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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 1,387 records · Page 77

Base Flow Model Validation

A method was developed of obtaining propulsive base flow data in both hot and cold jet environments, at Mach numbers and altitude of relevance to NASA launcher designs. The base flow data was used to perform computational fluid dynamics (CFD) turbulence model assessments of base flow predictive capabilities in order to provide increased confidence in base thermal and pressure load predictions obtained from computational modeling efforts. Predictive CFD analyses were used in the design of the experiments, available propulsive models were used to reduce program costs and increase success, and a wind tunnel facility was used. The data obtained allowed assessment of CFD/turbulence models in a complex flow environment, working within a building-block procedure to validation, where cold, non-reacting test data was first used for validation, followed by more complex reacting base flow validation.

Sinha, Neeraj↗

Evaluation of a Traditional Regression Model Term Selection Process for Balance Calibration Data Sets

Key elements of a traditional regression model term selection process for the analysis of wind tunnel strain-gage balance calibration data are discussed. The traditional process is sometimes applied when regression models of the gage outputs are needed and an analyst does not have access to a term selection algorithm. In principle, the traditional process identifies supported regression model terms of a gage output by combining an analyst's subject- matter knowledge with a visual examination of selected plots of the calibration loads. Twelve empirical rules are listed that may be used to select regression model terms. Data from the manual calibration of a force balance is used to illustrate the application of the traditional term selection process. The data example shows that the traditional process can become very complex. Its successful application highly depends on an analyst's experience and skills. Therefore, it is suggested to replace the traditional term selection process with an automated term selection algorithm. Then, objective metrics are systematically applied during the term selection that make the identification of the regression model more repeatable and less dependent on an analyst's personal skills.

strain-gage balance↗

PyKrev: A Python Library for the Analysis of Complex Mixture FT-MS Data

In this study, we present PyKrev, a Python library for the analysis of complex mixture Fourier transform mass spectrometry (FT-MS) data. PyKrev is a comprehensive suite of tools for analysis and visualization of FT-MS data after formula assignment has been performed. These comprise formula manipulation and calculation of chemical properties, intersection analysis between multiple lists of formulas, calculation of chemical diversity, assignment of compound classes to formulas, multivariate analysis, and a variety of visualization tools producing van Krevelen diagrams, class histograms, PCA score, and loading plots, biplots, scree plots, and UpSet plots. The library is showcased through analysis of hot water green tea extracts and Scotch whisky FT-ion cyclotron resonance-MS data sets. PyKrev addresses the lack of a single, cohesive toolset for researchers to perform FT-MS analysis in the Python programming environment encompassing the most recent data analysis techniques used in the field.

47 OTHER INSTRUMENTATION↗

Multi-Objective design of interlocking metasurfaces using conditional diffusion models

Unit cell design remains a major challenge for interlocking metasurfaces, a promising joining technology for dissimilar materials, due to the complex, competing, multivariate design space and the need for rapid adaptation to varying performance requirements. This study explores Conditional Diffusion Models as a design optimization tool for interlocking metasurfaces. Given the complex, competing, multivariate design space for interlocking metasurfaces, unit cell design remains a major challenge for this joining technology. We trained a conditional diffusion model on 25,000 finite element analysis-simulated interlocking metasurface unit cells to generate designs with tailored thermo-mechanical properties (tensile strength, shear strength, and thermal conductivity) based on specified performance criteria. The model demonstrated a success rate of approximately 72 % in producing designs that met specified property bounds. The conditional diffusion model generated both thermally resistive and conductive designs, revealing clear trends in design characteristics: taller, dendritic structures were advantageous for tensile loads, while shorter, robust designs excelled in shear applications. Our findings indicate that the model's performance is more influenced by the breadth of the design space than by the quantity of training data, highlighting the importance of expansive design domains for generating innovative solutions. This work establishes conditional diffusion models as a highly efficient and adaptable tool for rapid interlocking metasurface unit cell design, paving the way for advancements in multi-material joining technologies, as well as highlighting the justification to leverage conditional diffusion models as design tools across complex design domains.

