SEARCH · Engineering Papers

Results for “process coupling”

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.

SourceResearch connectionFrom yearThrough year

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 793 records · Page 44

All sources NASA NTRS DOE OSTI

DOE OSTI2020

Magnetic anomalies associated with domain wall freezing and coupled electron hopping in magnetite nanorods

Magnetite has fascinated researchers for decades, due to its wide range of applications from spintronics to biomedicine. Despite a large body of works aimed at its magnetic properties, no consensus has been reached on the physical origin of the low temperature magnetic anomalies observed in magnetite. Although, a lot of work has been done in studying magnetite nanoparticles, but studies on the low temperature anomalies in those nanoparticles still remains unresearched. We report on the observation of the low temperature magnetic anomalies in highly crystalline, stoichiometric Fe 3 O 4 nanorods and relate them to the coupled electron hopping relaxation process and domain wall motion. Both DC and AC susceptibility show the presence of a hump around 35 K, which is associated with the relaxation of Fe +2 extra electrons. Radiofrequency transverse susceptibility (TS) measurements indicated a noticeable increase in anisotropy field below ~ 25 K, which is attributed to the rearrangement of Fe +2 electrons in the octahedral sites. TS experiments also revealed the domain wall freezing below ~35 K. Our combined DC, AC and TS susceptibility studies shed light on the complex nature of the lowtemperature magnetic behavior in nanostructured magnetite.

36 MATERIALS SCIENCE↗

NASA NTRS2002

System Level Uncertainty Assessment for Collaborative RLV Design

A collaborative design process utilizing Probabilistic Data Assessment (PDA) is showcased. Given the limitation of financial resources by both the government and industry, strategic decision makers need more than just traditional point designs, they need to be aware of the likelihood of these future designs to meet their objectives. This uncertainty, an ever-present character in the design process, can be embraced through a probabilistic design environment. A conceptual design process is presented that encapsulates the major engineering disciplines for a Third Generation Reusable Launch Vehicle (RLV). Toolsets consist of aerospace industry standard tools in disciplines such as trajectory, propulsion, mass properties, cost, operations, safety, and economics. Variations of the design process are presented that use different fidelities of tools. The disciplinary engineering models are used in a collaborative engineering framework utilizing Phoenix Integration's ModelCenter and AnalysisServer environment. These tools allow the designer to join disparate models and simulations together in a unified environment wherein each discipline can interact with any other discipline. The design process also uses probabilistic methods to generate the system level output metrics of interest for a RLV conceptual design. The specific system being examined is the Advanced Concept Rocket Engine 92 (ACRE-92) RLV. Previous experience and knowledge (in terms of input uncertainty distributions from experts and modeling and simulation codes) can be coupled with Monte Carlo processes to best predict the chances of program success.

Charania, A. C.↗

NASA NTRS1989

An intelligent advisor for the design manager

A design problem is viewed as a complex system divisible into modules. Before the design of a complex system can begin, much time and money are spent in determining the couplings among modules and the presence of iterative loops. This is important because the design manager must know how to group the modules into substems and how to assign subsystems to design teams so that changes in one subsystem will have predictable effects on other subsystems. Determining these subsystems is not an easy, straightforward process and often important couplings are overlooked. Moreover, the planning task must be repeated as new information becomes available or as the design specifications change. The purchase of this research effort is to develop a knowledge-based tool to act as an intelligent advisor for the design manager. This tool identifies the subsystems of a complex design problem, orders them into a well-structured format, and marks the couplings among the subsystems to facilitate the use of multilevel tools. The tool was tested in the decomposition of the COFS (Control of Flexible Structures) mast design which has about 50 modules. This test indicated that this type of approach could lead to a substantial savings by organizing and displaying a complex problem as a sequence of subsystems easily divisible among design teams.

