Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “Data Staging”

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 1,027 records · Page 57
All sourcesNASA NTRSDOE OSTI
DOE OSTI2019

Additively Manufactured Intensified Device for Enhanced Carbon Capture

Additively manufactured packed bed devices for the enhancement of carbon capture were successfully developed, built, characterized, and tested in this project. The objective was to demonstrate that in situ cooling of chemical absorption could have beneficial effects on the absorption rate of CO 2 . This was achieved in two stages, divided between FY 2018 and FY 2019. First, the feasibility of printing conventional packing elements was investigated, and the core hydrodynamic metrics were experimentally validated. The data obtained in those studies informed the operating conditions set for the next stage, which was to validate the efficacy of in situ cooling provided by an additively manufactured packed bed element, referred to as the intensified device. The intensified device is designed to enable heat exchange between an internally flowing coolant and the gas-liquid system flowing on the external corrugated surface of the packing. Polymer and metal were both considered as the base materials for the device, and comparative studies on hydrodynamic properties were performed. These considerations, as well as thermal properties and leak tests led to aluminum being chosen as the base material for experimental validation of capture enhancement. The experimental validation was first conducted under non-reactive conditions, and after establishing heat-exchange capabilities, was subsequently conducted under reactive conditions. These studies demonstrated that in situ cooling can benefit absorption given the appropriate operating conditions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS1988

Interpreting forest biome productivity and cover utilizing nested scales of image resolution and biogeographical analysis

The objective was to relate spectral imagery of varying resolution with ground-based data on forest productivity and cover, and to create models to predict regional estimates of forest productivity and cover with a quantifiable degree of accuracy. A three stage approach was outlined. In the first stage, a model was developed relating forest cover or productivity to TM surface reflectance values (TM/FOREST models). The TM/FOREST models were more accurate when biogeographic information regarding the landscape was either used to stratigy the landscape into more homogeneous units or incorporated directly into the TM/FOREST model. In the second stage, AVHRR/FOREST models that predicted forest cover and productivity on the basis of AVHRR band values were developed. The AVHRR/FOREST models had statistical properties similar to or better than those of the TM/FOREST models. In the third stage, the regional predictions were compared with the independent U.S. Forest Service (USFS) data. To do this regional forest cover and forest productivity maps were created using AVHRR scenes and the AVHRR/FOREST models. From the maps the county values of forest productivity and cover were calculated. It is apparent that the landscape has a strong influence on the success of the approach. An approach of using nested scales of imagery in conjunction with ground-based data can be successful in generating regional estimates of variables that are functionally related to some variable a sensor can detect.

Iverson, Louis R.↗
NASA NTRS1994

An Aerodynamic Analysis of a Mixed Flow Turbine

The aerodynamic performance of a high-work Mixed Flow Turbine (MFT) is computed and compared with experimental data. A three dimensional (3-D) viscous analysis is applied to the single stage MFT geometry with a relatively long upstream transition duct. Predicted vane surface static pressures and circumferentially averaged spanwise quantities at stator and rotor exits agree favorably with data. Compared to the results of axisymmetric flow analysis from design intent, the 3-D computation agrees much better especially in the endwall regions where throughflow prediction fails to assess the loss mechanism properly. Potential sources of performance loss such as tip leakage and secondary flows are also properly captured by the analysis.

Kim, Chan M.↗
NASA NTRS1982

Time resolved measurements in a low aspect ratio transonic compressor stage

The time resolved flowfield in a low aspect ratio transonic compressor stage has been studied using a high frequency response sphere probe with a bandpass of D.C. to 20 kHz in a blowdown compressor facility. Averaged over the compressor annulus, the data agree well with those measured with standard pitot type probes on the same stage in a conventional test rig. Not all the spanwise distributions agree, however. These differences are explained as errors in the pitot probe readings due to fluctuations in the flow. The experimental data are compared to the results of a three-dimensional inviscid Euler calculation.

