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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 559 records · Page 31
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Effect of Surface Ionic Screening on Polarization Reversal and Phase Diagrams in Thin Antiferroelectric Films for Information and Energy Storage

Emergent behaviors in antiferroelectric thin films due to a coupling between surface electrochemistry and intrinsic polar instabilities are explored within the framework of the modified 2-4-6 Landau-Ginzburg-Devonshire (LGD) thermodynamic approach. By using phenomenological parameters of the LGD potential for a bulk antiferroelectric and a Stephenson-Highland (SH) approach, we study the role of surface ions with a charge density proportional to the relative partial oxygen pressure on the dipole states and their reversal mechanisms in antiferroelectric thin films. The combined LGDSH approach allows the boundaries of antiferroelectric, ferroelectriclike antiferroionic, and electretlike paraelectric states as a function of temperature, oxygen pressure, surface-ion formation energy and concentration, and film thickness to be delineated. This approach also allows the characterization of the polar and antipolar orderings dependence on the voltage applied to the antiferroelectric film, as well as the analysis of their static and dynamic hysteresis loops. Furthermore, the applications of the antiferroelectric films covered with a surface-ion layer for energy and information storage are explored and discussed.

25 ENERGY STORAGE↗
DOE OSTI2021

Pilot Testing of a Modular Oxygen Production System Using Oxygen Binding Adsorbents (Final Report)

In this project, RTI and Air Liquide have focused on the development of innovative oxygen separation materials and technologies based on reversibly binding of oxygen to enable smaller and cheaper air separations. In alignment with that object the team has had multiple achievements to advance the technology including: Synthesized and characterized novel M-CoSalen (RTIO2Sorb-1) material which showed a dynamic oxygen adsorption capacity in excess of 1wt%. Developed synthesis routes for RTIO2Sorb-1 with commercially relevant techniques and produced batches of 0.25kg and over 4 kg of total synthesis. Synthesized and characterized extrudate forms of the RTIO2Sorb-1 with relevant crush strength and maintained dynamic oxygen adsorption capacity in near 1wt%. Developed techniques for forming structured beds in fiber shapes with conventional materials. Developed a model for O 2 sorption processes to analyze various bed configurations and cycle parameters. Studied classic O 2 solid sorbents reported in the literature to learn oxygen binding mechanisms. Design a 10 kg/day O 2 VPSA pilot system with 2 or 4-bed operation. Completed a techno-economic analysis based on the experimental results and modeling. The overall objective of the project was to design, fabricate, and test a modular O 2 production system and perform a techno-economic analysis (TEA) after testing to determine the cost-benefit of the advanced modular air separation system. The goals of this technology development project were to achieve a bed-size factor (BSF) of less than 600 lb-adsorbent/TPD O 2 (ton/day O 2 ) (as compared with the state-of-the-art BSF of 850), and O 2 -purity greater than 95% at a cost that is projected to be equivalent or lower than the current state of the art (SOTA), commercially available large-scale cryogenic air separation systems. To achieve these goals and objective, the project team executed on (1) oxygen binding adsorbent optimization and scale up, (2) adsorbent material formation process studies to form the adsorbent material into structured beds for rapid pressure swing adsorption (PSA) cycles with low pressure drop, fast mass transfer, and low attrition, (3) cycle development studies to optimize the PSA process, and (4) develop simulation tools for rapid cycle modeling and numerical evaluation/optimization.

20 FOSSIL-FUELED POWER PLANTS↗
DOE OSTI2024

Power generation forecasting for solar plants based on Dynamic Bayesian networks by fusing multi-source information

A Dynamic Bayesian network (DBN) model for solar power generation forecasting in solar plants is proposed in this paper. The key idea is to fuse sensor data, operational indicators, meteorological data, lagged output power information, and model errors for more accurate short-term (e.g., hours) and mid-term (e.g., days to weeks) power generation forecasting. The proposed DBN augments automated data-driven structure learning with expert knowledge encoding using continuous and categorical data given constraints to represent causal relationships within a solar inverter system. Additionally, an error compensation mechanism is proposed to capture temporal fluctuation. The effectiveness of the DBN on solar power generation forecasting was evaluated by rolling window analysis with one-year testing data collected from a local solar plant. The proposed DBN is compared with four state-of-art methods including support-vector regression (SVR), k-nearest neighbors (kNN), artificial neural network (ANN), and long short-term memory (LSTM) models. The result show that the proposed DBN achieves better accuracy in general, and it is not as data-hungry as some neural network-based models. The proposed DBN is also shown to have robust and consistent forecasting power with different forecasting horizons. The accuracy is 92% - 95% from one hour to one week ahead forecasting.

