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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 1,063 records · Page 59

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NASA NTRS2011

Communal Sensor Network for Adaptive Noise Reduction in Aircraft Engine Nacelles

Emergent behavior, a subject of much research in biology, sociology, and economics, is a foundational element of Complex Systems Science and is apropos in the design of sensor network systems. To demonstrate engineering for emergent behavior, a novel approach in the design of a sensor/actuator network is presented maintaining optimal noise attenuation as an adaptation to changing acoustic conditions. Rather than use the conventional approach where sensors are managed by a central controller, this new paradigm uses a biomimetic model where sensor/actuators cooperate as a community of autonomous organisms, sharing with neighbors to control impedance based on local information. From the combination of all individual actions, an optimal attenuation emerges for the global system.

Jones, Kennie H.↗

NASA NTRS2009

Health Monitoring of a Rotating Disk Using a Combined Analytical-Experimental Approach

Rotating disks undergo rigorous mechanical loading conditions that make them subject to a variety of failure mechanisms leading to structural deformities and cracking. During operation, periodic loading fluctuations and other related factors cause fractures and hidden internal cracks that can only be detected via noninvasive types of health monitoring and/or nondestructive evaluation. These evaluations go further to inspect material discontinuities and other irregularities that have grown to become critical defects that can lead to failure. Hence, the objectives of this work is to conduct a collective analytical and experimental study to present a well-rounded structural assessment of a rotating disk by means of a health monitoring approach and to appraise the capabilities of an in-house rotor spin system. The analyses utilized the finite element method to analyze the disk with and without an induced crack at different loading levels, such as rotational speeds starting at 3000 up to 10 000 rpm. A parallel experiment was conducted to spin the disk at the desired speeds in an attempt to correlate the experimental findings with the analytical results. The testing involved conducting spin experiments which, covered the rotor in both damaged and undamaged (i.e., notched and unnotched) states. Damaged disks had artificially induced through-thickness flaws represented in the web region ranging from 2.54 to 5.08 cm (1 to 2 in.) in length. This study aims to identify defects that are greater than 1.27 cm (0.5 in.), applying available means of structural health monitoring and nondestructive evaluation, and documenting failure mechanisms experienced by the rotor system under typical turbine engine operating conditions.

Abdul-Aziz, Ali↗

DOE OSTI2025

A genome-scale metabolic model for the denitrifying bacterium Thauera sp. MZ1T accurately predicts degradation of pollutants and production of polymers

The denitrifying bacterium Thauera sp . MZ1T, a common member of microbial communities in wastewater treatment facilities, can produce different compounds from a range of carbon (C) and nitrogen (N) sources under aerobic and anaerobic conditions. In these different conditions, Thauera modifies its metabolism to produce different compounds that influence the microbial community. In particular, Thauera sp . MZ1T produces different exopolysaccharides with floc-forming properties, impacting the physical disposition of wastewater consortia and the efficiency of nutrient assimilation by the microbial community. Under N-limiting conditions, Thauera sp . MZ1T decreases its growth rate and accelerates the accumulation of polyhydroxyalkanoate-related (PHA) compounds including polyhydroxybutyrate (PHB), which plays a fundamental role as C and energy storage in this β-proteobacterium. However, the metabolic mechanisms employed by Thauera sp . MZ1T to assimilate and catabolize many of the different C and N sources under aerobic and anaerobic conditions remain unknown. Systems biology approaches such as genome-scale metabolic modeling have been successfully used to unveil complex metabolic mechanisms for various microorganisms. Here, we developed a comprehensive metabolic model (M-model) for Thauera sp . MZ1T ( i Thauera861), consisting of 1,744 metabolites, 2,384 reactions, and 861 genes. We validated the model experimentally using over 70 different C and N sources under both aerobic and anaerobic conditions. i Thauera861 achieved a prediction accuracy of 95% for growth on various C and N sources and close to 85% for assimilation of aromatic compounds under denitrifying conditions. The M-model was subsequently deployed to determine the effects of substrates, oxygen presence, and the C:N ratio on the production of PHB and exopolysaccharides (EPS), showing the highest polymer yields are achieved with nucleotides and amino acids under aerobic conditions. This comprehensive M-model will help reveal the metabolic processes by which this ubiquitous species influences communities in wastewater treatment systems and natural environments.

