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At least 1,675 records · Page 93

Cluster-dynamics-based parameterization for sulfuric acid–dimethylamine nucleation: comparison and selection through box and three-dimensional modeling

Clustering of gaseous sulfuric acid (SA) enhanced by dimethylamine (DMA) is a major mechanism for new particle formation (NPF) in polluted atmospheres. However, uncertainty remains regarding the SA–DMA nucleation parameterization that reasonably represents cluster dynamics and is applicable across various atmospheric conditions. This uncertainty hinders accurate three-dimensional (3-D) modeling of NPF and the subsequent assessment of its environmental and climatic impacts. Here we extensively compare different cluster-dynamics-based parameterizations for SA–DMA nucleation and identify the most reliable one through a combination of box model simulations, 3-D modeling, and in situ observations. Results show that the parameterization derived from Atmospheric Cluster Dynamic Code (ACDC) simulations, incorporating the latest theoretical insights (DLPNO-CCSD(T)/aug-cc-pVTZ//ωB97X-D/6-311++G(3df,3pd) level of theory) and adequate representation of cluster dynamics, exhibits dependable performance in 3-D NPF simulation for both winter and summer conditions in Beijing and shows promise for application in diverse atmospheric conditions. Another ACDC-derived parameterization, replacing the level of theory with RI-CC2/aug-cc-pV(T+d)Z//M06-2X/6–311++G(3df,3pd), also performs well in NPF modeling at relatively low temperatures around 280 K but exhibits limitations at higher temperatures due to inappropriate representation of SA–DMA cluster thermodynamics. Additionally, a previously reported parameterization incorporating simplifications is applicable for simulating NPF in polluted atmospheres but tends to overestimate particle formation rates under conditions of elevated temperature (>∼300 K) and low-condensation sink (<∼3×10 -3 s −1 ). Our findings highlight the applicability of the new ACDC-derived parameterization, which couples the latest SA–DMA nucleation theory and holistic cluster dynamics, in 3-D NPF modeling. The ACDC-derived parameterization framework provides a valuable reference for developing parameterizations for other nucleation systems.

Shen, Jiewen↗

Far-Field Acoustic Power Level and Performance Analyses of F31/A31 Open Rotor Model at Simulated Scaled Takeoff, Nominal Takeoff, and Approach Conditions: Technical Report I

Far-field acoustic power level and performance analyses of open rotor model F31/A31 have been performed to determine its noise characteristics at simulated scaled takeoff, nominal takeoff, and approach flight conditions. The nonproprietary parts of the data obtained from experiments in 9- by 15-Foot Low-Speed Wind Tunnel (915 LSWT) tests were provided by NASA Glenn Research Center to perform the analyses. The tone and broadband noise components have been separated from raw test data by using a new data analysis tool. Results in terms of sound pressure levels, acoustic power levels, and their variations with rotor speed, angle of attack, thrust, and input shaft power have been presented and discussed. The effect of an upstream pylon on the noise levels of the model has been addressed. Empirical equations relating model's acoustic power level, thrust, and input shaft power have been developed. The far-field acoustic efficiency of the model is also determined for various simulated flight conditions. It is intended that the results presented in this work will serve as a database for comparison and improvement of other open rotor blade designs and also for validating open rotor noise prediction codes.

Prop-Fan Technology↗

Constructing a Simulation Surrogate with Partially Observed Output

Gaussian process surrogates are a popular alternative to directly using computationally expensive simulation models. When the simulation output consists of many responses, dimension-reduction techniques are often employed to construct these surrogates. However, surrogate methods with dimension reduction generally rely on complete output training data. This article proposes a new Gaussian process surrogate method that permits the use of partially observed output while remaining computationally efficient. The new method involves the imputation of missing values and the adjustment of the covariance matrix used for Gaussian process inference. The resulting surrogate represents the available responses, disregards the missing responses, and provides meaningful uncertainty quantification. In conclusion, the proposed approach is shown to offer sharper inference than alternatives in a simulation study and a case study where an energy density functional model that frequently returns incomplete output is calibrated.

