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NASA NTRS1996

On-Line Tracking Controller for Brushless DC Motor Drives Using Artificial Neural Networks

A real-time control architecture is developed for time-varying nonlinear brushless dc motors operating in a high performance drives environment. The developed control architecture possesses the capabilities of simultaneous on-line identification and control. The dynamics of the motor are modeled on-line and controlled using an artificial neural network, as the system runs. The control architecture combines the experience and dependability of adaptive tracking systems with potential and promise of the neural computing technology. The sensitivity of real-time controller to parametric changes that occur during training is investigated. Such changes are usually manifested by rapid changes in the load of the brushless motor drives. This sudden change in the external load is simulated for the sigmoidal and sinusoidal reference tracks. The ability of the neuro-controller to maintain reasonable tracking accuracy in the presence of external noise is also verified for a number of desired reference trajectories.

Rubaai, Ahmed↗

DOE OSTI2024

On the Flow of a Cement Suspension: The Effects of Nano-Silica and Fly Ash Particles

Additives such as nano-silica and fly ash are widely used in cement and concrete materials to improve the rheology of fresh cement and concrete and the performance of hardened materials and increase the sustainability of the cement and concrete industry by reducing the usage of Portland cement. Therefore, it is important to study the effect of these additives on the rheological behavior of fresh cement. In this paper, we study the pulsating Poiseuille flow of fresh cement in a horizontal pipe by considering two different additives and when they are combined (nano-silica, fly ash, combined nano-silica, and fly ash). To model the fresh cement suspension, we used a modified form of the power-law model to demonstrate the dependency of the cement viscosity on the shear rate and volume fraction of cement and the additive particles. The convection–diffusion equation was used to solve for the volume fraction. After solving the equations in the dimensionless forms, we conducted a parametric study to analyze the effects of nano-silica, fly ash, and combined nano-silica and fly ash additives on the velocity and volume fraction profiles of the cement suspension. According to the parametric study presented here, larger nano-silica content results in lower centerline velocity of the cement suspension and larger non-uniformity of the volume fraction. Compared to nano-silica, fly ash exhibits an opposite effect on the velocity. Larger fly ash content results in higher centerline velocity, while the effect of the fly ash on the volume fraction is not obvious. For cement suspension containing combined nano-silica and fly ash additives, nano-silica plays a dominant role in the flow behavior of the suspension. The findings of the study can help the design and operation of the pulsating flow of fresh cement mortars and concrete in the 3D printing industry.

36 MATERIALS SCIENCE↗

DOE OSTI2025

Symplectic neural network and its application to charged particle dynamics in electromagnetic fields

Recently, machine learning models have shown many successes in various applications in science and technology. In this work, we focus on the charged particle dynamics, with the development of a class of symplectic neural networks, including a linear version, SympMat, and a nonlinear version, HénonNet. Both are designed to preserve the structure of Hamiltonian systems. We show that they can be used to model relevant Hamiltonian systems of interest in plasma physics and astrophysics, for linear and nonlinear charged particle dynamics, with the potential to bridge multi-scale simulations. These symplectic neural networks are adapted to the applications in plasma simulations and particle-wave interaction with parametric dependence and periodicity, where we have investigated their performance and accuracy. In particular, SympMat is shown to outperform the traditional Boris particle pusher down to the sub-gyroperiod scale in the case of charged particles in uniform magnetic fields. HénonNet successfully predicts the hot electron distribution, which is validated against theoretical results. These results highlight the potential of symplectic neural networks as a trajectory integrator for particle-in-cell simulations or a fast surrogate to replace conventional numerical schemes.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2021

