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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.

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At least 235 records · Page 13
All sourcesNASA NTRSDOE OSTI
NASA NTRS1980

Remote sensing of ozone in the middle ultraviolet

Earlier studies of the remote sensing of the ozone distribution from satellites in the middle ultraviolet are extended, giving particular attention to the analytic model method. After a brief introduction, the historical background of this subject is presented. This is followed by a summary and review of early work based upon the analytic model. Then a linearized approach to the problem and a linearized equation for a density correction are discussed. These indicate some of the general limitations of the inversion method. Finally the parametrized model approach is reexamined by using both simulated data and some actual satellite data.

Green, A. E. S.↗
NASA NTRS2003

Progress in Developing a New Field-theoretical Crossover Equation-of-State

A new field-theoretical crossover equation-of-state model is being developed. This model of a liquid-gas critical point provides a bridge between the asymptotic equation-of-state behavior close to the transition, obtained by the Guida and Zinn-Justin parametric model [J. Phys. A: Math. Gen. 31, 8103 (1998)], and the expected mean field behavior farther away. The crossover is based on the beta function for the renormalized fourth-order coupling constant and incorporates the correct crossover exponents and critical amplitude ratios in both regimes. A crossover model is now being developed that is consistent with predictions along the critical isochore and along the coexistence curve of the minimal subtraction renormalization approach developed by Dohm and co-workers and recently applied to the O(1) universality class [Phys. Rev. E, 67, 021106 (2003)]. Experimental measurements of the heat capacity at constant volume, isothermal susceptibility, and coexistence curve near the He-3 critical point are being compared to the predictions of this model. The results of these comparisons will be presented.

Rudnick, Joseph↗
DOE OSTI2024

Assessment of Machine Learning Wall Modeling Approaches for Large Eddy Simulation of Gas Turbine Film Cooling Flows: An a Priori Study

Here, in this work, a priori analysis of machine learning (ML) strategies is carried out with the goal of data-driven wall modeling for large eddy simulation (LES) of gas turbine film cooling flows. High-fidelity flow datasets are extracted from wall-resolved LES (WRLES) of flow over a flat plate interacting with the coolant flow supplied by a single row of 7-7-7 shaped cooling holes inclined at 30 degrees with the flat plate at different blowing ratios (BR). The WRLES are performed using the high-order Nek5000 spectral element computational fluid dynamics (CFD) solver. Light gradient boosting machine (LightGBM) is employed as the ML algorithm for the data-driven wall model. Parametric tests are conducted to systematically assess the influence of a wide range of input flow features (velocity components, velocity gradients, pressure gradients, and fluid properties) on the accuracy of ML wall model with respect to prediction of wall shear stress. In addition, the use of spatial stencil and time delay is also explored within the ML wall modeling framework. It is shown that features associated with gradients of the streamwise and spanwise velocity components have a major impact on the prediction fidelity of wall model, while the effect of gradients of wall-normal velocity component is found to be negligible. Moreover, adding flow feature information from an x-y-z spatial stencil significantly improves the ML model accuracy and generalizability compared to just using local flow features from the matching location. Overall, highest prediction accuracy is achieved when both spatial stencil and time delay features are incorporated within the data-driven wall modeling paradigm.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2024

Evaluating SWAT + model uncertainties for human and natural outcomes: Application in a Great Lakes agricultural watershed

Nutrient exports from agricultural lands in the Great Lakes Region pose significant threats to water quality and ecological health through eutrophication, hypoxia, and harmful algal blooms. Climate change and agricultural adaptation practices complicate future nutrient loading due to intensified hydrologic cycles and land use decisions. Our research focuses on evaluating the Soil and Water Assessment Tool (SWAT) plus model parametric uncertainties for human and natural outcomes across different scales. These factors are integral to ensuring a balance between productive agricultural practices and maintaining the health of watershed hydrology. However, uncertainties in modeling such complex interactions pose significant challenges, limiting our ability to precisely determine critical factors that influence crop yield and soil moisture. Our analysis employs Sobol global sensitivity analysis to evaluate first-order, second order, and total-order indices for SWAT crop growth parameter, ensuring comprehensive assessment of individual and interactive effects on model outputs. The objective is to identify the parameters that significantly affect model outputs for crop yield and soil moisture and improve our understanding of their interactions at the basin and hydrological response unit (HRU) scale. Our case study, the Portage River Watershed, which drains into Lake Erie, is chosen to better capture finer scale interactions crucial for predicting nutrient loading under future climate scenarios. This foundational work is aimed at setting the stage for the future development of an agent-based model (ABM). The ABM model would incorporate SWAT outputs to dynamically simulate decision-making processes.