42 ENGINEERING↗

Three-dimensional model of intracellular and intercellular Ca2+ waves propagation in endothelial cells

Highlights: • Image-based 3D simulation model for intercellular and intracellular Ca{sup 2+} waves. • Metabolic reactions were divided into membrane and cytoplasm domains. • Ca{sup 2+} and IP{sub 3} diffused across the cell and gap junctions. • Ca{sup 2+} waves are propagated from focal stimulated point in numerical simulation. • Ca{sup 2+} wave speed was in agreement with those from cell culture experiments. Intracellular and intercellular Ca{sup 2+} waves play key roles in cellular functions, and focal stimulation triggers Ca{sup 2+} wave propagation from stimulation points to neighboring cells, involving localized metabolism reactions and specific diffusion processes. Among these, inositol 1,4,5-trisphosphate (IP{sub 3}) is produced at membranes and diffuses into the cytoplasm to release Ca{sup 2+} from endoplasmic reticulum (ER). In this study, we developed a three-dimensional (3D) simulation model for intercellular and intracellular Ca{sup 2+} waves in endothelial cells (ECs). 3D model of 2 cells was reconstructed from confocal microscopic images and was connected via gap junctions. Cells have membrane and cytoplasm domains, and metabolic reactions were divided into each domain. Finally, the intracellular and intercellular Ca{sup 2+} wave propagations were induced using microscopic stimulation and were compared between numerical simulations and experiments. The experiments showed that initial sharp increases in intracellular Ca{sup 2+} occurred approximately 0.3 s after application of stimuli. In addition, Ca{sup 2+} wave speeds remained constant in cells, with intracellular and intercellular speeds of approximately 35 and 15 μm/s, respectively. Simulations indicated initial increases in Ca{sup 2+} concentrations at points of stimulation, and these were then propagated across stimulated and neighboring cells. In particular, initial rapid increases in intracellular Ca{sup 2+} were delayed and subsequent intracellular and intercellular Ca{sup 2+} wave speeds were approximately 25 and 12 μm/s, respectively. Simulation results were in agreement with those from cell culture experiments, indicating the utility of our 3D model for investigations of intracellular and intercellular messaging in ECs.

60 APPLIED LIFE SCIENCES↗

Conceptual and Mathematical Foundation for the FE/NETL CO 2 Prophet Model for Simulating CO 2 Enhanced Oil Recovery, Version 2

The United States (U.S.) Department of Energy (DOE) Office of Fossil Energy (FE) at the National Energy Technology Laboratory (NETL) has developed the FE/NETL CO 2 Prophet Model, which is Version 2 of CO 2 Prophet. This document describes the mathematical foundation for the FE/NETL CO 2 Prophet Model. CO 2 Prophet was originally developed in the 1990s by Texaco Exploration and Production and Technology Department for DOE. The FE/NETL CO 2 Prophet Model is an oil reservoir simulator that is suitable for simulating water floods and supercritical carbon dioxide (CO 2 ) enhanced oil recovery (EOR). The FE/NETL CO 2 Prophet Model uses a number of assumptions to simplify the equations describing the flow of oil, water (or brine), and CO 2 in the oil reservoir.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Simulation and Modeling of Cold-Wall Hypersonic Turbulent Boundary Layers on Flat Plate

