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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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Dynamic structural behavior of large rocket booster synthesized by two thin-walled cylinders and subjected to periodically varying end thrust
Multimodal luminescent materials, while promising for anti-counterfeiting, often lack dynamic time-dependent responses and controllable spatial distribution, limiting their encryption capabilities in the spatiotemporal dimension. Here, this work presents a coordinated control strategy based on entropy and defect engineering, and uses a backpropagation (BP) neural network for material screening to successfully prepare spinel Mg 0.8 (Fe 0.04 Co 0.04 Ni 0.04 Cu 0.04 Zn 0.04 )Cr 2 O 4 (MgA 5 CO) phosphors with time-dependent dynamic luminescence behavior. This phosphor simultaneously activated the d-d transition luminescence (∼618 nm) derived from Co 2+ /Cr 3+ and the defect luminescence (∼398 nm) related to zinc vacancies (V Zn ) in a single-phase solid solution. The phosphor exhibits a time-dependent color evolution from pink to purple under fixed-wavelength excitation, due to the different excited-state dynamics and decay lifetimes associated with the d-d transition and defect luminescence. Structural characterization and spectral analysis confirmed the existence of V Zn and its significant role in defect luminescence process. The fluorescent and dynamic luminescent properties of entropy-based spinel oxide enable its use in advanced anti-counterfeiting applications like fingerprint recognition and color-changing dedicated anti-counterfeiting mark, showing promise in high-end and time-dynamic anti-counterfeiting fields. This research not only developed a new type of fluorescent dynamic anti-counterfeiting material, but also provided a new idea for constructing advanced optical functional materials with multiple luminescence mechanisms.
Jet plume impingement forces acting on large flexible space structures may precipitate dynamically unstable behavior during space flights. Typical operating conditions in space involve rarefied gas flow regimes which are intrinsically distinct from continuum gas flow and are normally modeled using the kinetic theory of gas flow. Docking and undocking operations of the Space Shuttle with the Russian Mir space laboratory represent a scenario in which the stability boundaries of solar panels may be of interest. Extensive literature review of research work on the dynamic stability of rectangular panels in rarefied gas flow conditions indicated the lack of published reports dealing with this phenomenon. A recently completed preliminary study for NASA JSC dealing with the mathematical analysis of the stability of two-degree-of-freedom elastically supported rigid panels under the effect of rarefied gas flow was reviewed. A test plan outline is prepared for the purpose of conducting a series of experiments on four rectangular rigid test articles in a vacuum chamber under the effect of continuous and pulsating Nitrogen jet plumes. The purpose of the test plan is to gather enough data related to a number of key parameters to allow the validation of the two-degree-of-freedom mathematical model. The hardware required careful design to select a very lightweight material while satisfying rigidity and frequency requirements within the constraints of the test environment. The data to be obtained from the vacuum chamber tests can be compared with the predicted behavior of the theoretical two-degree-of-freedom model. Using the data obtained in this study, further research can identify the limitations of the mathematical model. In addition modifications to the mathematical model can be made, if warranted, to accurately predict the behavior of rigid panels under rarefied gas flow regimes.
Fiber reinforced polymer composites are finding applications in the automotive space for structurally critical applications including crash management. The use of recycled carbon fiber reinforcement can greatly reduce carbon emissions. In this study, recycled carbon fiber composites were manufactured into a self-supporting geometry using three matrices: polyphenylene sulfide (PPS), acrylonitrile butadiene styrene (ABS), and a structural epoxy, and subsequently crushed between flat platens at dynamic rates ranging from 4.6 to 9.1 ms -1 at temperatures in a range of -40°C to 80°C. Load-displacement data was used to evaluate their specific energy absorption, crush efficiency, and steady-state crush stress. Further, the energy absorption of the ABS composites was strongly sensitive to temperature, while the PPS composites exhibited strong crush efficiency dependence with both rate and temperature. The epoxy composites exhibited stable crush behavior at dynamic crush rates but exhibited a dramatic reduction in crush efficiency relative to quasi-static tests. The results of this study indicate that recycled fiber composites can achieve very high energy absorption levels (50–80kJkg -1 at room temperature) that make them an excellent alternative to more expensive and less environmentally friendly continuous virgin fiber laminates.
