Model atmospheres for O-type stars with ultraviolet line blanketing.
Surface gravity and temperature model atmospheres for O-type stars with UV line blanketing
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Surface gravity and temperature model atmospheres for O-type stars with UV line blanketing
This work traces the response of a granular material via the Ten Coefficient Truesdell rate-type constituitive model into the simplest meaningful loading: the triaxial test configuration. A functional relation has been posed for computing the rather peculiar relation between average applied stress and average porosity. Using that relation an attack has been mounted on the dilemma that exists between dynamic and constitutive use of the pressure variable; that is relating dynamic pressure, thermodynamic pressure, stress deviator and higher stress invariants. The resolution was as a linear superposition with a one-way feedback, in that while the dynamic component could not effect the constituitive component, the converse was not true since density appears in the momentum transport relation.
A new method for solving nonlinear heat and mass transfer design tasks was considered. Systems using the Number of Transfer Units (NTU) method are a special type of mathematical model of heat and mass exchangers. It was observed, that the NTU models in a form of differential-algebraic equations (DAEs) cannot be directly solved with higher values of NTU. The requirements for consistent initial conditions, as well as numerical limitations of DAEs solvers, result, that the solution to the considered design problems that cannot be obtained by a classical direct shooting procedure. To overcome the presented difficulties, the αDAE model optimization algorithm was adjusted for solving NTU-based models. The new approach consists of 3 main steps: 1) task discretization by a multiple-shooting approach, 2) design an appropriate function $f_{NTU}$(α) to effectively influence the variability of the state variables described by dynamical relations, 3) the iterative numerical optimization algorithm for the new parametrized system. Moreover, computations can be performed by a chosen numerical optimization approach, which can be communicated with an available outer procedure for solving differential-algebraic equations. The presented algorithm was implemented and applied to solve the design task with the NTU model of a counter-flow exchanger. Here, the new approach was used to modify the system dynamics to influence the difficulty of the considered problem. Finally, the presented method enabled failure-free numerical computations for the higher values of the NTU parameter.
Historically, microbiological spaceflight requirements have been established in a subjective manner based upon expert opinion of both environmental and clinical monitoring results and the incidence of disease. The limited amount of data, especially from long-duration missions, has created very conservative requirements based primarily on the concentration of microorganisms. Periodic reevaluations of new data from later missions have allowed some relaxation of these stringent requirements. However, the requirements remain very conservative and subjective in nature, and the risk of crew illness due to infectious microorganisms is not well defined. The use of modeling techniques for microbial risk has been applied in the food and potable water industries and has exceptional potential for spaceflight applications. From a productivity standpoint, this type of modeling can (1) decrease unnecessary costs and resource usage and (2) prevent inadequate or inappropriate data for health assessment. In addition, a quantitative model has several advantages for risk management and communication. By identifying the variable components of the model and the knowledge associated with each component, this type of modeling can: (1) Systematically identify and close knowledge gaps, (2) Systematically identify acceptable and unacceptable risks, (3) Improve communication with stakeholders as to the reasons for resource use, and (4) Facilitate external scientific approval of the NASA requirements. The modeling of microbial risk involves the evaluation of several key factors including hazard identification, crew exposure assessment, dose-response assessment, and risk characterization. Many of these factors are similar to conditions found on Earth; however, the spaceflight environment is very specialized as the inhabitants live in a small, semi-closed environment that is often dependent on regenerative life support systems. To further complicate modeling efforts, microbial dose-response characteristics may be affected by a potentially dysfunctional crew immune system during a mission. In addition, microbial virulence has been shown to change under certain conditions during spaceflight, further complicating dose-response characterization. An initial study of the applicability of microbial risk assessment techniques was performed using Crew Health Care System (CHeCS) operational data from the International Space Station potable water systems. The risk of infection from potable water was selected as the flight systems and microbial ecology are well defined. This initial study confirmed the feasibility of using microbial risk assessment modeling for spaceflight systems. While no immediate threat was detected, the study identified several medically significant microorganisms that could pose a health risk if uncontrolled. The study also identified several specific knowledge gaps in making a risk assessment and noted that filling these knowledge gaps is essential as the risk estimates may change by orders of magnitude depending on the answers. The current phase of the microbial risk assessment studies focuses on the dose-response relationship of specific infectious agents, focusing on Salmonella enterica Typhimurium, Pseudomonas spp., and Escherichia coli, as their evaluation will provide a better baseline for determining the overall hazard characterization. The organisms were chosen as they either have been isolated on spacecraft or have an identified route of infection during a mission. The characterization will utilize dose-response models selected either from the peer-reviewed literature and/or by using statistical approaches. Development of these modeling and risk assessment techniques will help to optimize flight requirements and to protect the safety, health, and performance of the crew.