Conditional diffusion models↗

Open‐Source Anaerobic Digestion Modeling Platform, Anaerobic Digestion Model No. 1 Fast (ADM1F)

An open‐source modeling platform, called Anaerobic Digestion Model No. 1 Fast (ADM1F), is introduced to achieve fast and numerically stable simulations of anaerobic digestion processes. ADM1F is compatible with an iPython interface to facilitate model configuration, simulation, data analysis, and visualization. Faster simulations and more stable results are accomplished by implementing an advanced open‐source library of numerical methods called Portable Extensive Toolkit for Scientific Computation (PETSc) to solve the ADM1 system of equations. Leveraging PETSc, ADM1F can consistently complete a steady‐state simulation under 0.2 s, over 99% faster than a benchmark ADM1 model implemented with MATLAB while achieving agreement of model outputs within 1% of those obtained with the benchmark model. For dynamic simulations, however, ADM1F has a computational speed advantage only when the influent characteristics update more frequently than every 4 h. The ability of ADM1F to be useful as a tool to study anaerobic digestion systems is demonstrated through two example implementations of ADM1F: (1) a two‐phase co‐digestion scenario evaluating the impact of the organic loading rate and the substrate composition on reactor performance and stability, and (2) a conventional digester scenario assessing the effectiveness of recovery strategies after disruptions that led to instability. These examples demonstrate how the high simulation speed and the convenience of the iPython interface allow ADM1F to complete complex analyses within minutes, much faster than computational strategies currently reported in the literature.

anaerobic co-digestion↗

Demand response event simulator and risk-aware bidding tool for industrial customers

Incentive Based Demand Response (IBDR) program participation delivers financial benefits to the consumers and resiliency benefits to the electricity grid. Effectively participating in these programs as an industrial consumer requires bidding strategies that balance financial risk with operational constraints. Existing bidding tools tend not to fully incorporate stochastic IBDR event modeling, program specific baseline and payment/penalty calculations, or demand reduction process control schemes that account for the cascading impacts of shutdown in complex facilities. Here, this work presents an IBDR event simulator and risk-aware bidding framework tool integrating three key components: a flexible, parameterized demand response event generator that rigorously accounts for program structures and stochasticity, a demand response operational simulation model that generates explicit control strategies for load reduction, and a Monte Carlo simulator to evaluate financial risk for varied capacity bids. A case study at a wastewater treatment plant participating in PG&E's Capacity Bidding Program demonstrates the framework's utility. In the peak capacity price month of August, optimal bidding by the wastewater treatment plant nets a mean IBDR benefit of $101,000 (67% of the August electricity bill) with 0.4% probability of a financial loss. This framework enables industrial operators to make informed bidding decisions, negotiate better program terms with demand response load aggregators, and analyze energy flexibility investments at their facilities. Ultimately, this work reduces participation barriers in IBDR programs and supports the broader goal of enhancing grid reliability and renewable energy integration.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Distributed Multi-GPU Community Detection on Exascale Computing Platforms

Community detection is a fundamental operation in graph mining, and by uncovering hidden structures and patterns within complex systems it helps solve fundamental problems pertaining to social networks, such as information diffusion, epidemics, and recommender systems. Scaling graph algorithms for massive networks becomes challenging on modern distributed-memory multi-GPU (Graphics Processing Unit) systems due to limitations such as irregular memory access patterns, load imbalances, higher communication-computation ratios, and cross-platform support. We present a novel algorithm HiPDPL-GPU (distributed parallel Louvain) to address these challenges. We conduct experiments involving different partitioning techniques to achieve optimized performance of HiPDPL-GPU on the two largest supercomputers: Frontier and Summit. Remarkably, HiPDPL-GPU processes a graph with 4.2 billion edges in less than 3 minutes using 1024 GPUs. Qualitatively performance of HiPDPL-GPU is similar or better compared to other state-of-the-art CPU- and GPU-based implementations. While prior GPU implementations have predominantly employed CUDA, our first-of-its-kind implementation for community detection is cross-platform, accommodating both AMD and NVIDIA GPUs.

graph algorithms, high performance comptuing↗

Integration Study of Converter-Interfaced Combined Heat and Power Plants

Combined Heat and Power (CHP) systems, as a proven technology, provide numerous benefits to the plant owner by saving electricity bill, reducing carbon dioxide emissions, and improving electricity service reliability. However, their integration into the distribution grid faces many barriers including the complexity of grid code requirements and the lack of technical expertise in commercial and small industrial plants to interface with the utility and accelerate the interconnection process. To solve these issues, this study proposes a converter-interfaced solution for CHP integration. Simulations including various fault scenarios and load flow under different grid conditions are carried out to compare technical performances of the proposed solution with directly-coupled CHP. Results show that the generator size of converter-interfaced CHP can be reduced by approximately 25% and it also provides advantageous features such as reduced stress level under fault conditions and a better dynamic stability margin. In addition, a power factor controller is designed and reactive power from CHP is dispatched in such a way that the CHP plant is compliant with power factor requirements from utilities under all operating conditions.

