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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 19 records

A multiscale design method using interpretable machine learning for phononic materials with closely interacting scales

Manipulating the dispersive characteristics of vibrational waves is beneficial for many applications, e.g., high-precision instruments. architected hierarchical phononic materials have sparked promise tunability of elastodynamic waves and vibrations over multiple frequency ranges. In this article, hierarchical unit-cells are obtained, where features at each length scale result in a band gap within a targeted frequency range. Our novel approach, the ‘‘hierarchical unit-cell template method,’’ is an interpretable machine-learning approach that uncovers global unit-cell shape/topology patterns corresponding to predefined band-gap objectives. A scale-separation effect is observed where the coarse-scale band-gap objective is mostly unaffected by the fine-scale features despite the closeness of their length scales, thus enabling an efficient hierarchical algorithm. Moreover, the hierarchical patterns revealed are not predefined or self-similar hierarchies as common in current hierarchical phononic materials. Furthermore, our approach offers a flexible and efficient method for the exploration of new regions in the hierarchical design space, extracting minimal effective patterns for inverse design in applications targeting multiple frequency ranges.

Architected materials↗

Bio-inspired multiscale design for perovskite solar cells

Metal halide perovskite semiconductors have attractive light-harvesting and charge-carrier transport properties for photovoltaics. Perovskite solar cells (PSCs) and modules have demonstrated their commercial promise with high power conversion efficiencies, but still face stability challenges. In this Review, we explore how biomaterials offer design inspiration for the development of durable and efficient PSCs at three different scales. At the molecular level, bio-inspired molecular interactions are harnessed towards crystallization control and degradation prevention, which offers an enhancement in long-term maximum-power-point tracking stability. At the microstructural level, self-healing and strength-enhancing strategies, utilizing dynamic bonds and interfacial reinforcement, can help PSCs to recover from physical damage and maintain high performance. At the device level, macroscopic functionalities, such as moth-eye-inspired structures tailored to different layers, can collectively enable antireflection, radiative cooling and self-cleaning to optimize light management, heat dissipation and encapsulation in PSCs. Bio-inspired PSC research can combine improved efficiency and lifetime, with abundant, biocompatible alternatives to conventional stabilizers. Future efforts should focus on screening bioinspired molecules to optimize film crystallization and stability, developing self-healing mechanisms triggered by operational stress, designing cost-efficient biomicrostructures, and integrating multifunctional encapsulation to enhance the efficiency and lifespan of PSCs.

Duan, Tianwei↗

Computational Modeling Approaches to Multiscale Design of Icephobic Surfaces

To aid in the design of surfaces that prevent icing, a model and computational simulation of impact ice formation at the single droplet scale was implemented. The nucleation of a single supercooled droplet impacting on a substrate, in rime ice conditions, was simulated. Open source computational fluid dynamics (CFD) software was used for the simulation. To aid in the design of surfaces that prevent icing, a model of impact ice formation at the single droplet scale was proposed•No existing model simulates simultaneous impact and freezing of a single super-cooled water droplet•For the 10-week project, a low-fidelity feasibility study was the goal.

adhesion↗

Advanced Materials for the Lunar Surface: Multiscale Computational Design of Refractory Alloys and Carbides

Emerging operational environments, such as the lunar surface, present novel challenges for NASA and drive the need for advanced materials in applications like fission surface power systems. To address these demands, computational materials science is rapidly evolving to augment or replace costly and hazardous empirical testing. Although materials selection at NASA remains predominantly experimentally driven, advanced simulation methodologies are being steadily integrated into the engineering lifecycle. This work details the application of multiscale simulation techniques—including first-principles calculations, CALPHAD, dislocation dynamics, and molecular dynamics—at NASA's Ames Research Center to evaluate advanced materials for extreme environments. First, we present contributions to the Space Nuclear Propulsion Project. Be-cause propellant channel coatings in nuclear thermal rockets must withstand high-pressure, high-temperature hydro-gen, optimizing these materials is critical. First-principles calculations were employed to establish a rigorous quantitative and qualitative understanding of the behavior of the refractory carbides ZrC, NbC, and their mixtures in high-enthalpy hydrogen environments. This necessitated the generation of high-fidelity thermodynamic models for both stoichiometric and carbon-depleted carbides, both with and without the presence of hydrogen. Furthermore, we highlight efforts under the Refractory Alloy Additive Manufacturing Build Optimization (RAAMBO) project, where existing and novel alloy compositions were assessed for additive manufacturing printability and subsequent performance in applications such as heat pipes and rocket nozzle extensions. This was accomplished through a comprehensive multiscale simulation framework that bridged the gap from the nanometer to the millimeter scale. Across both initiatives, rigorous validation against empirical data was prioritized. By systematically employing a verified and validated computational frame-work, we demonstrate how simulation effectively supports multidisciplinary engineering efforts, builds project-wide confidence, and drives critical materials development.