Tec-Campos, Diego (ORCID:0000000188194150)↗

DOE OSTI2016

Studying fuel failure behaviour with a micromechanical approach

Under Loss Of Coolant Accident (LOCA) conditions in light water reactors, the temperature evolution within the fuel pellets combined with a reduction of the cladding confinement can lead to fuel fragmentation. This work focuses on the pellet rim, where bubbles density increases owing to a higher irradiation level. This area, called 'High Burn-up Structure' (HBS), has a specific behaviour due to a microstructure reorganization composed of small grains about 100 nm compared to 10 μm for initial UO{sub 2} fuel. The aim of this study is to define a macroscopic fragmentation model based on a micro mechanical approach to have a better understanding of the fuel mechanical behaviour at lower scale: size and volume fraction of fragments. This paper introduces a stepwise micromechanical method: firstly, we detail how to model the HBS microstructure including pressurized porosities, based on experimental or numerical data and define a Representative Volume Element (RVE). Then we use 3D full field computations in order to determine crack snapshot. Elastic computations are performed to find the bubbles pressure level which is required to reach the cracks initiation threshold. Then nonlinear computations, using a failure local behavior law, are conducted to identify the failure snapshot. The results of these nonlinear computations will be used as an input data of the homogenization ('macroscopic') model. First computations with Full-Fields FEM method give promising results at local scale. Nevertheless, material parameters need to be refined as their experimental values are not perfectly defined yet, leaving an uncertainty in the model.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2013

Direct conversion of wet algae to crude biodiesel under supercritical ethanol conditions

This paper presents a single-step, environmentally friendly approach for the direct conversion of wet algae to crude biodiesel under supercritical ethanol conditions. Ethanol was used for the simultaneous extraction and transesterification of lipids in algae to produce fatty acid ethyl esters at supercritical conditions. In this work the effects of process parameters dry algae to ethanol (wt./vol.) ratio (1:6-1:15), reaction temperature (245-270 C), and reaction time (2-30 min.) on the yield of fatty acid ethyl esters (FAEE) were studied. 67% conversion was achieved at 265 C and 20 min of reaction time. The calorific value of a purified biodiesel sample produced at optimum conditions was measured to be 43 MJ/kg, which is higher than that of fatty acid methyl esters produced from the same biomass. The purified fatty acid ethyl esters were analyzed using GC-MS and FTIR. TGA analysis of algal biomass and purified FAEE was presented along with TEM images of the biomass captured before and after supercritical ethanol transesterification. This green conversion process has the potential to provide an energy-efficient and economical route for the production of renewable biodiesel production.

09 BIOMASS FUELS↗

DOE OSTI2025

Data-Driven Mapping of the Cesium Cadmium Bromide Phase Space Utilizing a Soft-Chemistry Approach

Soft-chemistry techniques provide a versatile approach to synthesizing inorganic materials under mild conditions, enabling access to compositions and structures that are challenging to achieve through traditional thermodynamically driven solid-state methods. However, these solution-based routes often result in phase competition, requiring precise control over reaction conditions to achieve selective product formation. While one-variable-at-a-time (OVAT) approaches have traditionally been used for phase selection, data-driven strategies are emerging as more efficient methods for navigating complex synthetic spaces. Ternary metal halides, such as cesium cadmium bromides (Cs–Cd–Br), are of growing interest due to their potential in wide and ultrawide band gap applications. Unlike the well-studied cesium lead halide phases, the compositional diversity and solution-based synthesis of ternary Cs–Cd–Br phases remain largely unexplored. This study systematically investigates the synthetic phase space of the Cs–Cd–Br system by constructing a data-driven phase map. Using a common set of precursors and a standardized experimental procedure, we successfully synthesize all four known Cs–Cd–Br phases—CsCdBr 3 , Cs 2 CdBr 4 , Cs 3 CdBr 5 , and Cs 7 Cd 3 Br 13 —each exhibiting distinct structures, morphologies, and optical properties. Our findings highlight the potential of soft-chemistry methods for expanding the library of ternary metal halides and provide key insights into the thermodynamic and kinetic factors governing phase formation.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

NASA NTRS1972

Studies of oscillatory combustion and fuel vaporization

Research projects involving oscillatory combustion and fuel vaporization are reported. Comparisons of experimental and theoretical droplet vaporization histories under ambient conditions such that the droplet may approach its thermodynamic critical point are presented. Experimental data on instantaneous heat transfer from a gas to a solid surface under conditions of oscillatory pressure with comparisons to an unsteady one-dimensional model are analyzed. Droplet size and velocity distribution in a spray as obtained by use of a double flash fluorescent method were investigated.

