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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 397 records · Page 22

Development of a Distribution Optimal Power Flow Federate for Open-Source OEDI-SI Platform

Increasing numbers of distributed generators in the electric power distribution networks require developing a control strategy to optimize solutions in real time. Linearized optimal distribution flow development has seen growth and acceptance in the distribution systems literature for efficiently modeling the \glspl{opf} for distribution systems. This paper examines the implementation and integration procedure for linearized optimal distribution flow federate to \gls{oedisi} platform. Specifically, we discuss i) the usage of the \gls{oedisi} platform, ii) obtaining a tractable solution using developed \gls{opf} federate, and iii) validation of solutions and bench-marking the \gls{oedisi} platform with developed \gls{opf} federate using OpenDSS. In brief, we demonstrate how a general linearized optimal distribution flow federate can be developed and integrated with a co-simulation environment to mimic real-world examples. The efficacy of the proposed method is demonstrated using the IEEE 123-bus test system under different scenarios to obtain a tractable solution and compare its results.

Sadnan, Rabayet↗

An Experimental Parametric Study of Geometric, Reynolds Number, and Ratio of Specific Heats Effects in Three-Dimensional Sidewall Compression Scramjet Inlets at Mach 6

Since mission profiles for airbreathing hypersonic vehicles such as the National Aero-Space Plane include single-stage-to-orbit requirements, real gas effects may become important with respect to engine performance. The effects of the decrease in the ratio of specific heats have been investigated in generic three-dimensional sidewall compression scramjet inlets with leading-edge sweep angles of 30 and 70 degrees. The effects of a decrease in ratio of specific heats were seen by comparing data from two facilities in two test gases: in the Langley Mach 6 CF4 Tunnel in tetrafluoromethane (where gamma=1.22) and in the Langley 15-Inch Mach 6 Air Tunnel in perfect gas air (where gamma=1.4). In addition to the simulated real gas effects, the parametric effects of cowl position, contraction ratio, leading-edge sweep, and Reynolds number were investigated in the 15-Inch Mach 6 Air Tunnel. The models were instrumented with a total of 45 static pressure orifices distributed on the sidewalls and baseplate. Surface streamline patterns were examined via oil flow, and schlieren videos were made of the external flow field. The results of these tests have significant implications to ground based testing of inlets in facilities which do not operate at flight enthalpies.

Holland, Scott D.↗

Cloud microstructure as determined by an optical cloud particle spectrometer.

Use of an improved single-particle light-scattering instrument for measurement of cloud microstructure in field studies. Cloud particle size and number information is measured over 12 sizing intervals, in the range from 4 to 85 microns in diameter. The microstructure can be observed in real time and with a spatial resolution not previously reported. The general features of water cloud droplet size and number distributions are consistent with previous direct capture and replication studies. The transition from water to ice phase regions in cumuliform clouds can be inferred from dramatic changes observed in the distribution features. Results are also presented for stratus and cirrus cloud penetrations.

Ryan, R. T.↗

Building workflows for an interactive human-in-the-loop automated experiment (hAE) in STEM-EELS

Exploring the structural, chemical, and physical properties of matter on the nano- and atomic scales has become possible with the recent advances in aberration-corrected electron energy-loss spectroscopy (EELS) in scanning transmission electron microscopy (STEM). However, the current paradigm of STEM-EELS relies on the classical rectangular grid sampling, in which all surface regions are assumed to be of equal a priori interest. However, this is typically not the case for real-world scenarios, where phenomena of interest are concentrated in a small number of spatial locations, such as interfaces, structural and topological defects, and multi-phase inclusions. One of the foundational problems is the discovery of nanometer- or atomic-scale structures having specific signatures in EELS spectra. Herein, we systematically explore the hyperparameters controlling deep kernel learning (DKL) discovery workflows for STEM-EELS and identify the role of the local structural descriptors and acquisition functions in experiment progression. In agreement with the actual experiment, we observe that for certain parameter combinations the experiment path can be trapped in the local minima. We demonstrate the approaches for monitoring the automated experiment in the real and feature space of the system and knowledge acquisition of the DKL model. Based on these, we construct intervention strategies defining the human-in-the-loop automated experiment (hAE). This approach can be further extended to other techniques including 4D STEM and other forms of spectroscopic imaging. The hAE library is available on Github at https://github.com/utkarshp1161/hAE/tree/main/hAE.

