Disaggregation of Vehicle Choice Modeling: Capturing Potential Spillover Effects in the LDV and HDV Markets.
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The effect of electron-electron Coulomb correlation on orbital electron capture by the nucleus was treated by the multiconfigurational Hartree-Fock approach. The theoretical Be-7 L/K capture ratio was found to be 0.086, and the Ar-37 M/L ratio, 0.102. Both ratios were smaller than the independent particle predictions. Measurements exist for the Ar M/L ratio, and agreement between theory and experiment was excellent.
The effect of electron-electron Coulomb correlation on orbital-electron capture by the nucleus has been treated by the multiconfigurational Hartree-Fock approach. The theoretical Be-7 L/K capture ratio is found to be 0.086, and the Ar-37 M/L ratio, 0.102. Both ratios are smaller than the independent-particle predictions. Measurements exist for the Ar M/L ratio, and agreement between theory and experiment is excellent.
An application of the new optimization algorithm called Static/Dynamic Control (SDC) to design low-thrust escape and capture trajectories is presented.
The interplay between microstructure and deformation twinning in a WE43-T6 Mg alloy under uniaxial compression was investigated using a combination of scanning electron microscopy with digital image correlation (SEM-DIC) and crystal plasticity finite element (CPFE) simulation. To improve understanding of the statistical characteristics of deformation twin formation, microstructural effects were characterized in over 1000 grains through metrics including the nominal Schmid Factor, grain size, geometric compatibility factor (m'), residual Burgers vector, and the strain accommodated by neighboring grains. There was a strong correlation between the nominal Schmid Factor and both twin activation and variant selection, but this was not fully deterministic. Deformation twinning also exhibited a strong dependence on existing slip and twinning in the neighboring grain and on the m' value. Within the range of grain sizes present in this condition, grain size was determined to have minimal effect on deformation twinning. Finally, statistical analysis of CPFE simulations was used to further investigate microstructural effects on twinning, and qualitatively captured the effect of the nominal Schmid Factor.
This paper summarizes findings from the sixth AIAA Propulsion Aerodynamics Workshop (PAW) nozzle test case. The focus of the workshop participants was turbulent supersonic round jets with variation in jet Mach number and jet heating. Three nozzles were utilized with on-design jet Mach numbers of 1.36, 1.63, and 2.00. A heated jet for each of these three nozzles at on-design conditions, a temperature matched on-design condition at Mach 1.63, and an off-design heated condition for the Mach 1.63 nozzle were the five cases examined. Workshop participants utilized Reynolds-averaged Navier-Stokes (RANS) and Large Eddy Simulation (LES) based techniques. Computational fluid dynamics (CFD) solutions were compared with non-intrusive measurements of velocities and temperatures, including both mean values and turbulence statistics. In general, the RANS approaches were unable to capture the trend of reduced mixing as the jet Mach number increased. Incorporation of compressibility corrections improved the agreement with experimental measurements in terms of trends with varying jet Mach number, but also increased the jet potential core lengths to be in worse agreement with data. RANS methods were able to reasonably capture trends of jet heating. The LES-based approaches as a whole were able to capture the effects of compressibility more accurately. Effects of jet heating were captured well by LES. None of the LES approaches introduced disturbances from the wall boundary layers of the nozzle into the jet mixing layer, which would affect the jet flow physics modeling in the initial part of the jet shear layer, but would be very computationally demanding.
Here, we consider the capture of a muon on a deuteron. An uncertainty analysis of the dominant channels is important for a careful analysis of forthcoming experimental data. We quantify the theoretical uncertainties of chiral effective-field-theory predictions of the muon-deuteron capture rate from the relevant neutron-neutron partial wave channels in the final state. We study the dependence on the cutoff used to regularize the interactions, low-energy constants calibrated using different fitting data and strategies, and truncation of the effective-field-theory expansion of the currents. Combining these approaches gives as an estimate of $Γ^{1/2}_{μd}$ = 399.1 ± 7.6 ± 4.4 s –1 for capture from the atomic doublet state, and $Γ^{3/2}_{μd}$= 12.31 ± 0.47 ± 0.04 s –1 for capture from the quartet state and the first and second uncertainties given here are due to the effective field theory truncation error and the uncertainty in the axial radius, respectively.