Epstein, A. H.↗
NASA NTRS1993

Computational Fluid Dynamics (CFD) Analysis for the Reduction of Impeller Discharge Flow Distortion

The use of Computational Fluid Dynamics (CFD) in the design and analysis of high performance rocket engine pumps has increased in recent years. This increase has been aided by the activities of the Marshall Space Flight Center (MSFC) Pump Stage Technology Team (PSTT). The team's goals include assessing the accuracy and efficiency of several methodologies and then applying the appropriate methodology(s) to understand and improve the flow inside a pump. The PSTT's objectives, team membership, and past activities are discussed in Garcia1 and Garcia2. The PSTT is one of three teams that form the NASA/MSFC CFD Consortium for Applications in Propulsion Technology (McConnaughey3). The PSTT first applied CFD in the design of the baseline consortium impeller. This impeller was designed for the Space Transportation Main Engine's (STME) fuel turbopump. The STME fuel pump was designed with three impeller stages because a two-stage design was deemed to pose a high developmental risk. The PSTT used CFD to design an impeller whose performance allowed for a two-stage STME fuel pump design. The availability of this design would have lead to a reduction in parts, weight, and cost had the STME reached production. One sample of the baseline consortium impeller was manufactured and tested in a water rig. The test data showed that the impeller performance was as predicted and that a two-stage design for the STME fuel pump was possible with minimal risk. The test data also verified another CFD predicted characteristic of the design that was not desirable. The classical 'jet-wake' pattern at the impeller discharge was strengthened by two aspects of the design: by the high head coefficient necessary for the required pressure rise and by the relatively few impeller exit blades, 12, necessary to reduce manufacturing cost. This 'jet-wake pattern produces an unsteady loading on the diffuser vanes and has, in past rocket engine programs, lead to diffuser structural failure. In industrial applications, this problem is typically avoided by increasing the space between the impeller and the diffuser to allow the dissipation of this pattern and, hence, the reduction of diffuser vane unsteady loading. This approach leads to small performance losses and, more importantly in rocket engine applications, to significant increases in the pump's size and weight. This latter consideration typically makes this approach unacceptable in high performance rocket engines.

Garcia, R.↗
DOE OSTI2021

Systems Engineering Approach for Design and Implementation of a Gas Breech for Actinide Experiments at the JASPER Facility

The Joint Actinide Shock Physics Experimental Research (JASPER) Facility is located approximately 65 miles north of Las Vegas, Nevada at the Nevada National Security Site (NNSS). The primary mission is to conduct shock physics research on actinide materials in support of NNSA’s Stockpile Stewardship Program. JASPER experiment uses a two-stage light gas gun to accelerate projectiles into targets at velocities up to 8 km/s (17,000 mph). The first stage uses an ignited propellent to drive a piston to compress gas in the pump tube. At the second stage, the gas compression exceeds a specified pressure and a rupture valve at the end of the pump tube opens. This launches a projectile to impact the target. The target is housed inside the target assembly and the debris field is contained inside the primary target chamber (PTC). The PTC is placed inside the secondary confinement chamber (SCC) as an added protection against possible contamination. These major components are illustrated in Figure 1.JASPER is capable of generating and measuring data on the properties of radioactive chemical elements at high shock pressures, temperatures, and strain rates approximating the conditions in nuclear weapons by using a two-stage gas gun. The data is used to determine material equations-of-state and validate computer models of material response. The work advances predictive capability, thus ensuring confidence in the nuclear stockpile.

42 ENGINEERING↗
DOE OSTI2022

Impact of jet-production data on the next-to-next-to-leading-order determination of HERAPDF2.0 parton distributions

