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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 415 records · Page 23

Non-Invasive Electrode Impedance Estimation for Optimized Charge Profile Parameterization of Lithium-Ion Batteries

This work presents a non-invasive method for parameterizing a physically motivated equivalent circuit model of lithium-ion batteries using operando electrochemical impedance spectroscopy and time-domain data. The proposed model consists exclusively of linear circuit elements, enabling computationally efficient simulation and real-time implementation on battery management system chips. By integrating frequency- and time-domain measurements, the model accurately estimates internal states such as the negative electrode potential, achieving a root mean square error of 12.3 mV during fast charging validation. Parameterization requires only rate tests with sinusoidal perturbations at three different ambient temperatures, making the approach experimentally accessible. The model reveals key insights into battery behavior, including rate-dependent overpotentials primarily governed by charge transfer kinetics at the positive electrode, and temperature-dependent impedance contributions from both charge transfer and solid-state diffusion processes. Validation using reference electrodes confirms the model’s ability to detect lithium plating onset and reproduce impedance behavior across a wide range of operating conditions. The approach enables in situ optimization of fast charging profiles and lays the foundation for future extensions incorporating aging effects and plating dynamics.

25 ENERGY STORAGE↗

A Model for the Vortex Pair Associated with a Jet in a Cross Flow

A model is presented for the contrarotating vortex pair that is formed by a round, turbulent, subsonic jet directed normally into a uniform, subsonic cross flow. The model consists of a set of algebraic equations that describe the properties of the vortex pair as a function of their location in the jet plume. The parameters of the model are physical characteristics of the vortices such as the vortex strength, spacing, and core size. These parameters are determined by velocity measurements at selective points in the jet plume.

Sellers, William L.↗

Operations research investigations of satellite power stations

A systems model reflecting the design concepts of Satellite Power Stations (SPS) was developed. The model is of sufficient scope to include the interrelationships of the following major design parameters: the transportation to and between orbits; assembly of the SPS; and maintenance of the SPS. The systems model is composed of a set of equations that are nonlinear with respect to the system parameters and decision variables. The model determines a figure of merit from which alternative concepts concerning transportation, assembly, and maintenance of satellite power stations are studied. A hybrid optimization model was developed to optimize the system's decision variables. The optimization model consists of a random search procedure and the optimal-steepest descent method. A FORTRAN computer program was developed to enable the user to optimize nonlinear functions using the model. Specifically, the computer program was used to optimize Satellite Power Station system components.

Cole, J. W.↗

Modular design attitude control system

A sequence of single axismodels and a series of reduced state linear observers of minimum order are used to reconstruct inaccessible variables pertaining to the modular attitude control of a rigid body flexible suspension model of a flexible spacecraft. The single axis models consist of two, three, four, and five rigid bodies, each interconnected by a flexible shaft passing through the mass centers of the bodies. Modal damping is added to each model. Reduced state linear observers are developed for synthesizing the inaccessible modal state variables for each modal model.

Chichester, F. D.↗

Numerical and experimental evaluation for single-axis control of an LSS laboratory model

One of the major problems of LSS attitude control design stems from the modeling uncertainties due to modal truncation errors and modal parameter estimation errors. This modeling problem is investigated by evaluating poles and zeros of the frequency response functions, described in terms of constrained or unconstrained modes. The frequency domain approach is utilized to evaluated the results of modal analyses and direct output feedback controller experiments using a simple flexible spacecraft model consisting of a rigid primary body and flexible aluminum beam(s) with a control moment gyro as an actuator. The modal data are compared under the conditions that the model is constrained as the canti-lever and it is rotationally free on a single-axis air bearing table. In addition, the open-loop responses are experimentally examined under the impulsive disturbance to the appendage. The results of the control experiments show that the first vibration mode of the appendage and the interacted rotational motion of the primary body are damped in a short time as predicted by the numerical analysis, to produce damping ratio of 10-20%.