Abstract The spatial features of ultrafast changes in magnetic textures carry detailed information on microscopic couplings and energy transport mechanisms. Electrons excel in imaging such picosecond or shorter processes at nanometer length scales. We review the range of physical interactions that produce ultrafast magnetic contrast with electrons, and specifically highlight the recent emergence of ultrafast Lorentz transmission electron microscopy. From the fundamental processes involved in demagnetization at extremely short timescales to skyrmion-based devices, we show that ultrafast electron imaging will be a vital tool in solving pressing problems in magnetism and magnetic materials where nanoscale inhomogeneity, microscopic field measurement, non-equilibrium behavior or dynamics are involved. Graphic abstract
A plurality of monitoring nodes may each generate a time-series of current monitoring node values representing current operation of a cyber-physical system. A feature-based forecasting framework may receive the time-series of and generate a set of current feature vectors using feature discovery techniques. The feature behavior for each monitoring node may be characterized in the form of decision boundaries that separate normal and abnormal space based on operating data of the system. A set of ensemble state-space models may be constructed to represent feature evolution in the time-domain, wherein the forecasted outputs from the set of ensemble state-space models comprise anticipated time evolution of features. The framework may then obtain an overall features forecast through dynamic ensemble averaging and compare the overall features forecast to a threshold to generate an estimate associated with at least one feature vector crossing an associated decision boundary.
Faceted grain boundaries can migrate in interesting and unexpected ways. For example, faceted Σ11 <110> tilt grain boundaries were observed to exhibit mobility values that could be strongly dependent on the direction of migration. In order to understand whether this directionally-anisotropic mobility is a general phenomenon and to isolate mechanistic explanations for this behavior, molecular dynamics simulations of bicrystals evolved under an artificial driving force are used to study interface migration for a range of boundary plane inclination angles and temperatures in multiple face centered cubic metals (Al, Ni, and Cu). We find that directionally anisotropic mobility is active in a large fraction of these boundaries in Ni and Cu and should therefore impact the coarsening of polycrystalline materials. On the other hand, no such anisotropy is observed in any of the Al boundaries, showing that this behavior is material-dependent. Migration of the faceted boundaries is accomplished through transformation events at facet nodes and incommensurate boundary plane facets, which are termed shuffling modes. Three major shuffling modes have been identified, namely Shockley shuffling, slip plane shuffling, and disordered shuffling. A shift from the first two ordered modes to the third disordered mode is found to be responsible for reducing or removing directionally-anisotropic mobility, especially at the highest temperatures studied.
Adaptable, Deployable, Entry, and Placement Technology (ADEPT) is a combination of a heatshield and an aerodynamic decelerator for atmospheric entry applications. The ADEPT Sounding Rocket (SR)-1 mission was a suborbital flight experiment of an 0.7 m-diameter ADEPT to verify system-level performance and to characterize dynamic stability behavior. The aerodynamic database for ADEPT SR-1 was constructed from non-continuum and continuum flowfield computations, along with data from recent ADEPT ground testing and the IRVE-3 flight test vehicle. High-altitude (free-molecular and transitional regimes) data were generated using DSMC methods. Pre-flight predictions of continuum static aerodynamics coefficients were derived from Reynolds-Averaged Navier-Stokes solutions at conditions along a design trajectory, with comparisons to available ground test data of the nano-ADEPT geometry. Dynamic pitch damping characteristics were taken from functional forms developed for the IRVE-3 flight test vehicle through ballistic range testing. Comparison of pre-flight predictions to post-flight reconstruction of aerodynamic force and moment coefficients is presented.
Dynamic hemiwicking behavior is observable in both nature and a wide range of industrial applications ranging from biomedical devices to thermal management. We present a semi-analytical modeling framework (without empirical fitting coefficients) to predict transient capillary-driven hemiwicking behavior of a liquid through a nano/microstructured surface, specifically a micropillar array. In our model framework, the liquid domain is discretized into micropillar unit cells to enable the time marching of the hemiwicking front. A simplified linear pressure drop is assumed along the hemiwicking length such that the local meniscus curvature, contact angle, and effective liquid height are determined at each time step in our transient model. This semi-analytical model is validated with experimental data from our own experiments and from published literature for different fluids. Our model predicts hemiwicking dynamics with <20% error over a broad range of micropillar geometries with height-to-pitch ratio ranging between ≈0.34 and 6.7 and diameter-to-pitch ratio in the range of ≈0.25–0.7 and without any fitting parameters. For lower diameter-to-pitch ratio data points related to sparse micropillar array arrangements, we suggest modifications to the semi-analytical model. This work sheds light on complex and dynamic solid–liquid–vapor interfacial interactions which could serve as a guide for the design of textured surfaces for wicking enhancement in multi-phase thermal and mass transport technologies and applications.