computational materials↗

Mechanical properties and deformation mechanisms of single crystal Mg micropillars subjected to high-strain-rate C-axis compression

Here, the mechanical properties and deformation mechanisms of single crystal magnesium under c-axis quasi-static and high-strain rate compressions are investigated through in situ scanning electron microscope (SEM) experiments and post-mortem transmission electron microscope (TEM) characterization. The findings revealed that ductility and high rates of hardening are preserved for pillars as large as 15 μm. Furthermore, rate effects result in a mild increase in flow stress with plastic deformations controlled primarily by the slip of type dislocations. Importantly and in contrast to other literature reports, plastic deformation occurs in the absence of twining. As the strain increases and plastic deformation exceeds about 4%, crystal rotation activates basal slip, <$\mathrm{a}$> type dislocations, resulting in a more rate independent flow stress. TEM observation on micropillars compressed at a strain rate of 250/s, revealed the activation of {${11}$$\bar{2}$$\bar{2}$} < $\bar{1}$$\bar{1}23$ > slip systems and high mobility of screw dislocations as major contributors to plastic strains in excess of 10% without fracture. These findings are relevant to the design of lightweight materials used in transportation systems, e.g., selection of material grain size. Moreover, the experimental data here reported provides the materials science community with a unique opportunity to validate discrete dislocation dynamics (DDD) formulations employed in multiscale design of materials.

36 MATERIALS SCIENCE↗

Multiscale modeling of packed-bed microwave reactors and estimation of intrinsic materials' permittivity

Modeling of packed-bed microwave reactors relies on an accurate representation of particle size, shape, and distribution within the bed, as well as the particles' dielectric properties. The measured permittivity of microwave susceptors (powders or structured materials) depends on the geometric features of the particles and the porosity of the bed, as well as the specific form factor of a structured material. These are effective properties and cannot be used to analyze other reactor configurations unless the geometric effects are removed. Therefore, we introduce a methodology for extracting the intrinsic particle permittivity from experimentally measured effective permittivity by combining cavity-based measurements with multiscale simulations and machine learning. Further, we develop the first multiscale model of packed-bed microwave reactors that incorporate particle effects (geometric features, random packing, and particle contact). This approach bridges macroscopic observables with mesoscopic physics, enabling analysis of local hotspots, arcing, and contact effects that control reactor performance. Using polymer-based spherical activated carbon (PBSAC) and silicon carbide (SiC) as examples, we demonstrate that the inferred particle permittivity is consistent with independent experimental heating profiles we collect from microwave reactors without adjustable parameters. Finally, this methodology establishes a foundation for predictive, multiscale design of microwave packed-bed reactors that explicitly accounts for particle-scale effects, enabling the estimation of intrinsic permittivity for the first time.

97 MATHEMATICS AND COMPUTING↗

Rapid Design of Cost-Effective Refractory High Entropy Alloys Strengthened by Precipitation

Funded by the ARPA-E ULTIMATE program, this project aims to develop cost-effective refractory high entropy alloys (RHEAs) for gas turbine blades applications at 1300 degree Celsius and above. The alloy design focuses on carbides precipitation strengthening in a strong and ductile solid solution BCC matrix. The goal is to achieve balanced mechanical properties including room temperature ductility & fracture toughness and high temperature strength and creep resistance, while maintaining comparable oxidation resistance and densities to Ni-base superalloys. To accelerate alloy design, multiscale modeling including CALPHAD and first-principles density functional theory (DFT) calculations and machine learning are performed. Specifically, high throughput phase diagram calculations and screening are carried out using CALPHAD; DFT calculations are performed to predict intrinsic ductility, grain boundary strengthening potential, coefficient of thermal expansion (CTE) and temperature-dependent elastic constants. Temperature dependent yield stress, creep strain and CTE are also predicted using machine learning. Down-selected alloys are synthesized in small buttons of about 250g using arc melting for rapid evaluation on microstructure and mechanical properties before employing plasma arc melting and additive manufacturing for producing large ingots. Preliminary computational and experimental results of this project will be presented and future direction in RHEA development will be discussed.

