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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 163 records · Page 9

Hubble Parameter Measurement Constraints on The Redshift of The Deceleration–Acceleration Transition, Dynamical Dark Energy, and Space Curvature

We compile an updated list of 38 measurements of the Hubble parameter $H(z)$ between redshifts 0.07 $≤ z ≤$ 2.36 and use them to place constraints on model parameters of constant and time-varying dark energy cosmological models, both spatially flat and curved. We use five models to measure the redshift of the cosmological deceleration–acceleration transition, $z_{da}$, from these H(z) data. Within the error bars, the measured zda are insensitive to the model used, depending only on the value assumed for the Hubble constant $H_0$. The weighted mean of our measurements is $z_{da}$ = 0.72 ± 0.05 (0.84 ± 0.03) for $H_0$ = 68 ± 2.8 (73.24 ± 1.74) km s -1 Mpc -1 and should provide a reasonably model-independent estimate of this cosmological parameter. The H(z) data are consistent with the standard spatially flat ΛCDM cosmological model but do not rule out nonflat models or dynamical dark energy models.

79 ASTRONOMY AND ASTROPHYSICS↗

Dealing with Measurement Uncertainties as Nuisance Parameters in Bayesian Model Calibration

In the presence of model discrepancy, the calibration of physics-based models for physical parameter inference is a challenging problem. Lack of identifiability between calibration parameters and model discrepancy requires additional identifiability constraints to be placed on the model discrepancy to obtain unique physical parameter estimates. If these assumptions are violated, the inference for the calibration parameters can be systematically biased. In many applications, such as in dynamic material property experiments, many of the calibration inputs refer to measurement uncertainties. Here, we develop a metric for identifying overfitting of these measurement uncertainties, propose a prior capable of reducing this overfitting, and show how this leads to a diagnostic tool for validation of physical parameter inference. The approach is demonstrated for a benchmark example and applied for a material property application to perform inference on the equation of state parameters of tantalum.

97 MATHEMATICS AND COMPUTING↗

Improved semiclassical model for real-time evaporation of matrix black holes

In this paper, we study real-time classical matrix mechanics of a simplified 2 × 2 matrix model inspired by the black hole evaporation problem. This is a step towards making a quantitative model of real-time evaporation of a black hole, which is realized as a bound state of D0-branes in string theory. The model we study is the reduction of Yang–Mills in 2 + 1 dimension to 0 + 1 dimensions, which has been corrected with an additional potential that can be interpreted as a zero-point energy for fermions. Our goal is to understand the lifetime of such a classical bound state object in the classical regime. To do so, we pay particular attention to when D-particles separate to check that the “off-diagonal modes” of the matrices become adiabatic and use that information to improve on existing models of evaporation. It turns out that the naive expectation value of the lifetime with the fermionic correction is infinite. This is a logarithmic divergence that arises from very large excursions in the separation between the branes near the threshold for classical evaporation. The adiabatic behavior lets us get some analytic control of the dynamics in this regime to get this estimate. This divergence is cutoff in the quantum theory due to quantization of the adiabatic parameter, resulting in a long lifetime of the bound state, with a parametric dependence of order log(1/ℏ).

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Isotherm Modeling and Techno-Economic Analysis of Contactor Technologies for New Tetraamine-Appended MOF for NGCC Applications