This report details the heat source impact testing performed at the Shock Thermodynamics Applied Research Facility (STAR). The purpose of these tests were to measure the impact behavior of a heated Ta-10W tantalum/tungsten alloy heat source exemplar. Each exemplar resembled a cylinder with a rectangular through-hole orthogonal to the cylinder axis-of-symmetry. In each test, the exemplar was impacted by a hardened steel impactor accelerated using the STAR air gun. The exemplars were impacted perpendicular to the through-hole and at an an angle to the cylindrical axis-of-symmetry. The exemplar bar stock source, impact angle, and impact velocity were varied throughout the testing series. High-speed video was used to measure dynamic impact behavior while photon doppler velocimetry (PDV) and shorting pins were used to measure the impact velocity. Foam support structures were used to thermally isolate the exemplar and provide a support structure which was non-perturbative to the impact event. Soft-catch techniques were used to minimize secondary impacts and enable recovery for detailed post-shot analysis. Results indicate positive correlation between exemplar fracture and the variables of impact velocity and impact angle. Exemplar fracture occurred consistently along a single corner of the through-hole.
An analytical model is derived to study the structural dynamic stability behavior for the free-flying heliogyro solar sail consisting of a finite set of symmetric or evenly distributed thin blades on a flat surface. Key properties of the flutter instability are described in terms of the relationship among the eigenvalues and eigenvectors associated with a flutter instability frequency. Various simulation cases for an idealized single blade, fixed rotational speed heliogyro model, and a generalized multi-bladed, freely spinning heliogyro model are presented to show how the flutter instability frequencies change as a function of the solar radiation pressure and the size of the dynamic model. Convergence of the flutter instability frequency versus the system order is demonstrated.
Alternative models of cell mechanics depict the living cell as a simple mechanical continuum, porous filament gel, tensed cortical membrane, or tensegrity network that maintains a stabilizing prestress through incorporation of discrete structural elements that bear compression. Real-time microscopic analysis of cells containing GFP-labeled microtubules and associated mitochondria revealed that living cells behave like discrete structures composed of an interconnected network of actin microfilaments and microtubules when mechanical stresses are applied to cell surface integrin receptors. Quantitation of cell tractional forces and cellular prestress by using traction force microscopy confirmed that microtubules bear compression and are responsible for a significant portion of the cytoskeletal prestress that determines cell shape stability under conditions in which myosin light chain phosphorylation and intracellular calcium remained unchanged. Quantitative measurements of both static and dynamic mechanical behaviors in cells also were consistent with specific a priori predictions of the tensegrity model. These findings suggest that tensegrity represents a unified model of cell mechanics that may help to explain how mechanical behaviors emerge through collective interactions among different cytoskeletal filaments and extracellular adhesions in living cells.
The world’s electric power grids have evolved over the last 120 years from a single power line to today’s large networks. The evolution will continue at an accelerated rate with extensive smart grid development worldwide. Here for example, the U.S. government has set a goal of reaching 100 percent carbon pollution-free electricity by 2035, while the Department of Energy (DOE) shared a goal to deploy 30 GW and 110 GW of offshore wind by 2030 and 2050, respectively. To meet such ambitious goals, in the years to come, a significant percentage of electricity will come from intermittent renewable sources, electric vehicles (EVs), and be supplied to a vast number of loads that will actively respond to grid conditions and incentive signals. This development is largely driven by environmental and economic factors, such as reducing carbon emissions and saving electricity cost for consumers. These energy resources lead to new uncertain behaviors and dynamics which the grid has never seen and were not considered in its design. Operating such a dynamic grid with sufficient reliability and efficiency is a monumental challenge.
We present results from a series of experiments where an airfoil is pitched at constant rate from 0 to 60 degrees angle of attack. It is well documented that the dynamic stall behavior of such an airfoil strongly depends on the nondimensional pitch rate K = dot-alpha C/(2U(sub infinity)), where C is the chord, dot-alpha the constant pitch rate, and U(sub infinity) the free stream speed. In reality, the actual motion of the airfoil deviates from the ideal ramp due to the finite acceleration and deceleration periods imposed by the damping of drive system and response characteristics of the airfoil. It is possible that the pitch rate alone may not suffice in describing the flow and that the details of the motion trajectory before achieving a desired constant pitch rate may also affect the processes involved in the dynamic stall phenomenon. The effects of acceleration and deceleration periods are investigated by systematically varing the acceleration magnitude and its duration through the initial acceleration phase to constant pitch rate. The magnitude and duration of deceleration needed to bring the airfoil motion to rest is similarly controlled.
