Unveiling Active Sites of CO[subscript 2] Reduction on Nitrogen-Coordinated and Atomically Dispersed Iron and Cobalt Catalysts
Abstract not provided
Pan, Fuping↗
SEARCH · Engineering Papers
Results for “structured model reduction”
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.
Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.
Small and arbitrary shock structures in spin 1/2 magnetohydrodynamic quantum plasma
The shock structures in spin-1/2 quantum plasma, in the presence of magnetic diffusivity, are studied in the framework of the quantum magnetohydrodynamic model. Linear dispersion relation for the system is carried out analytically, and the results are plotted numerically for several values of the plasma parameters. Numerical analysis for arbitrary amplitude waves is carried out, whereas for waves of small amplitude, the reductive perturbation technique is applied to obtain the Korteweg-de Vries-Burgers equation. Both the analyses are observed to give the same qualitative picture. Most importantly, the different plasma parameters are found to play significant roles in determining the nature of the shock waves. The parametric ranges for which monotonic shock and oscillatory shock solutions are observed, are found analytically.
70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
A limit to strong shock behavior in the dynamic response of matter at pressure
Solids under high pressures experience a series of regimes, where their microstructure adapts to the applied compression and these key transitions are discussed in this paper. As strain increases, new forces emerge at extreme pressures. A previous study introduced the concept of the weak shock limit (WSL), at which the ambient theoretical shear strength is overcome. Above the WSL, further deformation under strong shock conditions results in electrons occupying higher energy levels as strain increases. As pressure rises further, shock melting occurs in the material and at around three times this melting pressure, the strong shock limit is reached where the driving physics under pressure switches, with electrons forced into higher energy states. This leads to significant reduction in their compressibility due to changes in electronic structure and developing electron degeneracy pressures. A derivation for conditions at this state is presented, which indicates that a dependence of the threshold pressure on the free electron number density defines the limit observed. This correlation suggests that ambient material moduli govern material compression up to nearly 50% strain. These observations show that models should account for different behaviors as dominant physics changes in each regime accessed as shock pressure increases.
36 MATERIALS SCIENCE↗
Cross-sectoral synergies for household energy savings: the role of electric vehicles, solar photovoltaics, and remote work
Over the past two decades, new technologies and behavioral shifts – such as electric vehicles, solar photovoltaics, and increased work-from-home practices – have reshaped residential electricity consumption and cost. However, their combined or synergistic impact on a household’s electricity cost remains unexplored. Leveraging data from the 2020 Residential Energy Consumption Survey, this study uses a structural equation model to unravel the extent to which the bundled adoption of EV-PV and stay-at-home decisions impact the total electricity cost of households. Results indicate that adopting both EVs and PV reduces electricity costs by 31% despite a 16% rise in consumption. When combined with stay-at-home practices, households still experience a 13% cost reduction, even with a 25% increase in electricity consumption. In conclusion, these findings suggest that financial savings are not merely a byproduct of adopting new technologies or behavioral changes but could serve as a key consideration for household contemplating engagement with multiple modern energy solutions simultaneously.
14 SOLAR ENERGY↗
SU-F-T-116: Predicting IQ and the Risk of Hearing Loss Following Proton Versus Photon Radiotherapy for Pediatric Brain Tumor Patients
Purpose: The increased sparing of normal tissues in intensity modulated proton therapy (IMPT) compared to photon intensity modulated radiotherapy (IMRT) in brain tumor treatments should translate into improved neurocognitive outcomes. Models were used to estimate the intelligence quotient (IQ) and the risk of hearing loss 5 years post radiotherapy and to compare outcomes of proton against photon in pediatric brain tumors. Methods: Patients who had received radical IMRT were randomly selected from our retrospective database: 10 cases each of craniopharyngioma, ependymoma and medulloblastoma, and 20 cases of glioma. The existing planning CT and contours were used to generate IMPT plans. The RBE-corrected dose to brain structures and cochleas were calculated for both IMPT and IMRT. A model was applied to estimate IQ using a Markov chain Monte Carlo technique. The reported incidence of hearing loss as a function of cochlear dose was used to estimate the rate of occurrence. Results: The average brain dose was less in all IMPT plans compared to IMRT: ranging from a 6.7% reduction (P=0.003) in the case of medulloblastoma to 38% (P=0.007) for craniopharyngioma. This dose reduction translated into a gain in IQ of 1.9 points on average for protons vs photons for the whole cohort at 5 years post-treatment (P=0.011). In terms of specific diseases, the gains in IQ ranged from 0.8 points for medulloblastoma, to 2.7 points for craniopharyngioma. Hearing loss probability was evaluated on a per-ear-basis and was found to be systematically less for proton versus photon: overall 2.9% versus 7.2% (P < 0.001). Conclusion: A novel method was developed to predict neurocognitive outcomes in pediatric brain tumor patients on a case-by-case basis. A modest gain in IQ was systematically observed for proton in all patients. Given the uncertainties within the model used and our reinterpretation, these gains may be underestimated.