14 SOLAR ENERGY↗
DOE OSTI2021

A moving morphable component‐based topology optimization approach considering transient structural dynamic responses

Abstract A novel approach is developed under the moving morphable component (MMC) framework to solve topology optimization problems considering transient structural dynamic responses, where the structure for optimization is constructed with a collection of structural components, and the structural layout can be described explicitly via only a small number of design variables characterizing the positions and geometries of the components. The transient dynamic response of the structure and corresponding sensitivities are computed via step‐by‐step numerical integration and mode reduction technique is also employed to enhance the computational efficiency. Compared with existing works, the numerical instabilities induced by localized vibration modes can be substantially alleviated and the computational effort for direct sensitivity analysis is significantly reduced in the proposed approach. Two and three‐dimensional numerical examples considering the cases of nonproportional damping mechanism and time‐varying mass are also provided to manifest the validity of the proposed approach.

Li, Jialin↗
DOE OSTI2022

Numerical investigation of the influence of shear and thermal stratification on the wind turbine tip‐vortex stability

Summary The interaction between wind turbine wakes and atmospheric turbulence is characterised by complex dynamics. In this study, two major components of the atmospheric boundary layer dynamics have been isolated, namely, the mean velocity profile shear and the thermal stratification, to examine their impact on the near‐wake development by undertaking a series of highly resolved large‐eddy simulations. Subsequently, instantaneous flow fields are extracted from the simulations and used to conduct Fourier analysis and proper orthogonal decomposition (POD) and compute the mean kinetic energy fluxes by different POD modes to better understand the tip‐vortex instability mechanisms. Our findings indicate that shear can significantly affect the breakup of the wind turbine tip‐vortices and the shape and stable length of the wake, whereas thermal stratification seems to only have limited contribution to the spatial development of the near‐wake field. Finally, our analysis shows that the applied perturbation frequency determines the tip‐vortex breakup location as it controls the onset of the mutual inductance instability.

17 WIND ENERGY↗
DOE OSTI2024

Altered excitation energy transfer between phycobilisome and photosystems in the absence of ApcG, a small linker peptide, in Synechocystis sp. PCC 6803, a cyanobacterium

Phycobilisome (PBS) is a large pigment-protein complex in cyanobacteria and red algae responsible for capturing sunlight and transferring its energy to photosystems (PS). Spectroscopic and structural properties of various PBSs have been widely studied, however, the nature of so-called complex-complex interactions between PBS and PSs remains much less explored. In this work, we have investigated the function of a newly identified PBS linker protein, ApcG, some domain of which, together with a loop region (PB-loop in ApcE), is possibly located near the PBS-PS interface. Using Synechocystis sp. PCC 6803, we generated an ApcG deletion mutant and probed its deletion effect on the energetic coupling between PBS and photosystems. Steady-state and time-resolved spectroscopic characterization of the purified ΔApcG-PBS demonstrated that ApcG removal weakly affects the photophysical properties of PBS that the spectroscopic properties of terminal energy emitters are comparable to those of PBS from wild-type. However, analysis of fluorescence decay imaging datasets reveals that ApcG deletion induces disruptions within the allophycocyanin (APC) core, resulting in the emergence (splitting) of two spectrally diverse subgroups with some short-lived APC. Profound spectroscopic changes of the whole ΔApcG mutant cell, however, emerge during state transition, a dynamic process of light scheme adaptation. The mutant cells in State I show a substantial increase in PBS-related fluorescence. On the other hand, global analysis of time-resolved fluorescence demonstrates that in general ApcG deletion does not alter or inhibit state transitions if it is interpreted only in terms of the changes of the PSII and PSI fluorescence emission intensity. Furthermore, the results revealed yet–to–be discovered mechanism of ApcG-docking induced excitation energy transfer regulation within PBS or to Photosystems.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

MtrA modulates Mycobacterium tuberculosis cell division in host microenvironments to mediate intrinsic resistance and drug tolerance

The success of Mycobacterium tuberculosis (Mtb) is largely attributed to its ability to physiologically adapt and withstand diverse localized stresses within host microenvironments. Here, we present a data-driven model (EGRIN 2.0) that captures the dynamic interplay of environmental cues and genome-encoded regulatory programs in Mtb. Analysis of EGRIN 2.0 shows how modulation of the MtrAB two-component signaling system tunes Mtb growth in response to related host microenvironmental cues. Disruption of MtrAB by tunable CRISPR interference confirms that the signaling system regulates multiple peptidoglycan hydrolases, among other targets, that are important for cell division. Further, MtrA decreases the effectiveness of antibiotics by mechanisms of both intrinsic resistance and drug tolerance. Together, the model-enabled dissection of complex MtrA regulation highlights its importance as a drug target and illustrates how EGRIN 2.0 facilitates discovery and mechanistic characterization of Mtb adaptation to specific host microenvironments within the host.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Quantifying the Dynamics of Protein Self-Organization Using Deep Learning Analysis of Atomic Force Microscopy Data