Several current searches for physics beyond the standard model are based on measuring the electron-capture (EC) decay of radionuclides implanted into cryogenic high-resolution sensors. The sensitivity of these experiments has already reached the level where systematic effects related to atomic state energy changes from the host material are a limiting factor. One example is a neutrino mass study based on the nuclear EC decay of 7 Be to 7 Li inside cryogenic Ta-based sensors. Here, to understand the material effects at the required level, we use density-functional theory to model the electronic structure of lithium atoms in different atomic environments of the polycrystalline Ta absorber film. The calculations reveal that the Li 1s binding energies can vary by more than 2 eV due to insertion at different lattice sites, at grain boundaries, in disordered Ta, and in the vicinity of various impurities. However, the total range of Li 1s shifts does not exceed 4 eV, even for extreme amorphous disorder. Furthermore, when investigating the effects on the Li 2s levels, we find broadening of more than 5 eV due to hybridization with the Ta band structure. Material effects are shown to contribute significantly to peak broadening in Ta-based sensors that are used to search for physics beyond the standard model in the EC decay of 7 Be, but they do not explain the full extent of observed broadening. Understanding these in-medium effects will be required for current- and future-generation experiments that observe low-energy radiation from the EC decay of implanted isotopes to evaluate potential limitations on the measurement sensitivity.
Underresolved simulations are unavoidable in high Reynolds (Re) and Mach (Ma) number turbulent flow applications at scale. Implicit large-Eddy simulation (ILES) often becomes the effective strategy to capture the dominating effects of convectively driven flow instabilities. We evaluate the impact of three distinct numerical strategies in simulations of transition and turbulence decay with ILES: the Harten–Lax–van Leer (HLL) Riemann solver applying Strang splitting and a Lagrange-plus-Remap formalism to solve the directional sweep—denoted split; the Harten–Lax–Van Leer-Contact (HLLC) Riemann solver using a directionally unsplit strategy and parabolic reconstruction—denoted unsplit; and the HLLC Riemann solver using unsplit and a low-Ma correction (LMC)—denoted unsplit*. Three case studies are considered: (1) a shock tube problem prototyping shock-driven turbulent mixing, (2) the Taylor–Green Vortex (TGV) prototyping transition to turbulence, and, (3) an homogeneous isotropic turbulence (HIT) case, focusing on the impact of discretization on transition and decay from fixed well-characterized initial conditions. Significantly more accurate predictions are provided by the unsplit schemes, in particular, when augmented with the LMC. For given resolution, only the unsplit schemes predict the turbulent mixing transition after reshock observed in the shock tube experiments. Relevant comparisons of ILES based on Euler and Navier–Stokes equations addressing potential occurrence of low-Re regimes in the applications are presented. Unsplit schemes are instrumental in allowing to capture the spatial development of the TGV flow and its validation at prescribed Re with significantly less resolution. HIT analysis confirms higher simulated turbulence Re and increased small-scale content associated with the unsplit discretizations.
Information asymmetry between the Distribution System Operator (DSO) and Distributed Energy Resource Aggregators (DERAs) obstructs designing effective incentives for voltage regulation. To capture this effect, we employ a Stackelberg game-theoretic framework, where the DSO seeks to overcome the information asymmetry and refine its incentive strategies by learning from DERA behavior over multiple iterations. We introduce a model-based online learning algorithm for the DSO, aimed at inferring the relationship between incentives and DERA responses. Given the uncertain nature of these responses, we also propose a distributionally robust incentive design model to control the probability of voltage regulation failure and then reformulate it into a convex problem. This model allows the DSO to periodically revise distribution assumptions on uncertain parameters in the decision model of the DERA. Finally, we present a gradient-based method that permits the DSO to adaptively modify its conservativeness level, measured by the size of a Wasserstein metric-based ambiguity set, according to historical voltage regulation performance. The effectiveness of our proposed method is demonstrated through numerical experiments.