Ohkami, Y.↗

A simplified generic cryostat thermal model for predicting cryogen mass and lifetime

This study presents a simple generic cryostat thermal model developed for predicting cryogen mass and the lifetime of cryogenic space telescopes. The model is based on a lumped parameter representation of eight nodes and over 35 conductors. The major telescope Dewar components represented as nodes are the main cryogen tank, the three vapor-cooled shields, the outer shell, barrel baffle, and the barrel baffle heat exchanger. The input to the model consists of the vapor-cooled shield, support straps and instrument cable geometry, and the cryostat heat loads from the instrument and through the aperture. The predictions from the model were compared with those from the more detailed models of IRAS, COBE, and SIRTF. Correlation of the helium flow rates of the IRAS and COBE Dewars was 12 percent above the actual flight or ground test data and for SIRTF it was less than 2 percent of the prediction from the detailed model.

Birur, G. C.↗

Reduced Complexity Model Intercomparison Project Phase 2: Synthesizing Earth System Knowledge for Probabilistic Climate Projections

Over the last decades, climate science has evolved rapidly across multiple expert domains. Our best tools to capture state-of-the-art knowledge in an internally self-consistent modelling framework are the increasingly complex fully coupled Earth System Models (ESMs). However, computational limitations and the structural rigidity of ESMs mean that the full range of uncertainties across multiple domains are difficult to capture with ESMs alone. The tools of choice are instead more computationally efficient reduced complexity models (RCMs), which are structurally flexible and can span the response dynamics across a range of domain-specific models and ESM experiments. Here we present Phase 2 of the Reduced Complexity Model Intercomparison Project (RCMIP Phase 2), the first comprehensive intercomparison of RCMs that are probabilistically calibrated with key benchmark ranges from specialized research communities. Unsurprisingly, but crucially, we find that models which have been constrained to reflect the key benchmarks better reflect the key benchmarks. Under the low-emissions SSP1-1.9 scenario, across the RCMs, median peak warming projections range from 1.3 to 1.7°C (relative to 1850-1900, using an observationally-based historical warming estimate of 0.8°C between 1850-1900 and 1995-2014). Further developing methodologies to constrain these projection uncertainties seems paramount given the international community's goal to contain warming to below 1.5°C above pre-industrial in the long-term. Our findings suggest that users of RCMs should carefully evaluate their RCM, specifically its skill against key benchmarks and consider the need to include projections benchmarks either from ESM results or other assessments to reduce divergence in future projections.

Climate↗

Combining Force Fields and Neural Networks for an Accurate Representation of Chemically Diverse Molecular Interactions

A key goal of molecular modeling is the accurate reproduction of the true quantum mechanical potential energy of arbitrary molecular ensembles with a tractable classical approximation. The challenges are that analytical expressions found in general purpose force fields struggle to faithfully represent the intermolecular quantum potential energy surface at close distances and in strong interaction regimes; that the more accurate neural network approximations do not capture crucial physics concepts, e.g., nonadditive inductive contributions and application of electric fields; and that the ultra-accurate narrowly targeted models have difficulty generalizing to the entire chemical space. We therefore designed a hybrid wide-coverage intermolecular interaction model consisting of an analytically polarizable force field combined with a short-range neural network correction for the total intermolecular interaction energy. Here, we describe the methodology and apply the model to accurately determine the properties of water, the free energy of solvation of neutral and charged molecules, and the binding free energy of ligands to proteins. The correction is subtyped for distinct chemical species to match the underlying force field, to segment and reduce the amount of quantum training data, and to increase accuracy and computational speed. For the systems considered, the hybrid ab initio parametrized Hamiltonian reproduces the two-body dimer quantum mechanics (QM) energies to within 0.03 kcal/mol and the nonadditive many-molecule contributions to within 2%. Simulations of molecular systems using this interaction model run at speeds of several nanoseconds per day.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