Recently, a family of tetraamine-functionalized metal-organic frameworks (MOF) has been reported as promising sorbent materials for capturing CO2 from flue gas conditions relevant to natural gas combined cycle (NGCC) applications. The main advantages of these materials are their two-step cooperative CO2 adsorption, which gives rise to unusual two step-shaped CO2 adsorption profiles and their high thermal stability. This work presents the modelling of the two-transition isotherm of the tetraamine-appended MOF, N,N'-bis(3-aminopropyl)-1,4-diaminobutane (3-4-3)-appended Mg2(dobpdc), and the techno-economic analysis (TEA) of carbon capture processes utilizing this sorbent. Due to the unusual isotherm shapes of the experimental CO2 adsorption data for tetraamine-appended Mg2(dobpdc) and the strong nonlinearity of CO2 loading with respect to temperature and pressure, we tested two different models which use logistic functions for representing the different isotherm behaviors in the different pressure ranges. The first model uses the quadratic isotherm model in the low-pressure region, the Langmuir isotherm model in the middle pressure range, and the dual site Langmuir isotherm model in the high-pressure range. To model the transition between regions we used the arctangent functions independent of temperature and the thermal effect was accounted by using the Clausius-Clapeyron relation]. The second model is an extension of the weighted dual-site Langmuir isotherm model presented by Hughes et al.. In this extended model, the dual-site Langmuir isotherm is employed in the three transition regions, using temperature-dependent logistic functions to activate or deactivate the isotherm model in the low, middle, and high-pressure ranges. Both models fit the experimental data quite well with root mean squared errors (RMSE’s) of 0.41 and 0.17 for model 1 and model 2, respectively. Since model 2 resulted in a lower RMSE, it was leveraged for the development of the gas/solid contactor models used by the TEA. Specifically, two different contactor models, an axial-flow fixed bed and moving bed contactor, were developed as part of this work. These models are dynamic, pressure-driven, and consist of mass, energy, and momentum conservation equations. A kinetic model was also developed by performing parameter estimation using experimental fixed bed breakthrough data. These models are then used to simulate CO2 capture processes from the flue gas generated from a ~600 gross MW NGCC power plant. A cost model was developed which considers the capital cost of the reactors and the significant operating costs such as steam and electricity. Using NETL’s Framework for the Optimization and Quantification of Uncertainty of Uncertainty and Surrogates tool (FOQUS), which has the capability of linking models built using numerous modelling platforms with derivative-free optimization solvers, a techno-economic optimization of the carbon capture processes was performed which minimizes the cost of capture.

Caballero, Daison↗

Reduced-order model to estimate safe flammable refrigerant charge limits for a one-room air conditioner

The Heating, Ventilation, Air-Conditioning and Refrigeration (HVAC&R) industry is currently transitioning away from high global warming potential (GWP) hydrofluorocarbon (HFC) refrigerants. However, many lower-GWP alternatives are flammable. Current safety codes restrict use of all flammable refrigerants; revision of the codes is needed to facilitate wider use of flammable alternatives. Hence, information is needed to enable reliable estimates of safe charge limits for flammable refrigerant options for different HVAC&R applications. A reduced-order model (ROM) was developed and validated to help estimate safe charge limits based on computational fluid dynamics (CFD) simulations of refrigerant releases in a single room for a range of parameters. Validation of the ROM vs. the CFD results showed good general agreement for mean refrigerant concentration. The normalized mean bias error (NMBE) was 0.67% with a maximum error of 15%.

Edwards, Dean↗

Practical Hamiltonian learning with unitary dynamics and Gibbs states

We study the problem of learning the parameters for the Hamiltonian of a quantum many-body system, given limited access to the system. In this work, we build upon recent approaches to Hamiltonian learning via derivative estimation. We propose a protocol that improves the scaling dependence of prior works, particularly with respect to parameters relating to the structure of the Hamiltonian (e.g., its locality k). Furthermore, by deriving exact bounds on the performance of our protocol, we are able to provide a precise numerical prescription for theoretically optimal settings of hyperparameters in our learning protocol, such as the maximum evolution time (when learning with unitary dynamics) or minimum temperature (when learning with Gibbs states). Thanks to these improvements, our protocol has practical scaling for large problems: we demonstrate this with a numerical simulation of our protocol on an 80-qubit system.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Subterahertz Longitudinal Phonon Modes Propagating in a Lipid Bilayer Immersed in an Aqueous Medium