60 APPLIED LIFE SCIENCES↗
The AWAKEN wind farm benchmark, Part 2: Modeling results
Accurately modeling wind farm performance in complex atmospheric flows remains a challenge. This paper presents the modeling results of the American WAKE experimeNt (AWAKEN) wind farm benchmark, a collaborative effort involving 16 research groups from academia and industry within the International Energy Agency Wind Technology Collaboration Programme Task 57. The study evaluates a diverse suite of simulation tools, ranging from fast-running engineering wake models to high-fidelity large-eddy simulations, against a diurnal case study observed during the AWAKEN campaign. The benchmark utilized a three-phase structure to progressively assess model performance as observational data availability increased. Initial blind predictions showed that higher-fidelity models did not uniformly outperform simpler simulation tools. A distinct spatial bias was observed where models struggled to resolve the interplay between a low-level jet, wakes, and terrain-induced flow acceleration. In subsequent phases, leveraging additional measurements for model improvement led to a reduction in mean absolute error across the model ensemble; however, this effect was most pronounced in engineering wake models, where targeted calibration reduced error by up to 40~\%. Overall, the study demonstrates that inflow characterization remains a primary prerequisite for accuracy, particularly for models relying on coarse forcing datasets. While the limited ability to resolve local terrain-flow interactions under single-day conditions represent a recognized constraint, the overall findings on wake modeling and real-world validation still provide valuable guidance for model application and for mitigating this limitation.
Bodini, Nicola↗
Analysis and design of advanced composite bounded joints
Advances in the analysis of adhesive-bonded joints are presented with particular emphasis on advanced composite structures. The joints analyzed are of double-lap, single-lap, scarf, stepped-lap and tapered-lap configurations. Tensile, compressive, and in-plane shear loads are covered. In addition to the usual geometric variables, the theory accounts for the strength increases attributable to adhesive plasticity (in terms of the elastic-plastic adhesive model) and the joint strength reductions imposed by imbalances between the adherends. The solutions are largely closed-form analytical results, employing iterative solutions on a digital computer for the more complicated joint configurations. In assessing the joint efficiency, three potential failure modes are considered. These are adherend failure outside the joint, adhesive failure in shear, and adherend interlaminar tension failure (or adhesive failure in peel). Each mode is governed by a distinct mathematical analysis and each prevails throughout different ranges of geometric sizes and proportions.
Hart-Smith, L. J.↗
Superconducting electromagnets for large wind tunnel magnetic suspension and balance systems
A superconducting electromagnetic suspension and balance system for an 8 x 8-ft, Mach 0.9 wind tunnel is presented. The system uses a superconducting solenoid as a model core 70 cm long and with a 11.5 cm OD, and a combination of permanent magnet material in the model wings to produce the required roll torque. The design, which uses an integral cold structure rather than separate cryostats for mounting all control magnets, has 14 external magnets, including 4 racetrack-shaped roll coils. Helium capacity of the system is 3.0 to 3.5 l with idling boiloff rate predicted at 0.147 to 0.2 l/h. The improvements yielded a 50-percent reduction in the system size, weight, and cost.
Boom, R. W.↗
New computing systems and their impact on structural analysis and design
A review is given of the recent advances in computer technology that are likely to impact structural analysis and design. The computational needs for future structures technology are described. The characteristics of new and projected computing systems are summarized. Advances in programming environments, numerical algorithms, and computational strategies for new computing systems are reviewed, and a novel partitioning strategy is outlined for maximizing the degree of parallelism. The strategy is designed for computers with a shared memory and a small number of powerful processors (or a small number of clusters of medium-range processors). It is based on approximating the response of the structure by a combination of symmetric and antisymmetric response vectors, each obtained using a fraction of the degrees of freedom of the original finite element model. The strategy was implemented on the CRAY X-MP/4 and the Alliant FX/8 computers. For nonlinear dynamic problems on the CRAY X-MP with four CPUs, it resulted in an order of magnitude reduction in total analysis time, compared with the direct analysis on a single-CPU CRAY X-MP machine.