Rogers, James L.↗

DOE OSTI2021

ParFlow

ParFlow is an open-source, modular, parallel watershed flow model. It includes fully-integrated overland flow, the ability to simulate complex topography, geology and heterogeneity and coupled land-surface processes including the land-energy budget, biogeochemistry and snow (via CLM). It is multi-platform and runs with a common I/O structure from laptop to supercomputer. ParFlow is the result of a long, multi-institutional development history and is now a collaborative effort between CSM, LLNL, UniBonn and UCB. ParFlow has been coupled to the mesoscale, meteorological code ARPS and the NCAR code WRF.

Smith, Steven↗

DOE OSTI2021

ParFlow

Smith, Steven↗

NASA NTRS1995

On-line removal of volatile fatty acids from CELSS anaerobic bioreactor via nanofiltration

The CELSS (controlled ecological life support system) resource recovery system, which is a waste processing system, uses aerobic and anaerobic bioreactors to recover plants nutrients and secondary foods from the inedible biomass. The anaerobic degradation of the inedible biomass by means of culture of rumen bacteria,generates organic compounds such as volatile fatty acids (acetic, propionic, butyric, VFA) and ammonia. The presence of VFA in the bioreactor medium at fairly low concentrations decreases the microbial population's metabolic reactions due to end-product inhibition. Technologies to remove VFA continuously from the bioreactor are of high interest. Several candidate technologies were analyzed, such as organic solvent liquid-liquid extraction, adsorption and/or ion exchange, dialysis, electrodialysis, and pressure driven membrane separation processes. The proposed technique for the on-line removal of VFA from the anaerobic bioreactor was a nanofiltration membrane recycle bioreactor. In order to establish the nanofiltration process performance variables before coupling it to the bioreactor, a series of experiments were carried out using a 10,000 MWCO tubular ceramic membrane module. The variables studied were the bioreactor slurry permeation characteristics, such as, the permeate flux, VFA and the nutrient removal rates as a function of applied transmembrane pressure, fluid recirculation velocity, suspended matter concentration, and process operating time. Results indicate that the permeate flux, VFA and nutrients removal rates are directly proportional to the fluid recirculation velocity in the range between 0.6 to 1.0 m/s, applied pressure when these are low than 1.5 bar, and inversely proportional to the total suspended solids concentration in the range between 23,466 to 34,880. At applied pressure higher than 1.5 bar the flux is not more linearly dependent due to concentration polarization and fouling effects over the membrange surface. It was also found that the permeate flux declines rapidly during the first 5 to 8 hours, and then levels off with a diminishing rate of flux decay.

Colon, Guillermo↗

DOE OSTI2021

Quantifying physical parameterization uncertainties associated with land-atmosphere interactions in the WRF model over Amazon

The Weather Research and Forecasting (WRF) model can be used to diagnose regional land-atmosphere (L-A) coupling strength in the absence of sufficient observations but subjected to uncertainties associated with model physical parameterizations. In this study, we propose a framework to quantify and reduce model physical parameterization uncertainties associated with surface fluxes and L-A coupling. An ensemble of WRF simulations with different physical schemes is used to simulate surface fluxes and land-atmosphere coupling strength over the Amazon region. The physical parameterizations investigated include cloud microphysics (MP), land surface processes (LSM), planetary boundary layer (PBL), surface layer (SL), and cumulus (CU). We perform 120 ensemble simulations using the WRF model and different combinations of six MPs, three LSMs, six PBLs and SLs and three CUs. The measurements from the GoAMAZON field campaign and satellite data are used to evaluate model performance. A Multi-way analysis of variance (ANOVA) approach is applied to quantify the relative importance of different physics processes on L-A coupling. The Tukey’s test is used to sort schemes that have no significant differences into one group. The suite of physics that result in the best simulations of the corresponding variables are selected based on the Taylor skill score. Results show that the relative importance of processes and their interaction vary with the variables of interest. For example, CU was the most important process in modulating soil moisture, 2 m-humidity, latent heat, and net radiation. LSM showed dominant effects on 2 m-temperature and also has the largest impact on sensible heat and the lifting condensation level. The best physical parameterization ensembles show much narrower ranges of the variables of interest than the priori ensemble. Results of this study show the roles of different physical processes in modulating L-A interactions, quantify model uncertainties from physical processes, and provide insights for improving the model physics parameterizations.