Converter, Combined heat and power, Distributed en↗

Metamaterials for Mechanically Directing Cell Phenotype

Recently, abundant research has begun to reveal how microscale surface topography can influence a wide range of cell phenotypes in vitro, such as cell mobility, cell size and cell viability (Flemming et al. 1999, Nikkhah et al. 2012, Wang et al. 2016). However, while these studies shed some light on cell interactions with 2D surfaces of different length scales, cells in vivo experience their surroundings in 3D. Therefore, investigations into cell interactions with varying 3D microstructures are needed to gain biologically relevant insight into how microarchitecture and feature size influences cell behavior. Understanding this relationship between 3D microstructure and cell behavior will have a huge impact on tissue engineering and mechanobiology. Until now, the ability to fabricate complex 3D microstructures for cell behavior studies has been limited. This study harnessed LLNL’s Projection Micro-Stereolithography (PμSL) capability to probe the effects of micron-scale changes in 3D architecture on cell phenotype. Furthermore, our studies explored the application of external forces—such as cyclic loading and flow-induced shear stress—to cell-seeded 3D microstructures to further examine cell behavior.

36 MATERIALS SCIENCE↗

Data Processing Package for Cyclic Integrated Reversible Bending Fatigue Testing

A data processing software package has been introduced. The package was developed using MATLAB with the aid of the Curve Fitting Toolbox. The package is made up of four modules: pre-processing, data processing for static testing, data processing for monitoring, and data processing for measurements. CIRFT data are structured with multiple levels of architecture involving group, specimen, session, and scan/block. The degree of complexity of the data structure depends on whether a test is static or cyclic.The test results are presented in figures, scatter plots, and tables. For static testing, the output in tables provides bending mechanical properties and characteristic points of moment–curvature relation: flexural rigidities in linear segments of loading and unloading stages, intersection points between characteristic segments of the curve, and equivalent stress and strain quantities. For cyclic testing, the table output lists control and fatigue life and responsive/dependent quantities including moment, curvature, flexural rigidity, flexural hysteresis, rigidity phase angle, and equivalent stresses and strains. In addition, derivatives such as half-gage length and sensor spacing correction are included. The output also provides standard deviations of the reported quantities when they are applicable or available. The data processing package can serve as a fundamental characterization tool in mechanical study of materials. The package is intended primarily for data processing for the CIRFT process and can also be used in applications for which similar testing requirements exist.

36 MATERIALS SCIENCE↗

Additional Data Focused on Phase 1 Geared Toward Computational Fluid Dynamics (CFD) validation

A new validation campaign was developed within the Offshore Code Comparison Collaboration, Continued, with Correlation and unCertainty (OC6) to better understand the complex interactions between components of a floating wind system (e.g., columns, pontoons, etc.) in a more generic sense, and to validate modeling approaches for a variety of floating designs. A set of cylinders based on the Offshore Code Comparison Collaboration Continuation (OC4)-DeepCwind semidesign were tested under wave loading, both individually and in different combinations (including the attachment of heave plates of different sizes). The cylinders were held rigid, and pressure sensors were used to measure the distributed loading on the structures, while load cells measured the total integrated hydrodynamic loads.

17 WIND ENERGY↗

Interactive design of large end rings on stiffened conical shells using composites

Design study methods and results for a composite reinforced base ring for the conical aeroshell structure of the planetary lander vehicle for Project Viking, an unmanned mission to Mars, are presented. The aeroshell is a ring and stringer-stiffened conical shell structure having a half angle of 70 degrees with a large base ring mounted at the outer edge of the cone and a large pay-load ring in the interior with many smaller rings spaced along the inside shell surface. The purpose of the structure is to develop the aerodynamic drag required to decelerate the lander in the Mars atmosphere to facilitiate a soft landing. The design of a shell structure of this complexity requires the use of the latest technology available in a large general-purpose shell buckling program. The large general-purpose non-linear shell buckling program (BOSOR 2) which was used for this purpose is described.

Davis, R. C.↗

Numerical method to calculate the induced drag or optimum loading for arbitrary non-planar aircraft

A simple unified numerical method applicable to non-planar subsonic aircraft has been developed for calculating either the induced drag for an arbitrary loading or the optimum aircraft loading which results in minimum induced drag. The method utilizes a vortex lattice representation of the aircraft lifting surfaces coupled with the classic equations and theorems for computing and minimizing induced drag. Correlation of results from the numerical method with non-planar solutions obtained from other more complex theories indicates very good agreement. Comparison of the induced-drag computations using the numerical method with experimental data for planar and non-planar configurations was also very good.