Bunyon, Enock↗
NASA NTRS1987

Structural analysis demonstration of constitutive and life models

The overall objective of this program is to demonstrate the applicability of NASA-developed advanced constitutive and life damage models for calculating cyclic structural response and crack initiation in selected components of reusable space propulsion systems. The computer model resulting from this program will enable the user to produce an accurate life prediction of hot gas path, life limiting components of propulsion systems such as the space shuttle main engine (SSME). Previously developed computer models addressing constitutive modeling and life damage will be combined in an advanced finite element analysis to generate a sophisticated baseline life prediction program. A material data base will be established for the constitutive and life models parametrically involving temperature, strain range, strain rate, mean strain/stress, and dwell time. The verified computer program will be used to accomplish the life predictions of three SSME critical components as evidence of the model functionality.

Bechtel, G.↗
DOE OSTI2024

A novel Bayesian approach for decomposing the radio emission of quasars: I. Modelling the radio excess in red quasars

ABSTRACT Studies show that both radio jets from the active galactic nuclei (AGNs) and the star formation (SF) activity in quasar host galaxies contribute to the quasar radio emission; yet their relative contributions across the population remain unclear. Here, we present an improved parametric model that allows us to statistically separate the SF and AGN components in observed quasar radio flux density distributions, and investigate how their relative contributions evolve with AGN bolometric luminosity ($L_\mathrm{bol}$) and redshift (z) using a fully Bayesian method. Based on the newest data from LOw-Frequency ARray Two-metre Sky Survey data release 2, our model gives robust fitting results out to $z\sim 4$, showing a quasar host galaxy SF rate (SFR) evolution that increases with bolometric luminosity and with redshift out to $z\sim 4$. This differs from the global cosmic SFR density, perhaps due to the importance of galaxy mergers. The prevalence of radio AGN emissions increases with quasar luminosity, but has little dependence on redshift. Furthermore, our new methodology and large sample size allow us to subdivide our data set to investigate the role of other parameters. Specifically, in this paper, we explore quasar colour and demonstrate that the radio excess in red quasars is due to an enhancement in AGN-related emission, since the host galaxy SF contribution to the total radio emission is independent of quasar colour. We also find evidence that this radio enhancement occurs mostly in quasars with weak or intermediate radio power.

Yue, B. -H (ORCID:0009000989352929)↗
NASA NTRS1988

Vectoring Single Expansion Ramp Nozzle (VSERN) static model test program

A variable throat-area, side-vectoring single expansion ramp nozzle (VSERN) concept's internal performance characteristics are studied with a view to controlling the bypass flow of an unmixed turbofan engine. Static tests have been conducted on VSERN at NASA-Langley using a variety of parametric models giving attention to the effects of upstream bend angle, ramp geometry, area ratio, and nozzle pressure ratio on static thrust and flow performance. Advantages of VSERN over the conventional vectoring axisymmetric convergent side-nozzles typified by those of the Harrier's Pegasus engine.

Eames, D. J. H.↗
DOE OSTI2023

Phase transition phenomenology with nonparametric representations of the neutron star equation of state

Astrophysical observations of neutron stars probe the structure of dense nuclear matter and have the potential to reveal phase transitions at high densities. Most recent analyses are based on parametrized models of the equation of state with a finite number of parameters and occasionally include extra parameters intended to capture phase-transition phenomenology. However, such models restrict the types of behavior allowed and may not match the true equation of state. We introduce a complementary approach that extracts phase transitions directly from the equation of state without relying on, and thus being restricted by, an underlying parametrization. We then constrain the presence of phase transitions in neutron stars with astrophysical data. Current pulsar mass, tidal deformability, and mass-radius measurements disfavor only the strongest of possible phase transitions (latent energy per particle ≳ 100 MeV). Weaker phase transitions are consistent with observations. Here we further investigate the prospects for measuring phase transitions with future gravitational-wave observations and find that catalogs of O (100) events will (at best) yield Bayes factors of ~ 10 : 1 in favor of phase transitions even when the true equation of state contains very strong phase transitions. Our results reinforce the idea that neutron star observations will primarily constrain trends in macroscopic properties rather than detailed microscopic behavior. Fine-tuned equation of state models will likely remain unconstrained in the near future.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