Spin-lattice model for cubic crystals

In this work, we present a methodology based on the Néel model to build a classical spin-lattice Hamiltonian for cubic crystals capable of describing magnetic properties induced by the spin-orbit coupling like magnetocrystalline anisotropy and anisotropic magnetostriction, as well as exchange magnetostriction. Taking advantage of the analytical solutions of the Néel model, we derive theoretical expressions for the parametrization of the exchange integrals and Néel dipole and quadrupole terms that link them to the magnetic properties of the material. This approach allows us to build accurate spin-lattice models with the desired magnetoelastic properties. We also explore a possible way to model the volume dependence of magnetic moment based on the Landau energy. This feature allows us to consider the effects of hydrostatic pressure on the saturation magnetization. We apply this method to develop a spin-lattice model for BCC Fe and FCC Ni, and we show that it accurately reproduces the experimental elastic tensor, magnetocrystalline anisotropy under pressure, anisotropic magnetostrictive coefficients, volume magnetostriction, and saturation magnetization under pressure at zero temperature. This work could constitute a step towards large-scale modeling of magnetoelastic phenomena.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

DOE OSTI2026

Neuralized fermionic tensor networks for quantum many-body systems

In this work, we describe a class of neuralized fermionic tensor network states (NN-fTNSs) that introduce nonlinearity into fermionic tensor networks through configuration-dependent neural network transformations of the local tensors. The construction uses the fTNS algebra to implement a natural fermionic sign structure and is compatible with standard tensor network algorithms but gains enhanced expressivity through the neural network parametrization. Using the 1D and 2D Fermi-Hubbard models as benchmarks, we demonstrate that NN-fTNSs achieve order of magnitude improvements in the ground-state energy compared to pure fTNSs with the same bond dimension and can be systematically improved through both the tensor network bond dimension and the neural network parametrization. Compared to existing fermionic neural quantum states based on Slater determinants and Pfaffians, NN-fTNSs offer a physically motivated alternative fermionic structure. Furthermore, compared to such states, NN-fTNSs naturally exhibit improved computational scaling and we demonstrate a construction that achieves linear scaling with the lattice size.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

NASA NTRS2013

Commercial Non-Dispersive Infrared Spectroscopy Sensors for Sub-Ambient Carbon Dioxide Detection

Carbon dioxide produced through respiration can accumulate rapidly within closed spaces. If not managed, a crew's respiratory rate increases, headaches and hyperventilation occur, vision and hearing are affected, and cognitive abilities decrease. Consequently, development continues on a number of CO2 removal technologies for human spacecraft and spacesuits. Terrestrially, technology development requires precise performance characterization to qualify promising air revitalization equipment. On-orbit, instrumentation is required to identify and eliminate unsafe conditions. This necessitates accurate in situ CO2 detection. Recursive compensation algorithms were developed for sub-ambient detection of CO2 with commercial off-the-shelf (COTS) non-dispersive infrared (NDIR) sensors. In addition, the source of the exponential loss in accuracy is developed theoretically. The basis of the loss can be explained through thermal, Doppler, and Lorentz broadening effects that arise as a result of the temperature, pressure, and composition of the gas mixture under analysis. The objective was to develop a mathematical routine to compensate COTS CO2 sensors relying on NDIR over pressures, temperatures, and compositions far from calibration conditions. The routine relies on a power-law relationship for the pressure dependency of the sensors along with an equivalent pressure to account for the composition dependency. A Newton-Raphson iterative technique solves for actual carbon dioxide concentration based on the reported concentration. Moreover, first principles routines were established to predict mixed-gas spectra based on sensor specifications (e.g., optical path length). The first principles model can be used to parametrically optimize sensors or sensor arrays across a wide variety of pressures/temperatures/ compositions. In this work, heuristic scaling arguments were utilized to develop reasonable compensation techniques. Experimental results confirmed this approach and provided evidence that composition broadening significantly alters spectra when pressure is reduced. Consequently, a recursive compensation technique was developed with the Newton-Raphson method, which was subsequently verified through experimentation.

