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DOE OSTI2020

Elliptic flow coalescence to identify the $f_0$(980) content

Here we use a simple coalescence model to generate $f_0$(980) particles for three configurations: a $s\bar{s}$ meson, a $u\bar{u}s\bar{s}$ tetraquark, and a $K^+K^–$ molecule. The phase-space information of the coalescing constituents is taken from a multiphase transport (AMPT) simulation of heavy-ion collisions. It is shown that the number of constituent quarks scaling of the elliptic flow anisotropy can be used to discern $s\bar{s}$ from $u\bar{u}s\bar{s}$ and $K^+K^–$ configurations.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

NASA NTRS1983

Further development of a method for computing three-dimensional subsonic viscous flows in turbofan lobe mixers

Procedure for computing subsonic, turbulent flow in turbofan lobe mixers was extended to allow consideration of flow fields in which a swirl component of velocity may be present. Additional, an optional k-lambda turbulence model was added to the procedure. The method of specifying the initial flow field was also modified, allowing parametric specification or radial secondary flow velocities, and making it possible to consider initial flow fields which have significant inlet secondary flow vorticity. A series of example calculations was performed which demonstrate the various capabilities of the modified code. These calculations demonstrate the effects of initial secondary flows of various magnitudes, the effects of swirl, and the effects of turbulence model on the mixing process. The results of these calculations indicate that the initial secondary flows, presumed to be generated within the lobes, play a dominant role in the mixing process, and that the predicted results are relatively insensitive to the turbulence model used.

Lin, S. J.↗

DOE OSTI2023

Understanding How Reservoir Operations Influence Methane Emissions: A Conceptual Model

Because methane is a potent greenhouse gas (GHG), understanding controls on methane emissions from reservoirs is an important goal. Yet, reservoirs are complex ecosystems, and mechanisms by which reservoir operations influence methane emissions are poorly understood. In part, this is because emissions occur in ‘hot spots’ and ‘hot moments’. In this study, we address three research questions, ‘What are the causal pathways through which reservoir operations and resulting water level fluctuations (WLF) influence methane emissions?’; ‘How do influences from WLF differ for seasonal drawdown and diurnal hydropeaking operations?’; and ‘How does understanding causal pathways inform practical options for mitigation?’. A graphical conceptual model is presented that links WLF in reservoirs to methane emissions via four causal pathways: (1) water-column mixing (2) drying–rewetting cycles, (3) sediment delivery and redistribution, and (4) littoral vegetation. We review what is known about linkages for WLF at seasonal and diurnal resolutions generate research questions, and hypothesize strategies for moderating methane emissions by interrupting each causal pathway. Those related to flow management involve basin-scale management of tributary flows, seasonal timing of hydropeaking (pathway #1), timing and rates of drawdown (pathway #2). In addition, we describe how sediment (pathway #3) and vegetation management (pathway #4) could interrupt linkages between WLF and emissions. We demonstrate the strength of conceptual modeling as a tool for generating plausible hypotheses and suggesting mitigation strategies. Future research is needed to develop simpler models at appropriate timescales that can be validated and used to manage flow releases from reservoirs.

13 HYDRO ENERGY↗

NASA NTRS1989

Aerodynamic stability and heating analyses for the aeroassist flight experiment vehicle

Since ground based flow simulations are presently unable to model flight conditions expected for AOTVs (Aeroassist Orbital Transfer Vehicle) and other hypersonic space vehicles, computer codes are being developed to provide design parameters necessary for structure, guidance, and control aspects. Over the past four years, VRFLO (Viscous Reactive Flow) has been written to model finite-rate chemistry and viscous effects for a variety of aerobrake bodies. VRFLO includes a number of unique features that are summarized as follows: (1) Grid generation is an integral part of the code for several aerobrake configurations which includes the wake flow region; (2) The formulation is valid for three air chemical models; (3) An ADI central difference technique is used to solve the Navier-Stokes and species continuity equations in split groups; and (4) Grid density and numerical damping are minimized by shock-fitting and conformal mapping of body points.