high temperature materials↗

Thermoplastic Matrix Composite Design for Cryotanks Using Multiscale Modeling and Bayesian Optimization

Designing lightweight, robust cryogenic storage tanks is critical for future launch vehicles, in-space propellant storage, and hydrogen powered aircraft. This work presents a multiscale modeling and Bayesian optimization framework for the design of thermoplastic matrix composite cryotanks. Molecular dynamics simulations are first used to determine temperature-dependent constituent properties for candidate thermoplastic matrices, which are homogenized to the lamina scale using NASA’s Multiscale Analysis Tool (NASMAT). These lamina properties, in combination with laminate family generation rules, are evaluated in HyperX structural optimization software to identify stacking sequences that meet all cryogenic load requirements. A Bayesian optimization framework is applied, with HyperX in the loop (via the HyperX API) to efficiently search across material and laminate design variables, yielding an optimized cryotank configuration with significant reductions in design cycle time compared to exhaustive search approaches.

thermoplastics↗

Comparison of Magnetospheric MultiScale (MMS) Formation Design Algorithms

The MMS mission consists of four identical spinning spacecraft in a tetrahedron-like formation during predefined orbital regions-of-interest [1]. The MMS formation will fly about a highly eccentric orbit to study magnetic reconnection in the Earth.s magnetosphere. The mission is divided in two main science phases of markedly different orbit size. Phase 1 is a 1.2 R(sub E) x 12 R(sub E) (R(sub E) equals one Earth radius) orbit phase where science will be performed on the day-side of the magnetosphere, and Phase 2 is a 1.2 R(sub E) x 25 R(sub E) orbit phase where science will be performed on the night-side of the magnetosphere. For each phase, the MMS formation initially will fly a series of tetrahedron sizes ranging between 10-km and 400-km to assist the science team in determining the best value for the remainder of the phase. This paper presents a preliminary comparison of the algorithms currently available to determine desired MMS formation states. After a brief description of the MMS formation flying metrics and associated requirements, the five formation design algorithm combinations considered here are presented. Monte Carlo simulations determine the performance of each algorithm defined in terms of formation lifetime and fuel consumption. Preliminary results focusing on the smaller formation size for Phase 1 are discussed and the conclusions are presented along with indications for future work.

Mann, L.↗

A Multiscale, Nonlinear, Modeling Framework Enabling the Design and Analysis of Composite Materials and Structures

A framework for the multiscale design and analysis of composite materials and structures is presented. The ImMAC software suite, developed at NASA Glenn Research Center, embeds efficient, nonlinear micromechanics capabilities within higher scale structural analysis methods such as finite element analysis. The result is an integrated, multiscale tool that relates global loading to the constituent scale, captures nonlinearities at this scale, and homogenizes local nonlinearities to predict their effects at the structural scale. Example applications of the multiscale framework are presented for the stochastic progressive failure of a SiC/Ti composite tensile specimen and the effects of microstructural variations on the nonlinear response of woven polymer matrix composites.

Bednarcyk, Brett A.↗

A Multiscale, Nonlinear, Modeling Framework Enabling the Design and Analysis of Composite Materials and Structures

A framework for the multiscale design and analysis of composite materials and structures is presented. The ImMAC software suite, developed at NASA Glenn Research Center, embeds efficient, nonlinear micromechanics capabilities within higher scale structural analysis methods such as finite element analysis. The result is an integrated, multiscale tool that relates global loading to the constituent scale, captures nonlinearities at this scale, and homogenizes local nonlinearities to predict their effects at the structural scale. Example applications of the multiscale framework are presented for the stochastic progressive failure of a SiC/Ti composite tensile specimen and the effects of microstructural variations on the nonlinear response of woven polymer matrix composites.

Bednarcyk, Brett A.↗

Design of a Variational Multiscale Method for Turbulent Compressible Flows

A spectral-element framework is presented for the simulation of subsonic compressible high-Reynolds-number flows. The focus of the work is maximizing the efficiency of the computational schemes to enable unsteady simulations with a large number of spatial and temporal degrees of freedom. A collocation scheme is combined with optimized computational kernels to provide a residual evaluation with computational cost independent of order of accuracy up to 16th order. The optimized residual routines are used to develop a low-memory implicit scheme based on a matrix-free Newton-Krylov method. A preconditioner based on the finite-difference diagonalized ADI scheme is developed which maintains the low memory of the matrix-free implicit solver, while providing improved convergence properties. Emphasis on low memory usage throughout the solver development is leveraged to implement a coupled space-time DG solver which may offer further efficiency gains through adaptivity in both space and time.

