author is very interested in implementations of PGAS that may allow further optimization for one-sided, read-only memory access (e.g. Open SHMEM). The MPICH_RMA_OVER_DMAPP option and library is required to make one-sided messaging scale on Trinitite - Moonlight scales poorly. Interconnect specific libraries or functions are likely necessary to ensure performance. BRANSON has been used to directly compare the current standard method to a proposed method on idealized problems. The mesh passing algorithm performs well on problems that are designed to show the scalability of the particle passing method. BRANSON can now run load-imbalanced, dynamic problems. Potential avenues of improvement in the mesh passing algorithm will be implemented and explored. A suite of test problems that stress DD methods will elucidate a possible path forward for production codes.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Geomechanical Simulation of Bayou Choctaw Strategic Petroleum Reserve - Model Calibration.

A finite element numerical analysis model has been constructed that consists of a realistic mesh capturing the geometries of Bayou Choctaw (BC) Strategic Petroleum Reserve (SPR) site and multi - mechanism deformation ( M - D ) salt constitutive model using the daily data of actual wellhead pressure and oil - brine interface. The salt creep rate is not uniform in the salt dome, and the creep test data for BC salt is limited. Therefore, the model calibration is necessary to simulate the geomechanical behavior of the salt dome. The cavern volumetric closures of SPR caverns calculated from CAVEMAN are used for the field baseline measurement. The structure factor, A 2 , and transient strain limit factor, K 0 , in the M - D constitutive model are used for the calibration. The A 2 value obtained experimentally from the BC salt and K 0 value of Waste Isolation Pilot Plant (WIPP) salt are used for the baseline values. T o adjust the magnitude of A 2 and K 0 , multiplication factors A2F and K0F are defined, respectively. The A2F and K0F values of the salt dome and salt drawdown skins surrounding each SPR cavern have been determined through a number of back fitting analyses. The cavern volumetric closures calculated from this model correspond to the predictions from CAVEMAN for six SPR caverns. Therefore, this model is able to predict past and future geomechanical behaviors of the salt dome, caverns, caprock , and interbed layers. The geological concerns issued in the BC site will be explained from this model in a follow - up report .

58 GEOSCIENCES↗

Geomechanical Simulation of Big Hill Strategic Petroleum Reserve - Calibration of Model Containing Shear Zone

A finite element numerical analysis model, that consists of a realistic mesh capturing the geometries of Big Hill (BH) Strategic Petroleum Reserve (SPR) site using the multi-mechanism deformation (MD) salt constitutive model and including data taken daily of the wellhead pressure and level of the oil-brine interface, has been upgraded. The upgraded model contains the shear zone to examine the interbed behavior in a realistic manner. The salt creep rate is not uniform in the salt dome, and creep test data for BH salt is limited. Therefore, a model calibration is necessary to simulate the geomechanical behavior of the salt dome. Cavern volumetric closures of SPR caverns calculated from sonar survey reports are used for the field baseline measurement. The structure factor, A 2 , and transient strain limit factor, K 0 , in the M-D constitutive model are used for model calibration. An A 2 value obtained experimentally from the BH salt and K 0 value of WIPP salt are used as the baseline values. To adjust the magnitude of A 2 and K 0 , multiplication factors A 2 F and K 0 F are defined, respectively. The A 2 F and K 0 F values of the salt dome and salt drawdown layer of elements surrounding each SPR cavern have been determined through a number of back fitting analyses. The trendlines of the predictions and sonar data match up well for BH 101, 103, 104, 106, 110, 111, 112, and 113. The prediction curves are close to the sonar data for BH 102 and 114. However, the prediction curves for BH 105, 107, 108, and 109 are not close to the sonar data. An inconsistency was found in the sonar data, i.e. the volume measured later is larger than that before in some time intervals, even if the leached volume is taken into account, for BH 101, 104, 106, 107, and 112. Project discussions are needed to determine possibilities on how to resolve the issues and determine the best path forward for future computer modeling attempts.

02 PETROLEUM↗

The Importance of Freeze/Thaw Cycles on Lateral Transport in Ice-Wedge Polygons: Modeling Archive

This Modeling Archive is in support of an NGEE Arctic publication "The importance of freeze/thaw cycles on lateral transport in ice-wedge polygons". The dataset includes xml input/configuration files. These files are compatible with the ATS version 1.0 and higher. The mesh folder contains mesh files used for high-centered polygon (hcp) and low-centered polygon (lcp). The mesh files represent the transect of the polygonal tundra (Fig 1). Here we used two types of mesh with impermeable layer and without. The mesh with an impermeable layer corresponds to the synthetic permafrost (no freezeup case). The freeze up case uses mesh without impermeable layer to simulated frozen ground start at the same depth where the impermeable layer is for the no freezeup case. The meteorological data used drive the model saved in the "inputs" folder. The processed tracer flow rates are saved in the "tracer-flow-ratesCfolder. To plot figures 1 and 2, we used VisIt software. To plot all the flow rates, we used ipython notebook script. All required inputs are saved in "freezeup" and "no freezeup" folders. Each folder includes the corresponding "lcp" and "hcp" folders. The "freezeup" folder has also flat-centered polygon (fcp) case, low porosity "lpor", and low permeability "lper" cases. Included are *.xml, *.exo, *.h5, *pdf, *.ipynb, *.sh, *.py, and *.out files. NGEE Arctic Project Summary: The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was a research effort to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy's Office of Biological and Environmental Research. The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska. Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy's Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).