Swickrath, Michael J.↗

DOE OSTI2025

Multi-stage heat pump with two-phase injection for cold climate applications implementing natural refrigerants

Heat pump adoption in cold climates is limited by various technical challenges, including heat capacity degradation, compressor deterioration, and frost accumulation on the outdoor heat exchanger. Furthermore, wide-spread adoption of heat pumps with high global warming potential presents a possible environmental concern. Thus, we present a heat pump concept termed the “saturation cycle,” which uses numerous compression stages to improve energy efficiency and injects two-phase refrigerant between compression stages to dramatically reduce compressor discharge temperatures. Given the growing interest in heat pumps, there is a need for a straightforward framework for parametric evaluation of natural refrigerants in high-efficiency heat pump cycle architectures, like the saturation cycle, in adverse climates. This work develops a thermodynamic modeling framework and focuses on the application of natural refrigerants to explore the performance trends at extremely cold climates down to −25 °C. This study shows that a two-stage saturation cycle and four-stage saturation cycle can reduce the compressor discharge superheating by up to 51–57 % or 73–80 %, respectively, depending on the refrigerant. Furthermore, at −25 °C, a two-stage R-290 saturation cycle heat pump theoretically can use 25 % less power than a single-stage heat pump or can provide up to 59 % more heating capacity when using the same compressor power as the baseline single-stage heat pump. The exergetic parametric analyses show that two-phase refrigerant injection fundamentally improves the thermodynamic performance of the heat pump, reducing overall exergy destruction by 10 % compared to a vapor-injection heat pump, compared at −25 °C. Thus, the saturation cycle is a promising heat pump cycle architecture for cold climate applications due to its superior energy savings (or capacity improvement) and substantial de-superheating capabilities.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2026

Modeling and Experimental Validation of a Direct-Contact Counter-Flow Fluidized Bed Heat Exchanger for Thermal Energy Storage (TES) Applications

Particle-based thermal energy storage (TES) systems are an emerging energy storage technology. The technological advances have reduced costs, making TES more competitive and reliable in the marketplace but an efficient and reliable operation is heavily dependent on coherent heat transfer between air to particles or vice versa. The particle-based TES technologies provide an intermediate system that can store energy for short (0-10 h), long (10-200 h) and seasonal (> 200 h) timescales. The TES systems store energy by converting electricity to thermal energy; electricity can be directly sourced intermittent generation technologies and/or the grid, helping manage peak loads and other mismatches in supply and demand. The overall efficiency of the TES system depends on the performance of system components (particle storage silos and particle transfer mechanism etc.). The particle heat exchanger is one of the key system components that affects the system efficiency. The pressurized fluidized bed heat exchanger (PFB HX) performance is challenging to predict due to the chaotic behavior of particle and fluid interaction. This research presents a computational study of a novel direct-contact, counter-flow and air-to-particles PFB HX, that contributes in advancing the particle-based long-duration TES technologies. For the current analysis an unsteady Eulerian-Eulerian CFD model was developed and validated against experiments performed at the National Laboratory of the Rockies for two particle sizes (600 ..mu..m and 825 ..mu..m ). Following validation, parametric simulations were conducted to evaluate the effects of interphase drag models (Syamlal-O'Brien and Gidaspow), particle size, bed height and the influence of a frictional-viscosity term on hydrodynamics and heat transfer between the air & particles. The key findings from the analysis are: (1) for the studied operating window Syamlal-O'Brien provides superior agreement with measured gas temperatures (errors generally < 10%) while Gidaspow shows large deviations for the coarse particle case; (2) model predictions are most sensitive in the lower 0.2 m above the air distributor where bubble initiation and local mixing dominate interphase heat transfer; (3) representation of the distributor (number of inlet ports) materially affects predicted local mixing and temperature stratification; and (4) the Eulerian-Eulerian framework reproduces bulk thermal trends but shows regime dependent limitations for coarse particles, motivating mesoscale informed closures for scale-up analysis for future studies. These results provide validated guidance for drag selection and distributor design in particle-based thermal energy storage applications. Collectively, the validated model and parametric results quantify key drivers of PHB-HX performance and provide practical guidance for design and optimization. The results provide confidence in the model predictability and provide a step forward to improve on heat exchange performance. The demonstrated performance and modeling approach support the deployment and further development of this novel PHB-HX concept for robust, particle-based long-duration thermal energy storage systems.