The HERAPDF2.0 ensemble of parton distribution functions (PDFs) was introduced in 2015. The final stage is presented, a next-to-next-to-leading-order (NNLO) analysis of the HERA data on inclusive deep inelastic ep scattering together with jet data as published by the H1 and ZEUS collaborations. A perturbative QCD fit, simultaneously of $\alpha _s(M_Z^2)$ and the PDFs, was performed with the result $\alpha _s(M_Z^2)= 0.1156 \pm 0.0011~\mathrm{(exp)}~ ^{+0.0001}_{-0.0002}~ \mathrm{(model}$ $\mathrm{+ parameterisation)}~ \pm 0.0029~\mathrm{(scale)}$. The PDF sets of HERAPDF2.0Jets NNLO were determined with separate fits using two fixed values of $\alpha _s(M_Z^2)$, $\alpha _s(M_Z^2)$ = 0.1155 and 0.118, since the latter value was already chosen for the published HERAPDF2.0 NNLO analysis based on HERA inclusive DIS data only. The different sets of PDFs are presented, evaluated and compared. The consistency of the PDFs determined with and without the jet data demonstrates the consistency of HERA inclusive and jet-production cross-section data. The inclusion of the jet data reduced the uncertainty on the gluon PDF. Predictions based on the PDFs of HERAPDF2.0Jets NNLO give an excellent description of the jet-production data used as input.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2022

Studying the Richtmyer–Meshkov instability in convergent geometry under high energy density conditions using the Decel platform

The “Decel” platform at Sandia National Laboratories investigates the Richtmyer–Meshkov instability (RMI) in converging geometry under high energy density conditions [Knapp et al., Phys. Plasmas 27, 092707 (2020)]. In Decel, the Z machine magnetically implodes a cylindrical beryllium liner filled with liquid deuterium, launching a converging shock toward an on-axis beryllium rod machined with sinusoidal perturbations. The passage of the shock deposits vorticity along the Be/D2 interface, causing the perturbations to grow. Here, we present platform improvements along with recent experimental results. To improve the stability of the imploding liner to the magneto Rayleigh–Taylor instability, we modified its acceleration history by shortening the Z electrical current pulse. Next, we introduce a “split rod” configuration that allows two axial modes to be fielded simultaneously in different axial locations along the rod, doubling our data per experiment. We then demonstrate that asymmetric slots in the return current structure modify the magnetic drive pressure on the surface of the liner, advancing the evolution on one side of the rod by multiple ns compared to its 180° counterpart. This effectively enables two snapshots of the instability at different stages of evolution per radiograph with small deviations of the cross-sectional profile of the rod from the circular. Using this platform, we acquired RMI data at 272 and 157 μm wavelengths during the single shock stage. Finally, we demonstrate the utility of these data for benchmarking simulations by comparing calculations using ALEGRA MHD and RageRunner.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2020

Adaptive Machine Learning for Bragg Coherent Diffraction Imaging (BCDI) of 3D Electron Density Maps with Application to La 2-x Ba x CuO 4 (LBCO) High Temperature Superconductor Studies [PowerPoint]

Understanding mesoscale heterogeneity is important for evaluating fatigue and failure of structural materials and for manufacturing processes. Data-driven tools can facilitate in guiding effort investment (measurements and computations) at various stages of the materials development. Our 3D reconstruction approach is to find a set of coefficients which define a bounding surface of the electron density. Data for training the 3D CNN was generated by sampling coefficients from uniform distributions. Test vs. prediction values are shown for the 28 even-valued coefficients for 1000 test structures, with the best and worst performers highlighted. The adaptive part of this work utilized a model independent extremum seeking (ES). The predictions of the CNN were used as the starting point for the ES algorithm. The convergence of the ES algorithm for 3 different structures is illustrated, and the robustness of the adaptive ML approach was demonstrated on experimentally measured 3D crystal from high energy diffraction microscopy. Reconstruction of a non-uniform density volume with different levels of Poisson noise is also shown. Preliminary attempts at reconstructing measured La 2-x Ba x CuO 4 diffraction patterns have so far failed.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
NASA NTRS2013