Pratiush, Utkarsh [Univ. of Tennessee, Knoxville, ↗

Integration of LIBS with Machine Learning for Real-Time Monitoring of Feedstock in H 2 Gasification Applications

This project, funded by the U.S. Department of Energy (DOE) – Office of Fossil Energy under Award Number DE-FE0032177, aimed to assess the feasibility of an integrated Laser-Induced Breakdown Spectroscopy (LIBS) system with advanced machine learning (ML) models for real-time characterization and potential control of hydrogen gasifiers running on waste materials as feedstocks. This was a multidisciplinary effort that encompassed the acquisition and standardized analysis of individual and blended feedstocks—comprising biomass, coal waste, and plastic waste, followed by the development of a dynamic LIBS bench system for material sample analysis and development of predictive ML models. Comprehensive laboratory testing enabled the creation of a robust elemental dataset that served as the foundation for ML model training. Techniques such as Random Forest, Gradient Boosting, Support Vector Regression, and Neural Networks were employed to predict key feedstock properties, including higher heating value (HHV), moisture content, thermal conductivity, and ash composition with high accuracy. The results were validated against experimental data and demonstrated strong potential for real-time application in gasifier control systems. The project concluded with a study on the integration of the LIBS+ML approach for gasifier control and a techno-economic analysis of the implementation of the approach into hydrogen (H 2 ) gasification systems. Dissemination of results was carried out at a DOE meeting. This work establishes a scalable framework for automated, in-line feedstock quality assessment, offering significant implications for process optimization and emissions reduction in hydrogen production.

01 COAL, LIGNITE, AND PEAT↗

The augmentation algorithm and molecular phylogenetic trees

Moore's (1977) augmentation procedure is discussed, and it is concluded that the procedure is valid for obtaining estimates of the total number of fixed nucleotide substitutions both theoretically and in practice, for both simulated and real data, and in agreement, for experimentally dense data sets, with stochastic estimates of the divergence, provided the restrictions on codon mutability resulting from natural selection are explicitly allowed for. Tateno and Nei's (1978) critique that the augmentation procedure has a systematic bias toward overestimation of the total number of nucleotide replacements is disputed, and a data analysis suggests that ancestral sequences inferred by the method of parsimony contain a large number of incorrectly assigned nucleotides.

Holmquist, R.↗

Cellular Decomposition Based Hybrid-Hierarchical Control Systems with Applications to Flight Management Systems

The work in this research project has been focused on the construction of a hierarchical hybrid control theory which is applicable to flight management systems. The motivation and underlying philosophical position for this work has been that the scale, inherent complexity and the large number of agents (aircraft) involved in an air traffic system imply that a hierarchical modelling and control methodology is required for its management and real time control. In the current work the complex discrete or continuous state space of a system with a small number of agents is aggregated in such a way that discrete (finite state machine or supervisory automaton) controlled dynamics are abstracted from the system's behaviour. High level control may then be either directly applied at this abstracted level, or, if this is in itself of significant complexity, further layers of abstractions may be created to produce a system with an acceptable degree of complexity at each level. By the nature of this construction, high level commands are necessarily realizable at lower levels in the system.

Caines, P. E.↗

Human Modeling Evaluations in Microgravity Workstation and Restraint Development

The International Space Station (ISS) will provide long-term missions which will enable the astronauts to live and work, as well as, conduct research in a microgravity environment. The dominant factor in space affecting the crew is "weightlessness" which creates a challenge for establishing workstation microgravity design requirements. The crewmembers will work at various workstations such as Human Research Facility (HRF), Microgravity Sciences Glovebox (MSG) and Life Sciences Glovebox (LSG). Since the crew will spend considerable amount of time at these workstations, it is critical that ergonomic design requirements are integral part of design and development effort. In order to achieve this goal, the Space Human Factors Laboratory in the Johnson Space Center Flight Crew Support Division has been tasked to conduct integrated evaluations of workstations and associated crew restraints. Thus, a two-phase approach was used: 1) ground and microgravity evaluations of the physical dimensions and layout of the workstation components, and 2) human modeling analyses of the user interface. Computer-based human modeling evaluations were an important part of the approach throughout the design and development process. Human modeling during the conceptual design phase included crew reach and accessibility of individual equipment, as well as, crew restraint needs. During later design phases, human modeling has been used in conjunction with ground reviews and microgravity evaluations of the mock-ups in order to verify the human factors requirements. (Specific examples will be discussed.) This two-phase approach was the most efficient method to determine ergonomic design characteristics for workstations and restraints. The real-time evaluations provided a hands-on implementation in a microgravity environment. On the other hand, only a limited number of participants could be tested. The human modeling evaluations provided a more detailed analysis of the setup. The issues identified during the real-time testing were investigated in the human modeling analyses. In some cases, the opposite was true where preliminary human modeling analyses provided the design engineers with critical issues that needed to be addressed further. This extensive approach provided an effective means to fully address ergonomic design considerations and accurately identify critical issues.

