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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 541 records · Page 30

Feasible Actuator Range Modifier (FARM), a Tool Aiding the Solution of Unit Dispatch Problems for Advanced Energy Systems

Integrated energy systems (IESs) seek to minimize power generating costs in future power grids through the coupling of different energy technologies. To accommodate fluctuations in load demand due to the penetration of renewable energy sources, flexible operation capabilities must be fully exploited, and even power plants that are traditionally considered as base-load units need to be operated according to unconventional paradigms. Thermomechanical loads induced by frequent power adjustments can accelerate the wear and tear. If a unit is flexibly operated without respecting limits on materials, the risk of failures of expensive components will eventually increase, nullifying the additional profits ensured by flexible operation. In addition to the bounds on power variations (explicit constraints),the solution of the unit dispatch problem needs to meet the limits on the variation of key process variables, including temperature, pressure and flow rate (implicit constraints).The FARM (Feasible Actuator Range Modifier) module was developed to enable existing optimization algorithms to identify solutions to the unit dispatch problem that are both economically favorable and technologically sustainable. Thanks to the iterative dispatcher–validator scheme, FARM permits addressing all the imposed constraints without excessively increasing the computational costs. In this work, the algorithms constituting the module are described, and the performance was assessed by solving the unit dispatch problem for an IES composed of three units, i.e., balance of plant, gas turbine, and high-temperature steam electrolysis. Finally, the FARM module provides dedicated tools for visualizing the response of the constrained variables of interest during operational transients and a tool aiding the operator at making decisions. These techniques might represent the first step towards the deployment of an ecological interface design (EID) for IES units.

47 OTHER INSTRUMENTATION↗

Development Of FIAT-Based Parametric Thermal Protection System Mass Estimating Relationships For NASA's Multi-Mission Earth Entry Concept

An integrated tool called the Multi Mission System Analysis for Planetary Entry Descent and Landing (M-SAPE) is being developed as part of NASAs In-Space Propulsion Technology (ISPT) program. Part of M-SAPEs development requires the formulation of mass estimating relationships (MERs) to determine the vehicle's Thermal Protection System (TPS) material and required thickness for safe Earth entry. The objective of this study was to develop MERs using simple correlations that were non-ITAR and matched as accurately as possible NASAs high-fidelity ablation modeling tool, the Fully Implicit Ablation and Thermal Analysis Program (FIAT ). These MERs would be a first-estimate for feasibility studies; it is understood that higher-fidelity modeling like FIAT would be necessary once a proposed trajectory was down-selected. The trajectory space for these MERS consisted of 840 different trajectories, and a materials heating limit was the main constraint for an allowable trajectory. MERs for the vehicle fore body included the ablating materials Phenolic Impregnated Carbon Ablator (PICA ) and Carbon Phenolic atop Advanced Carbon-Carbon. For the backshell the materials were Silicone Impregnated Reusable Ceramic Ablator (SIRCA ), Acusil II, SLA-561V, and LI-900. The MERFIAT ratio indicates MERs are accurate to within 14 percent (at one standard deviation) of FIAT prediction, and the most any MER can under-predict TPS thickness is 18.7 percent of FIAT prediction. This poster focuses on the development of these MERs, the resulting equations, model limitations, and model accuracy.

thermal protection system↗

Unsteady transonic airfoil computation using the integral solution of full-potential equation

The shock-capturing integral-equation scheme developed by Kandil and Hu (1987) for the analysis of steady transonic flow over airfoils is extended to the unsteady case. The full potential formulation of the governing equations is reviewed; the solution method is outlined; and results for a NACA 0012 airfoil in forced pitching oscillation at Mach 0.755 are presented in extensive graphs and briefly characterized. The present technique is shown to require significantly less computation time than finite-difference or finite-volume methods, and to give shock-motion predictions in good agreement with those of an implicit finite-volume Euler solver; the surface-pressure peaks are slightly underpredicted.