Mcgary, J.↗

DOE OSTI2021

Methane Hydrate Formation and Evolution During Sedimentation

We explored methane hydrate formation with sedimentation with a newly developed one-dimensional, multiphase flow, multicomponent transport numerical model. Our model couples methane hydrate formation from in situ microbial methane generation within the hydrate stability zone (HSZ), methane recycling, and microbial methane generation below the base of the hydrate stability zone (BHSZ). Both recycled methane and deeply generated methane are transported into the HSZ by buoyancy-driven free gas flow. Free gas flows through the HSZ by both the processes of capillary-dependent pore fillings and by salt exclusion during hydrate formation, with the former being the dominant mechanism. We quantitively illustrated the formation of enriched hydrate in muddy sediments above, and interconnected free gas below, the BHSZ, which are common features along the world's continental margin. In addition, we showed two ways to form concentrated methane hydrate above the BHSZ. The first mechanism is local free gas flow during methane recycling. This happens at sites with sufficient methane generation above the BHSZ. The second mechanism is deep microbial methane generation which is transported into the HSZ by free gas flow. This mechanism plays a more important role at sites with high sedimentation rates. This study provides new insights into methane hydrate formation and distribution below the seafloor. It is important for understanding the carbon cycle and carbon storage below the seafloor and for resource evaluation and exploitation.

58 GEOSCIENCES↗

NASA NTRS1994

Inducer analysis/pump model development

Current design of high performance turbopumps for rocket engines requires effective and robust analytical tools to provide design information in a productive manner. The main goal of this study was to develop a robust and effective computational fluid dynamics (CFD) pump model for general turbopump design and analysis applications. A finite difference Navier-Stokes flow solver, FDNS, which includes an extended k-epsilon turbulence model and appropriate moving zonal interface boundary conditions, was developed to analyze turbulent flows in turbomachinery devices. In the present study, three key components of the turbopump, the inducer, impeller, and diffuser, were investigated by the proposed pump model, and the numerical results were benchmarked by the experimental data provided by Rocketdyne. For the numerical calculation of inducer flows with tip clearance, the turbulence model and grid spacing are very important. Meanwhile, the development of the cross-stream secondary flow, generated by curved blade passage and the flow through tip leakage, has a strong effect on the inducer flow. Hence, the prediction of the inducer performance critically depends on whether the numerical scheme of the pump model can simulate the secondary flow pattern accurately or not. The impeller and diffuser, however, are dominated by pressure-driven flows such that the effects of turbulence model and grid spacing (except near leading and trailing edges of blades) are less sensitive. The present CFD pump model has been proved to be an efficient and robust analytical tool for pump design due to its very compact numerical structure (requiring small memory), fast turnaround computing time, and versatility for different geometries.

Cheng, Gary C.↗

DOE OSTI2021

Robust Distributed State Estimator for Interconnected Transmission and Distribution Networks (Final Report RPPR-1)

This project’s objective is to develop a combined transmission and distribution state estimator which accounts for very large system size and model complexity (by way of distributing the computations) and large number of solar PV units connected to the distribution system on multiple feeders. The project not only provides a robust formulation and solution to this problem but also tests the solution by implementing it on a well-established large utility system. It introduces several improvements with respect to the state of the art in existing state estimation software: (a) The developed state estimator (SE) allows robust and accurate monitoring of bidirectional flows in distribution systems which result due to the distributed energy sources which are not observable and thus not incorporated in generation dispatch; (b) Large utility systems with tens of thousands of transmission buses and hundreds of thousands of distribution nodes are difficult to model as a single integrated system. This shortcoming is addressed by developing a “scalable distributed computational framework” which allows splitting the ultra large system models into several small subsystems and coordinating their solution by a robust and practical state estimation formulation; (c) Measurement errors irrespective of their locations are detected and removed by the developed state estimator. Historically, transmission and distribution systems were analyzed and operated as two independent systems. Given the non-transposed short feeder sections, unevenly loaded phases, strictly radial configuration and unidirectional power flows in the absence of remote generation, distribution system analysis was customized to account for these characteristics. However, some of these assumptions are no longer valid (non-radial configuration, bidirectional power flows) and thus distribution system analysis should be revisited. Furthermore, in the past, the interaction between the transmission and distribution systems was quite passive, where distribution substations were modeled as lumped loads in the transmission system model. With substantial generation injected by renewable generation located in the distribution systems, such modeling will no longer be accurate. The developed state estimator facilitates proper monitoring of the interactions between the transmission and distribution systems and enables smart dispatch of these units which are made observable by the state estimator.