25 ENERGY STORAGE↗

DOE OSTI2022

Cosmology with the Roman Space Telescope – Synergies with CMB lensing

ABSTRACT We explore synergies between the Nancy Grace Roman Space Telescope and CMB lensing data to constrain dark energy and modified gravity scenarios. A simulated likelihood analysis of the galaxy clustering and weak lensing data from the Roman Space Telescope High Latitude Survey combined with CMB lensing data from the Simons Observatory is undertaken, marginalizing over important astrophysical effects and calibration uncertainties. Included in the modelling are the effects of baryons on small-scale clustering, scale-dependent growth suppression by neutrinos, as well as uncertainties in the galaxy clustering biases, in the intrinsic alignment contributions to the lensing signal, in the redshift distributions, and in the galaxy shape calibration. The addition of CMB lensing roughly doubles the dark energy figure-of-merit from Roman photometric survey data alone, varying from a factor of 1.7 to 2.4 improvement depending on the particular Roman survey configuration. Alternatively, the inclusion of CMB lensing information can compensate for uncertainties in the Roman galaxy shape calibration if it falls below the design goals. Furthermore, we report the first forecast of Roman constraints on a model-independent structure growth, parametrized by σ8(z), and on the Hu-Sawicki f(R) gravity as well as an improved forecast of the phenomenological (Σ0, μ0) model. We find that CMB lensing plays a crucial role in constraining σ8(z) at z > 2, with percent-level constraints forecasted out to z = 4. CMB lensing information does not improve constraints on the f(R) model substantially. It does, however, increase the (Σ0, μ0) figure-of-merit by a factor of about 1.5.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2021

Quantum Monte Carlo studies of a trimer scaling function with microscopic two- and three-body interactions

Here, we present an energy scaling function to predict, in a specific range, the energy of bosonic trimers with large scattering lengths and finite range interactions, which is validated by quantum Monte Carlo calculations using microscopic Hamiltonians with two- and three-body potentials. The proposed scaling function depends on the scattering length, effective range, and a reference energy, which we chose as the trimer energy at unitarity. We obtained the scaling function as a limit cycle from the solution of the renormalized zero-range model with effective range corrections. We proposed a simple parametrization of the energy scaling function. Besides the intrinsic interest in theoretical and experimental investigations, this scaling function allows one to probe Efimov physics with only the trimer ground states, which may open opportunities to identify Efimov trimers whenever access to excited states is limited.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

NASA NTRS1979

Analytical predictions of RTG power degradation

The DEGRA computer code that is based on a mathematical model which predicts performance and time-temperature dependent degradation of a radioisotope thermoelectric generator is discussed. The computer code has been used to predict performance and generator degradation for the selenide Ground Demonstration Unit (GDS-1) and the generator used in the Galileo Project. Results of parametric studies of load voltage vs generator output are examined as well as the I-V curve and the resulting predicted power vs voltage. The paper also discusses the increased capability features contained in DEGRA2 and future plans for expanding the computer code performance.

Noon, E. L.↗

NASA NTRS1990

Elastic/plastic analyses of advanced composites investigating the use of the compliant layer concept in reducing residual stresses resulting from processing