Kandil, O. A.↗

Generative adversarial networks for scintillation signal simulation in EXO-200

Generative Adversarial Networks trained on samples of simulated or actual events have been proposed as a way of generating large simulated datasets at a reduced computational cost. In this work, a novel approach to perform the simulation of photodetector signals from the time projection chamber of the EXO-200 experiment is demonstrated. The method is based on a Wasserstein Generative Adversarial Network — a deep learning technique allowing for implicit non-parametric estimation of the population distribution for a given set of objects. Our network is trained on real calibration data using raw scintillation waveforms as input. We find that it is able to produce high-quality simulated waveforms an order of magnitude faster than the traditional simulation approach and, importantly, generalize from the training sample and discern salient high-level features of the data. In particular, the network correctly deduces position dependency of scintillation light response in the detector and correctly recognizes dead photodetector channels. Furthermore, the network output is then integrated into the EXO-200 analysis framework to show that the standard EXO-200 reconstruction routine processes the simulated waveforms to produce energy distributions comparable to that of real waveforms. Finally, the remaining discrepancies and potential ways to improve the approach further are highlighted.

47 OTHER INSTRUMENTATION↗

Vibrational heat-bath configuration interaction with semistochastic perturbation theory using harmonic oscillator or VSCF modals

Vibrational heat-bath configuration interaction (VHCI)—a selected configuration interaction technique for vibrational structure theory—has recently been developed in two independent works [J. H. Fetherolf and T. C. Berkelbach, J. Chem. Phys. 154, 074104 (2021); A. U. Bhatty and K. R. Brorsen, Mol. Phys. 119, e1936250 (2021)], where it was shown to provide accuracy on par with the most accurate vibrational structure methods with a low computational cost. Here, we eliminate the memory bottleneck of the second-order perturbation theory correction using the same (semi)stochastic approach developed previously for electronic structure theory. This allows us to treat, in an unbiased manner, much larger perturbative spaces, which are necessary for high accuracy in large systems. Stochastic errors are easily controlled to be less than 1 cm−1. We also report two other developments: (i) we propose a new heat-bath criterion and an associated exact implicit sorting algorithm for potential energy surfaces expressible as a sum of products of one-dimensional potentials; (ii) we formulate VHCI to use a vibrational self-consistent field (VSCF) reference, as opposed to the harmonic oscillator reference configuration used in previous reports. Our tests are done with quartic and sextic force fields, for which we find that with VSCF, the minor improvements to accuracy are outweighed by the higher computational cost associated the matrix element evaluations. We expect VSCF-based VHCI to be important for more general potential representations, for which the harmonic oscillator basis function integrals are no longer analytic.

Chemistry↗

Computational Modeling of the Ames 11-Ft Transonic Wind Tunnel in Conjunction with IofNEWT

Technical advances in Computational Fluid Dynamics have now made it possible to simulate complex three-dimensional internal flows about models of various size placed in a Transonic Wind Tunnel. TWT wall interference effects have been a source of error in predicting flight data from actual wind tunnel measured data. An advantage of such internal CFD calculations is to directly compare numerical results with the actual tunnel data for code assessment and tunnel flow analysis. A CFD capability has recently been devised for flow analysis of the NASA/Ames 11-Ft TWT facility. The primary objectives of this work are to provide a CFD tool to study the NASA/Ames 11-Ft TWT flow characteristics, to understand the slotted wall interference effects, and to validate CFD codes. A secondary objective is to integrate the internal flowfield calculations with the Pressure Sensitive Paint data, a surface pressure distribution capability in Ames' production wind tunnels. The effort has been part of the Ames IofNEWT, Integration of Numerical and Experimental Wind Tunnels project, which is aimed at providing further analytical tools for industrial application. We used the NASA/Ames OVERFLOW code to solve the thin-layer Navier-Stokes equations. Viscosity effects near the model are captured by Baldwin-Lomax or Baldwin-Barth turbulence models. The solver was modified to model the flow behavior in the vicinity of the tunnel longitudinal slotted walls. A suitable porous type wall boundary condition was coded to account for the cross-flow through the test section. Viscous flow equations were solved in generalized coordinates with a three-factor implicit central difference scheme in conjunction with the Chimera grid procedure. The internal flow field about the model and the tunnel walls were descretized by the Chimera overset grid system. This approach allows the application of efficient grid generation codes about individual components of the configuration; separate minor grids were developed to resolve the model and overset onto a main grid which discretizes the interior of the tunnel test section. Individual grid components axe not required to have mesh boundaries joined in any special way to each other or to the main tunnel grid. Programs have been developed to rotate the model about the tunnel pivot point and rotation axis, similar to that of the tunnel turntable mechanism for adjusting the pitch of the physical model in the test section.