The dynamics of protein self-assembly on the inorganic surface and the resultant geometric patterns are visualized using high-speed atomic force microscopy. The time dynamics of the classical macroscopic descriptors such as 2D fast Fourier transforms, correlation, and pair distribution functions are explored using the unsupervised linear unmixing, demonstrating the presence of static ordered and dynamic disordered phases and establishing their time dynamics. Here, the deep learning (DL)-based workflow is developed to analyze detailed particle dynamics and explore the evolution of local geometries. Finally, we use a combination of DL feature extraction and mixture modeling to define particle neighborhoods free of physics constraints, allowing for a separation of possible classes of particle behavior and identification of the associated transitions. Overall, this work establishes the workflow for the analysis of the self-organization processes in complex systems from observational data and provides insight into the fundamental mechanisms.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Securing Smart Manufacturing: Detection of Cyber-Physical Attacks in CNC-Based Systems

As Industry 4.0 advances, the integration of computer numerical control (CNC) machines and advanced manufacturing technologies is transforming production into smart manufacturing systems that blend physical and digital processes as cyber-physical systems. However, this increased cyber-physical connectivity exposes manufacturing systems to cyber threats that can cause severe operational and financial disruptions. This paper presents a comparative study on cyber attacks and anomaly detection techniques in manufacturing, focusing on network traffic from CNC machines. The data extracted from network packets includes machine commands and control signals exchanged between the machine's interface and control system, crucial for maintaining operational integrity. We explore two types of cyber attacks, design modification and command injection, which pose substantial risks to CNC machine productivity and system integrity. Our investigation involves experiments on a real CNC system, highlighting the urgent need for effective detection mechanisms. To address these threats, we evaluate three anomaly detection methods: dynamic time warping (DTW), rolling average, and a deep learning, long short-term memory (LSTM) time-series-based autoencoder. Each is assessed for its effectiveness in identifying anomalous behaviors caused by the attacks. Our findings demonstrate the unique strengths and limitations of each detection technique, providing a deeper understanding of their applicability in realworld manufacturing environments. The comparative analysis indicates that while certain methods are highly effective against specific attack types, others offer broader applicability across different attacks. This study contributes to the accurate detection of anomalies in CNC machining processes, thereby enhancing the reliability and security of smart manufacturing systems against diverse cyber threats.

Williams, Bethanie [Tennessee Technological Univer↗
DOE OSTI2025

Revealing atomic-scale switching pathways in van der Waals ferroelectrics

Two-dimensional (2D) van der Waals (vdW) materials hold the potential for ultrascaled ferroelectric (FE) devices due to their silicon compatibility and robust polarization down to atomic scale. However, the inherently weak vdW interactions enable facile sliding between layers, introducing complexities beyond those encountered in conventional ferroelectric materials and presenting substantial challenges in uncovering intricate switching pathways. Here, we combine atomic-resolution imaging under in situ electrical biasing conditions with first-principles calculations to unravel the atomic-scale switching mechanisms in SnSe, a vdW group IV monochalcogenide. Our results uncover the coexistence of a consecutive 90° switching pathway and a direct 180° switching pathway from antiferroelectric (AFE) to FE order in this vdW system. Atomic-scale investigations and strain analysis reveal that the switching processes simultaneously induce interlayer sliding and compressive strain, while the lattice remains coherent despite the presence of multidomain structures. These findings elucidate vdW ferroelectric switching dynamics at atomic scale and lay the foundation for the rational design of 2D ferroelectric nanodevices.