An Offload NIC for NASA, NLR, and Grid Computing

This work addresses distributed data management and access dynamically configurable high-speed access to data distributed and shared over wide-area high-speed network environments. An offload engine NIC (network interface card) is proposed that scales at nX10-Gbps increments through 100-Gbps full duplex. The Globus de facto standard was used in projects requiring secure, robust, high-speed bulk data transport. Novel extension mechanisms were derived that will combine these technologies for use by GridFTP, bandwidth management resources, and host CPU (central processing unit) acceleration. The result will be wire-rate encrypted Globus grid data transactions through offload for splintering, encryption, and compression. As the need for greater network bandwidth increases, there is an inherent need for faster CPUs. The best way to accelerate CPUs is through a network acceleration engine. Grid computing data transfers for the Globus tool set did not have wire-rate encryption or compression. Existing technology cannot keep pace with the greater bandwidths of backplane and network connections. Present offload engines with ports to Ethernet are 32 to 40 Gbps f-d at best. The best of ultra-high-speed offload engines use expensive ASICs (application specific integrated circuits) or NPUs (network processing units). The present state of the art also includes bonding and the use of multiple NICs that are also in the planning stages for future portability to ASICs and software to accommodate data rates at 100 Gbps. The remaining industry solutions are for carrier-grade equipment manufacturers, with costly line cards having multiples of 10-Gbps ports, or 100-Gbps ports such as CFP modules that interface to costly ASICs and related circuitry. All of the existing solutions vary in configuration based on requirements of the host, motherboard, or carriergrade equipment. The purpose of the innovation is to eliminate data bottlenecks within cluster, grid, and cloud computing systems, and to add several more capabilities while reducing space consumption and cost. Provisions were designed for interoperability with systems used in the NASA HEC (High-End Computing) program. The new acceleration engine consists of state-ofthe- art FPGA (field-programmable gate array) core IP, C, and Verilog code; novel communication protocol; and extensions to the Globus structure. The engine provides the functions of network acceleration, encryption, compression, packet-ordering, and security added to Globus grid or for cloud data transfer. This system is scalable in nX10-Gbps increments through 100-Gbps f-d. It can be interfaced to industry-standard system-side or network-side devices or core IP in increments of 10 GigE, scaling to provide IEEE 40/100 GigE compliance.

Awrach, James↗
NASA NTRSDate not supplied

Py MILab: Capturing, Analyzing and Storing Test Data

Integrated Computational Materials Engineering (ICME) has recently received widespread attention due to its promises in reducing dependence on physical testing for engineering design by relying on simulation, reducing both time and cost to market for various applications. ICME however requires validated multiscale material models, which is heavily dependent on available test data with full material and test pedigree, including material processing, test and measurement equipment, raw data collection, and analysis methodology and results. Populating searchable information management systems with such rich data sets is often burdensome for data producers, resulting in a lack of findable data for modelers to validate and verify their models. To overcome these cultural barriers to ICME, NASA has developed of various database-integration toolsets that perform both data management activities within the organization’s best practices with additional functionality that relieves the effort of the data producer and promotes adoption of information management system. One such tool currently under development is Py MILab, an automatic framework for automatic capturing, analysis, maintenance, and storage of material test data. Py MILab uses a modular approach for capturing raw data, analyzing the data, and storing the data in a database, interfaced by neutral file structures, to promote plug-and-play capabilities for various analysis types. TMAnalysis is a Python-based tool that performs automatic data reduction and analysis of uniaxial thermomechanical test data. The TMAnalysis toolset can be implemented within the Analysis module of Py MILab, and thus requires a populated neutral file form the Raw Data Module of Py MILab and outputs a Analysis neutral file compatible with the Database Module of Py MILab. TMAnalysis is able to perform automatic segmentation of multistage tests and perform data analysis and reduction, including determination of point-wise properties in tension, compression, and shear, analysis of stress relaxation tests, creep analysis and zone identification, and combination of these stage types for tests with complex loading histories. The TMAnalysis code is accompanied with a graphical user interface (GUI) that allows users to easily analyze test data in bulk, verify the automatic, consistent analysis performed by the backend code, and edit stage segmentation if necessary before producing the output neutral files, ensuring data is properly analyzed and maintained with full traceability.