Catalytic reaction networks of multiple elementary steps operating under dynamic conditions via a programmed input oscillation are difficult to interpret and optimize due to reaction system complexity. To understand these dynamic systems, individual elementary catalytic reactions oscillating between catalyst states were evaluated to identify their three fundamental characteristics that define their ability to promote reactions away from equilibrium. First, elementary catalytic reactions exhibit directionality to promote reactions forward or backward from equilibrium as determined by a ratchet directionality metric comprised of the input oscillation duty cycle and the reaction rate constants. Second, catalytic ratchets are defined by the catalyst state of strong or weak binding that permit reactants to proceed through the transition state. Third, elementary catalytic ratchets exhibit a cutoff frequency which defines the transition in applied frequency for which the catalytic ratchet functions to promote chemistry away from equilibrium. All three ratchet characteristics are calculated from chemical reaction parameters including rate constants derived from linear scaling parameters, reaction conditions, and catalyst state. The characteristics of the reaction network’s constituent elementary catalytic reactions provided an interpretation of complex reaction networks and a method of predicting the behavior of dynamic surface chemistry on oscillating catalysts.
With the increasing integration of variable renewable energy sources into power systems, the role of flexible power generation technologies like gas turbines (GT) in rapid grid balancing remains crucial. This sustained importance underscores the need for scaled and precise modeling of GT to ensure effective integration within evolving energy frameworks. While physics-driven GT models integrate thermodynamics, fluid dynamics, and combustion principles, they often rely on approximate mathematical representations to accommodate scaling that may not capture the actual complex dynamics for GTs and inertial effects associated to GTs with different ratings. In this study, a data-driven model is proposed using machine learning (ML) techniques to conduct GT scalability analysis and performance evaluation with high accuracy. The ML model, trained on data from various operating conditions and performance parameters, aims to uncover intricate relationships and patterns, resembling GT characteristics at different scales (ratings). The model is developed to capture complex system interaction and to adapt to changing operational scenarios at different capacities, providing valuable insights of power system dynamics. In this study, the real-time digital simulator platform was employed to generate training data for the ML model and assess its dynamic characteristics. The ultimate objective was to develop a detailed modeling framework based on governing equations and data-driven ML capable of predicting key performance indicators, in thermal systems such as GTs, including power output, speed, fuel consumption, and exhaust temperature under diverse operating conditions at different scales. The developed ML framework demonstrated high accuracy, with mean relative errors for GT power prediction, reference speed, exhaust temperature, and compressor pressure ratio (CPR) parameters consistently below 0.1% across typical load fluctuation scenarios. Maximum deviations were limited to approximately 0.5 K for exhaust temperature and 0.009 for CPR, underscoring the model’s ability to replicating dynamic GT behavior with high precision. The adaptability of the ML model enables its application across diverse operational conditions and its extension to other thermal systems. By leveraging advanced ML techniques, this study presents a robust and scalable modeling framework that enhances GT simulation precision, facilitating improved integration into evolving power systems.
Solar-tracking photovoltaic arrays are susceptible to aeroelastic fluttering during high-wind events. This dynamic fluttering behavior can grow in amplitude until the panels enter an unstable mode known as torsional galloping which can lead to panel failure or total array destruction. To better understand the physics of the torsional galloping phenomenon and to inform the discussion around panel design and recommended panel stow positions during high wind events, a fluid-structure interaction solver composed of a simulated atmospheric boundary layer with simplified panel structural responses was designed. The simulation choices and features of this solver were informed by the geometry and physical properties of an experimental panel array known to exhibit torsional galloping behavior during hind-wind events. Furthermore, these simulations revealed that the torsional galloping instability is driven by a combination of cyclic vortex shedding from the sun-facing side of the panel and the elastic properties of the torque tube linking the panel assemblies. Testing different stow angles across a range of wind speeds indicates that panels are generally more stable when stowed at negative angles where the leading edge is closer to the ground, hypothesized to be due to ground-blocking effects. These results are supplemented by a discussion of stability trends noted during testing and possible implications when considering multi-row array interactions.
Effect of dynamic recrystallization (DRX) on the grain refinement and texture modification was studied by conducting a series of hot compression on AZ31B Mg alloy. Processing-grain size-texture maps were established as a function of temperature, strain rate, strain, and the Zener-Hollomon parameter (Z). Moreover, influence of simultaneous changes in the grain size and texture on tensile yield strength and ductility of the hot-worked Mg alloy was studied using the grain size and texture maps established. The processing-grain size map showed that the DRX grain size decreased with the increase in Z, also revealing various characteristics ranging from a grain growth, grain refinement, to a bimodal distribution of ultrafine grains and partially recrystallized grains. The effect of twinning on the grain refinement was also evident at high Z conditions. The processing-texture map revealed that the initial fiber texture was altered significantly to a shear, off-normal, or extension-twin texture with the increase in Z. The Schmid-factor maps were calculated to identify a dominant deformation mode during a subsequent tensile deformation of the hot-worked samples. Finally, a corresponding Hall-Petch relationship for each dominant deformation mode was used to establish tensile yield-strength maps, which agree well with the measured data.