Li, Xinyan [Rice University, Houston, TX (United S↗
DOE OSTI2021

Constraining Physical Models at Gigabar Pressures

High-energy-density (HED) experiments in convergent geometry are able to test physical models at pressures beyond hundreds of millions of atmospheres. The measurements from these experiments are generally highly integrated and require unique analysis techniques to procure quantitative information. This work describes a methodology to constrain the physics in convergent HED experiments by adapting the methods common to many other fields of physics. As an example, a mechanical model of an imploding shell is constrained by data from a thin-shelled direct-drive exploding-pusher experiment on the OMEGA Laser System using Bayesian inference, resulting in the reconstruction of the shell dynamics and energy transfer during the implosion. The model is tested by analyzing synthetic data from a 1-D hydrodynamics code and is sampled using a Markov chain Monte Carlo to generate the posterior distributions of the model parameters. The goal of this work is to demonstrate a general methodology that can be used to draw conclusions from a wide variety of HED experiments.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

Influence of Initial fabric and water-wetting on particle fracture and force chain evolution in natural silica sand

Particle fracture has a significant influence on the engineering behavior of granular materials. However, the combined influence of the initial fabric and wetting on particle fracture and force chain evolution in granular materials, particularly in sands, remains insufficiently explored in the current literature. Here, in this paper, one-dimensional (1D) confined compression experiments were conducted on dry and wet specimens, and particle-level fracture was captured using three-dimensional (3D) in-situ Synchrotron Micro-Computed Tomography (SMT). A quantitative assessment of particle fracture revealed that wet specimens, which have disturbed fabric, exhibited a higher fracture percentage in comparison to dry specimens. Complementary 3D finite element (FE) simulations were performed using dry and wet (only solid fabric was considered and the influence of pore water is not considered) sand assemblies to assess interparticle contact forces and particle-scale stress distributions within the specimens. Force chain analysis was subsequently conducted, encompassing quantification of interparticle forces, characterization of force network structures, and monitoring the dynamic evolution of force chains under different strain levels. The results show that the specimens with disturbed fabric led to a more dynamic and less persistent force network, more fabric instability, and thus more reorganization of force chain structures. In addition, the frequent rearrangement of the force network in the presence of water (with reduced inter-particle contact friction) likely exacerbates localized stress concentrations, promoting failure in previously unengaged or weakly connected particles. The results reported in this paper offer a new insight into how the initial fabric and wetting cause different fracture behavior. The findings can also pave the way for more in-depth future investigations into the mechanics governing particle fracture in granular assemblies.

Finite element analysis↗
DOE OSTI2023

Behavioral simulations and experimental evaluations of stress induced spatial nonuniformity of dynamic bulk modulus in additive friction stir deposited AA 6061

Additive friction stir deposition (AFSD) is a rapidly developing solid-state additive manufacturing (AM) technology that enables the fabrication of customized products on a relatively large scale. The unique forge-liked process offers high quality products with refined equiaxed microstructure and exceptional mechanical performance. However, in AFSD, the spatially distributed mechanical properties within a deposited layer have not been established so far, due to the lack of a suitable large-scale mapping method. In the present work, an ultrasonic dynamic-elasticity mapping method was employed to map the distribution of physical properties in a AFSD 6061 Al. Strong spatial asymmetries in elastographies were mainly due to the residual stresses. The origin of the asymmetries was investigated through thermo-mechanical simulations of the AFSD process. It was observed that majority of the asymmetries were associated with the mechanical residual stresses instead of the symmetric thermal residual stresses during linear deposition of the AFSD process. However, the thermal residual stresses can be manipulated to become asymmetric with a 90° turn in the linear deposition path, due to the difference between the levels of cooling along the edges of the inner and outer corners. Hence, the mechanical and thermo-mechanical residual stresses can be additive or subtractive depending on the direction of the turns. Here, such numerically predicted behaviors were also experimentally observed on the AFSD fabricated samples by ultrasonic elastography. Furthermore, additional preliminary studies on multi-layer AFSD fabrications show the asymmetric mechanical stresses generated during the deposition process on different layers generate constructive or destructive interference which results to spatially variable dynamic bulk modulus depending on the deposition orientations of layers.

36 MATERIALS SCIENCE↗
DOE OSTI2020

An integrated computational materials engineering framework to analyze the failure behaviors of carbon fiber reinforced polymer composites for lightweight vehicle applications

A bottom-up multi-scale modeling approach is used to develop an Integrated Computational Materials Engineering (ICME) framework for carbon fiber reinforced polymer (CFRP) composites, which has the potential to reduce development to deployment lead time for structural applications in lightweight vehicles. In this work, we develop and integrate computational models comprising of four size scales to fully describe and characterize three types of CFRP composites. In detail, the properties of the interphase region are determined by an analytical gradient model and molecular dynamics analysis at the nano-scale, which is then incorporated into micro-scale unidirectional (UD) representative volume element (RVE) models to characterize the failure strengths and envelopes of UD CFRP composites. Then, the results are leveraged to propose an elasto-plastic-damage constitutive law for UD composites to study the fiber tows of woven composites as well as the chips of sheet molding compound (SMC) composites. Subsequently, the failure mechanisms and failure strengths of woven and SMC composites are predicted by the meso-scale RVE models. Finally, building upon the models and results from lower scales, we show that a homogenized macro-scale model can capture the mechanical performance of a hat-section-shaped part under four-point bending. Along with the model integration, we will also demonstrate that the computational results are in good agreement with experiments conducted at different scales. The present work illustrates the potential and significance of integrated multi-scale computational modeling tools that can virtually evaluate the performance of CFRP composites and provide design guidance for CFRP composites used in structural applications.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Flow dynamics and heat transfer in simplified battery energy storage systems with heated battery modules