A Bayesian Multi-fidelity Neural Network to Predict Nonlinear Frequency Backbone Curves

The use of structural mechanics models during the design process often leads to the development of models of varying fidelity. Often low-fidelity models are efficient to simulate but lack accuracy, while the high-fidelity counterparts are accurate with less efficiency. Here, this paper presents a multi-fidelity surrogate modeling approach that combines the accuracy of a high-fidelity finite element model with the efficiency of a low-fidelity model to train an even faster surrogate model that parameterizes the design space of interest. The objective of these models is to predict the nonlinear frequency backbone curves of the Tribomechadynamics Research Challenge benchmark structure which exhibits simultaneous nonlinearities from frictional contact and geometric nonlinearity. The surrogate model consists of an ensemble of neural networks that learn the mapping between low and high-fidelity data through nonlinear transformations. Bayesian neural networks are used to assess the surrogate model's uncertainty. Once trained, the multi-fidelity neural network is used to perform sensitivity analysis to assess the influence of the design parameters on the predicted backbone curves. Additionally, Bayesian calibration is performed to update the input parameter distributions to correlate the model parameters to the collection of experimentally measured backbone curves.

42 ENGINEERING↗

Spinning no-scale $${\mathcal {F}}$$-SU(5) in the right direction

Abstract The Fermi National Accelerator Laboratory (FNAL) recently announced confirmation of the Brookhaven National Lab (BNL) measurements of the $$g-2$$ g - 2 of the muon that uncovered a discrepancy with the theoretically calculated Standard Model value. We suggest an explanation for the combined BNL+FNAL 4.2 $$\sigma $$ σ deviation within the supersymmetric grand unification theory (GUT) model No-Scale $${\mathcal {F}}$$ F - $$SU(5)$$ S U ( 5 ) supplemented with a string derived TeV-scale extra $$10+\overline{10}$$ 10 + 10 ¯ vector-like multiplet and charged vector-like singlet $$(XE,XE^c)$$ ( X E , X E c ) , dubbed flippons. We introduced these vector-like particles into No-Scale Flipped SU (5) many years ago, and as a result, the renormalization group equation (RGE) running was immediately shaped to produce a distinctive and rather beneficial two-stage gauge coupling unification process to avoid the Landau pole and lift unification to the string scale, in addition to contributing through 1-loop to the light Higgs boson mass. The flippons have long stood ready to tackle another challenge, and now do so yet again, where the charged vector-like “lepton”/singlet couples with the muon, the supersymmetric down-type Higgs $$H_d$$ H d , and a singlet S , using a chirality flip to easily accommodate the muonic $$g-2$$ g - 2 discrepancy in No-Scale $${\mathcal {F}}$$ F - $$SU(5)$$ S U ( 5 ) . Considering the phenomenological success of this string derived model over the prior 11 years that remains accommodative of all presently available LHC limits plus all other experimental constraints, including no fine-tuning, and the fact that for the first time a Starobinsky-like inflationary model consistent with all cosmological data was derived from superstring theory in No-Scale Flipped SU (5), we believe it is imperative to reconcile the BNL+FNAL developments within the model space.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Comparison of Mars Atmospheric Density Estimates from Models to Measurements from Mars Global Surveyor (MGS) Data

A recent study (Desai, 2008) has shown that the actual landing sites of Mars Pathfinder, the Mars Exploration Rovers (Spirit and Opportunity) and the Phoenix Mars Lander have been further downrange than predicted by models prior to landing Desai's reconstruction of their entries into the Martian atmosphere showed that the models consistently predicted higher densities than those found upon entry, descent and landing. Desai's results have raised a question as to whether there is a systemic problem within Mars atmospheric models. Proposal is to compare Mars atmospheric density estimates from Mars atmospheric models to measurements made by Mars Global Surveyor (MGS). Comparison study requires the completion of several tasks that would result in a greater understanding of reasons behind the discrepancy found during recent landings on Mars and possible solutions to this problem.