The properties of subterahertz longitudinal acoustic phonon modes in the hydrophobic region of a lipid bilayer immersed in a compressible viscous aqueous medium are investigated theoretically. An approximate expression is obtained for the Mandelstam–Brillouin components of the dynamic structure factor of a bilayer. The analysis is based on a generalized hydrodynamic model of the “two-dimensional lipid bilayer + three-dimensional fluid medium” system, as well as on known sharp estimates for the frequencies and lifetimes of long-wavelength longitudinal acoustic phonons in a free hydrated lipid bilayer and in water, obtained from inelastic X-ray scattering experiments and molecular dynamics simulations. It is shown that, for characteristic values of the parameters of the membrane system, subterahertz longitudinal phonon-like excitations in the hydrophobic part of the bilayer are underdamped. In this case, the contribution of the viscous flow of the aqueous medium to the damping of a longitudinal membrane mode is small compared with the contribution of the lipid bilayer. Quantitative estimates of the damping ratio agree well with the experimental results for the vibration mode of the enzyme lysozyme in aqueous solution [1]. It is also shown that a coupling between longitudinal phonon modes of the bilayer and relaxation processes in its fluid environment gives rise to an additional peak in the scattering spectrum, which corresponds to a non-propagating mode.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Optical soliton solutions, explicit power series solutions and linear stability analysis of the quintic derivative nonlinear Schrödinger equation

In this paper, the quintic derivative nonlinear Schrödinger equation is investigated into two main aspects. Firstly, a series of solutions of this equation are derived. More specifically, the singular solitons and dark solitons are obtained by using the ansatz method. The explicit power series solutions for the equation has also been constructed by employing power series method. Secondly, linear stability analysis is applied to estimate the stability of the equation. Finally, all solutions are presented via 3-dimensional plots with choices some special parameters to show the dynamic characteristics.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Cyber-Physical Attacks With Control Objectives

This study studies attackers with control objectives against cyber-physical systems (CPSs). The goal of the attacker is to counteract the CPS's controller and move the system to a target state while evading detection. We formulate a cost function that reflects the attacker's goals, and, using dynamic programming, we show that the optimal attack strategy reduces to a linear feedback of the attacker's state estimate. By changing the parameters of the cost function, we show how an attacker can design optimal attacks to balance the control objective and the detection avoidance objective. In conclusion, we provide a numerical illustration based on a remotely controlled helicopter under attack.

97 MATHEMATICS AND COMPUTING↗

Vibration-Based Sensor Design: A Grey-Box Approach

Knowledge of the internal structure of an object or device under investigation proceeds from the basic idea of constructing its dynamic behavioral relations governed by a set of differential/algebraic equations that characterize its response. These equations can be partial differential equations leading to finite element or finite difference relations requiring a complex numerical solution on a super computer or ordinary differential equations requiring sophisticated numerical integration techniques to obtain the desired solution. Discrete dynamic systems evolving from digitized data acquisition are typically captured by sampled-data (continuous-to-discrete) representations characterized by a set of difference equations specifying the underlying system dynamics. In any case, with a mathematical description in hand, Grey-Box modeling techniques have evolved, concerned with the estimation of model parameters embedded in a prescribed set of equations (the system) governing its behavior, while capturing the underlying physical phenomenology of the problem at hand.

97 MATHEMATICS AND COMPUTING↗

Predictive Scheduling for Electric Vehicles Considering Uncertainty of Load and User Behaviors

Un-coordinated Electric Vehicle (EV) charging can create unexpected load in local distribution grid, which may degrade the power quality and system reliability. The uncertainty of EV load, user behaviors and other baseload in distribution grid, is one of challenges that impedes optimal control for EV charging problem. Previous researches did not fully solve this problem due to lack of real-world EV charging data and proper stochastic model to describe these behaviors. In this paper, we propose a new predictive EV scheduling algorithm (PESA) inspired by Model Predictive Control (MPC), which includes a dynamic load estimation module and a predictive optimization module. The user-related EV load and base load are dynamically estimated based on the historical data. At each time interval, the predictive optimization program will be computed for optimal schedules given the estimated parameters. Only the first element from the algorithm outputs will be implemented according to MPC paradigm. Current-multiplexing function in each Electric Vehicle Supply Equipment (EVSE) is considered and accordingly a virtual load is modeled to handle the uncertainties of future EV energy demands. This system is validated by the real-world EV charging data collected on UCLA campus and the experimental results indicate that our proposed model not only reduces load variation up to 40% but also maintains a high level of robustness. Finally, IEC 61850 standard is utilized to standardize the data models involved, which brings significance to more reliable and large-scale implementation.