Direct numerical simulations (DNS) of flat-plate, zero-pressure-gradient turbulent boundary layers are presented for nominal freestream Mach numbers of 11 and 14 and a highly cooled wall (wall-to-recovery temperature of approximately 0.2). The flow conditions of the DNS are representative of the experimental data for a Mach 11.1 turbulent boundary layer on a flat plate that was tested at Calspan–University of Buffalo Research Center (CUBRC) and the operational conditions of the AEDC Hypervelocity Tunnel No. 9 at Mach 14. The wall shear stress and turbulent heat flux predicted by DNS show good comparisons with those measured at CUBRC and those modeled with a Baldwin-Lomax model. The generated DNS database extends the range of Reynolds numbers from those typical of previous DNS studies for hypersonic boundary-layer flows and confirms the validity of Morkovin’s hypothesis within the relatively broader range of Reynolds numbers considered in this study. A priori assessment of turbulent heat flux models with DNS data shows that the algebraic energy flux (AEF) formulation gives better predictions of the streamwise turbulent heat flux than the commonly used constant turbulent Prandtl number model while both models give similarly good predictions of the wall-normal turbulent heat flux. A posteriori assessment shows that the AEF model improves the prediction of the temperature profiles while keeping a good prediction of the velocity field.

Junji Huang↗

Combining geometric-optical and spectral invariants theories for modeling canopy fluorescence anisotropy

The spectral invariants theory ( p -theory) has received much attention in the field of quantitative remote sensing over the past few decades and has been adopted for modeling of canopy solar-induced chlorophyll fluorescence (SIF). However, the spectral invariant properties (SIP) in simple analytical formulae have not been applied for modeling canopy fluorescence anisotropy primarily because they are parameterized in terms of leaf total scattering, which precludes the differentiation between forward and backward leaf SIF emissions. In this study, we have developed the canopy-SIP SIF model by combining geometric-optical (GO) theory to account for asymmetric leaf SIF forward and backward emissions at the first-order scattering and by modeling multiple scattering based on the p-theory, thus avoiding the dependence on radiative transfer models. The applicability of the model simulations especially over 3D heterogeneous canopies was improved by incorporating canopy structure through multi-angular clumping index, and by modeling single scattering from the four components of the scene in view according to the GO approach. The results show good consistency with both the state-of-the-art SIF models and multi-angular field SIF observations over grass and chickpea canopies. Further, the coefficient of determination (R²) between the simulated SIF and field measurements was 0.75 (red) and 0.74 (far-red) for chickpea, and 0.65 (both red and far-red) for grass. The average relative error was approximately 3% for 1D homogeneous scenes when comparing the canopy-SIP SIF model simulations to the SCOPE model simulations, and around 4% for the 3D heterogeneous scene when comparing to the LESS model simulations. The results indicate that the proposed approach for separating asymmetric leaf SIF emissions is a robust way to keep a balance between satisfactory simulation accuracy and efficiency. Model simulations suggest that neglecting the leaf SIF asymmetry can lead to an underestimation of canopy red SIF by 6.3% to 42.6% for various leaf biochemical and canopy structural parameters. This study presents a simple but efficient analytical approach for canopy fluorescence modeling, with potential for large-scale canopy fluorescence simulations.

3D heterogeneous structure↗

Utilization of municipal wastewater for cooling in thermoelectric power plants

A process simulation model has been developed using Aspen Plus® with the OLI (OLI System, Inc.) water chemistry model to predict water quality in the recirculating cooling loop utilizing secondary- and tertiary-treated municipal wastewater as the source of makeup water. Simulation results were compared with pilot-scale experimental data on makeup water alkalinity, loop pH, and ammonia evaporation. The effects of various parameters including makeup water quality, salt formation, NH 3 and CO 2 evaporation mass transfer coefficients, heat load, and operating temperatures were investigated. The results indicate that, although the simulation model can capture the general trends in the loop pH, experimental data on the rates of salt precipitation in the system are needed for more accurate prediction of the loop pH. It was also found that stripping of ammonia and carbon dioxide in the cooling tower can influence the cooling loop pH significantly. The effects of the NH 3 mass transfer coefficient on cooling loop pH appear to be more significant at lower values (e.g., k NH3 < 4×10 -3 m/s) when the makeup water alkalinity is low (e.g., <90 mg/L as CaCO 3 ). The effect of the CO2 mass transfer coefficient was found to be significant only at lower alkalinity values (e.g., k CO2 <4×10 -6 m/s).