54 ENVIRONMENTAL SCIENCES↗

Recent applications of the transonic wing analysis computer code, TWING

An evaluation of the transonic-wing-analysis computer code TWING is given. TWING utilizes a fully implicit approximate factorization iteration scheme to solve the full potential equation in conservative form. A numerical elliptic-solver grid-generation scheme is used to generate the required finite-difference mesh. Several wing configurations were analyzed, and the limits of applicability of this code was evaluated. Comparisons of computed results were made with available experimental data. Results indicate that the code is robust, accurate (when significant viscous effects are not present), and efficient. TWING generally produces solutions an order of magnitude faster than other conservative full potential codes using successive-line overrelaxation. The present method is applicable to a wide range of isolated wing configurations including high-aspect-ratio transport wings and low-aspect-ratio, high-sweep, fighter configurations.

Subramanian, N. R.↗

SIAM Conference on Parallel Processing for Scientific Computing, 4th, Chicago, IL, Dec. 11-13, 1989, Proceedings

Attention is given to such topics as an evaluation of block algorithm variants in LAPACK and presents a large-grain parallel sparse system solver, a multiprocessor method for the solution of the generalized Eigenvalue problem on an interval, and a parallel QR algorithm for iterative subspace methods on the CM2. A discussion of numerical methods includes the topics of asynchronous numerical solutions of PDEs on parallel computers, parallel homotopy curve tracking on a hypercube, and solving Navier-Stokes equations on the Cedar Multi-Cluster system. A section on differential equations includes a discussion of a six-color procedure for the parallel solution of elliptic systems using the finite quadtree structure, data parallel algorithms for the finite element method, and domain decomposition methods in aerodynamics. Topics dealing with massively parallel computing include hypercube vs. 2-dimensional meshes and massively parallel computation of conservation laws. Performance and tools are also discussed.

Dongarra, Jack↗

Active Aerodynamic Load Reduction on a Rotorcraft Fuselage With Rotor Effects: A CFD Validation Effort

A rotorcraft fuselage is typically designed with an emphasis on operational functionality with aerodynamic efficiency being of secondary importance. This results in a significant amount of drag during high-speed forward flight that can be a limiting factor for future high-speed rotorcraft designs. To enable higher speed flight, while maintaining a functional fuselage design (i.e., a large rear cargo ramp door), the NASA Rotary Wing Project has conducted both experimental and computational investigations to assess active flow control as an enabling technology for fuselage drag reduction. This paper will evaluate numerical simulations of a flow control system on a generic rotorcraft fuselage with a rotor in forward flight using OVERFLOW, a structured mesh Reynolds-averaged Navier-Stokes flow solver developed at NASA. The results are compared to fuselage forces, surface pressures, and PN flow field data obtained in a wind tunnel experiment conducted at the NASA Langley 14-by 22-Foot Subsonic Tunnel where significant drag and download reductions were demonstrated using flow control. This comparison showed that the Reynolds-averaged Navier-Stokes flow solver was unable to predict the fuselage forces and pressure measurements on the ramp for the baseline and flow control cases. While the CFD was able to capture the flow features, it was unable to accurately predict the performance of the flow control.

Allan, Brian G.↗

Reduced order modeling for flow and transport problems with Barlow Twins self-supervised learning

Abstract We propose a unified data-driven reduced order model (ROM) that bridges the performance gap between linear and nonlinear manifold approaches. Deep learning ROM (DL-ROM) using deep-convolutional autoencoders (DC–AE) has been shown to capture nonlinear solution manifolds but fails to perform adequately when linear subspace approaches such as proper orthogonal decomposition (POD) would be optimal. Besides, most DL-ROM models rely on convolutional layers, which might limit its application to only a structured mesh. The proposed framework in this study relies on the combination of an autoencoder (AE) and Barlow Twins (BT) self-supervised learning, where BT maximizes the information content of the embedding with the latent space through a joint embedding architecture. Through a series of benchmark problems of natural convection in porous media, BT–AE performs better than the previous DL-ROM framework by providing comparable results to POD-based approaches for problems where the solution lies within a linear subspace as well as DL-ROM autoencoder-based techniques where the solution lies on a nonlinear manifold; consequently, bridges the gap between linear and nonlinear reduced manifolds. We illustrate that a proficient construction of the latent space is key to achieving these results, enabling us to map these latent spaces using regression models. The proposed framework achieves a relative error of 2% on average and 12% in the worst-case scenario (i.e., the training data is small, but the parameter space is large.). We also show that our framework provides a speed-up of $$7 \times 10^{6}$$ 7 × 10 6 times, in the best case, and $$7 \times 10^{3}$$ 7 × 10 3 times on average compared to a finite element solver. Furthermore, this BT–AE framework can operate on unstructured meshes, which provides flexibility in its application to standard numerical solvers, on-site measurements, experimental data, or a combination of these sources.

97 MATHEMATICS AND COMPUTING↗

Final Report on Project “Ton-scale Germanium: Beyond Zeptobarn WIMP Cross-section”

The DOE CAREER proposal primarily focused on establishing a modern semiconductor detector fabrication facility that would provide significant improvement in the cost profile and performance of the cryogenic semiconductor detectors used by the CDMS experiment so as to enable a next generation ton-scale experiment. The proposal also included significant work on performing data analysis on the Soudan experiment.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