Wang, Bin↗

Rare Lepton Decays and Differentiable Hadronization Models - From Signatures of New Physics to Data-driven Event Generation

This dissertation is partitioned into two parts: phenomenological studies focused on rare lepton decays as probes of heavy and light new physics, and the development of differentiable, data-driven hadronization models. Part I develops the phenomenology of new physics signatures stemming from rare charged lepton flavor violating decays probed by experiments at the intensity frontier. These include interactions mediated by both high-scale effective operators and light new physics, manifesting in multi-lepton final states ($\mu \to 5e$), elastic nuclear transitions ($\mu \to e$ conversion), baryon-number-violating muon capture, and time-dependent signals from ultralight dark matter ($\mu \to e \phi, \tau \to \ell \phi$). Part II develops two distinct strategies for advancing differentiable and data-driven hadronization models. One involves comprehensive reweighting frameworks for hadronization that enable efficient uncertainty estimation, facilitate parameter tuning, and interface naturally with differentiable programming paradigms. The other introduces machine-learning-based methods for extracting microscopic fragmentation dynamics directly from macroscopic observables through the deformation of existing models -- effectively providing solutions to the inverse problem of hadronization. Altogether, these studies advance the interpretability, flexibility, and precision of theoretical predictions for both high-intensity and high-energy experiments.

Menzo, Tony [Cincinnati U.] (ORCID:000000022013457↗

Using Pantheon and DES supernova, baryon acoustic oscillation, and Hubble parameter data to constrain the Hubble constant, dark energy dynamics, and spatial curvature

ABSTRACT We use Pantheon Type Ia supernova (SN Ia) apparent magnitude, DES-3 yr binned SN Ia apparent magnitude, Hubble parameter, and baryon acoustic oscillation measurements to constrain six spatially flat and non-flat cosmological models. These sets of data provide mutually consistent cosmological constraints in the six cosmological models we study. A joint analysis of these data sets provides model-independent estimates of the Hubble constant, $H_0=68.8\pm 1.8\ \rm {km \, s^{-1} \ Mpc^{-1}}$, and the non-relativistic matter density parameter, $\Omega _{\rm m_0}=0.294\pm 0.020$. Although the joint constraints prefer mild dark energy dynamics and a little spatial curvature, they do not rule out dark energy being a cosmological constant and flat spatial hypersurfaces. We also add quasar angular size and H ii starburst galaxy measurements to the combined data set and find more restrictive constraints.

79 ASTRONOMY AND ASTROPHYSICS↗

Bifurcation and Stability Analysis of the Equilibrium States in Thermodynamic Systems in a Small Vicinity of the Equilibrium Values of Parameters

The dynamic behavior of thermodynamic system, described by one order parameter and one control parameter, in a small neighborhood of ordinary and bifurcation equilibrium values of the system parameters is studied. Using the general methods of investigating the branching (bifurcations) of solutions for nonlinear equations, we performed an exhaustive analysis of the order parameter dependences on the control parameter in a small vicinity of the equilibrium values of parameters, including the stability analysis of the equilibrium states, and the asymptotic behavior of the order parameter dependences on the control parameter (bifurcation diagrams). The peculiarities of the transition to an unstable state of the system are discussed, and the estimates of the transition time to the unstable state in the neighborhood of ordinary and bifurcation equilibrium values of parameters are given. The influence of an external field on the dynamic behavior of thermodynamic system is analyzed, and the peculiarities of the system dynamic behavior are discussed near the ordinary and bifurcation equilibrium values of parameters in the presence of external field. The dynamic process of magnetization of a ferromagnet is discussed by using the general methods of bifurcation and stability analysis presented in the paper.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Estimating evapotranspiration from deciduous broadleaf forests by considering the effect of foliar litter