24 POWER TRANSMISSION AND DISTRIBUTION↗

NASA NTRS1974

The ratio of specific heats for postshock plasmas of a detached bow shock - An MHD model

The empirical relationship between the standoff distance of a detached bow shock (generated by the flow of a supersonic gas past an impenetrable obstacle), the size of the obstacle, the Mach number of the gas, and the ratio of specific heats has been generalized to include the magnetic field. The value of the ratio of specific heats (gamma-prime) in the postshock plasma has been calculated in terms of the preshock Alfvenic and sonic Mach numbers and orientation of the magnetic field. The empirical relationship is further generalized by taking into consideration the normal momentum and energy flux due to waves and/or turbulence and/or heat flow in association with high Mach number shocks. The computed value of gamma prime is substantially modified in comparison with that given by the MHD or the gas dynamic model. For this generalized model the computed gamma prime can be considered to be a more precise thermodynamic quantity, since the macroscopic parameters of the plasma have been separated out. Application of this empirical relationship to the earth's bow shock has been given.

Chao, J. K.↗

DOE OSTI2025

Computational Algorithms for Unit Commitment with AC Power Flows (Final Report)

Security-constrained unit commitment (SCUC) is a key component in power system operations. When AC power flow constraints are considered in the SCUC model (AC-SCUC), the problem becomes extremely difficult due to its discrete and non-convex nature, as described in “Grid Optimization Competition Challenge 3 Problem Formulation (GOCC)”. There are four main challenges: (i) Discrete decisions regarding unit online/offline status and start-up/shut-down procedures for every single unit. The number of discrete decision variables increases considerably when a system integrates multiple generators; (ii) Configuration-based combined-cycle formulations, and multi-commodity models that include ramping products, spin/non-spin products, and regulation up/down products. The combined-cycle units introduce additional discrete decision variables and auxiliary service products further complicate the model by connecting multi-commodity products’ continuous and discrete variables; (iii) SCUC models with AC power flow constraints are far more complex due to massive bilinear terms in the large-scale nonlinear power balance equations. The nonlinear power balance equations are further complicated by the discrete step control variables of shunts; (iv) N − 1 contingency analysis. The size of the model increases linearly with the number of contingencies considered, greatly increasing the size of the optimization model. Accordingly, there is an emergent need to develop a robust algorithm capable of deriving a high-quality solution in a short time and passing through contingency tests simultaneously. In this project, we explore innovative techniques to address this challenging problem by integrating advanced polyhedral theory, approximation methods, relaxation strategies, decomposition techniques, and parallel computing. Each technique approaches the problem from a different perspective, leveraging its specific strengths to tackle distinct challenges. Each individual method has demonstrated its effectiveness in the PI’s previous research. Their integration is expected to significantly reduce the computational time required to solve the proposed complex problem. Successful completion of this project has the potential to transform the industry by enhancing optimization solvers capable of handling large-scale day-ahead energy market clearing models within strict time constraints, while incorporating AC power flow constraints. This advancement will lead to reduced overall generation costs and, consequently, increased social welfare.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