Pulsed Thermal Tomography Nondestructive Examination of Additively Manufactured Reactor Materials and Components (Final Technical Report)

Metal Additive Manufacturing (AM) is a promising method for cost-efficient fabrication of complex shape structures for applications in harsh environment, such as in a nuclear reactor. However, internal defects (pores) occur in high-strength AM alloys, which are manufactured with Laser Powder Bed Fusion (LPBF) AM method. Pulsed Infrared Thermography (PIT) is an efficient nondestructive evaluation (NDE) method to examine actual structures, because this method offers one-sided non-contact measurements, and fast processing of large sample areas. However, imaging of material defects, particularly defects with sizes at microscopic level, is challenging. In this report, we benchmark the performance of several Unsupervised Learning (UL) algorithms designed to enhance imaging of microscopic defects in metals with PIT. UL aims to learn the latent principal patterns (dictionaries) in PIT data to detect defects with minimal human supervision. Performance of Independent Component Analysis (ICA), Sparse Coding (SC), Principal Component Analysis (PCA) and Exploratory Factor Analysis (EFA) was compared using F-score, UL model training time and defects reconstruction time. We obtained the average F-score of 0.75, and a highest F-score of 0.89 for the EFA algorithm. Overall, EFA outperforms other UL algorithms considered in this study. In another approach, we investigate Thermal Tomography (TT), which is a computational method for reconstruction of depth profile of internal material defects from PIT nondestructive evaluation (NDE). TT algorithm obtains depth reconstructions of thermal effusivity, which has been shown to provide visualization of subsurface internals defects in metals. In many applications, one needs to determine the defect shape and orientation from reconstructed effusivity images. Interpretation of TT images is non-trivial because of blurring, which increases with depth due to heat diffusion-based nature of image formation. We have developed a deep learning convolutional neural network (CNN) to classify size and orientation of subsurface material defects in TT images. CNN was trained with TT images produced with computer simulations of 2D metallic structures (thin plates) containing elliptical subsurface voids. Performance of CNN was investigated using test TT images developed with computer simulations of plates containing elliptical defects, and defects with shape imported from scanning electron microscopy (SEM) images. CNN demonstrated the ability to classify radii and angular orientation of elliptical defects in previously unseen test TT images. We have also demonstrated that CNN trained on TT images of elliptical defects is capable of classifying shape and orientation of irregular defects. Training the CNN on irregular defect shapes instead of on elliptical shapes would make the resulting classifications more descriptive of actual defect shapes. However, this requires a much higher volume of SEM images of material defects, which are difficult to obtain because of random occurrence of defects in LPBF. To address this challenge, we developed a generative adversarial network (GAN) to augment the existing dataset of SEM defect images. The GAN model is demonstrated to create novel yet realistic defect shapes that can be used as input for simulated PTT images to train CNN. We also investigate several approaches based on Gaussian Random Circle and Bezier Curves for constructing parametric models of irregular-shape defects.