Two general types of numerical models for predicting microwave emission from soils are compared-coherent and noncoherent. In the former, radiation in the soil is treated coherently, and the boundary conditions on the electric fields across the layer boundaries are used to calculate the radiation intensity. In the latter, the radiation is assumed to be noncoherent, and the intensities of the radiation are considered directly. The results of the two approaches may be different because of the effects of interference, which can cause the transmitted intensity at the surface (i.e., emissivity) to be sometimes higher and sometimes lower for the coherent case than for the noncoherent case, depending on the relative phases of reflected fields from the lower layers. This coupling between soil layers in the coherent models leads to greater soil moisture sampling depths observed with this type of model, and is the major difference that is found between the two types of models. In noncoherent models, the emissivity is determined by the dielectric constraint at the air/soil interface. The subsequent differences in the results are functions of both the frequency of the radiation being considered and the steepness of the moisture gradient near the surface. The calculations were performed at frequencies of 1.4 and 19.4 GHz and for two sets of soil profiles. Little difference was observed between the models at 19.4 GHz; and only at the lower frequency were differences apparent because of the greater soil moisture sampling depth at this frequency.
The development of a general link between three dimensional wire frame models and rigid solid models is discussed. An interactive computer graphics program was developed to serve as a front end to an algorithm (COSMIC Program No. ARC-11446) which offers a general solution to the hidden line problem where the input data is either line segments of n-sided planar polygons of the most general type with internal boundaries. The program provides a general interface to CAD/CAM data bases and is implemented for models created on the Unigraphics VAX 11/780-based CAD/CAM systems with the display software written for DEC's VS11 color graphics devices.
Abstract Cement manufacturing is energy‐intensive (5Gj/t) and comprises a significant portion of the energy footprint of concrete systems. Incorporating modern monitoring, simulation and control systems will allow lower energy use, lower environmental impact, and lower costs of this widely used construction material. One of the goals of the CESMII roadmap project on the Smart Manufacturing of Cement included developing an analytical process model for clinker quality that includes the chemistry of the kiln feed and accounts for critical process variables. This predictive model will be used in nonlinear model predictive control system designed to significantly reduce process energy use while maintaining or improving product quality. In the cement manufacturing plant used in this study, the kiln feed (meal) is tested every 12 h and used to estimate the mineral composition of the cement kiln output (clinker) using the stoichiometry‐based Bogue's model and the expertise of the plant operators. During kiln operation, kiln output (clinker) is sampled and tested every 2 h to measure its chemical and mineral composition. The predicted and measured values of the clinker composition are used by the plant operators to adjust the kiln input stream and the production process characteristics to maintain stable operation and uniform product quality. However, the time delay between prediction and testing, along with inaccuracies inherent in the Bogue's model have made any process changes designed to minimize energy use problematic, especially in‐light of potential clinker quality issues that process changes often pose. A new analytical model that integrates quality information and process operation information has been developed from data collected from 2 years of production from an operating cement facility. To make the model fuel‐type‐independent, consumed heat energy was computed in the model instead of fuel type and amount. A Feedforward Network was trained and tailored from collected data. Many data‐based simulations were conducted to quantitatively evaluate the proposed model and the 5‐fold cross‐validation procedure was used to test the models. The resulting predictive model was shown to have a low root mean square error (MSE) with respect to the estimated clinker mineral composition compared to that using the industry standard “Bogue’ model”. The end goal of this work was to develop a single machine learning tool that allows the use of quality control data and process control variables to improve energy efficiency of the process in a continuous fashion. The proposed nonlinear model predictive control system (NMPC) can generate predicted kiln production characteristics based on manipulated variables in manner that accurately follows the target product quality values. Simulation results also show that the proposed model produced accurate predictions of kiln outputs that fell within the required constraints, while manipulating control variables within typical operational ranges.