Whitmore, Mihriban↗

SpaceFOM: An Interoperability Standard for Space Systems Simulations

There is a long history of simulation supporting space systems development. This includes relatively simple parametric simulations to more complex trajectory simulations to large scale integrated vehicle simulation. One area of relatively recent development is in the area of distributed or interoperable simulation. Distributed simulation has been in wide use by the US military for years but is being used more widely in the aerospace community. To support large scale distributed simulation, the military community has developed a number of standards to support a priori interoperability between large collections of disparate simulation. For example, the IEEE 1516 High Level Architecture (HLA) and the Real-time Platform Reference Federation Object Model (RPR FOM). While HLA is suitable for space systems, there are a number of design decisions made in the development of the RPR FOM that prevent it from working well for space applications. In order to address these deficiencies, the Simulation Interoperability Standards Organization (SISO) developed a new HLS-compatible interoperability standard to support the needs of complex space systems. This standard is the Space Reference Federation Object Model (SpaceFOM). This paper presents on overview of the SpaceFOM including the fundamentals of the SpaceFOM, the key features of the SpaceFOM, and how the SpaceFOM supports large scale distributed simulation of complex space systems.

SISO↗

The role of the host in a cooperating mainframe and workstation environment, volumes 1 and 2

In recent years, advancements made in computer systems have prompted a move from centralized computing based on timesharing a large mainframe computer to distributed computing based on a connected set of engineering workstations. A major factor in this advancement is the increased performance and lower cost of engineering workstations. The shift to distributed computing from centralized computing has led to challenges associated with the residency of application programs within the system. In a combined system of multiple engineering workstations attached to a mainframe host, the question arises as to how does a system designer assign applications between the larger mainframe host and the smaller, yet powerful, workstation. The concepts related to real time data processing are analyzed and systems are displayed which use a host mainframe and a number of engineering workstations interconnected by a local area network. In most cases, distributed systems can be classified as having a single function or multiple functions and as executing programs in real time or nonreal time. In a system of multiple computers, the degree of autonomy of the computers is important; a system with one master control computer generally differs in reliability, performance, and complexity from a system in which all computers share the control. This research is concerned with generating general criteria principles for software residency decisions (host or workstation) for a diverse yet coupled group of users (the clustered workstations) which may need the use of a shared resource (the mainframe) to perform their functions.

Kusmanoff, Antone↗

pystorms: A simulation sandbox for the development and evaluation of stormwater control algorithms

Advances in cyber–physical technologies have enabled real-time sensing and adaptive control of stormwater infrastructure. These smart stormwater systems allow for inexpensive, minimally-invasive stormwater control interventions in lieu of new construction. Importantly, however promising the area of smart stormwater control, there still remain barriers – for experts and novices alike – to access shared tools and methods for investigating, developing, and contributing to it. In an effort to make smart stormwater control research more methodical and accessible, we present pystorms, an open-source Python-based simulation sandbox that facilitates the quantitative evaluation and comparison of control strategies. pystorms consists of a collection of real world-inspired smart stormwater control scenarios on which any number of control strategies can be applied and tested via an accompanying Python programming interface and coupled stormwater simulator. pystorms provides a framework for the rigorous and efficient evaluation of smart stormwater control methodologies across diverse watersheds with only a few lines of code.

54 ENVIRONMENTAL SCIENCES↗

Understanding the Polymorphism of Cobalt Nanoparticles Formed in Electrodeposition–An In Situ XRD Study

An advanced synchrotron-based in situ X-ray diffraction (XRD) technique is successfully developed and employed to track and monitor the formation and phase selection of cobalt (Co) in electrodeposition in real time and verify DFT computational results. The impacts of a number of controlling factors including the pH of the electrolyte and deposition overpotential are systematically studied. The results show that the yielded phase of the electrodeposited Co is controlled by both thermodynamics and kinetics. The low pH low overpotential condition favors the formation of the thermodynamically stable fcc phase. While the high pH high overpotential condition promotes the formation of the metastable hcp phase. The experimental results agree well with the nanometric phase diagram computed with DFT. Layer-by-layer alternative stacking of fcc-hcp polymorphic phases can be facilely fabricated by just varying the overpotential. This work not only offers an effective means to control the phase of electroplating of Co but also presents a new approach to reveal the fundamental insights of the formation of metals under electrochemical reduction driving force.

36 MATERIALS SCIENCE↗

Geant4 Monte-Carlo (GEMC) A database-driven simulation program

GEMC[1] is an application that harnesses the power of databases to execute Geant4 Monte-Carlo simulations. The databases (MYSQL, CSQL, TEXT) define the geometry, materials, digitization algorithms, readout electronics and output formats. Implemented in C++, GEMC also boasts a user-friendly Python API that facilitates detector construction and database population. GEMC can handle real-life scenarios such as geometry variations and the run number-dependent calibration constants and digitization parameters. This abstract provides an overview of GEMC, accompanied by examples that showcase its versatility. We delve into the practical application of GEMC within the the CLAS12 experimental program at Jefferson Lab.