Noor, Ahmed K.↗
Model-Based Fatigue Prognosis of Fiber-Reinforced Laminates Exhibiting Concurrent Damage Mechanisms
Prognostics of large composite structures is a topic of increasing interest in the field of structural health monitoring for aerospace, civil, and mechanical systems. Along with recent advancements in real-time structural health data acquisition and processing for damage detection and characterization, model-based stochastic methods for life prediction are showing promising results in the literature. Among various model-based approaches, particle-filtering algorithms are particularly capable in coping with uncertainties associated with the process. These include uncertainties about information on the damage extent and the inherent uncertainties of the damage propagation process. Some efforts have shown successful applications of particle filtering-based frameworks for predicting the matrix crack evolution and structural stiffness degradation caused by repetitive fatigue loads. Effects of other damage modes such as delamination, however, are not incorporated in these works. It is well established that delamination and matrix cracks not only co-exist in most laminate structures during the fatigue degradation process but also affect each other's progression. Furthermore, delamination significantly alters the stress-state in the laminates and accelerates the material degradation leading to catastrophic failure. Therefore, the work presented herein proposes a particle filtering-based framework for predicting a structure's remaining useful life with consideration of multiple co-existing damage-mechanisms. The framework uses an energy-based model from the composite modeling literature. The multiple damage-mode model has been shown to suitably estimate the energy release rate of cross-ply laminates as affected by matrix cracks and delamination modes. The model is also able to estimate the reduction in stiffness of the damaged laminate. This information is then used in the algorithms for life prediction capabilities. First, a brief summary of the energy-based damage model is provided. Then, the paper describes how the model is embedded within the prognostic framework and how the prognostics performance is assessed using observations from run-to-failure experiments
Prognostics↗
TAT-C: A Trade-Space Analysis Tool for Constellations
Under a changing technological and economic environment, there is growing interest in implementing future NASA Earth Science missions as Distributed Spacecraft Missions (DSM). The objective of our project is to provide a framework that facilitates DSM Pre-Phase A investigations and optimizes DSM designs with respect to a-priori Science goals. In this first version of our Trade-space Analysis Tool for Constellations (TAT-C), we are investigating questions such as: Which type of constellations should be chosen? How many spacecraft should be included in the constellation? Which design has the best costrisk value? This paper describes the overall architecture of TAT-C including: a User Interface (UI) interacting with multiple users - scientists, missions designers or program managers; an Executive Driver gathering requirements from UI and formulating Trade-space Search Requests for the Trade-space Search Iterator, which in collaboration with the Orbit Coverage, Reduction Metrics, and Cost Risk modules generates multiple potential architectures and their associated characteristics. UI will include Graphical, Command Line and Application Programmer Interfaces to respond to the demands of various levels of users expertise. Science inputs are grouped into various mission concepts, satellite specifications, and payload specifications, while science outputs are grouped into several types of metrics - spatial, temporal, angular and radiometric. Orbit Coverage leverages the use of the Goddard Mission Analysis Tool (GMAT) to compute coverage and ancillary data that are passed to Reduction Metrics. Then, for each architecture design, Cost Risk will provide estimates of the cost and life cycle cost as well as technical and cost risk of the proposed mission. Additionally, the Knowledge Base module is a centralized store of structured data readable by humans and machines. It will support both TAT-C analysis when composing new mission concepts from existing model inputs, and TAT-C exploration when discovering new mission concepts by querying previous results.
Science Data Processing↗
Semi-Empirical Modeling and Prediction of Direct Combustor Noise
Due to turbofan design trends, advances in fan-noise-mitigation techniques, and expected aircraft configuration changes, the impact on overall airport community noise from certain aircraft-propulsion noise sources, such as fan and jet noise, will be reduced at all certification points in the future. The situation with regard to turbofan-core noise is less clear however. Combustor noise in particular—which presently is an important core-noise component, but not dominant from an overall noise perspective—could become more prominent in upcoming high-power-density core designs. Its detailed source structure in the combustor, including the indirect combustor-noise mechanism, and the effects of the propagation path through the engine and exhaust nozzle need to be better understood. This report reviews the current status of modeling and prediction of direct combustor noise. This work is carried out under the NASA Advanced Air Vehicles Program, Advanced Air Transport Technology Project, Aircraft Noise Reduction Subproject.