Justh, Hilary L.↗

Aeroelastic Modeling of X-56A Stiff-Wing Configuration Flight Test Data

Aeroelastic stability and control derivatives for the X-56A Multi-Utility Technology Testbed (MUTT), in the stiff-wing configuration, were estimated from flight test data using the output-error method. Practical aspects of the analysis are discussed. The orthogonal phase-optimized multisine inputs provided excellent data information for aeroelastic modeling. Consistent parameter estimates were determined using output error in both the frequency and time domains. The frequency domain analysis converged faster and was less sensitive to starting values for the model parameters, which was useful for determining the aeroelastic model structure and obtaining starting values for the time domain analysis. Including a modal description of the structure from a finite element model reduced the complexity of the estimation problem and improved the modeling results. Effects of reducing the model order on the short period stability and control derivatives were investigated.

Grauer, Jared A.↗

Development of an Effective Finite-rate Oxidation Model for NuSil-coated Charred Carbon Preform Ablators

Recently, a detailed effective finite-rate surface chemistry model was developed for the oxidation of FiberForm [1] using the molecular beam experimental data of Poovathingal et al., [2]. FiberForm is the major building block of the thermal protection system (TPS) material Phenolic Impregnated Carbon Ablator (PICA), commonly used by NASA. The surface chemistry model consists of detailed surface reaction mechanisms such as adsorption, desorption, and several types of Langmuir-Hinshelwood (LH) reactions to characterize the oxygen-carbon interactions at the surface. This model provides excellent agreement with the experimental data for oxidation product compositions and corresponding translational energy distributions. Further, an effective oxidation model was constructed that captures the equivalent interaction of oxygen inside the microstructure (including multiple surface collisions) via a modified reactivity for a smooth wall boundary condition. This enables the use of this model directly into Computational Fluid Dynamics (CFD) codes and Material Response (MR) codes to accurately simulate the gas–surface interactions within FiberForm without using the detailed micro-structure. However, this effective model is valid only for the virgin FiberForm. As the TPS material undergoes ablation, the preform carbon burns and turns into char. In addition, PICA is also coated with a protective silicon coating called NuSil for the purpose of mitigating the spread of phenolic dust, and limit contamination during clean room operations. Fig. 1 shows a X-ray microtomography image of a charred NuSil-coated PICA. The NuSil layer introduces species containing silicon into the product mixture. Further, the reactivity of the carbon within the char layer is different from the virgin FiberForm as shown in Fig. 2. Recently a new set of molecular beam experiments were performed on this NuSil-coated TPS material [3] with the same type of oxygen beam used in the previous experiments. Using the latest experimental data, the previously developed effective model will be extended to account for the charred carbon as well as the NuSil coating. Finally, this new effective model with three phases – preform carbon, char, and NuSil; will be compared and validated against the experimental product compositions.

K Swaminathan Gopalan↗

ExaCA: A performance portable exascale cellular automata application for alloy solidification modeling

Modeling the as-solidified grain structures that form during alloy processing is a critical component in understanding process-property relationships, particularly for additive manufacturing (AM) where grain structure is very sensitive to processing conditions. While cellular automata (CA)-based models have proven able to predict aspects of microstructure for several alloys and AM process conditions, long run times and large resource sets required limit the utility and the problem size to which existing CA models can be applied. As part of the ExaAM project, an initiative within the Exascale Computing Project (ECP) to develop, test, and optimize an exascale-capable coupled and self-consistent model of AM parts, we developed ExaCA (https://github.com/LLNL/ExaCA) for the liquid–solid phase transformation in the wake of AM melt pools. The CA-based code is parallelized using MPI and the Kokkos programming model, the latter enabling simulation on both CPUs and GPUs within a single-source implementation. Here, we detail the steps taken to transform a baseline, MPI-based CA code into one that is performant on CPUs and GPUs. Performance testing of ExaCA on Summit (a pre-exascale machine at Oak Ridge National Laboratory) was used to quantify CPU–GPU speedup comparing with equal numbers of nodes. Testing showed comparable CPU performance to the MPI-only CA code and a 5-20x speedup when running AM-based test problems using GPUs. The improved performance of CA through GPU utilization and the performance portable nature of ExaCA will enable accurate part-scale modeling by harnessing the power of current and future generations of high performance computing resources. Future work will include improving the strong scaling of ExaCA on GPUs by reducing load imbalance associated with the locality of the problem, and continuing performance optimization across exascale hardware.