Wang, Chen↗

DOE OSTI2022

Automated processing of environmental transmission electron microscopy images for quantification of thin film dewetting and carbon nanotube nucleation dynamics

We report scalable production of carbon nanotubes (CNTs) requires catalysts and reaction conditions that provide high nucleation efficiency. In situ characterization methods such as environmental transmission electron microscopy (ETEM) can reveal fundamental mechanisms of synthesis, but to date have primarily provided qualitative observations on small sample sizes. Here, quantitative analysis is performed using high-resolution, high-rate video capture of ETEM experimentation coupled with automated image processing, involving computer vision algorithms and convolutional neural networks. By this approach, we detect distinct nanoparticle formation from an alumina-supported iron thin film and subsequent CNT nucleation from the nanoparticles. The statistical summary of particles in each video shows that, compared to a H 2 -only atmosphere, pretreatment of the catalyst with carbon added to the H 2 atmosphere results in a smaller average particle diameter, a 2-fold increase in particle density (to 5300 particles/μm 2 ), a 3-fold increase in CNT nucleation efficiency (to 92%), and more than a 5-fold increase in CNT density (to 4800/μm 2 ). Addition of carbon during exposure to H 2 is also more effective than NH 3 at dewetting the catalyst film and increasing the CNT nucleation efficiency, in spite of NH 3 being a stronger reducing agent for iron. Insights from this study are applicable to improving CNT yield and productivity in both batch-style and continuous processes.

25 ENERGY STORAGE↗

NASA NTRS2000

Monsoon-Enso Relationships: A New Paradigm

This article is partly a review and partly a new research paper on monsoon-ENSO relationship. The paper begins with a discussion of the basic relationship between the Indian monsoon and ENSO dating back to the work of Sir Gilbert Walker up to research results in more recent years. Various factors that may affect the monsoon-ENSO, relationship, including regional coupled ocean-atmosphere processes, Eurasian snow cover, land-atmosphere hydrologic feedback, intraseasonal oscillation, biennial variability and inter-decadal variations, are discussed. The extreme complex and highly nonlinear nature of the monsoon-ENSO relationship is stressed. We find that for regional impacts on the monsoon, El Nino and La Nina are far from simply mirror images of each other. These two polarities of ENSO can have strong or no impacts on monsoon anomalies depending on the strength of the intraseasonal oscillations and the phases of the inter-decadal variations. For the Asian-Australian monsoon (AAM) as a whole, the ENSO impact is effected through a east-west shift in the Walker Circulation. For rainfall anomalies over specific monsoon areas, regional processes play important roles in addition to the shift in the Walker Circulation. One of the key regional processes identified for the boreal summer monsoon is the anomalous West Pacific Anticyclone (WPA). This regional feature has similar signatures in interannual and intraseasonal time scales and appears to determine whether the monsoon-ENSO relationship is strong or weak in a given year. Another important regional feature includes a rainfall and SST dipole across the Indian Ocean, which may have strong impact on the austral summer monsoon. Results are shown indicating that monsoon surface wind forcings may induce a strong biennial signal in ENSO and that strong monsoon-ENSO coupling may translate into pronounced biennial variability in ENSO. Finally, a new paradigm is proposed for the study of monsoon variability. This paradigm provides a unified framework in which monsoon predictability, the role of regional vs. basin-scale processes, its relationship with different climate subsystems, and causes of secular changes in monsoon-ENSO relationship can be investigated.