Borman, G. L.↗

NASA NTRS1993

Model updating based on sensitivities of system matrices

A new approach, which allows the physical parameters to be adjusted and preserves the structural connectivity condition, is developed in this paper. This approach is based on the sensitivities of the mass and stiffness matrices with respect to physical parameters in an attempt to use test data to correct the analytical model. The analytical mass and stiffness matrices can be corrected simultaneously. The modal data of the updated model dramatically converges to that of the test model. A numerical example is presented to illustrate the feasibility of this approach. Comparisons with the other methods are also given.

Huang, Hsin-Hsen↗

NASA NTRS1990

A superlinear interior points algorithm for engineering design optimization

We present a quasi-Newton interior points algorithm for nonlinear constrained optimization. It is based on a general approach consisting of the iterative solution in the primal and dual spaces of the equalities in Karush-Kuhn-Tucker optimality conditions. This is done in such a way to have primal and dual feasibility at each iteration, which ensures satisfaction of those optimality conditions at the limit points. This approach is very strong and efficient, since at each iteration it only requires the solution of two linear systems with the same matrix, instead of quadratic programming subproblems. It is also particularly appropriate for engineering design optimization inasmuch at each iteration a feasible design is obtained. The present algorithm uses a quasi-Newton approximation of the second derivative of the Lagrangian function in order to have superlinear asymptotic convergence. We discuss theoretical aspects of the algorithm and its computer implementation.

Herskovits, J.↗

DOE OSTI2024

Scalable and Quench-Free Processing of Metal Halide Perovskites in Ambient Conditions

With the rise of global warming and the growing energy crisis, scientists have pivoted from typical resources to look for new materials and technologies. Perovskite materials hold the potential for making high-efficiency, low-cost solar cells through solution processing of Earth-abundant materials; however, scalability, stability, and durability remain key challenges. In order to transition from small-scale processing in inert environments to higher throughput processing in ambient conditions, the fundamentals of perovskite crystallization must be understood. Classical nucleation theory, the LaMer relation, and nonclassical crystallization considerations are discussed to provide a mechanism by which a gellan gum (GG) additive—a nontoxic polymeric saccharide—has enabled researchers to produce quality halide perovskite thin-film blade coated in ambient conditions without a quench step. Furthermore, we report on the improved stability and durability properties inherent to these films, which feature improved morphologies and optoelectronic properties compared to films spin-coated in a glovebox with antisolvent. We tune the amount of GG in the perovskite precursor and study the interplay between GG concentration and processability, morphological control, and increased stability under humidity, heat, and mechanical testing. The simplicity of this approach and insensitivity to environmental conditions enable a wide process window for the production of low-defect, mechanically robust, and operationally stable perovskites with fracture energies among the highest obtained for perovskites.

14 SOLAR ENERGY↗

NASA NTRS1998

Automatic Generation of CFD-Ready Surface Triangulations from CAD Geometry

This paper presents an approach for the generation of closed manifold surface triangulations from CAD geometry. CAD parts and assemblies are used in their native format, without translation, and a part's native geometry engine is accessed through a modeler-independent application programming interface (API). In seeking a robust and fully automated procedure, the algorithm is based on a new physical space manifold triangulation technique which was developed to avoid robustness issues associated with poorly conditioned mappings. In addition, this approach avoids the usual ambiguities associated with floating-point predicate evaluation on constructed coordinate geometry in a mapped space, The technique is incremental, so that each new site improves the triangulation by some well defined quality measure. Sites are inserted using a variety of priority queues to ensure that new insertions will address the worst triangles first, As a result of this strategy, the algorithm will return its 'best' mesh for a given (prespecified) number of sites. Alternatively, the algorithm may be allowed to terminate naturally after achieving a prespecified measure of mesh quality. The resulting triangulations are 'CFD-ready' in that: (1) Edges match the underlying part model to within a specified tolerance. (2) Triangles on disjoint surfaces in close proximity have matching length-scales. (3) The algorithm produces a triangulation such that no angle is less than a given angle bound, alpha, or greater than Pi - 2alpha This result also sets bounds on the maximum vertex degree, triangle aspect-ratio and maximum stretching rate for the triangulation. In addition to tile output triangulations for a variety of CAD parts, tile discussion presents related theoretical results which assert the existence of such all angle bound, and demonstrate that maximum bounds of between 25 deg and 30 deg may be achieved in practice.