NASA NTRS2004

NASA Multidimensional Stirling Convertor Code Developed

A high-efficiency Stirling Radioisotope Generator (SRG) for use on potential NASA Space Science missions is being developed by the Department of Energy, Lockheed Martin, Stirling Technology Company, and the NASA Glenn Research Center. These missions may include providing spacecraft onboard electric power for deep space missions or power for unmanned Mars rovers. Glenn is also developing advanced technology for Stirling convertors, aimed at substantially improving the specific power and efficiency of the convertor and the overall power system. Performance and mass improvement goals have been established for second- and third-generation Stirling radioisotope power systems. Multiple efforts are underway to achieve these goals, both in house at Glenn and under various grants and contracts. These efforts include the development of a multidimensional Stirling computational fluid dynamics code, high-temperature materials, advanced controllers, an end-to-end system dynamics model, low-vibration techniques, advanced regenerators, and a lightweight convertor. Under a NASA grant, Cleveland State University (CSU) and its subcontractors, the University of Minnesota (UMN) and Gedeon Associates, have developed a twodimensional computer simulation of a CSUmod Stirling convertor. The CFD-ACE commercial software developed by CFD Research Corp. of Huntsville, Alabama, is being used. The CSUmod is a scaled version of the Stirling Technology Demonstrator Convertor (TDC), which was designed and fabricated by the Stirling Technology Company and is being tested by NASA. The schematic illustrates the structure of this model. Modeled are the fluid-flow and heat-transfer phenomena that occur in the expansion space, the heater, the regenerator, the cooler, the compression space, the surrounding walls, and the moving piston and displacer. In addition, the overall heat transfer, the indicated power, and the efficiency can be calculated. The CSUmod model is being converted to a two-dimensional model of the TDC at NASA Glenn. Validation of the multidimensional Stirling code is an important part of the grant effort. UMN has been generating data in an oscillating-flow test facility using two different test sections: a 90 turn and a cooler/regenerator/heater test section. CSU has created computational fluid dynamics models of both these test sections and has been making comparisons with the data, then improving their models to improve the agreement with the test data. CSU has also been using data available in the literature for code validation. UMN is now preparing to begin fabrication of a new 180 turn test section that will be more representative of certain portions of the Stirling engine geometry. Simulations to almost periodic steady state with the two-dimensional CSUmod model indicate that, to reach periodic steady state on a single 2-GHz desktop computer, 75 to 100 complete simulation cycles would be required and between 1 and 2 months of computer time. Therefore, Glenn has purchased the first 8 computers, of a 64-computer cluster, to be run in parallel to accelerate the simulation. On the basis of CFD Research Corp.'s experience with running the parallelized version of CFD-ACE on their clusters, we estimate that the complete 64-computer cluster will reduce simulation computing time by a factor of about 40. Plans are to continue development of these multidimensional Stirling codes and to use them to study the fluid-flow and heat-transfer phenomena that occur inside Stirling convertors. This is expected to lead to improved thermodynamic loss understanding, onedimensional design and performance codes, and engine performance.

Tew, Roy C.↗

DOE OSTI2022

Finding Hidden Patterns in High Resolution Wind Flow Model Simulations

Wind flow data is critical in terms of investment decisions and policy making. High resolution data from wind flow model simulations serve as a supplement to the limited resource of original wind flow data collection. Given the large size of data, finding hidden patterns in wind flow model simulations are critical for reducing the dimensionality of the analysis. In this work, we first perform dimension reduction with two autoencoder models: the CNN-based autoencoder (CNN-AE) [1], and hierarchical autoencoder (HIER-AE) [2], and compare their performance with the Principal Component Analysis (PCA). We then investigate the super-resolution of the wind flow data. By training a Generative Adversarial Network (GAN) with 300 epochs, we obtained a trained model with 2× resolution enhancement. We compare the results of GAN with Convolutional Neural Network (CNN), and GAN results show finer structure as expected in the data field images. Also, the kinetic energy spectra comparisons show that GAN outperforms CNN in terms of reproducing the physical properties for high wavenumbers and is critical for analysis where high-wavenumber kinetics play an important role.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2021

Neural Density Estimation and Uncertainty Quantification for ChemCam Spectra [Slides]