Lau, K. M.↗

DOE OSTI2024

Graph-Based Representations and Applications to Process Simulation

Rapid and robust convergence of a process flowsheet is critical to enable large-scale simulations that address core scientific questions related to process design, optimization, and sustainability. However, due to the highly coupled and nonlinear nature of chemical processes, efficiently solving a flowsheet remains a challenge. In this work, we show that graph representations of the underlying physical phenomena in unit operations may help identify potential avenues to systematically reformulate the network of equations and enable more robust topology-based convergence of flowsheets. To this end, we developed graph abstractions of the governing equations of vapor-liquid and liquid-liquid equilibrium separation equipment. These graph abstractions consist of a mesh of interconnected variable nodes and equation nodes that are systematically generated through PhenomeNode, a new open-source library in Python developed in this study. We show that partitioning the graph into separate mass, energy, and equilibrium subgraphs can help decouple nonlinearities and guide decomposition algorithms. By employing the graph abstraction on an industrial separation process for separating glacial acetic acid from water, we implemented a new block decomposition scheme in BioSTEAM and demonstrated that this can accelerate convergence over a traditional sequential modular approach.

Distillation↗

NASA NTRS1992

Metrology of X-ray optics utilizing shearing interferometric techniques

This paper will discuss the optical testing of extreme grazing incidence mirror systems and normal incidence high-precision mirror systems during fabrication processing of the optical substrates. The optical metrology is closely coupled with an advanced material removal process which will be discussed in terms of the optical metrology. Interferometric data will be presented of the optical surfaces. Surface roughness data will be shown and discussed.

Baker, Phillip C.↗

NASA NTRS1994

Erosional dynamics, flexural isostasy, and long-lived escarpments: A numerical modeling study

Erosional escarpments common features of high-elevation rifted continets. Fission track data suffest that these escarpments form by base level lowering and/or marginal uplift during rifting, followed by lateral retreat of an erosion front across tens to hundreds of kioometers. Previous modeling studies have shown that this characteristic pattern of denudation can have a profound impact upon marginal isostatic uplift and the evolution of offshore sedimentary basins. Yet at present there is only a rudimentary understanding of the geomorphic mechanisms capable of driving such prolonged escarpment retreat. In this study we present a nonlinear, two-dimensional landscape evolution model tha tis used to asses the necessary and sufficient conditions for long-term retreat of a rift-generated escarpment. The model represents topography as a grid of cells, with drainage networkds evolving as water flows across the grid in the direction of steepest descent. The model accounts for sediment production by weathering, fluvial sediment transport, bedrock channel erosion, and hillslope sediment transport by diffusive mechanisms and by mass failure. Numerical experiments presented explore the effects of different combinations of erosion processes and of dynamic coupling between denudation and flexural isostatic uplift. Model results suggest that the necessary and sufficient conditions for long-term escarpment retreat are (1) incising bedrock channels in which the erosion rate increases with increasing drainage area, so that the channels steepen and propagate headward; (2) a low rate of sediment production relative to sediment transport efficiency, which promotes relief-generating processes over diffusive ones; (3) high continental elevation, which allows greater freedom for fluvial dissection; and (4) any process, including flexural isostatic uplift, that helps to maintain a drainage divide near an escarpment crest. Flexural isostatic uplift also facilitates escarpment, thereby increasing channel gradients and accelerating erosion which in turn generates additional isostatic uplift. Of all the above conditions, high continental elevation is common ot most rift margin escarpments and may ultimately be the most important factor.