Aftosmis, M. J.↗

NASA NTRS2002

Toward a Concept of Operations for Aviation Weather Information Implementation in the Evolving National Airspace System

The capacity of the National Airspace System is being stressed due to the limits of current technologies. Because of this, the FAA and NASA are working to develop new technologies to increase the system's capacity which enhancing safety. Adverse weather has been determined to be a major factor in aircraft accidents and fatalities and the FAA and NASA have developed programs to improve aviation weather information technologies and communications for system users The Aviation Weather Information Element of the Weather Accident Prevention Project of NASA's Aviation Safety Program is currently working to develop these technologies in coordination with the FAA and industry. This paper sets forth a theoretical approach to implement these new technologies while addressing the National Airspace System (NAS) as an evolving system with Weather Information as one of its subSystems. With this approach in place, system users will be able to acquire the type of weather information that is needed based upon the type of decision-making situation and condition that is encountered. The theoretical approach addressed in this paper takes the form of a model for weather information implementation. This model addresses the use of weather information in three decision-making situations, based upon the system user's operational perspective. The model also addresses two decision-making conditions, which are based upon the need for collaboration due to the level of support offered by the weather information provided by each new product or technology. The model is proposed for use in weather information implementation in order to provide a systems approach to the NAS. Enhancements to the NAS collaborative decision-making capabilities are also suggested.

McAdaragh, Raymon M.↗

NASA NTRS1999

On the Use of CAD-Native Predicates and Geometry in Surface Meshing

Several paradigms for accessing CAD geometry during surface meshing for CFD are discussed. File translation, inconsistent geometry engines and non-native point construction are all identified as sources of non-robustness. The paper argues in favor of accessing CAD parts and assemblies in their native format, without translation, and for the use of CAD-native predicates and constructors in surface mesh generation. The discussion also emphasizes the importance of examining the computational requirements for exact evaluation of triangulation predicates during surface meshing. The native approach is demonstrated through an algorithm for the generation of closed manifold surface triangulations from CAD geometry. CAD parts and assemblies are used in their native format, and a part's native geometry engine is accessed through a modeler-independent application programming interface (API). In seeking a robust and fully automated procedure, the algorithm is based on a new physical space manifold triangulation technique specially developed to avoid robustness issues associated with poorly conditioned mappings. In addition, this approach avoids the usual ambiguities associated with floating-point predicate evaluation on constructed coordinate geometry in a mapped space. The technique is incremental, so that each new site improves the triangulation by some well defined quality measure. The algorithm terminates after achieving a prespecified measure of mesh quality and produces a triangulation such that no angle is less than a given angle bound, a or greater than pi - 2alpha. This result also sets bounds on the maximum vertex degree, triangle aspect-ratio and maximum stretching rate for the triangulation. In addition to the output triangulations for a variety of CAD parts, the discussion presents related theoretical results which assert the existence of such an angle bound, and demonstrate that maximum bounds of between 25 deg and 30 deg may be achieved in practice.

Aftosmis, M. J.↗

NASA NTRS2019

CFD Evaluation of Lean-Direct Injection Combustors for Commercial Supersonics Technology

An overview is given of an effort that focused on using CFD analysis to complement design and configuration definition of Lean-Direct Injection (LDI) combustion concepts for NASA's Commercial Supersonic Transport (CST) program. The National Combustion Code (OpenNCC) was used to perform non-reacting and two-phase reacting flow computations for second and third generation LDI configurations at CST cruise conditions. All computations were performed with a consistent approach of mesh-generation, spray modeling, ignition and kinetics modeling. Emissions (EINOx) characteristics were predicted for CST cruise conditions, and compared with emissions data from experimental measurements to evaluate the fidelity of the CFD modeling approach to predict emissions changes in response to changes in supersonic cycle conditions.

nitrogen oxides injectors↗

NASA NTRS2019

CFD Evaluation Of Lean-Direct Injection Combustors for Commercial Supersonics Technology

Ajmani, Kumud↗

DOE OSTI2019

Development of a multiaxial deformation measure and creep-fatigue damage summation for multiple load cycle types in support of an improved creep-fatigue design method

This report describes methods for extending the elastic perfectly plastic (EPP) simplified model test (SMT) approach to cover multiaxial load conditions and methods to combine EPP+SMT use fractions for multiple loading cycles. The completion of this work, in conjunction with companion reports on constructing and validating SMT design curves, marks the development of a complete methodology for assessing creep-fatigue damage in high temperature nuclear reactor structural components. This EPP+SMT method aims to better account for elastic follow up effects, simplify the design process, and reduce overconservatism when compared to current simplified bounding approaches in the ASME Boiler and Pressure Vessel Code Section III, Division 5, Subsection HB, Subpart B covering high temperature nuclear reactors.