Ungaro, Maurizio↗

Multi-modal chemical characterization of highly viscous submicrometer organic particles

Distinguishing highly viscous organic particles within complex mixtures of atmospheric aerosol and accurate descriptions of their composition, size distributions, and mixing states are challenges at the forefront of aerosol measurement science and technology. Here, we present results obtained from complementary single-particle measurement techniques employed for the in-depth characterization of highly viscous particles. In this study, we demonstrate advantages and synergy of this multi-modal particle characterization approach based on the analysis of individual viscous particles formed in the air-discharged waste produced by a common sewer pipe rehabilitation technology. Using oil immersion flow microscopy, we investigate particle size distributions and morphology of colloidal components present in field-collected aqueous waste condensates. We compare these results with corresponding measurements of viscous particles formed in drying droplets of the aerosolized discharged waste. The colloidal components and viscous particles were found to be approximately 10 µm and 0.5 µm, respectively. The aerosolized viscous particles exhibited a spherical morphology, while the colloidal particles appeared noticeably fractal, resembling fragments of a cured composite material. Chemical imaging of the viscous particles collected on substrates was performed using scanning electron microscopy and soft X-ray spectro-microscopy techniques. Through these methods, comprehensive description of these particles emerged, confirming their high solid-like viscosity, wide-ranging sizes, diverse carbon speciation with high degrees of oxygenation, and high organic volume fractions. The aerosolized viscous particles were further characterized using high-throughput single particle mass spectrometry. This technique provides real-time measurements of composition, size, and morphological metrics for large numbers of individual particles, enabling the identification of their distinct mass spectrometric signatures.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Advection algorithms for quantum neutrino moment transport

Neutrino transport in compact objects is an inherently challenging multidimensional problem. Here, this difficulty is compounded if one includes flavor transformation—an intrinsically quantum phenomenon requiring one to follow the coherence between flavors and thus necessitating the introduction of complex numbers. To reduce the computational burden, simulations of compact objects that include neutrino transport often make use of momentum-angle-integrated moments (the lowest order ones being commonly referred to as the energy density and flux) and these quantities can be generalized to include neutrino flavor, i.e., they become quantum moments. Numerous finite-volume approaches to solving the moment evolution equations for classical neutrino transport have been developed based on solving a Riemann problem at cell interfaces. In this paper we describe our generalization of a Riemann solver for quantum moments, specifically decomposing complex numbers in terms of a (signed) magnitude and phase instead of real and imaginary parts. We then test our new algorithm in numerous cases showing a neutrino fast flavor instability, varying from toy models with analytic solutions to snapshots from neutron star merger simulations. Compared to previous algorithms for neutrino transport with flavor mixing, we find uniformly smaller growth rates of the flavor transformation along with concomitantly larger length-scales, and that the results are a better match with the growth rates seen from multiangle codes.

79 ASTRONOMY AND ASTROPHYSICS↗

Natural boundaries for scattering amplitudes

Singularities, such as poles and branch points, play a crucial role in investigating the analytic properties of scattering amplitudes that inform new computational techniques. In this note, we point out that scattering amplitudes can also have another class of singularities called natural boundaries of analyticity. They create a barrier beyond which analytic continuation cannot be performed. More concretely, we use unitarity to show that 2 \to 2 2 → 2 scattering amplitudes in theories with a mass gap can have a natural boundary on the second sheet of the lightest threshold cut. There, an infinite number of ladder-type Landau singularities densely accumulates on the real axis in the center-of-mass energy plane. We argue that natural boundaries are generic features of higher-multiplicity scattering amplitudes in gapped theories.

97 MATHEMATICS AND COMPUTING↗

3D Convective Urca Process in a Simmering White Dwarf

Abstract A proposed setting for thermonuclear (Type Ia) supernovae is a white dwarf that has gained mass from a companion to the point of carbon ignition in the core. In the early stages of carbon burning, called the simmering phase, energy released by the reactions in the core drive the formation and growth of a core convection zone. One aspect of this phase is the convective Urca process, a linking of weak nuclear reactions to convection, which may alter the composition and structure of the white dwarf. The convective Urca process is not well understood and requires 3D fluid simulations to properly model the turbulent convection, an inherently 3D process. Because the neutron excess of the fluid both sets and is set by the extent of the convection zone, the realistic steady state can only be determined in simulations with real 3D mixing processes. Additionally, the convection is relatively slow (Mach number less than 0.005) and thus a low Mach number method is needed to model the flow over many convective turnovers. Using the MAESTROeX low Mach number hydrodynamic software, we present the first full-star 3D simulations of the A = 23 convective Urca process, spanning hundreds of convective turnover times. Our findings on the extent of mixing across the Urca shell, the characteristic velocities of the flow, the energy-loss rates due to neutrino emission, and the structure of the convective boundary can be used to inform 1D stellar models that track the longer-timescale evolution.

Boyd, Brendan (ORCID:0000000254199751)↗