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Modeling and Simulation - Virtual

The purpose of this report is to describe the body of work I have produced as a NASA Office of Science Technology Engineering and Math (OSTEM) intern in the Fall 2020 semester. My mentor during this session was Antonio Pego and my main task was to research and develop solutions in augmented and virtual reality technologies for use in training simulations. A main focus of this project was the development of human models for use in the game engine, with the purpose of creating simulations that would help with realistic analysis of tasks that will be performed by personnel. A steep learning curve had to be tackled in order to learn and catch up with current MR technologies. Along the way I created documentation of the different techniques utilized to support future continuation of the project.

Peter Leroy Santana Rodriguez↗

A Global System for Transportation Simulation and Visualization in Emergency Evacuation Scenarios

Simulation-based studies are frequently used for evacuation planning and decision making processes. Given the transportation systems complexity and data availability, most evacuation simulation models focus on certain geographic areas. With routine improvement of OpenStreetMap road networks and LandScanTM global population distribution data, we present WWEE, a uniform system for world-wide emergency evacuation simulations. WWEE uses unified data structure for simulation inputs. It also integrates a super-node trip distribution model as the default simulation parameter to improve the system computational performance. Two levels of visualization tools are implemented for evacuation performance analysis, including link-based macroscopic visualization and vehicle-based microscopic visualization. For left-hand and right-hand traffic patterns in different countries, the authors propose a mirror technique to experiment with both scenarios without significantly changing traffic simulation models. Ten cities in US, Europe, Middle East, and Asia are modeled for demonstration. With default traffic simulation models for fast and easy-to-use evacuation estimation and visualization, WWEE also retains the capability of interactive operation for users to adopt customized traffic simulation models. For the first time, WWEE provides a unified platform for global evacuation researchers to estimate and visualize their strategies performance of transportation systems under evacuation scenarios.

Emergency Evacuation↗

Antarctic ice sheet model comparison with uncurated geological constraints shows that higher spatial resolution improves deglacial reconstructions

Accurately reconstructing past changes to the shape and volume of the Antarctic ice sheet relies on the use of physically based and thus internally consistent ice sheet modeling, benchmarked against spatially limited geologic data. The challenge in model benchmarking against geologic data is diagnosing whether model-data misfits are the result of an inadequate model, inherently noisy or biased geologic data, and/or incorrect association between modeled quantities and geologic observations. In this work we address this challenge by (i) the development and use of a new model-data evaluation framework applied to an uncurated data set of geologic constraints, and (ii) nested high-spatial-resolution modeling designed to test the hypothesis that model resolution is an important limitation in matching geologic data. While previous approaches to model benchmarking employed highly curated datasets, our approach applies an automated screening and quality control algorithm to an uncurated public dataset of geochronological observations (specifically, cosmogenic-nuclide exposure-age measurements from glacial deposits in ice-free areas). This optimizes data utilization by including more geological constraints, reduces potential interpretive bias, and allows unsupervised assimilation of new data as they are collected. We also incorporate a nested model framework in which high-resolution domains are downscaled from a continent-wide ice sheet model. We highlight the application of this framework by applying these methods to a small ensemble of deglacial ice-sheet model simulations, and demonstrate that the nested approach improves the ability of model simulations to match exposure age data collected from areas of complex topography and ice flow. We develop a range of diagnostic model-data comparison metrics to provide more insight into model performance than possible from a single-valued misfit statistic, showing that different metrics capture different aspects of ice sheet deflation.