Djomehri, M. Jahed↗

Navier-Stokes analysis of cold scramjet-afterbody flows

The progress of two efforts in coding solutions of Navier-Stokes equations is summarized. The first effort concerns a 3-D space marching parabolized Navier-Stokes (PNS) code being modified to compute the supersonic mixing flow through an internal/external expansion nozzle with multicomponent gases. The 3-D PNS equations, coupled with a set of species continuity equations, are solved using an implicit finite difference scheme. The completed work is summarized and includes code modifications for four chemical species, computing the flow upstream of the upper cowl for a theoretical air mixture, developing an initial plane solution for the inner nozzle region, and computing the flow inside the nozzle for both a N2/O2 mixture and a Freon-12/Ar mixture, and plotting density-pressure contours for the inner nozzle region. The second effort concerns a full Navier-Stokes code. The species continuity equations account for the diffusion of multiple gases. This 3-D explicit afterbody code has the ability to use high order numerical integration schemes such as the 4th order MacCormack, and the Gottlieb-MacCormack schemes. Changes to the work are listed and include, but are not limited to: (1) internal/external flow capability; (2) new treatments of the cowl wall boundary conditions and relaxed computations around the cowl region and cowl tip; (3) the entering of the thermodynamic and transport properties of Freon-12, Ar, O, and N; (4) modification to the Baldwin-Lomax turbulence model to account for turbulent eddies generated by cowl walls inside and external to the nozzle; and (5) adopting a relaxation formula to account for the turbulence in the mixing shear layer.

Baysal, Oktay↗

Software Model Checking of ARINC-653 Flight Code with MCP

The ARINC-653 standard defines a common interface for Integrated Modular Avionics (IMA) code. In particular, ARINC-653 Part 1 specifies a process- and partition-management API that is analogous to POSIX threads, but with certain extensions and restrictions intended to support the implementation of high reliability flight code. MCP is a software model checker, developed at NASA Ames, that provides capabilities for model checking C and C++ source code. In this paper, we present recent work aimed at implementing extensions to MCP that support ARINC-653, and we discuss the challenges and opportunities that consequentially arise. Providing support for ARINC-653 s time and space partitioning is nontrivial, though there are implicit benefits for partial order reduction possible as a consequence of the API s strict interprocess communication policy.

Thompson, Sarah J.↗

Comparison between PARFUME and Bison Using the AGR-2 Irradiation Experiment

This report documents comparisons between Fuel Model (PARFUME) model predictions versus Bison for selected compacts from the second irradiation test of the Advanced Gas Reactor (AGR) program that occurred from June 2010 to October 2013 in the Advanced Test Reactor (ATR) at Idaho National Laboratory (INL). PARFUME is a fuel performance analysis and modeling code, used for evaluating gas-reactor tristructural isotropic (TRISO) coated particle fuel for prismatic, pebble bed, plate, and cylindrical type fuel geometries. PARFUME is an integrated mechanistic computer code that evaluates the thermal, mechanical, and physico-chemical behavior of TRISO coated-fuel particles and the probability for fuel failure given the particle-to-particle statistical variations in physical dimensions and material properties that arise during the fuel fabrication process. Bison is a nuclear fuel performance application built using the Multiphysics Object-Oriented Simulation Environment (MOOSE) finite element library (Permann 2020). Bison is capable of modeling multiple fuel forms in a wide variety of dimensions and geometries. It solves coupled nonlinear partial differential equations, including heat conduction, mechanics, fission product species transport etc., in a fully implicit manner. Comparisons between PARFUME and Bison were performed using four compacts from the AGR-2 experiment. Selected outputs were chosen based on their impact on the probability of the SiC layer failing. In general there was good agreement between PARFUME and Bison with the exception of predicting the gap formed between the buffer and IPyC. Further comparisons between PARFUME and Bison are planned to further develop Bison’s capabilities.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