36 MATERIALS SCIENCE↗

DOE OSTI2023

Train, Inform, Borrow, or Combine? Approaches to Process–Guided Deep Learning for Groundwater–Influenced Stream Temperature Prediction

Although groundwater discharge is a critical stream temperature control process, it is not explicitly represented in many stream temperature models, an omission that may reduce predictive accuracy, hinder management of aquatic habitat, and decrease user confidence. We assessed the performance of a previously-described process-guided deep learning model of stream temperature in the Delaware River Basin (USA). We found lower accuracy (root mean square error [RMSE] of 1.71 versus 1.35°C) and stronger seasonal bias (absolute mean monthly bias of 1.06 vs. 0.68°C) for reaches primarily influenced by deep groundwater as compared to atmospheric conditions. We then tested four approaches for improving groundwater process representation: (a) a custom loss function leveraging the unique patterns of air and water temperature coupling characteristic of different temperature drivers, (b) inclusion of additional groundwater-relevant catchment attributes, (c) incorporation of additional process model outputs, and (d) a composite model. The custom loss function and the additional attributes significantly improved the predictive accuracy in groundwater-dominated reaches (RMSE of 1.37 and 1.26°C) and reduced the seasonal bias (absolute mean monthly bias of 0.44 and 0.48°C), but neither approach could identify holdout groundwater reaches. Variable importance analysis indicates the custom loss function nudges the model to use the existing inputs more efficiently, whereas with the added features the model relies on a broader suite of inputs. This analysis is a substantial step toward more accurately representing groundwater discharge processes in stream temperature models and will improve predictive accuracy and inform habitat management.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS2001

Portfolios in Stochastic Local Search: Efficiently Computing Most Probable Explanations in Bayesian Networks

Portfolio methods support the combination of different algorithms and heuristics, including stochastic local search (SLS) heuristics, and have been identified as a promising approach to solve computationally hard problems. While successful in experiments, theoretical foundations and analytical results for portfolio-based SLS heuristics are less developed. This article aims to improve the understanding of the role of portfolios of heuristics in SLS. We emphasize the problem of computing most probable explanations (MPEs) in Bayesian networks (BNs). Algorithmically, we discuss a portfolio-based SLS algorithm for MPE computation, Stochastic Greedy Search (SGS). SGS supports the integration of different initialization operators (or initialization heuristics) and different search operators (greedy and noisy heuristics), thereby enabling new analytical and experimental results. Analytically, we introduce a novel Markov chain model tailored to portfolio-based SLS algorithms including SGS, thereby enabling us to analytically form expected hitting time results that explain empirical run time results. For a specific BN, we show the benefit of using a homogenous initialization portfolio. To further illustrate the portfolio approach, we consider novel additive search heuristics for handling determinism in the form of zero entries in conditional probability tables in BNs. Our additive approach adds rather than multiplies probabilities when computing the utility of an explanation. We motivate the additive measure by studying the dramatic impact of zero entries in conditional probability tables on the number of zero-probability explanations, which again complicates the search process. We consider the relationship between MAXSAT and MPE, and show that additive utility (or gain) is a generalization, to the probabilistic setting, of MAXSAT utility (or gain) used in the celebrated GSAT and WalkSAT algorithms and their descendants. Utilizing our Markov chain framework, we show that expected hitting time is a rational function - i.e. a ratio of two polynomials - of the probability of applying an additive search operator. Experimentally, we report on synthetically generated BNs as well as BNs from applications, and compare SGSs performance to that of Hugin, which performs BN inference by compilation to and propagation in clique trees. On synthetic networks, SGS speeds up computation by approximately two orders of magnitude compared to Hugin. In application networks, our approach is highly competitive in Bayesian networks with a high degree of determinism. In addition to showing that stochastic local search can be competitive with clique tree clustering, our empirical results provide an improved understanding of the circumstances under which portfolio-based SLS outperforms clique tree clustering and vice versa.

Mengshoel, Ole J.↗