36 MATERIALS SCIENCE↗
NASA NTRS1994

Ionospheric calibration for single frequency altimeter measurements

This study is a preliminary analysis of the effectiveness (in terms of altimeter calibration accuracy) of various ionosphere models and the Global Positioning System (GPS) to calibrate single frequency altimeter height measurements for ionospheric path delay. In particular, the research focused on ingesting GPS Total Electron Content (TEC) data into the physical Parameterized Real-Time Ionospheric Specification Model (PRISM), which estimates the composition of the ionosphere using independent empirical and physical models and has the capability of adjusting to additional ionospheric measurements. Two types of GPS data were used to adjust the PRISM model: GPS receiver station data mapped from line-of-sight observations to the vertical at the point of interest and a grid map (generated at the Jet Propulsion Laboratory) of GPS derived TEC in a sun-fixed longitude frame. The adjusted PRISM TEC values, as well as predictions by the International Reference Ionosphere (IRI-90), a climatological (monthly mean) model of the ionosphere, were compared to TOPEX dual-frequency TEC measurements (considered as truth) for a number of TOPEX sub-satellite tracks. For a 13.6 GHz altimeter, a Total Electron Content (TEC) of 1 TECU 10(exp 16) electrons/sq m corresponds to approximately 0.218 centimeters of range delay. A maximum expected TEC (at solar maximum or during solar storms) of 10(exp 18) electrons/sq m will create 22 centimeters of range delay. Compared with the TOPEX data, the PRISM predictions were generally accurate within the TECU when the sub-satellite track of interest passed within 300 to 400 km of the GPS TEC data or when the track passed through a night-time ionosphere. If neither was the case, in particular if the track passed through a local noon ionosphere, the PRISM values differed by more than 10 TECU and by as much as 40 TECU. The IRI-90 model, with no current ability to unseat GPS data, predicted TEC to a slightly higher error of 12 TECU. The performance of PRISM is very promising for predicting TEC and will prove useful for calibrating single frequency altimeter height measurements for ionospheric path delay. When adjusted to the GPS line-of-sight data the PRISM URSI empirical model predicted TEC over a day's period to within a global error of 8.60 TECU rms during a nighttime ionosphere and 9.74 TECU rms during the day. When adjusted to the GPS derived TEC grid, the PRISM parametrized model predicted TEC to within an error of 8.47 TECU rms for a nighttime ionosphere and 12.83 TECU rms during the day. However, the grid cannot be considered globally due to the lack of sufficient numbers of GPS stations and large latitude gaps in GPS data. It is the opinion of the authors that using the PRISM model and adjusting to the global sun-fixed TEC grid regenerated with a localized weighted interpolation offers the best possibility of meeting the 10 TECU global rms (or 2 cm at 13.6 GHz) ionosphere range correction accuracy requirement of TOPEX/Poseidon and should be the subject of further study. However, it is clear that the anticipated requirement of 34 TECU global rms for TOPEX/Poseidon Follow-On (corresponding to the TOPEX/Poseidon performance) can not be met with any realizable combination of existing models and data assimilation schemes.

Schreiner, William S.↗
NASA NTRS2016

Compatibility Assessment Tool

In support of ground system development for the Space Launch System (SLS), engineers are tasked with building immense engineering models of extreme complexity. The various systems require rigorous analysis of pneumatics, hydraulic, cryogenic, and hypergolic systems. There are certain standards that each of these systems must meet, in the form of pressure vessel system (PVS) certification reports. These reports can be hundreds of pages long, and require many hours to compile. Traditionally, each component is analyzed individually, often utilizing hand calculations in the design process. The objective of this opportunity is to perform these analyses in an integrated fashion with the parametric CADCAE environment. This allows for systems to be analyzed on an assembly level in a semi-automated fashion, which greatly improves accuracy and efficiency. To accomplish this, component specific parameters were stored in the Windchill database to individual Creo Parametric models based on spec control drawings. These parameters were then accessed by using the Prime Analysis within Creo Parametric. MathCAD Prime spreadsheets were created that automatically extracted these parameters, performed calculations, and generated reports. The reports described component compatibility based on local conditions such as pressure, temperature, density, and flow rates. The reports also determined component pairing compatibility, such as properly sizing relief valves with regulators. The reports stored the input conditions that were used to determine compatibility to increase traceability of component selection. The desired workflow for using this tool would begin with a Creo Schematics diagram of a PVS system. This schematic would store local conditions and locations of components. The schematic would then populate an assembly within Creo Parametric, using Windchill database parts. These parts would have their attributes already assigned, and the MathCAD spreadsheets could begin running through database parts to determine which components would be suited for specific locations within the assembly. This eliminates a significant amount of time from the design process, and makes initial analysis assessments more accurate. Each component that would be checked for a location within the assembly would generate a report, showing whether the component was compatible. These reports could be used to generate the PVS report without the need to perform the same analysis multiple times. This process also has the potential to be expanded upon to further automate PVS reports. The integration of software codes or macros could be used to automatically check through hundreds of parts for each location on the schematic. If the software could recognize which type of component would be necessary for each location, it is possible that simply starting the macro could completely choose all the components needed for the schematic, and in turn the system. This would save many hours of work initially selecting components, which could end up saving money. Overall, this process helps to automate initial component selections for PVS systems to fit local design specifications. These selections will automatically generate reports showing how the design criteria are met by the specific component that was chosen. These reports will contribute to easier compilation of the PVS certification reports, which currently take a great amount of time and effort to produce.