Tucker, Gregory E.↗

DOE OSTI2021

Data assimilation empowered neural network parametrizations for subgrid processes in geophysical flows

In the past couple of years, there has been a proliferation in the use of machine learning approaches to represent subgrid-scale processes in geophysical flows with an aim to improve the forecasting capability and to accelerate numerical simulations of these flows. Despite its success for different types of flow, the online deployment of a data-driven closure model can cause instabilities and biases in modeling the overall effect of subgrid-scale processes, which in turn leads to inaccurate prediction. To tackle this issue, we exploit the data assimilation technique to correct the physics-based model coupled with the neural network as a surrogate for unresolved flow dynamics in multiscale systems. In particular, we use a set of neural network architectures to learn the correlation between resolved flow variables and the parametrizations of unresolved flow dynamics and formulate a data assimilation approach to correct the hybrid model during their online deployment. We illustrate our framework in a set of applications of the multiscale Lorenz 96 system for which the parametrization model for unresolved scales is exactly known, and the two-dimensional Kraichnan turbulence system for which the parametrization model for unresolved scales is not known a priori. Our analysis, therefore, comprises a predictive dynamical core empowered by (i) a data-driven closure model for subgrid-scale processes, (ii) a data assimilation approach for forecast error correction, and (iii) both data-driven closure and data assimilation procedures. We show significant improvement in the long-term prediction of the underlying chaotic dynamics with our framework compared to using only neural network parametrizations for future prediction. Moreover, we demonstrate that these data-driven parametrization models can handle the non-Gaussian statistics of subgrid-scale processes, and effectively improve the accuracy of outer data assimilation workflow loops in a modular nonintrusive way.

42 ENGINEERING↗

NASA NTRS1997

Predictive Modeling in Plasma Reactor and Process Design

Research continues toward the improvement and increased understanding of high-density plasma tools. Such reactor systems are lauded for their independent control of ion flux and energy enabling high etch rates with low ion damage and for their improved ion velocity anisotropy resulting from thin collisionless sheaths and low neutral pressures. Still, with the transition to 300 mm processing, achieving etch uniformity and high etch rates concurrently may be a formidable task for such large diameter wafers for which computational modeling can play an important role in successful reactor and process design. The inductively coupled plasma (ICP) reactor is the focus of the present investigation. The present work attempts to understand the fundamental physical phenomena of such systems through computational modeling. Simulations will be presented using both computational fluid dynamics (CFD) techniques and the direct simulation Monte Carlo (DSMC) method for argon and chlorine discharges. ICP reactors generally operate at pressures on the order of 1 to 10 mTorr. At such low pressures, rarefaction can be significant to the degree that the constitutive relations used in typical CFD techniques become invalid and a particle simulation must be employed. This work will assess the extent to which CFD can be applied and evaluate the degree to which accuracy is lost in prediction of the phenomenon of interest; i.e., etch rate. If the CFD approach is found reasonably accurate and bench-marked with DSMC and experimental results, it has the potential to serve as a design tool due to the rapid time relative to DSMC. The continuum CFD simulation solves the governing equations for plasma flow using a finite difference technique with an implicit Gauss-Seidel Line Relaxation method for time marching toward a converged solution. The equation set consists of mass conservation for each species, separate energy equations for the electrons and heavy species, and momentum equations for the gas. The sheath is modeled by imposing the Bohm velocity to the ions near the walls. The DSMC method simulates each constituent of the gas as a separate species which would be analogous in CFD to employing separate species mass, momentum, and energy equations. All particles including electrons are moved and allowed to collide with one another with the stipulation that the electrons remain tied to the ions consistent with the concept of ambipolar diffusion. The velocities of the electrons are allowed to be modified during collisions and are not confined to a Maxwellian distribution. These benefits come at a price in terms of computational time and memory. The DSMC and CFD are made as consistent as possible by using similar chemistry and power deposition models. Although the comparison of CFD and DSMC is interesting, the main goal of this work is the increased understanding of high-density plasma flowfields that can then direct improvements in both techniques. This work is unique in the level of the physical models employed in both the DSMC and CFD for high-density plasma reactor applications. For example, the electrons are simulated in the present DSMC work which has not been done before for low temperature plasma processing problems. In the CFD approach, for the first time, the charged particle transport (discharge physics) has been self-consistently coupled to the gas flow and heat transfer.