36 MATERIALS SCIENCE↗

SAM Enhancements and Model Developments for Molten-Salt-Fueled Reactors

To support the development and utilization of the SAM code for molten-salt-fueled reactor (MSR) safety analysis and licensing, an effort was devoted to enhancing code capabilities and developing reference models for the MSR primary loop. A reference standard problem of a prototypical reactor design is foundational to NRC to verify the adequacy of computer codes and evaluation models for a specific reactor type. A thermo-fluid model of the Molten Salt Reactor Experiment (MSRE) has been developed. The MSRE primary loop model consists of a 2-D core region and external core components in 1-D or 0-D. Both the steady-state and a transient scenario are simulated. The porous medium model is utilized for both the molten salt fluid channels and the moderator matrix in the MSRE core. The use of the porous medium model for the MSRE core is verified with the higher-fidelity simulation results using 1-D representations of the fluid channels and 3-D modeling of core structures. To further enhance SAM multi-scale simulation capabilities for MSRs, a mass transport model is developed and implemented in SAM multi-dimension flow module for modeling of species transport such as delayed neutron precursors in MSRs.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Solid rocket motor cost model

A systematic and standardized procedure for estimating life cycle costs of solid rocket motor booster configurations. The model consists of clearly defined cost categories and appropriate cost equations in which cost is related to program and hardware parameters. Cost estimating relationships are generally based on analogous experience. In this model the experience drawn on is from estimates prepared by the study contractors. Contractors' estimates are derived by means of engineering estimates for some predetermined level of detail of the SRM hardware and program functions of the system life cycle. This method is frequently referred to as bottom-up. A parametric cost analysis is a useful technique when rapid estimates are required. This is particularly true during the planning stages of a system when hardware designs and program definition are conceptual and constantly changing as the selection process, which includes cost comparisons or trade-offs, is performed. The use of cost estimating relationships also facilitates the performance of cost sensitivity studies in which relative and comparable cost comparisons are significant.

Harney, A. G.↗

Analytical study of the twin-jet shielding

The development of the analytical model of twin-jet shielding is summarized. The models consist of a point noise source impinging on a cylinder of heated flow in which the temperature and flow velocity are uniform cross the cross section. In the formulation of the model, the wave equations are written for the regions outside the flow and within the flow cylinder. The solutions to the wave equations are matched at the jet boundary under the conditions of continuity of pressure and continuity of the vortex sheet. The solution reduces to an indefinite integral involving Bessel functions. The integral is solved approximately using a saddle point method.

Gerhold, C. H.↗

Low-speed aerodynamic test of an axisymmetric supersonic inlet with variable cowl slot

The experimental low-speed aerodynamic characteristics of an axisymmetric mixed-compression supersonic inlet with variable cowl slot are described. The model consisted of the NASA P-inlet centerbody and redesigned cowl with variable cowl slot powered by the JT8D single-stage fan simulator and driven by an air turbine. The model was tested in the NASA Lewis Research Center 9- by 15-foot low-speed tunnel at Mach numbers of 0, 0.1, and 0.2 over a range of flows, cowl slot openings, centerbody positions, and angles of attack. The variable cowl slot was effective in minimizing lip separation at high velocity ratios, showed good steady-state and dynamic distortion characteristics, and had good angle-of-attack tolerance.

Powell, A. G.↗