Data management↗
DOE OSTI2024

Imitating the “breeder's eye”: Predicting grain yield from measurements of non‐yield traits

Abstract Plant breeding relies on information gathered from field trials to select promising new crop varieties for release to farmers and to develop genomic prediction models that can enhance the efficiency of genetic improvement in future breeding cycles. However, generating the genetic marker data required to apply genomic prediction at the early stages of a breeding program remains costly for many public‐sector breeding programs as well as for many plant breeders operating in developing countries. As the pace of climate change intensifies, the time lag of developing and deploying new crop varieties requires plant breeders to make selection decisions without knowing the future environments those crop varieties will encounter in farmers’ fields. Therefore, both lower cost and higher accuracy methods for prediction of crop performance are essential for creating and maintaining resilient agricultural systems in the latter half of the 21 st century. To address this challenge, we conducted linked yield trials of 752 public maize ( Zea mays ) genotypes in two distinct environments. We developed and trained a phenotypic prediction model to predict yield from manually scored plant traits. The phenotypic prediction approach we employed outperformed genomic prediction in predicting yields in a second environment, with 8.7%–63% higher R 2 and 4%–13% less root mean square error than the genomic prediction. The phenotypic prediction has the potential to be applied to a wider range of breeding programs, including those that lack the resources to genotype large populations, such as programs in the developing world, breeding programs for specialty crops, and public sector programs.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2023

Renewable electricity capacity planning with uncertainty at multiple scales

Abstract We formulate and compare optimization models of investment in renewable generation using a suite of social planning models that compute optimal generation capacity investments for a hydro-dominated electricity system where inflow uncertainty results in a risk of energy shortage. The models optimize the expected cost of capacity expansion and operation allowing for investments in hydro, geothermal, solar, wind, and thermal plant, as well as battery storage for smoothing load profiles. A novel feature is the integration of uncertain seasonal hydroelectric energy supply and short-term variability in renewable supply in a two-stage stochastic programming framework. The models are applied to data from the New Zealand electricity system and used to estimate the costs of moving to a 100% renewable electricity system by 2035. We also explore the outcomes obtained when applying different forms of CO 2 constraint that limit respectively non-renewable capacity, non-renewable generation, and CO 2 emissions on average, almost surely, or in a chance-constrained setting, and show how our models can be used to investigate the merits of a proposed pumped-hydro scheme in New Zealand’s South Island.

Ferris, Michael C.↗
DOE OSTI2021

Prediction of softening kinetics and recrystallization texture in non-isothermally annealed bulged tubes using CPFEM and CA models

A hierarchically coupled cellular automata (CA) model, crystal plasticity finite element method (CPFEM), and thermal finite element (FE) model is developed to predict the softening kinetics of the bulged steel tube during non-isothermal annealing. Through the developed model, the kinetics of softening mechanisms including static recovery (SRV) and static recrystallization (SRX), as well as the recrystallization texture are predicted. Later, the Johnson-Mehl-Avrami-Kohnogorov (JMAK) model based on the predicted SRX data is developed to interpret the recrystallization behavior of the material. To perform this study, diverse experimental tests including tube hydroforming (THF), annealing, uniaxial tensile test, hardness test, as well as microstructure observations through optical microscopy and Electron Backscatter Diffraction (EBSD) tests on steel tube are performed. The obtained experimental data are utilized to calibrate and verify the implemented CPFEM model for simulation of THF process, thermal FE model for prediction of the local temperature over annealing time, and CA algorithm for modeling of the softening kinetics and texture evolution throughout the annealing process. The study shows that the predicted deformation characteristics, softening kinetics, recrystallization texture and temperature profile during non-isothermal annealing are in good agreement with experimental data. During the annealing process, a total of four stages for the kinetics of softening mechanisms is observed: No softening; SRV only; SRV dominant; and SRX dominant. During the progress of SRX, the behavior of recrystallization is abruptly changed, confirming that two different mechanisms are controlling the kinetics of transformation.