Design↗

Multiscale modeling-enabled design of multifunctional composites

This study aims to create a comprehensive model that considers multiple scales and physics for predicting the electromechanical behavior of fiber-reinforced composites enhanced with barium titanate (BaTiO3). In our earlier work, we have demonstrated that depositing BaTiO3 microparticles of 200-nm-diameter, on fiber surfaces during fiber-reinforced composite fabrication enhances mechanical strength, passive self-sensing, and energy harvesting properties. The key is to carefully control the microparticle concentration to prevent agglomeration. Since the particles are micron-sized, understanding how agglomeration affects the composites' electromechanical properties is crucial for guiding such multifunctional materials’ design. This study introduces a micromechanics-based approach to explore the impact of microparticle dispersion on the bulk composites' electromechanical properties. Insights gained from this investigation are applied in experiments, enabling accurate predictions of mechanical and self-sensing responses in BaTiO3-enhanced fiber-reinforced composites. Micro-level findings from this computational approach can be integrated into larger continuum models to comprehensively capture the electromechanical behavior of the composite structures at bulk scale. The proposed model is validated by comparing predictions with experimental results, accounting for the nonlinear mechanical and electromechanical behaviors of constituent materials. Consequently, this computational model serves as a digital platform for efficiently designing multifunctional composites.

Gupta, Sumit↗

Guided Design of Alloys

Using multiscale materials modeling, we are designing stronger alloys for the airspace applications. We focus on improving mechanical properties of materials at operating temperature. We employ basic science and fundamental theory for guided design of the next-generation alloys. Among the examples, we consider precipitated superalloys with a local phase transformation strengthening. We acknowledge funding by NASA’s Aeronautics Research Mission Directorate (ARMD) via Transformational Tools and Technologies (TTT) Project.

multiscale↗

Magnetospheric Multiscale (MMS) Mission Attitude Ground System Design

This paper describes the attitude ground system (AGS) design to be used for support of the Magnetospheric MultiScale (MMS) mission. The AGS exists as one component of the mission operations control center. It has responsibility for validating the onboard attitude and accelerometer bias estimates, calibrating the attitude sensors and the spacecraft inertia tensor, and generating a definitive attitude history for use by the science teams. NASA's Goddard Space Flight Center (GSFC) in Greenbelt, Maryland is responsible for developing the MMS spacecraft, for the overall management of the MMS mission, and for mission operations. MMS is scheduled for launch in 2014 for a planned two-year mission. The MMS mission consists of four identical spacecraft flying in a tetrahedral formation in an eccentric Earth orbit. The relatively tight formation, ranging from 10 to 400 km, will provide coordinated observations giving insight into small-scale magnetic field reconnection processes. By varying the size of the tetrahedron and the orbital semi-major axis and eccentricity, and making use of the changing solar phase, this geometry allows for the study of both bow shock and magnetotail plasma physics, including acceleration, reconnection, and turbulence. The mission divides into two phases for science; these phases will have orbit dimensions of 1.2 x 12 Earth radii in the first phase and 1.2x25 Earth radii in the second in order to study the dayside magnetopause and the nightside magnetotail, respectively. The orbital periods are roughly one day and three days for the two mission phases. Each of the four MMS spacecraft will be spin stabilized at 3 revolutions per minute (rpm), with the spin axis oriented near the ecliptic north pole but tipped approximately 2.5 deg towards the Sun line. The main body of each spacecraft will be an eight-sided platform with diameter of 3.4 m and height of 1.2 m. Several booms are attached to this central core: two axial booms of 14.9 m length, two radial magnetometer booms of 5 m length, and four radial wire booms of 60 m length. Attitude and orbit control will use a set of axial and radial thrusters. A four-head star tracker and a slit-type digital Sun sensor (DSS) provide input for attitude determination. In addition, an accelerometer will be used for closed-loop orbit maneuver control. The primary AGS product will be a daily definitive attitude history. Due to power limitations, the star tracker and accelerometer data will not be available at all times. However, tracker data from at least 10 percent of each orbit and continuous DSS data will be provided. An extended Kalman filter (EKF) will be used to estimate the three-axis attitude (i.e., spin axis orientation and spin phase) and rotation rate for all times when the tracker data is valid. For other times, the attitude is generated by assuming a constant angular momentum vector in the inertial frame. The DSS sun pulse will provide a timing signal to maintain an accurate spin phase. There will be times when the Sun is occulted and DSS data is not available. If this occurs at the start or end of a definitive attitude product, then the spin phase will be extrapolated using the mean rate determined by the EKF.