Forest litter cover significantly alters the ground surface resistance, which influences the water and energy transfer processes between the land surface and atmosphere. Penman-Monteith (PM) model is widely used to estimate land surface evapotranspiration (ET). However, it was shown to overestimate ET during the period when foliar litter covers the ground surface. Therefore, incorporating the effect of foliar litter on ground surface resistance can potentially improve ET estimates. Here, in this study, we proposed a foliar litter surface resistance model to describe the effect of litter cover on water vapor transport, then incorporated the litter surface resistance into the PM model (noted as PM-EL model). The performance of the PM-EL model was evaluated using observations from 18 deciduous broadleaf forest (DBF) flux sites across global FLUXNET2015 datasets. Results showed that: (1) both the PM model and the PM-EL model are most sensitive to ground surface resistance among resistance parameters; (2) the proposed litter resistance model is capable of describing the seasonal dynamic of litter in DBF ; (3) the PM-EL model, has been shown to improve ET estimates with the coefficient of determination increased by 8.5 %, the mean absolute error and relative root mean square error decreased by 22.1 % and 20.9 %, respectively. The study contributes to our understanding of the effect of litter cover on ET estimation and provides insights into forest ecohydrology and land surface mass and energy transfer processes.

Deciduous Broadleaf Forest↗

An efficient algorithm for simulating ensembles of parameterized flow problems

Abstract Many applications of computational fluid dynamics require multiple simulations of a flow under different input conditions. In this paper, a numerical algorithm is developed to efficiently determine a set of such simulations in which the individually independent members of the set are subject to different viscosity coefficients, initial conditions and/or body forces. The proposed scheme, when applied to the flow ensemble, needs to solve a single linear system with multiple right-hand sides, and thus is computationally more efficient than solving for all the simulations separately. We show that the scheme is nonlinearly and long-term stable under certain conditions on the time-step size and a parameter deviation ratio. A rigorous numerical error estimate shows the scheme is of first-order accuracy in time and optimally accurate in space. Several numerical experiments are presented to illustrate the theoretical results.

Mathematics↗

Sticking Coefficients of Fusion Reactor Impurities from Molecular Dynamics Simulations for the Design of Cryopumps

A cryopump can be utilized as an impurity removal component of a direct internal recirculation (DIR) system for the fusion fuel cycle. The DIR facilitates a low fuel inventory by continuously pumping unburnt fuel while removing impurities from the fusion exhaust stream. A cryopump can target multiple impurity species by maintaining a temperature lower than the gas triple-point temperature that promotes desublimation. The desublimation/condensation of gases in cryopumps can be characterized by the sticking coefficient, which is defined as the probability for a gas particle to stick to a (cryo-)surface upon collision. The sticking coefficient is one of the important design/operation parameters for cryopumps, and it depends on a variety of surface and gas properties. Here, in this study, molecular dynamics simulations were utilized to estimate the sticking coefficients of typical fusion gas impurity species N 2 , CO 2 , and CH 4 over a Cu surface for a range of gas temperatures and surface coverages. The molecular dynamics study showed that the sticking coefficients for gases decrease with an increase in gas temperature. The presence of a single full monolayer of condensate on the metallic surface showed an adverse effect on the sticking of gases; however the sticking improved with two full monolayers of condensate on the surface. The sticking of gases over the mixed condensate on a surface was more favorable than the condensate of the same species for N 2 and CH 4 , with an exception for CO 2 , which showed a decrease in sticking over the mixed condensate.

cryopump↗

Bayesian analysis of (3 +1)⁢D relativistic nuclear dynamics with the RHIC beam energy scan data

This work presents a Bayesian inference study for relativistic heavy-ion collisions in the beam energy scan program at the BNL Relativistic Heavy-Ion Collider. The theoretical model simulates event-by-event (3+1)-dimensional [(3+1)⁢D] collision dynamics using hydrodynamics and hadronic transport theory. We analyze the model's 20-dimensional posterior distributions obtained using three model emulators with different accuracy and demonstrate the essential role of training an accurate model emulator in the Bayesian analysis. Our analysis provides robust constraints on the quark-gluon plasma's transport properties and various aspects of (3+1)⁢D relativistic nuclear dynamics. By running full model simulations with 100 parameter sets sampled from the posterior distribution, we make predictions for p T -differential observables and estimate their systematic theory uncertainty. Here, a sensitivity analysis is performed to elucidate how individual experimental observables respond to different model parameters, providing useful physics insights into the phenomenological model for heavy-ion collisions.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