We used historical data to build two types of model that predict Ground Delay Program implementation decisions and also produce insights into how and why those decisions are made. More specifically, we built behavioral cloning and inverse reinforcement learning models that predict hourly Ground Delay Program implementation at Newark Liberty International and San Francisco International airports. Data available to the models include actual and scheduled air traffic metrics and observed and forecasted weather conditions. We found that the random forest behavioral cloning models we developed are substantially better at predicting hourly Ground Delay Program implementation for these airports than the inverse reinforcement learning models we developed. However, all of the models struggle to predict the initialization and cancellation of Ground Delay Programs. We also investigated the structure of the models in order to gain insights into Ground Delay Program implementation decision making. Notably, characteristics of both types of model suggest that GDP implementation decisions are more tactical than strategic: they are made primarily based on conditions now or conditions anticipated in only the next couple of hours.
The development of high fidelity models of mechanical systems with flexible components is in flux. Many working models of these devices assume the elastic motion is small and can be superimposed on the overall rigid body motion. A drawback associated with this type of modeling technique is that it is required to regenerate the linear modal model of the device if the elastic motion is sufficiently far from the base rigid motion. An advantage to this type of modeling is that it uses NASTRAN modal data which is the NASA standard means of modal information exchange. A disadvantage to the linear modeling is that it fails to accurately represent large motion of the system, unless constant modal updates are performed. In this study, which is a continuation of a project started last year, the drawback of the currently used modal snapshot modeling technique is addressed in a rigorous fashion by novel and easily applied means.
Three sting-mounted winged-body models with tunnel blockages of 0.1, 1.0, and 2.0 percent were tested in the Lewis Research Center's 8- by 6- Foot Supersonic Wind Tunnel. Fuselage pressures were obtained over a Mach number range of 0.6 to 1.0 at angles of attack from 0 deg to 4 deg. Two other types of model support were investigated, which included simulated wing-tip and fuselage support-strut mountings. The effects of tunnel porosity and sidewall geometry were also investigated. Model blockage effects were small up to M sub 0 = 0.95. At higher speeds the major blockage effect observed was a displacement of the local transonic terminal shocks on the model. The effects of the wing-tip type of model support were small up to M sub 0 = 0.95, but disturbances were observed on the fuselage at higher speeds. Changes in local tunnel porosity were effective in reducing the disturbances up to M sub 0 = 0.975, but a change in sidewall geometry was not.
The behavior of novae may be divided roughly into two separate stages: quiescence and outburst. However, at closer inspection, both stages cannot be separated. It should be attempted to explain features in both stages with a similar model. Various simple models to explain the observed light and spectral observations during post optical maximum activity are conceivable. In instantaneous ejection models, all or nearly all material is ejected in a time that is short compared with the duration of post optical maximum activity. Instantaneous ejection type 1 models are those where the ejected material is in a fairly thin shell, the thickness of which remains small. In the instantaneous ejection type 2 model ('Hubble Flow'), a thick envelope is ejected instantaneously. This envelope remains thick as different parts have different velocities. Continued ejection models emphasize the importance of winds from the nova after optical maximum. Ejection is supposed to occur from one of the components of the central binary, and one can imagine a general swelling of one of the components, so that something resembling a normal, almost stationary, stellar photosphere is observed after optical maximum. The observed characteristics of recurrent novae in general are rather different from those of classical novae, thus, models for these stars need not be the same.