Information asymmetry between the Distribution System Operator (DSO) and Distributed Energy Resource Aggregators (DERAs) obstructs designing effective incentives for voltage regulation. To capture this effect, we employ a Stackelberg game-theoretic framework, where the DSO seeks to overcome the information asymmetry and refine its incentive strategies by learning from DERA behavior over multiple iterations. We introduce a model-based online learning algorithm for the DSO, aimed at inferring the relationship between incentives and DERA responses. Given the uncertain nature of these responses, we also propose a distributionally robust incentive design model to control the probability of voltage regulation failure and then reformulate it into a convex problem. This model allows the DSO to periodically revise distribution assumptions on uncertain parameters in the decision model of the DERA. Finally, we present a gradient-based method that permits the DSO to adaptively modify its conservativeness level, measured by the size of a Wasserstein metric-based ambiguity set, according to historical voltage regulation performance. The effectiveness of our proposed method is demonstrated through numerical experiments.
This publication is the final report of research performed under an NRA/Cooperative Interagency Agreement, and includes a supplemental CD-ROM with detailed data. It is complemented by NASA/CR-2012-217416 and NASA/CR-2012-217417 which include a Ph.D. Dissertation and an M.S. thesis respectively, performed under this contract. In this study the effects of unsteady wakes and flow control using vortex generator jets (VGJs) were studied experimentally and computationally on the flow over the L1A low pressure turbine (LPT) airfoil. The experimental facility was a six passage linear cascade in a low speed wind tunnel at the U.S. Naval Academy. In parallel, computational work using the commercial code FLUENT (ANSYS, Inc.) was performed at Cleveland State University, using Unsteady Reynolds Averaged Navier Stokes (URANS) and Large Eddy Simulations (LES) methods. In the first phase of the work, the baseline flow was documented under steady inflow conditions without flow control. URANS calculations were done using a variety of turbulence models. In the second phase of the work, flow control was added using steady and pulsed vortex generator jets. The VGJs successfully suppressed separation and reduced aerodynamic losses. Pulsed operation was more effective and mass flow requirements are very low. Numerical simulations of the VGJs cases showed that URANS failed to capture the effect of the jets. LES results were generally better. In the third phase, effects of unsteady wakes were studied. Computations with URANS and LES captured the wake effect and generally predicted separation and reattachment to match the experiments. Quantitatively the results were mixed. In the final phase of the study, wakes and VGJs were combined and synchronized using various timing schemes. The timing of the jets with respect to the wakes had some effect, but in general once the disturbance frequency was high enough to control separation, the timing was not very important.
This publication is the final report of research performed under an NRA/Cooperative Interagency Agreement, and includes a supplemental CD-ROM with detailed data. It is complemented by NASA/CR-2012-217416 and NASA/CR-2012-217417 which include a Ph.D. Dissertation and an M.S. thesis respectively, performed under this contract. In this study the effects of unsteady wakes and flow control using vortex generator jets (VGJs) were studied experimentally and computationally on the flow over the L1A low pressure turbine (LPT) airfoil. The experimental facility was a six passage linear cascade in a low speed wind tunnel at the U.S. Naval Academy. In parallel, computational work using the commercial code FLUENT (ANSYS, Inc.) was performed at Cleveland State University, using Unsteady Reynolds Averaged Navier Stokes (URANS) and Large Eddy Simulations (LES) methods. In the first phase of the work, the baseline flow was documented under steady inflow conditions without flow control. URANS calculations were done using a variety of turbulence models. In the second phase of the work, flow control was added using steady and pulsed vortex generator jets. The VGJs successfully suppressed separation and reduced aerodynamic losses. Pulsed operation was more effective and mass flow requirements are very low. Numerical simulations of the VGJs cases showed that URANS failed to capture the effect of the jets. LES results were generally better. In the third phase, effects of unsteady wakes were studied. Computations with URANS and LES captured the wake effect and generally predicted separation and reattachment to match the experiments. Quantitatively the results were mixed. In the final phase of the study, wakes and VGJs were combined and synchronized using various timing schemes. The timing of the jets with respect to the wakes had some effect, but in general once the disturbance frequency was high enough to control separation, the timing was not very important. This is the supplemental CD-ROM