The ChemCam instrument of Curiosity uses laser-induced breakdown spectroscopy (LIBS). It fires a laser at target and vaporizes rock surfaces, creating a plasma. Three spectrographs divide the plasma light into wavelengths for chemical analysis: ultraviolet, violet, and visible near-infrared. Regression methods (SVR, PCR, CNN) have been employed for calibration (prediction of the elemental composition of samples); however, labeled ChemCam samples are limited. Here, we focus on unsupervised learning and employ generative models from ChemCam analysis. Further, we use labels (supervised) in combination to the generative model to compute uncertainties related to predictions. We report generative modeling can be successfully applied to model real-world data. Normalizing flow models can be efficiently constructed on latent spaces for fast downstream inference. Unsupervised and supervised learning can be combined to form an uncertainty quantification framework.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2022

Resolution requirements for energy conservation in kinetic plasma simulations

The kinetic codes used to model the coupled dynamics of electromagnetic fields and charged particle transport have requirements for spatial, temporal, and charge resolution. These requirements may vary by the solution technique and scope of the problem. In this report, we investigate the resolution limits in the energy-conserving implicit particle-in-cell code CHICAGO. This report has the narrow aim of determining the maximum acceptable grid spacing for the dense plasmas generated in models of z-pinch target gases and power-flow electrode plasmas. In the 2D sample problem, the plasma drifts without external forces with velocity of 10 cm/µs. Simulations are scaled by plasma density to maintain uniform strides across the plasma and from the plasma to the boundaries. Additionally, the cloud-in-cell technique is used with 400 particles per cell and Δ t = 0.85× the Courant limit. For the linear cloud distribution, the criterion for conserving energy is Δ E/E tot < 0.01 for 50,000 time steps. The grid resolution is determined to crudely be Δx ≲ 3 l s , where l s is the electron collisionless skin depth. For the second-order cloud distribution the criterion is Δ E/E tot < 0.005 yielding Δx ≤ 15 l s . These scalings are functions of the chosen v d , Δ t , particles-per-cell, and number of steps.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

NASA NTRS1991

Simulation Of Flow In A Turbine Cascade

Report discusses application of lower-upper (LU) implicit numerical-integration scheme, together with interactive grid-generation method, to simulation of inviscid, compressible flow in two-dimensional model of turbine cascade. Study part of continuing effort to develop techniques for computation of complicated three-dimensional flows in turbomachinery.

Choo, Yung K.↗

NASA NTRSDate not supplied

Wind-US Simulations of the NASA 1507 Inlet Test Case

Steady-state, Reynolds-Averaged Navier-Stokes (RANS) computational fluid dynamics (CFD) simulations were performed of the NASA 1507 Inlet Test Case from the 6th AIAA Propulsion Aerodynamics Workshop (PAW) held in January 2023 using the Wind-US CFD solver. The simulations were performed with bleed regions modeled as surface patches and the Slater bleed boundary condition models were applied within those regions. Both the constant-plenum-pressure and the fixed-plenum-exit bleed models where applied. The vortex generators were modeled using the Bender-Anderson-Yagle (BAY) vortex generator model. The CFD simulations were performed for inlet engine-face flow ratios varying from supercritical to subcritical inlet operation until inlet unstart. The results of the CFD simulations were compared to wind-tunnel data which included boundary layer profiles, axial static pressure distributions, bleed rates, total pressure recovery performance curves, and engine-face total pressure rake profiles. The CFD simulations were able to match most of the boundary layer rake data near the geometric throat, but the boundary layers on the centerbody were thinner than indicated by the wind-tunnel data. For the supercritical CFD simulations, the engine-face flow ratio was at least 2% to 2.5% lower than indicated by the wind-tunnel data, but still consistent with the level of supercritical bleed. The engine-face flow rates of the wind-tunnel tests had an uncertainty of ±2% which could explain the differences. The supercritical engine-face flow rates of the wind-tunnel data indicated a 5% supercritical bleed rate rather than the reported 7.18% bleed rate. The CFD simulations were able to calculate the maximum total pressure recovery of pt2/pt = 0.907 as observed for the wind-tunnel data. The CFD simulations with the constant-pressure bleed model were able to obtain a much lower engine-face total pressure ratio than indicated by both the wind-tunnel data and the CFD simulations using a fixed-plenum-exit bleed model. The CFD simulations indicated a sharp static pressure rise for the terminal shock rather than a more gradual rise indicated by the wind-tunnel data. The CFD simulations were not able to accurately compute the total pressure variation across the engine-face total pressure rake.