Large-scale energy storage systems (ESSs) composed of batteries show promise in addressing current energy challenges, but dissipation of generated heat is important. Here, this paper focuses on buoyant convective flows in simplified ESS battery racks. Natural convection is not generally the primary cooling strategy but can be important in abnormal scenarios where there is module overheat or potentially thermal runaway. We use computational fluid dynamics to investigate the flow dynamics and heat transfer mechanisms in a simplified parameterized rack design. Despite its simplicity, this configuration produces many of the relevant features expected in real ESSs without details of module geometry or hardware, allowing broad conclusions independent of manufacture-specific designs. We start by providing visualizations of the flowfield and measurements of entrainment, heat flux, and pressure. To characterize the dependence on the system parameters, we develop an integral-scale analysis of the average temperature equation to highlight the dominant source terms. We use results from this analysis to derive a steady network model composed of simple algebraic expressions to provide first-order predictions of entrainment through the rack. The network model leads to a linear scaling of the Reynolds number based on convective mass flux with respect to the Grashof number based on the heat source. We deduce empirical relationships that relate the heat exchanged between modules using a surface-averaged Nusselt number as a function of the local Reynolds and Rayleigh numbers. Lastly, we investigate how space between the modules and rack in the spanwise direction creates flow bypass, resulting in different flow pathways.

Battery thermal management↗
DOE OSTI2026

PARP1-HPF1 structure and dynamics on nicked DNA suggest a mechanism for acute and localized ADP-ribosylation

PARP1 detection of DNA strand breaks allosterically leads to PARP1 synthesis of poly(ADP-ribose) modifications that signal DNA damage. HPF1 engages activated PARP1 to control modification site selection. Understanding of the mechanism of DNA break detection and catalytic activation is incomplete, due largely to limited structural information for full-length PARP1. Here, single-particle cryo-EM provides views of the full complement of PARP1 domains engaging a DNA single-strand break in the presence of HPF1 and a fragment of binding partner Timeless. Cryo-EM, single-molecule DNA dynamics, and small-angle X-ray scattering analysis indicate that PARP1 remains dynamic even when the multi-domain structure is organized on a DNA break, with the minimal catalytic region displaying high mobility relative to domains engaging damage. We propose that the organization of PARP1 domains on a DNA break releases a tethered, constitutively active catalytic region to modify molecules in a radius surrounding the DNA break site.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Electron transport in a tokamak scrape-off layer: impact of toroidal nonuniformities of divertor targets

An analysis of electron dynamics is carried out in the tokamak scrape-off layer (SOL) region. Small non-axisymmetric perturbations of the divertor target sheath potential affect electron drift orbits in the SOL and may lead to non-ambipolar electron radial transport. The resulting rates of electron convection, diffusion, and mobility are calculated analytically, and the analytic results are compared with direct numerical simulations of electron drift orbits. The proposed mechanism of non-ambipolar electron transport may be relevant to the sustainment of the SOL plasma quasi-neutrality in the ‘heuristic’ model of the SOL width (Eich et al 2011 Phys. Rev. Lett. 107 215001).

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2020

Trends and drivers of marine fish landings in Portugal since its entrance in the European Union

Abstract Marine landings in Portugal have decreased at a higher rate than fishing effort in the last 20 years. Identifying the variables driving the quantity and composition of landings is pivotal to understand the dynamics of the fisheries sector, which entails complex social and environmental aspects. In this study, we investigate the main drivers of marine fish landings in continental Portugal between 1989 and 2014. To identify common trends in time series, and quantify the importance of environmental factors, we applied a dynamic factor analysis considering four regions and three types of gear (trawling, purse-seine, and a multi-gear fishery). Our results show the importance of fishing effort as the most relevant factor driving marine landings in Portugal, both at the long and short terms. In addition, the effect of environmental factors such as the winter river discharge and the spring East Atlantic Teleconnection index should not be neglected, probably through mechanisms affecting coastal productivity. We provide a comprehensive amount of information that permits to improve our understanding of the trends of the most important commercial species in Portugal during the period of study.

Bueno-Pardo, Juan↗