Ice-mass change induces regionally varying patterns of sea-level change due to gravitational, rotational, and deformational (GRD) effects, which in turn influence marine-based ice stability in Antarctica. For improved projection of the Antarctic Ice Sheet (AIS), there is a need for including GRD effects in modeling and improving understanding of basin-by-basin sensitivity of ice evolution to GRD effects under a range of climate scenarios. We couple a high-resolution, higher-order ice-sheet model with a 1D global sea-level model that fully captures GRD effects, and simulate ice evolution in Antarctica under the Ice Sheet Model Intercomparison Project for CMIP6 experiments. We perform two sets of coupled simulations incorporating 1D Maxwell solid Earth structure suitable for West and East Antarctica and show that the Amundsen Sea Embayment (ASE) in West Antarctica has the highest sensitivity to GRD effects—in high-emission scenarios, grounding-line retreat accelerates by hundreds of kilometers by 2300 without GRD effects, but GRD effects delay this retreat on a timescale of decades. However, we find that delay times do not show a clear relationship to the strength of climate forcing alone. Furthermore, GRD effects can influence ice-sheet dynamics more than the choice of climate model for a given emissions scenario. In contrast, East Antarctica exhibits minimal sensitivity to GRD effects throughout the study period. These findings underscore the critical role of GRD effects in shaping future West AIS evolution, highlighting the importance of constraining the regional 3D Earth structure and bed topography in West Antarctica, particularly the ASE.
Electron capture cross section by protons in hydrogen atom obtained, using perturbed wave functions due to electric field
Many important industrial and biological processes depend on ring-opening polymerization (ROP), including large-scale production polymers, such as nylon 6, and a variety of biodegradable polymers and high-performance resins. Large-scale simulations (>200K atoms) of ROP were performed using a deep neural network-based method that captured the effect of the local chemical environment of the reactive sites using training data from quantum chemical methods. The utility of this method was demonstrated by modeling the cationic ROP of bis-benzoxazine, a promising resin for use in advanced high-temperature application composites (>200°C). Density functional theory calculations were used to map out the various ring opening and polymerization reaction paths that occur during the thermal processing of bis-benzoxazine. The probabilities of these reactions, as a function of local atomic configurations, were used to construct committor functions using a neural network approach. The learned committor functions were then used to determine when a particular reaction occurred within the REACTER framework for reactive molecular dynamics simulations. The experimentally observed exotherm that occurs during bis-benzoxazine ROP was captured in an effective manner in the simulations by imposing a local heating of the system that corresponds to the enthalpy of reaction for each reaction. The dependence of the final polymer morphology on the ROP reaction temperature was analyzed at the molecular scale. The results presented in this work indicate that machine-learned committor functions are a promising approach for incorporating high-fidelity reactivity criteria that capture the effect of local chemical environments into large-scale polymerization simulations.
Wind farm simulations often do not accurately represent wake-atmospheric boundary layer (ABL) interactions, blade boundary layer (BL) dynamics, and turbine-turbine interactions. In this work, we use Active Model Split (AMS), a new hybrid Reynolds-Averaged Navier Stokes (RANS)-large eddy simulation (LES) model, which is well suited to capture these effects because the model can (i) accurately simulate the ABL with the Coriolis effect, (ii) is accurate in adverse pressure gradients such as those near wind turbine blades, and (iii) has sufficiently low computational cost to simulate multiple turbines while resolving the blade BL. For simplicity and consistency we develop AMS to be used throughout the domain rather than in a zonal method. We implement our work in the massively parallel flow solver, Nalu-Wind, so that our model can access the compute resources needed for blade-resolved simulations of multiple wind turbines. To accomplish these aims, we modify the baseline AMS by changing the RANS contribution to SST k - omega with a length scale limiter, adding the Coriolis effect, and developing an appropriate wall treatment. We show that AMS of the ABL with the Coriolis effect matches LES reference results better than those obtained with RANS. We describe our plans to add buoyancy effects and wind turbines to our AMS simulations.