Egbert, James Allen↗
DOE OSTI2022

Insights Into the Aerodynamic Versus Radiometric Surface Temperature Debate in Thermal-Based Evaporation Modeling

Global evaporation monitoring from Earth observation thermal infrared satellite missions is historically challenged due to the unavailability of any direct measurements of aerodynamic temperature. State-of-the-art one-source evaporation models use remotely sensed radiometric surface temperature as a substitute for the aerodynamic temperature and apply empirical corrections to accommodate for their inequality. This introduces substantial uncertainty in operational drought mapping over complex landscapes. By employing a non-parametric model, we show that evaporation can be directly retrieved from thermal satellite data without the need of any empirical correction. Independent evaluation of evaporation in a broad spectrum of biome and aridity yielded statistically significant results when compared with eddy covariance observations. While our simplified model provides a new perspective to advance spatio-temporal evaporation mapping from any thermal remote sensing mission, the direct retrieval of aerodynamic temperature also generates the highly required insight on the critical role of biophysical interactions in global evaporation research.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Determining the ballistic threshold velocity for a composite structure using multiple failure models

A composite structure, such as a laminated composite panel, for example, comprises one or more layers or “plies” embedded in a matrix material or otherwise fixed together in an arrangement, commonly referred to as a “stack up.” Each material in the structure has a corresponding material failure model (MFM) defining the physical characteristics of that material. A ballistic threshold velocity computing device obtains the MFMs for each material in the composite structure, generates a predicted ballistic velocity threshold velocity for each MFM, and then generates a parametric model to compute a composite ballistic velocity threshold velocity for the composite structure.

36 MATERIALS SCIENCE↗
NASA NTRS2010

Uterine Contraction Modeling and Simulation

Building a training system for medical personnel to properly interpret fetal heart rate tracing requires developing accurate models that can relate various signal patterns to certain pathologies. In addition to modeling the fetal heart rate signal itself, the change of uterine pressure that bears strong relation to fetal heart rate and provides indications of maternal and fetal status should also be considered. In this work, we have developed a group of parametric models to simulate uterine contractions during labor and delivery. Through analysis of real patient records, we propose to model uterine contraction signals by three major components: regular contractions, impulsive noise caused by fetal movements, and low amplitude noise invoked by maternal breathing and measuring apparatus. The regular contractions are modeled by an asymmetric generalized Gaussian function and least squares estimation is used to compute the parameter values of the asymmetric generalized Gaussian function based on uterine contractions of real patients. Regular contractions are detected based on thresholding and derivative analysis of uterine contractions. Impulsive noise caused by fetal movements and low amplitude noise by maternal breathing and measuring apparatus are modeled by rational polynomial functions and Perlin noise, respectively. Experiment results show the synthesized uterine contractions can mimic the real uterine contractions realistically, demonstrating the effectiveness of the proposed algorithm.

Liu, Miao↗
DOE OSTI2026

Validation of the NLR Pumped Storage Hydropower Cost Model

The National Laboratory of the Rockies (NLR) first released its pumped storage hydropower (PSH) cost model in 2023 as the most detailed bottom-up PSH cost model available to the public. It is available both as a spreadsheet and an interactive web tool, enabling users with a variety of PSH interests to transparently characterize costs of alternative PSH sites and designs. The PSH cost model cannot replace detailed site-level studies and design, but it is important to validate it against other industry PSH cost estimates. The initial model methodology report validated the cost model for a single proposed site, the Eagle Mountain Project in California. This slide deck documents an expanded validation exercise using cost data from six other sites: Goldendale (Washington), Seminoe (Wyoming), Gordon Butte (Montana), Swan Lake (Oregon), White Pine (Oregon), and Lewis Ridge (Kentucky). It compares itemized costs from Federal Energy Regulatory Commission (FERC) applications and other reported costs with NLR PSH cost model outputs after customizing inputs for each site. The validation exercise finds that the NLR model's conservative indirect cost assumptions often drive overall cost overestimation, with direct cost comparisons typically agreeing more closely. All cost model estimates are well within an Association for the Advancement of Cost Engineering (AACE) Class 5 estimation range (-50% to +100%), with five within the AACE Class 4 range (-30% to +50%) and four being within 15%. This result is considered reasonable performance for a parametric model applied at a preliminary design stage.