Blackwell, J. A., Jr.↗

Space plasma laboratory - Experiment in simulated ionospheric plasma

Several experiments with simulated ionospheric plasma were performed in the Johnson Space Center's large (17 m diameter x 27 m height) vacuum chamber. Two of these, the RF discharge and the electron-beam plasma discharge, are described here. The RF experiment involved measurement of the loading on a 5 m dipole and a 5 m loop antenna caused by the presence of a plasma. The results indicate that when the RF frequency is near the electron gyro frequency a self-sustained plasma discharge is set up and the real part of the complex antenna impedance increases. The beam-plasma experiment was carried out to study a discharge produced by an electron beam with an energy of about 1 keV when the electron beam was injected parallel to the ambient magnetic field. As the beam current was raised to a critical level, a spontaneous transition occurred whereby a luminous halo was formed around the electron beam indicating a sustained discharge.

Konradi, A.↗

Potential utilization of the NASA/George C. Marshall Space Flight Center in earthquake engineering research

Earthquake engineering research capabilities of the National Aeronautics and Space Administration (NASA) facilities at George C. Marshall Space Flight Center (MSFC), Alabama, were evaluated. The results indicate that the NASA/MSFC facilities and supporting capabilities offer unique opportunities for conducting earthquake engineering research. Specific features that are particularly attractive for large scale static and dynamic testing of natural and man-made structures include the following: large physical dimensions of buildings and test bays; high loading capacity; wide range and large number of test equipment and instrumentation devices; multichannel data acquisition and processing systems; technical expertise for conducting large-scale static and dynamic testing; sophisticated techniques for systems dynamics analysis, simulation, and control; and capability for managing large-size and technologically complex programs. Potential uses of the facilities for near and long term test programs to supplement current earthquake research activities are suggested.

Scholl, R. E.↗

The 3-D inelastic analysis methods for hot section components: Brief description

Advanced 3-D inelastic structural/stress analysis methods and solution strategies for more accurate yet more cost-effective analysis of components subjected to severe thermal gradients and loads in the presence of mechanical loads, with steep stress and strain gradients are being developed. Anisotropy, time and temperature dependent plasticity and creep effects are also addressed. The approach is to develop four different theories, one linear and three higher order theories (polynomial function, special function, general function). The theories are progressively more complex from linear to general function in order to provide streamlined analysis capability with increasing accuracy for each hot section component and for different parts of the same component according to the severity of the local stress, strain and temperature gradients associated with hot spots, cooling holes and surface coating cracks. To further enhance the computational effectiveness, the higher order theories will have embedded singularities (cooling passages, for example) in the generic modeling region. Each of the four theories consists of three formulation models derivable from independent theoretical formulations. These formulation models are based on: (1) mechanics of materials; (2) special finite elements; and (3) an advanced formulation to be recommended by the contractor.

Chamis, C. C.↗

Recent progress in research pertaining to estimates of gas-side heat transfer in an aircraft gas turbine

A decade ago several important fundamental heat transfer phenomena were identified which were considered basic to the ability to predict heat transfer loads in aircraft gas turbines. The progress in addressing these fundamentals over the past ten years is assessed. Much reseach effort has been devoted to their study in university, industry and government labs and significant progress has been achieved. Advances in computer technology have enabled the modeling of complex 3-D fluid flow in gas turbines so necessary for heat transfer calculations. Advances in instrumentation plus improved data acquisition have brought about more reliable data sets. While much has advanced in the 1980's, much challenging research remains to be done. Several of these areas are suggested.

Graham, Robert W.↗

Using factor analysis to identify neuromuscular synergies during treadmill walking

Neuroscientists are often interested in grouping variables to facilitate understanding of a particular phenomenon. Factor analysis is a powerful statistical technique that groups variables into conceptually meaningful clusters, but remains underutilized by neuroscience researchers presumably due to its complicated concepts and procedures. This paper illustrates an application of factor analysis to identify coordinated patterns of whole-body muscle activation during treadmill walking. Ten male subjects walked on a treadmill (6.4 km/h) for 20 s during which surface electromyographic (EMG) activity was obtained from the left side sternocleidomastoid, neck extensors, erector spinae, and right side biceps femoris, rectus femoris, tibialis anterior, and medial gastrocnemius. Factor analysis revealed 65% of the variance of seven muscles sampled aligned with two orthogonal factors, labeled 'transition control' and 'loading'. These two factors describe coordinated patterns of muscular activity across body segments that would not be evident by evaluating individual muscle patterns. The results show that factor analysis can be effectively used to explore relationships among muscle patterns across all body segments to increase understanding of the complex coordination necessary for smooth and efficient locomotion. We encourage neuroscientists to consider using factor analysis to identify coordinated patterns of neuromuscular activation that would be obscured using more traditional EMG analyses.

NASA Center JSC↗