This dataset contains supporting documents and images for ESS-DIVE terrestrial model data archiving guidelines.Terrestrial models are broadly defined as numerical models that couple both land dynamics and energy, water, carbon, or nutrient fluxes. We created these guidelines based on input from the U.S. Department of Energy’s Biological and Environmental Research land modeling community. The guidelines are intended to help modelers determine which components of their terrestrial model data associated with publication should be archived. Based on input from the land modeling community, the guidelines recommend archiving both model input and testing data, as well as code, script, and metadata. The guidelines also recommend archiving model data output, depending on the limitations set by data repositories. Lastly, we provide recommendations for bundling data files for publication as well as a discussion about tools that can facilitate model data archiving and reuse.This dataset is an archive of the associated GitHub repository for our model archiving guidelines (https://github.com/ess-dive-community/essdive-model-data-archiving-guidelines). The ‘README.pdf’ file gives a general introduction to the guidelines, and the ‘instructions.pdf’ file provides more detailed steps for following the guidelines. We also provide 2 figures in this data package: 1) a decision tree (model_data_guidelines_decision_tree.png) that can help users determine which components of their model data to archive. and 2) the ‘model_data_guidelines_flmd.png’ file depicts the different files that can be archived in addition to the model data itself. Lastly, we include 3 digitized tables from our associated manuscript and 3 CSV files with anonymized input from DOE scientists about the importance of different aspects of model data archiving from which we developed the guidelines.Dataset updates for v1.1.0: We updated this data package on 2021-11-22 in response to review comments on our related manuscript. In this update we removed one figure so that the model archiving guidelines are conveyed in text rather than an image. We updated the file-level metadata (FLMD) figure to be in accord with the most recent FLMD recommendations. We made minor edits to the README file to update the recommended citation and added two co-authors. We also added 6 new data files (3 are anonymized input from DOE scientists that helped to inform guidelines, and 3 are digitized tables from our manuscript.
A hierarchy of steady, nonlinear, semianalytic models of different types of convection were produced. These provide a theoretical framework for determining cloud outflow fluxes of both dynamic and thermodynamic quantities, which can be used to formulate dynamical transports in parameterization schemes. This was achieved by exploiting certain Lagrangian conservation properties of steady flow, from which an equation for the vertical displacement of particles can be obtained and the outflow entropy, energy and momentum fluxes and the infow/outflow mass fluxes can be determined from solution to the equation. These fluxes are determined in terms of grid scale parameters such as convective available potential energy (CAPE), cloud layer shear, and horizontal pressure gradients. Five main types of system models are identified, respectively representing archtypes of convection in zero shear, large shear, midlatitude squall lines, tropical squall lines and cellular convection. The downdraught is an important aspect in the first four of these and the cloud scale transport of momentum is very distinctive.
A critical mechanical system in advanced hypersonic engines is the panel-edge seal system that seals gaps between the articulating horizontal engine panels and the adjacent engine splitter walls. Significant advancements in seal technology are required to meet the extreme demands placed on the seals, including the simultaneous requirements of low leakage, conformable, high temperature, high pressure, sliding operation. In this investigation, the seal concept design and development of two new seal classes that show promise of meeting these demands will be presented. These seals include the ceramic wafer seal and the braided ceramic rope seal. Presented are key elements of leakage flow models for each of these seal types. Flow models such as these help designers to predict performance-robbing parasitic losses past the seals, and estimate purge coolant flow rates. Comparisons are made between measured and predicted leakage rates over a wide range of engine simulated temperatures and pressures, showing good agreement.