Sedlak, Joseph E.↗

Magnetospheric Multiscale (MMS) Mission Attitude Ground System Design

This paper describes the attitude ground system (AGS) design to be used for support of the Magnetospheric MultiScale (MMS) mission. The AGS exists as one component of the mission operations control center. It has responsibility for validating the onboard attitude and accelerometer bias estimates, calibrating the attitude sensors and the spacecraft inertia tensor, and generating a definitive attitude history for use by the science teams. NASA's Goddard Space Flight Center (GSFC) in Greenbelt, Maryland is responsible for developing the MMS spacecraft, for the overall management of the MMS mission, and for mission operations. MMS is scheduled for launch in 2014 for a planned two-year mission. The MMS mission consists of four identical spacecraft flying in a tetrahedral formation in an eccentric Earth orbit. The relatively tight formation, ranging from 10 to 400 km, will provide coordinated observations giving insight into small-scale magnetic field reconnection processes. By varying the size of the tetrahedron and the orbital semi-major axis and eccentricity, and making use of the changing solar phase, this geometry allows for the study of both bow shock and magnetotail plasma physics, including acceleration, reconnection, and turbulence. The mission divides into two phases for science; these phases will have orbit dimensions of l.2xl2 Earth radii in the first phase and l.2x25 Earth radii in the second in order to study the dayside magnetopause and the nightside magnetotail, respectively. The orbital periods are roughly one day and three days for the two mission phases. Each of the four MMS spacecraft will be spin stabilized at 3 revolutions per minute (rpm), with the spin axis oriented near the ecliptic north pole but tipped approximately 2.5 deg towards the Sun line. The main body of each spacecraft will be an eight-sided platform with diameter of 3.4 m and height of 1.2 m. Several booms are attached to this central core: two axial booms of 14.9 m length, two radial magnetometer booms of 5 m length, and four radial -wire booms of 60 m length. Attitude and orbit control will use a set of axial and radial thrusters. A four-head star tracker and a slit-type digital Sun sensor (DSS) provide input for attitude determination. In addition, an accelerometer will be· used for closed-loop orbit maneuver control. The primary AGS product will be a daily definitive attitude history. Due to power limitations; the star tracker and accelerometer data will not be available at all times. However, tracker data from at least 10 percent of each orbit and continuous DSS data will be provided. An extended Kalman filter (EKF) will be used to estimate the three-axis attitude (i.e., spin axis orientation and spin phase) and rotation rate for all times when the tracker data is valid. For other times, the attitude is generated by assuming a constant angular momentum vector in the inertial frame. The DSS sun pulse will provide a timing signal to maintain an accurate spin phase. There will be times when the Sun is occulted and DSS data is not available. If this occurs at the start or end of a definitive attitude product, then the spin phase will be extrapolated using the mean rate determined by the EKF.

Sedlak, Joseph E.↗

Macro-micro multiscale modeling to assist the design of HPDC Al castings microstructure and alloys for EV super-large body structures (Phase 1)

Implementation of High Pressure Die Casting (HPDC) Aluminum (Al) body structures for high volume electrified vehicles (EV) to improve electric efficiency remains a key strategy within many original equipment manufacturers (OEM)s. In addition to high strength for safety requirements, superior Self Piercing Riveting (SPR) performance is demanded for HPDC Al alloys to be compatible with high volume SPR joining. In this work, it is proposed to extend and validate an existing Contractor finite element multiscale macro-micro modeling approach to quantify the influence of the microstructure of HPDC alloys on the fracture strain/displacement under 3-point bend and clinch testing. The success of this work will allow to replace solution treatment stage with low energy consumption heat treatment (HT) processes, or to design new non heat treatable (NHT) HPDC Al alloys to eliminate HT requirements. Ultimately, this project will facilitate the application of HPDC Al alloys for super-large vehicle structures to significantly reduce vehicle weight and thus improving energy efficiency. The purpose of this project is to extend and validate an existing f

99 GENERAL AND MISCELLANEOUS↗