36 MATERIALS SCIENCE↗
DOE OSTI2023

State-Level Trends in Renewable Energy Procurement via Solar Installation versus Green Electricity

In recent years, options for procuring renewable energy have increased, ranging from rooftop solar installation to utility green pricing to Community Choice Aggregation. These options vary in terms of costs and benefits to the consumer as well as grid integration implications. However, little is known regarding how the presence of a wide range of voluntary utility-scale renewable procurement options as well as their growth could affect adoption of distributed residential solar. To examine this relationship, we fit a two-stage least squares random effects regression model on panel data from 2016 to 2019 for all fifty US states plus the District of Columbia, controlling for variables that measure state-level policies, economic factors, and resource availability. Although there was no evidence of a strong relationship between demand for utility-scale and distributed options across all states, the state-level correlations suggest a wide variation between states including a positive, zero or negative relationship between utility-scale and distributed generation.

consumer demand↗
DOE OSTI2022

More Realistic Intermediate Depth Dry Firn Densification in the Energy Exascale Earth System Model (E3SM)

Abstract Earth system models account for seasonal snow cover, but many do not accommodate the deeper snowpack on ice sheets (aka firn) that slowly transforms to ice under accumulating snowfall. To accommodate and resolve firn depths of up to 60 m in the Energy Exascale Earth System Model's land surface model (ELM), we add 11 layers to its snowpack and evaluate three dry snow compaction equations in multi‐century simulations. After comparing results from ELM simulations (forced with atmospheric reanalysis) with empirical data, we find that implementing into ELM a two‐stage firn densification model produces more accurate dry firn densities at intermediate depths of 20–60 m. Compared to modeling firn using the equations in the (12 layer) Community Land Model (version 5), switching to the two‐stage firn densification model (with 16 layers) significantly decreases root‐mean‐square errors in upper 60 m dry firn densities by an average of 41 kg m −3 (31%). Simulations with three different firn density parameterizations show that the two‐stage firn densification model should be used for applications that prioritize accurate upper 60 m firn air content (FAC) in regions where the mean annual surface temperature is greater than roughly −31°C. Because snow metamorphism, firn density, and FAC are major components in modeling ice sheet surface albedo, melt water retention, and climatic mass balance, these developments advance broader efforts to simulate the response of land ice to atmospheric forcing in Earth system models.

58 GEOSCIENCES↗
DOE OSTI2021

The Plant a Trillion Trees Campaign to Reduce Global Warming – Fleshing Out the Concept

The campaign to plant a trillion trees provided an easily understood approach to reduce the threat of global warming. However, focusing on trees does not consider that a maturing forest releases carbon (C) from dying trees offsetting C intake from growth of other trees, and results in only a one-time carbon storage benefit. Under sustainable management that harvests before forest growth slows down, forest C is transferred to wood products that substitute for fossil fuel (FF)- intensive products, reducing the carbon dioxide (CO 2 ) emissions with every harvest. Sustainably managed forests maintain growth by replanting (or regenerating), sustaining the C stored in products, as well as avoiding FF-intensive product emissions with every harvest. This paper addresses the question: Could planting more trees significantly reduce atmospheric CO 2 ; and if so, how? Survey data from many wood-producing mills show life cycle inventory (LCI) data on C that has been tracked through every stage of processing for many different wood products specific to each United States (USA) supply region, as well as C displacement measurements when substituting wood for FFintensive products. Results show that more and better-managed forest lands and more efficient product uses provide significant opportunities to reduce CO 2 emissions, especially in highly productive forest regions.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

REDI – Readiness Engine for Data Integration

The Readiness Engine for Data Integration (REDI) is an open-source framework for automating, standardizing, and assessing the process of preparing scientific data for AI training. REDI implements a five-stage pipeline (ingest, preprocess, transform, structure, output) with per-stage provenance instrumentation via Flowcept, domain-aware transformation logic (PII anonymization, regridding, graph encoding, and more), and built-in readiness assessment and validation modes. REDI has been evaluated across climate, proteomics, materials science, and nuclear fusion datasets, demonstrating near-ideal parallel scaling to 100 nodes on OLCF's Frontier system. REDI is deployable as an agent-callable skill in coding environments such as Claude Code and OpenAI Codex, and is complemented by SetGo for FAIR compliance and catalog publication.

Brewer, Wesley [Oak Ridge National Laboratory (ORN↗