Turbomachinery Noise↗
Usage of ChatGPT for Engineering Design and Analysis Tool Development
ChatGPT, a generative AI large language model, has recently captured significant attention in both the computer science community and the broader public domain. It has demonstrated a wide range of capabilities, from answering simple questions to writing fully functional computer code. This study spotlights both the capabilities and limitations of ChatGPT when addressing engineering problems. The model's capacity to generate practical engineering tools is highlighted through an example of a prompt that leads to an interactive plotting tool, enabling the examination of the fluid boundary layer around a fan blade. Subsequently, the paper also uncovers potential pitfalls in ChatGPT’s application, shown through an unsuccessful attempt to use ChatGPT to automate a process in Ansys Workbench through scripting. The research further investigates ChatGPT's proficiency in addressing inquiries and providing explanations about the functionalities of OpenMDAO, an open-source, multidisciplinary design, analysis, and optimization tool developed at NASA Glenn Research Center. Finally, an optimization methodology, developed with ChatGPT’s help, is applied to the structural optimization of a fan blade. The developed optimization method utilizes T-Blade3 for geometry generation, Ansys Mechanical for meshing and finite element analysis, and sci-kit learn’s MLPRegressor method to generate a trained neural network model of the design space. OpenMDAO is then used to find the optimal point within the design space. The outcome is a significant reduction in stress in the optimized model—less than one-fifth of the stress value in the baseline model.
Design↗
Usage of ChatGPT for Engineering Design and Analysis Tool Development
ChatGPT, a generative AI large language model, has recently captured significant attention in both the computer science community and the broader public domain. It has demonstrated a wide range of capabilities, from answering simple questions to writing fully functional computer code. This study spotlights both the capabilities and limitations of ChatGPT when addressing engineering problems. The model's capacity to generate practical engineering tools is highlighted through an example of a prompt that leads to an interactive plotting tool, enabling the examination of the fluid boundary layer around a fan blade. Subsequently, the paper also uncovers potential pitfalls in ChatGPT’s application, shown through an unsuccessful attempt to use ChatGPT to automate a process in Ansys Workbench through scripting. The research further investigates ChatGPT's proficiency in addressing inquiries and providing explanations about the functionalities of OpenMDAO, an open-source, multidisciplinary design, analysis, and optimization tool developed at NASA Glenn Research Center. Finally, an optimization methodology, developed with ChatGPT’s help, is applied to the structural optimization of a fan blade. The developed optimization method utilizes T-Blade3 for geometry generation, Ansys Mechanical for meshing and finite element analysis, and sci-kit learn’s MLPRegressor method to generate a trained neural network model of the design space. OpenMDAO is then used to find the optimal point within the design space. The outcome is a significant reduction in stress in the optimized model—less than one-fifth of the stress value in the baseline model.
Design↗
Structural Design and Aeromechanical Analysis of Unconventional Blades for Future Mars Rotorcraft
The structural design for rotor blades with thin, unconventional airfoils for Earth-based testing is obtained using three-Dimensional (3D) aeromechanical analysis. This analysis is in support of the NASA ROAMX project. The outer mold was provided by NASA, but the internal structural design was developed at the University of Maryland and is presented here, along with a thorough aeromechanical analysis. The main objectives are to verify the structural integrity of the design and understand the unique aeroelastic behavior of the non-conventional airfoils designed for low-Reynolds number and high-Mach number flow. Six different blade models are considered, with the pitch axis varied from quarter-chord to mid-chord to determine the effect of C.G. offset on natural frequencies, blade deformations, root loads, and 3D stresses. All six blade designs are first studied under rotation in pure vacuum, and significant reductions in root loads and 3D stresses are achieved by moving the pitch axis closer to mid-chord to reduce the C.G. offset. Based on the vacuum analysis, the blade design with the pitch axis at 40% chord is selected for aerodynamic analysis. The blade control load, airloads, deformations, and 3D stresses are studied for steady hover. Dynamic control load and dynamic 3D stresses are studied for unsteady hover achieved using cyclic. Significant elastic twist is observed due to the trapeze effect and propeller moment, affecting the spanwise distribution of aerodynamic loads on the blades. However, the effect of aerodynamic loads on 3D stresses and the blade control load is found to be minimum. The dynamic control load is found to increase significantly due to inertial coupling from the C.G. offset. The dynamic stresses also increase, although still have factors of safety greater than two for both tensile and compressive stress.