Geosciences↗

Improved Models for Simulation of Cryogenic Spray Cooling for Propellant Tank Chilldown

This paper presents advances in spray boiling models for cryogenic fluids that exhibit strong variation in thermodynamic properties; it accounts for the interaction of the spray droplets with walls and the complex heat transfer and boiling processes that play a vital role in chilling solid surfaces. The model has been developed by corroborating and validating it with test data in liquid nitrogen obtained at the University of Connecticut. The test data includes detailed visualization and plate temperature measurements for liquid nitrogen sprays impinging on a warm test plate and subsequent transient chilldown of the plate. Simulations of transient plate chilldown in liquid nitrogen were carried out and temperature histories at various locations on the plate were compared with test measurements to demonstrate the validity of the spray boiling models that have been developed for cryogens.

Boiling↗

Improved Models for Simulation of Cryogenic Spray Cooling for Propellant Tank Chilldown

This paper presents advances in spray boiling models for cryogenic fluids that exhibit strong variation in thermodynamic properties; it accounts for the interaction of the spray droplets with walls and the complex heat transfer and boiling processes that play a vital role in chilling solid surfaces. The model has been developed by corroborating and validating it with test data in liquid nitrogen obtained at the University of Connecticut. The test data includes detailed visualization and plate temperature measurements for liquid nitrogen sprays impinging on a warm test plate and subsequent transient chilldown of the plate. Simulations of transient plate chilldown in liquid nitrogen were carried out and temperature histories at various locations on the plate were compared with test measurements to demonstrate the validity of the spray boiling models that have been developed for cryogens.

Boiling↗

Aggregation of Inverter-Based Resources for Modeling and Simulation

In order to conduct system dynamic studies, it is necessary to have dynamic models of both inverter and plant levels. Detailed and aggregated modeling approaches are two essential options. The detailed modeling method involves capturing the dynamic characteristics of each individual device (e.g., wind turbine or PV array), as well as their interconnections. However, as the scale of the IBR plant increases, the complexity and computation time required for detailed modeling also increase. On the other hand, aggregated modeling offers a more efficient way of representing large-scale IBRs in power system dynamic studies. This approach involves aggregating a large number of wind turbines, PV arrays, inverters, and/or plant controllers into one or a smaller number of equivalent models. In order to analyze the impact of a high-level IBR penetration in power systems, it is important to develop accurate and computationally efficient models for both the detailed and aggregated methods.

14 SOLAR ENERGY↗

Effects of a simulated microgravity model on cell structure and function in rat testis and epididymis

The effect of simulated microgravity on the structure and function of the testis and epididymis cells was investigated in rats subjected to 7 days of tail suspension. Results of a histological examination revealed presence of disorganized seminiferous tubules and accumulation of large multinucleated cells and spermatids in the lumen of the epididymis. In addition, decreases in the content of testis protein and in testosterone levels in the testis, the interstitial fluid, and the epididymis were observed.

Hadley, Jill A.↗

Employing a Modified Diffuser Momentum Model to Simulate Ventilation of the Orion CEV (DRAFT)

Computational Fluid Dynamics (CFD) is used to model the flow field in the Orion CEV cabin. The CFD model employs a momentum model used to account for the effect of supply grilles on the supply flow. The momentum model is modified to account for non-uniform velocity profiles at the approach of the supply grille. The modified momentum model is validated against a detailed vane-resolved model before inclusion into the Orion CEV cabin model. Results for this comparison, as well as that of a single ventilation configuration are presented.

Straus, John↗

Bayesian optimization for inverse calibration of expensive computer models: A case study for Johnson-Cook model in machining

Inverse model calibration for identifying the constitutive model parameters can be computationally demanding for expensive-to-evaluate simulation models. Here, this paper presents a modified Bayesian optimization (BO) method, denoted as BO-bound, that incorporates theoretical bounds on the quantity of interest. A case study for the inverse calibration of the Johnson Cook (J-C) flow stress model parameters is presented using machining (cutting) force data. The results show fast calibration of the five J-C parameters within 25 simulations. In general, the BO-bound method is applicable for inverse calibration of any expensive simulation models as well as optimization problems with known bounds.

Bayesian optimization↗