Stress rupture is a failure mechanism where failures can occur after a period of time, even though the material has seen no increase in load. Carbon/epoxy composite materials have demonstrated the stress rupture failure mechanism. In a previous work, a model was proposed for stress rupture of composite overwrap pressure vessels (COPVs) and similar composite structures based on strength degradation. However, the original model was limited to constant load periods (holds) at constant load. The model was expanded in this paper to address arbitrary loading histories and specifically the inclusions of ramp loadings up to holds and back down. The broadening of the model allows for failures on loading to be treated as any other failure that may occur during testing instead of having to be treated as a special case. The inclusion of ramps can also influence the length of the "safe period" following proof loading that was previously predicted by the model. No stress rupture failures are predicted in a safe period because time is required for strength to decay from above the proof level to the lower level of loading. Although the model can predict failures during the ramp periods, no closed-form solution for the failure times could be derived. Therefore, two suggested solution techniques were proposed. Finally, the model was used to design an experiment that could detect the difference between the strength decay model and a commonly used model for stress rupture. Although these types of models are necessary to help guide experiments for stress rupture, only experimental evidence will determine how well the model may predict actual material response. If the model can be shown to be accurate, current proof loading requirements may result in predicted safe periods as long as 10(13) years. COPVs design requirements for stress rupture may then be relaxed, allowing more efficient designs, while still maintaining an acceptable level of safety.
We perform wall-modeled large eddy simulations (WMLES) of turbulent flow over a Gaussian-shaped bump geometry, to assess its performance in the acceleration and separation regions of the flow. An unstructured finite-volume solver is used along with an equilibrium wall model. The Mach number of the oncoming flow selected for the simulation is 0.176, and two Reynolds numbers (Re) are simulated that are about 10000 and 36000 based on boundary layer thickness upstream of the bump. Spanwise periodic results for the lower Re case are compared with the available DNS data, while the full three-dimensional simulation results for the higher Re case are compared to available experimental data. Sensitivity of WMLES results are assessed for a number of factors including grid resolution, wall model exchange location, type of wall model, and unstructured grid topology. The WMLES results for the lower Re case agree well with available DNS data in terms of the wall pressure variation, velocity and turbulent stress profile comparisons. The skin-friction predictions show a reduced tendency to separate. This appears to be accentuated for the higher Re case, for the medium resolution grid used in this study, where WMLES does not predict any flow separation in the mean, which is in contrast to the large separation bubble observed in the experiments.
Currently, when the Reynolds-Averaged Navier-Stokes (RANS) equations are solved using turbulence modeling, most often the one-equation model of Spalart and Allmaras is used. Then, it is only necessary to solve the RANS equations in conjunction with a single transport equation for modeling turbulence. For this model, considerable assessment and analysis has been performed, allowing the possibility of a reliable solution method for an eddy viscosity required to compute the Reynolds stresses in the RANS equations. Such evaluation along with analysis has not been achieved to realize similar performance with two-equation models of the k-w type. The primary objective of this paper is to present and discuss the components of an effective numerical algorithm for solving the RANS equations and the two transport equations of k-w type turbulence models. All the important details of the turbulence model as actually implemented are given, which is sometimes not done in various papers considering such modeling. The viability and effectiveness of this solution algorithm are demonstrated by solving both two-dimensional and three-dimensional aerodynamic flows. In all applications, a linear rate of convergence without oscillations or other evidence of unstable behavior is observed. This behavior is also particularly true when the proposed algorithm is applied to systematically renewed mesh sequences, which is generally not observed with algorithms solving more than one transport equation. Thus, numerical integration errors are systematically reduced, allowing for a significantly more reliable assessment of the effectiveness of the turbulence model. Additionally, in this paper, analysis of the solution algorithm, including linear stability, is also performed for a particular flow problem.
An investigation was made of the static, wind-on aerodynamic and static noise characteristics of an augmentor wing having lobe type nozzles. The study was made in the Ames 7-by 10-Foot No. 1 Wind Tunnel using a small-scale, quasi-two-dimensional model. Several configurations of lobe nozzles as well as a normal slot nozzle were tested. Results indicate that lobe nozzles offer improved static and wind-on aerodynamics and reduced static noise relative to slot nozzles. Best wind-on performance was obtained when the tertiary gap was closed even though the static thrust augmentation was maximum with the gap open. Static thrust augmentation, wind-on lift and drag, and static noise directivity are presented as well as typical static and wind-on exit velocity profiles, surface pressure distributions and noise spectrums. The data are presented with limited discussion.