Hash, D. B.↗

DOE OSTI2020

Reactive chemical transport simulations of geologic carbon sequestration: Methods and applications

Chemical reaction simulations are considerably used to quantitatively assess the long-term geologic carbon sequestration (GCS), such as CO 2 sequestration capacity estimations, leakage pathway analyses, enhanced oil recovery (EOR) efficiency studies, and risk assessments of sealing formations (caprocks), wellbores, and overlying underground water resources. All these require a deep understanding of the CO 2 - associated chemical reactions. To ensure long-term, safe CO 2 sequestration in the intended formations, modeling is the only way to plausibly assess the CO 2 flow, reaction, and transport over thousands of years. This review summarizes the multiple methodologies for describing homogeneous and heterogeneous chemical reaction patterns and multiscale application examples, the recent progress and current status of chemical reaction simulations for GCS, and the impact of such simulations on geological CO2 sequestration performance. Technical gaps and future challenges are also discussed for further study. The trends and challenges of such studies include: (1) the combination of coupled chemical, mechanical, and transport processes with calibrated experiments and associated uncertainty/risk assessments; (2) enhancement of the ability to simulate detailed geophysical and geochemical equations to mimic in situ conditions; and (3) characterization of multiscale subsurface systems with detailed conceptual models and assignment of suitable boundary conditions for field-scale sequestration fields. One major gap remaining is the current lack of accurate (and scale-justified) kinetic and equilibrium chemical reaction parameters under reservoir conditions. Advanced models that couple chemical, mechanical, and transport processes with scale-justified parameters, from lab to field-scale experiments, are required for quantitative assessments of sequestration capacity and the long-term safety of GCS projects.

58 GEOSCIENCES↗

DOE OSTI2026

BNF Radar b1 Data Processing Report: Spring 2025

The U.S. Department of Energy’s Atmospheric Radiation Measurement (ARM) User Facility supports atmospheric science through an integrated network of fixed and mobile observatories. These facilities collect continuous and campaign-based observations of atmospheric properties, with the goal of improving the representation of clouds, aerosols, precipitation, and radiation in Earth system models. The Bankhead National Forest (BNF) site, established as an ARM Mobile Facility (AMF) on 1 October 2024, is situated in a forested region of northern Alabama. Its strategic location in a southeastern U.S. environment characterized by complex terrain, diverse land cover, and frequent convective storms provides a valuable opportunity to examine coupled land-atmosphere processes under natural variability.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS2008

Safety Modification of Cam-and-Groove Hose Coupling

A modification has been made in the mating halves of a cam-and-groove hose coupling to prevent rapid separation of the halves in the event that the cam levers are released while the fluid in the hose is pressurized. The need for this modification arises because commercial off-the-shelf cam-and-groove hose-coupling halves do not incorporate safety features to prevent separation in the pressurized state. Especially when the pressurized fluid is compressible (e.g., steam or compressed air), the separated halves can be propelled with considerable energy, causing personal injury and/or property damage. Therefore, one purpose served by the modification is to provide for venting to release compressive energy in a contained and safe manner while preventing personal injury and/or property damage. Another purpose served by the modification, during the process of connecting the coupling halves, is to ensure that the coupling halves are properly aligned before the cam levers can be locked into position.

Schwindt, Paul↗

DOE OSTI2021

Coupling of Spark Plasma Sintering with Advanced Modeling to Enable Process Scale-Up: LDRD Final Project Poster

Electric-field assisted sintering (EFAS) manufacturing techniques reduce energy usage requirements, fabricate near-net-shape parts, and produce bulk nanostructured materials through rapid heating and cooling rates achievable through Joule heating. Process parameters of pulsed DC voltage and constant pressure are applied through stainless steel rams and graphite tooling to the ceramic yttrium oxide powder to be sintered. Our high-fidelity modeling code application advances manufacturing for extreme environments by enabling process-informed design and improving microstructure consistency through multiphysics multiscale process-structure-property-performance correlation simulations.

36 MATERIALS SCIENCE↗