Structural Design↗
HERUS: A CO ATLAS FROM SPIRE SPECTROSCOPY OF LOCAL ULIRGs
We present the Herschel SPIRE Fourier Transform Spectroscopy (FTS) atlas for a complete flux-limited sample of local ultraluminous infrared galaxies (ULIRGs) as part of the HERschel Ultra Luminous InfraRed Galaxy Survey (HERUS). The data reduction is described in detail and was optimized for faint FTS sources ,with particular care being taken for the subtraction of the background, which dominates the continuum shape of the spectra. To improve the final spectra, special treatment in the data reduction has been given to any observation suffering from artifacts in the data caused by anomalous instrumental effects. Complete spectra are shown covering 200–671 μ m, with photometry in the SPIRE bands at 250, 350, and 500 μ m. The spectra include near complete CO ladders for over half of our sample, as well as fine structure lines from [C i] 370 μ m, [C i] 609 μ m, and [N ii] 205 μ m. We also detect H{sub 2}O lines in several objects. We construct CO spectral line energy distributions (SLEDs) for the sample, and compare their slopes with the far-infrared (FIR) colors and luminosities. We show that the CO SLEDs of ULIRGs can be broadly grouped into three classes based on their excitation. We find that the mid- J (5 < J < 8) lines are better correlated with the total FIR luminosity, suggesting that the warm gas component is closely linked to recent star formation. The higher J transitions do not linearly correlate with the FIR luminosity, consistent with them originating in hotter, denser gas that is unconnected to the current star formation. We conclude that in most cases more than one temperature component is required to model the CO SLEDs.
79 ASTRONOMY AND ASTROPHYSICS↗
Magnetic study of M-type Ru–Ti doped strontium hexaferrite nanocrystalline particles
We carried out a systematic study on the effect of the substitution of Ti2+ and Ru4+ ions for Fe3+ ions on the structural and magnetic properties of the strontium ferrite SrFe12-2xRuxTixO19 nanoparticles with (0 <= x <= 0: 3), using x-ray diffraction, Quantum Design PPMS-9 magnetometry, and electrical resistivity. A clear irreversibility between the zero-field-cooled and field-cooled curves was observed below room temperature and the zero-field-cooled magnetization curves displayed a broad peak at a temperature TM. These results were discussed within the framework of random particle assembly model and associated with the magnetic domain wall motion. The resistivity data showed some kind of a transition from insulator to perfect insulator around TM. The high-temperature magnetization measurements exhibited sharp peaks just below T-c indicating a superparamagnetic behavior. With Ru-Ti substitution, the saturation magnetization at 5 K showed small variations were it slightly increased with increasing x up to 0.2, and then decrease for x = 0.3, while the coercivity decreased monotonically, recording a reduction of about 78% at x = 0.3. These results were discussed in light of the cationic distributions based on the results of the structural refinements.
Alsmadi, A. M.↗
Generative learning of densities on manifolds
A generative modeling framework is proposed that combines diffusion models and manifold learning to efficiently sample data densities on manifolds. The approach utilizes Diffusion Maps to uncover possible low-dimensional underlying (latent) spaces in the high-dimensional data (ambient) space. Two approaches for sampling from the latent data density are described. The first is a score-based diffusion model, which is trained to map a standard normal distribution to the latent data distribution using a neural network. The second one involves solving an Itô stochastic differential equation in the latent space. Additional realizations of the data are generated by lifting the samples back to the ambient space using Double Diffusion Maps , a recently introduced technique typically employed in studying dynamical system reduction; here the focus lies in sampling densities rather than system dynamics. The proposed approaches enable sampling high dimensional data densities restricted to low-dimensional, a priori unknown manifolds. The efficacy of the proposed framework is demonstrated through a benchmark problem and a material with multiscale structure.
Double diffusion maps↗