High residual stresses within intermetallic and metal matrix composite systems can develop upon cooling from the processing temperature to room temperature due to the coefficient of thermal expansion (CTE) mismatch between the fiber and matrix. As a result, within certain composite systems, radial, circumferential, and/or longitudinal cracks have been observed to form at the fiber-matrix interface. The compliant layer concept (insertion of a compensating interface material between the fiber and matrix) was proposed to reduce or eliminate the residual stress buildup during cooling and thus minimize cracking. The viability of the proposed compliant layer concept is investigated both elastically and elastoplastically. A detailed parametric study was conducted using a unit cell model consisting of three concentric cylinders to determine the required character (i.e., thickness and material properties) of the compliant layer as well as its applicability. The unknown compliant layer mechanical properties were expressed as ratios of the corresponding temperature dependent Ti-24Al-11Nb (a/o) matrix properties. The fiber properties taken were those corresponding to SCS-6 (SiC). Results indicate that the compliant layer can be used to reduce, if not eliminate, radial and circumferential residual stresses within the fiber and matrix and therefore also reduce or eliminate the radial cracking. However, with this decrease in in-plane stresses, one obtains an increase in longitudinal stress, thus potentially initiating longitudinal cracking. Guidelines are given for the selection of a specific compliant material, given a perfectly bonded system.

Arnold, Steven M.↗

NASA NTRS1992

Reduction of Thermal Residual Stresses in Advanced Metallic Composites Based upon a Compensating/Compliant Layer Concept

High residual stresses within metal and intermetallic matrix composite systems can develop upon cooling from the processing temperature to room temperature due to the coefficient of thermal expansion (CTE) mismatch between the fiber and matrix. As a result, within certain composite systems, radial, circumferential, and/or longitudinal cracks have been observed to form at the fiber-matrix interface region. The compliant layer concept (insertion of a compensating interface material between the fiber and matrix) has been proposed to reduce or eliminate the residual stress buildup during cooling, and thus minimize cracking. The present study investigates elastic-plastically the viability of the proposed compliant layer concept. A detailed parametric study was conducted utilizing a unit cell model consisting of three concentric cylinders to determine the required character (i.e., thickness and mechanical properties) of the compliant layer as well as its applicability. The unknown compliant layer mechanical properties were expressed as ratios of the corresponding temperature dependent Ti-24Al-11Nb (a/o) matrix properties. The fiber properties taken were those corresponding to SCS-6 (SiC). Results indicated that the compliant layer can be used to reduce, if not eliminate, radial and circumferential residual stresses within the fiber and matrix and therefore also reduce or eliminate the radial cracking. However, with this decrease in in-plane stresses, one obtains an increase in longitudinal stress, thus potentially initiating longitudinal cracking. Guidelines are given for the selection of a specific compensating/ compliant material, given a perfectly bonded system.

S. M. Arnold↗

NASA NTRSDate not supplied

CFD Model Development of a Cryogenic Storage Tank Self-Pressurization in Normal Gravity and Validation against SHIIVER Experiment

Two-phase flow and heat transfer simulations with interfacial phase change of the Structural Heat Intercept, Insulation, and Vibration Evaluation Rig (SHIIVER) self-pressurization experiment were conducted using storage tank CFD model in the framework of the ANSYS Fluent CFD code. The simulations were performed for the 70% fill level case with MLI on domes and no vapor cooling. All the phase change calculations in these simulations were generated by in-house Schrage-based evaporation-condensation model. The calculations were performed using both the Volume of Fluid (VOF) and Sharp Interface multiphase 2D axisymmetric models. A number of parametric and sensitivity studies were performed to check the various aspects of the CFD model. These studies helped to understand the effects of varying several parameters on the tank pressure and temperature during self-pressurization. Turbulence modeling; turbulence damping at the interface; and using constant vs. temperature dependent fluid properties were shown to have the most profound influence on predicted tank pressures and temperatures. Current study indicates that including phase change at the interface into the computational model is crucial for accurate prediction of the tank self-pressurization process. The effect of accommodation coefficient was also studied. Tank pressure values predicted by the VOF, and Sharp Interface models are within 4% of the experimental ones.