Supersonics↗

DOE OSTI2021

Thermal effects mediating the flow induced by laser-induced optical breakdown

Here, a short focused laser pulse can generate a hot plasma, which expands then contracts and can eject a hot jet, the speed and direction of which is sensitive to the details of the plasma kernel. The coupling of thermal and chemical nonequilibrium plasma mechanisms with this hydrodynamic development is assessed with detailed simulations of a two-temperature, three-species plasma model. Time scales for electron recombination, thermal relaxation, and diffusion are compared to that of the plasma expansion to anticipate conditions in which these mechanisms might affect the vorticity generation that leads to the ultimate flow pattern. The effect of these mechanisms are analyzed through comparison with corresponding inert-gas and equilibrium models. Thermal-nonequilibrium effects are found to be weak due to rapid relaxation of the heavy-particle and electronic temperatures. In contrast, chemical equilibration occurs at a rate comparable to the expansion and thereby enhance both it and subsequent hydrodynamic mechanisms as the energy stored in ion formation during the preceding breakdown is released by electron recombination. Thermal conduction, enhanced by high-temperature free electrons, weakens the ejection.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2022

Microgrid Assisted Design for Remote Areas

In this work, we present a three-stage multiobjective mixed-integer linear programming (MILP) for the optimal expansion planning and operation of isolated multienergy microgrids in remote areas. By selecting the optimal distributed generators (DGs) and energy storage systems (ESSs) mix selection, siting, sizing, and scheduling in the remote microgrid, the proposed model is targeted to minimize the annualized total cost of microgrids while enhancing the performance of the system, i.e., minimizing the voltage deviations and line power loss. To represent the electricity and heat flow between generation resources and various electrical, heating, and cooling loads in the isolated microgrid, linearized power flow, and heat flow constraints are employed in the proposed optimization model. The available capacity of DGs and ESSs are modeled as discrete constants instead of continuous variables for practical purpose. Numerical simulation results on a remote microgrid consisting of DGs, ESSs, and various loads validate the proposed method.

24 POWER TRANSMISSION AND DISTRIBUTION↗

NASA NTRS1986

Helicopter rotor noise due to ingestion of atmospheric turbulence

A theoretical study was conducted to develop an analytical prediction method for helicopter main rotor noise due to the ingestion of atmospheric turbulence. This study incorporates an atmospheric turbulence model, a rotor mean flow contraction model and a rapid distortion turbulence model which together determine the statistics of the non-isotropic turbulence at the rotor plane. Inputs to the combined mean inflow and turbulence models are controlled by atmospheric wind characteristics and helicopter operating conditions. A generalized acoustic source model was used to predict the far field noise generated by the non-isotropic flow incident on the rotor. Absolute levels for acoustic spectra and directivity patterns were calculated for full scale helicopters, without the use of empirical or adjustable constants. Comparisons between isotropic and non-isotropic turbulence at the rotor face demonstrated pronounced differences in acoustic spectra. Turning and contraction of the flow for hover and low speed vertical ascent cases result in a 3 dB increase in the acoustic spectrum energy and a 10 dB increase in tone levels. Compared to trailing edge noise, turbulence ingestion noise is the dominant noise mechanism below approximately 30 rotor harmonics, while above 100 harmonics, trailing edge noise levels exceed turbulence ingestion noise by 25 dB.

Simonich, J. C.↗