13 HYDRO ENERGY↗
DOE OSTI2020

Vitality models found useful in modeling tag-failure times in acoustic-tag survival studies

Abstract Acoustic telemetry studies often rely on the assumption that premature tag failure does not affect the validity of inferences. However, in some cases this assumption is possibly or likely invalid and it is necessary to apply a correction to estimation procedures. The question of which approaches and specific models are best suited to modeling acoustic tag failures has received little research attention. In this short communication, we present a meta-analysis of 42 acoustic tag-life studies, originally used to correct survival studies involving outmigrating juvenile salmonids in the Columbia/Snake river basin. We compare the performance of nine alternative parametric models including common failure–time/survival models and the vitality models of Li and Anderson Theor Popul Biol 76:118–131, (2009) and Demogr Res 28:341–372, (2013). The tag-life studies used acoustic tags from three different tag manufacturers, had expected lifetimes between 12 and 61 days, and had dry weights ranging from 0.22 to 1.65 g. In 57% of the cases, the vitality models of Li and Anderson Theor Popul Biol 76:118–131, (2009) and Demogr Res 28:341–372, (2013) fit the tag-failure times best. The vitality models were also the second-best choices in 17% of the cases. Together, the vitality models, log-logistic, (19%), and gamma models (14%) accounted for 90% of the models selected. Unlike more traditional failure–time models (e.g., Weibull, Gompertz, gamma, and log-logistic), the vitality models are capable of characterizing both the early onset of tag failure due to manufacturing errors and the anticipated battery life. We provide further guidance on appropriate sample sizes (50–100 tags) and procedures to be considered when applying precise tag-life corrections in release–recapture survival studies.

Skalski, John R. (ORCID:0000000270702505)↗
NASA NTRS1989

Modeling, simulation, and analysis of optical remote sensing systems

Remote Sensing of the Earth's resources from space-based sensors has evolved in the past 20 years from a scientific experiment to a commonly used technological tool. The scientific applications and engineering aspects of remote sensing systems have been studied extensively. However, most of these studies have been aimed at understanding individual aspects of the remote sensing process while relatively few have studied their interrelations. A motivation for studying these interrelationships has arisen with the advent of highly sophisticated configurable sensors as part of the Earth Observing System (EOS) proposed by NASA for the 1990's. Two approaches to investigating remote sensing systems are developed. In one approach, detailed models of the scene, the sensor, and the processing aspects of the system are implemented in a discrete simulation. This approach is useful in creating simulated images with desired characteristics for use in sensor or processing algorithm development. A less complete, but computationally simpler method based on a parametric model of the system is also developed. In this analytical model the various informational classes are parameterized by their spectral mean vector and covariance matrix. These class statistics are modified by models for the atmosphere, the sensor, and processing algorithms and an estimate made of the resulting classification accuracy among the informational classes. Application of these models is made to the study of the proposed High Resolution Imaging Spectrometer (HRIS). The interrelationships among observational conditions, sensor effects, and processing choices are investigated with several interesting results.

Kerekes, John Paul↗
NASA NTRS1998

Geometry Modeling and Grid Generation for Design and Optimization

Geometry modeling and grid generation (GMGG) have played and will continue to play an important role in computational aerosciences. During the past two decades, tremendous progress has occurred in GMGG; however, GMGG is still the biggest bottleneck to routine applications for complicated Computational Fluid Dynamics (CFD) and Computational Structures Mechanics (CSM) models for analysis, design, and optimization. We are still far from incorporating GMGG tools in a design and optimization environment for complicated configurations. It is still a challenging task to parameterize an existing model in today's Computer-Aided Design (CAD) systems, and the models created are not always good enough for automatic grid generation tools. Designers may believe their models are complete and accurate, but unseen imperfections (e.g., gaps, unwanted wiggles, free edges, slivers, and transition cracks) often cause problems in gridding for CSM and CFD. Despite many advances in grid generation, the process is still the most labor-intensive and time-consuming part of the computational aerosciences for analysis, design, and optimization. In an ideal design environment, a design engineer would use a parametric model to evaluate alternative designs effortlessly and optimize an existing design for a new set of design objectives and constraints. For this ideal environment to be realized, the GMGG tools must have the following characteristics: (1) be automated, (2) provide consistent geometry across all disciplines, (3) be parametric, and (4) provide sensitivity derivatives. This paper will review the status of GMGG for analysis, design, and optimization processes, and it will focus on some emerging ideas that will advance the GMGG toward the ideal design environment.

Samareh, Jamshid A.↗