Computational Fluid Dynamics↗

DOE OSTI2021

The Drell-Yan process with pions and polarized nucleons

The Drell-Yan process provides important information on the internal structure of hadrons including transverse momentum dependent parton distribution functions (TMDs). In this work we present calculations for all leading twist structure functions de- scribing the pion induced Drell-Yan process. The non-perturbative input for the TMDs is taken from the light-front constituent quark model, the spectator model, and available parametrizations of TMDs extracted from the experimental data. TMD evolution is implemented at Next-to-Leading Logarithmic precision for the first time for all asymmetries. Our results are compatible with the first experimental information, help to interpret the data from ongoing experiments, and will allow one to quantitatively assess the models in future when more precise data will become available.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2024

Spontaneous symmetry breaking, gauge hierarchy, and electroweak vacuum metastability

The so-called metastability bound asserts that an unnaturally small Higgs mass is a necessary condition for electroweak vacuum metastability, offering a new approach toward solving the hierarchy problem. So far, this result relies on the assumption of a negative Higgs mass parameter, or equivalently, on electroweak spontaneous symmetry breaking. We derive a new, corresponding bound for the case of a positive mass parameter. When the new bound is significantly more restrictive than or comparable to its established counterpart, it may offer an explanation for the sign of the Higgs mass parameter, and thus, spontaneous symmetry breaking itself. New physics at scales O ( 1 – 10 ) TeV can lower these bounds as far as the TeV scale. As an illustration, we consider vacuum stability in the presence of additional TeV-scale fermions with Yukawa couplings to the Higgs, as well as a dimension-six term parametrizing new physics in the UV. This scenario requires new physics that couples strongly to the Higgs, and can potentially be probed at future colliders. Finally, to allow for comparison with concrete mechanisms predicting metastability, we provide the mass-dependent lifetime of the electroweak vacuum for this model. Published by the American Physical Society 2024

Benevedes, Sean (ORCID:000000016390198X)↗

NASA NTRS1993

Modeling bristle lift-off in idealized brush seal configurations

We attempt in this paper to develop a model for the flow through brush seals and determine their elastic behavior in order to predict the dependence of brush/journal clearance on geometry and operating conditions. Several idealizations regarding brush seal configuration, flow conditions, and elastic behavior are made in the analysis in order to determine closed form parametric dependence. This formulation assumes that there is no initial interference between the bristle tip and the rotor. Also, interbristle, bristle-backing plate, and bristle-rotor friction is neglected. The bristle bundle or the brush seal as it is alternately called is assumed homogeneous and isotropic on a macroscopic scale so that a physical property like permeability is uniform. The fluid is assumed to be homogeneous, incompressible, viscous, and flowing under steady conditions. A schematic of a brush seal is shown. If the nominal bristle-shaft interference is absent then under static conditions the bristles may deflect axially due to the imposed pressure differential. This axial deflection may create a clearance permitting leakage flow in excess of that which occurs through the porous matrix formed by the bristle bundles. Under dynamic conditions the Couette flow created by shaft motion could be strong enough to cause bristle deflection and once again a clearance may develop. The paper proposes a means to determine this clearance (or at least describe its parametric dependence on geometry and operating conditions) under static as well as dynamic conditions.

Modi, Vijay↗

NASA NTRS1994

Theoretical studies of the solar atmosphere and interstellar pickup ions

Solar atmosphere research activities are summarized. Specific topics addressed include: (1) coronal mass ejections and related phenomena; (2) parametric instabilities of Alfven waves; (3) pickup ions in the solar wind; and (4) cosmic rays in the outer heliosphere. Also included is a list of publications covering the following topics: catastrophic evolution of a force-free flux rope; maximum energy release in flux-rope models of eruptive flares; sheet approximations in models of eruptive flares; material ejection, motions of loops and ribbons of two-ribbon flares; dispersion relations for parametric instabilities of parallel-propagating; parametric instabilities of parallel-propagating Alfven waves; beat, modulation, and decay instabilities of a circularly-polarized Alfven wave; effects of time-dependent photoionization on interstellar pickup helium; observation of waves generated by the solar wind pickup of interstellar hydrogen ions; ion thermalization and wave excitation downstream of the quasi-perpendicular bowshock; ion cyclotron instability and the inverse correlation between proton anisotrophy and proton beta; and effects of cosmic rays and interstellar gas on the dynamics of a wind.

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