LinkML: an open data modeling framework

Background Scientific research relies on well-structured, standardized data; however, much of it is stored in formats such as free-text lab notebooks, nonstandardized spreadsheets, or data repositories. This lack of structure challenges interoperability, making data integration, validation, and reuse difficult. Findings LinkML (Linked Data Modeling Language) is an open framework that simplifies the process of authoring, validating, and sharing data. LinkML can describe a range of data structures, from flat, list-based models to complex, interrelated, and normalized models that utilize polymorphism and compound inheritance. It offers an approachable syntax that is not tied to any one technical architecture and can be integrated seamlessly with many existing frameworks. The LinkML syntax provides a standard way to describe schemas, classes, and relationships, allowing modelers to build well-defined, stable, and optionally ontology-aligned data structures. Once defined, LinkML schemas may be imported into other LinkML schemas. These key features make LinkML an accessible platform for interdisciplinary collaboration and a reliable way to define and share data semantics. Conclusions LinkML helps reduce heterogeneity, complexity, and the proliferation of single-use data models while simultaneously enabling compliance with FAIR (Findable, Accessible, Interoperable, and Reusable) data standards. LinkML has seen increasing adoption in various fields, including biology, chemistry, biomedicine, microbiome research, finance, electrical engineering, transportation, and commercial software development. In short, LinkML makes implicit models explicitly computable and allows data to be standardized at their origin. LinkML documentation and code are available at https://linkml.io/.

AI-ready data↗

Conjugate Compressible Fluid Flow and Heat Transfer in Ducts

A computational approach to modeling transient, compressible fluid flow with heat transfer in long, narrow ducts is presented. The primary application of the model is for analyzing fluid flow and heat transfer in solid propellant rocket motor nozzle joints during motor start-up, but the approach is relevant to a wide range of analyses involving rapid pressurization and filling of ducts. Fluid flow is modeled through solution of the spatially one-dimensional, transient Euler equations. Source terms are included in the governing equations to account for the effects of wall friction and heat transfer. The equation solver is fully-implicit, thus providing greater flexibility than an explicit solver. This approach allows for resolution of pressure wave effects on the flow as well as for fast calculation of the steady-state solution when a quasi-steady approach is sufficient. Solution of the one-dimensional Euler equations with source terms significantly reduces computational run times compared to general purpose computational fluid dynamics packages solving the Navier-Stokes equations with resolved boundary layers. In addition, conjugate heat transfer is more readily implemented using the approach described in this paper than with most general purpose computational fluid dynamics packages. The compressible flow code has been integrated with a transient heat transfer solver to analyze heat transfer between the fluid and surrounding structure. Conjugate fluid flow and heat transfer solutions are presented. The author is unaware of any previous work available in the open literature which uses the same approach described in this paper.

Cross, M. F.↗

Extending an Economical Third-Order Inviscid Nodal-Gradient Cell-Centered Finite-Volume Method to Mixed-Element Grids

In this paper, we extend an economical third-order nodal-gradient cell-centered finite-volume method, originally developed for tetrahedral grids, to mixed-element grids. It is shown that the efficient quadratic interpolation formula essential to eliminating second derivatives from a third-order accurate discretization can be easily extended to an arbitrary cell type. For the surface flux integration, we consider a split-face approach, where a quadrilateral face is split into two triangles, and the third-order method for tetrahedra is directly applied. Also, we derive a second-derivative-free, high-order, volume quadrature formula for an arbitrary cell. Numerical results are presented for accuracy verification and applications with three-dimensional nontetrahedral grids.

Computational Fluid Dynamics↗

Development of a Multi-Disciplinary Computing Environment (MDICE)

The growing need for and importance of multi-component and multi-disciplinary engineering analysis has been understood for many years. For many applications, loose (or semi-implicit) coupling is optimal, and allows the use of various legacy codes without requiring major modifications. For this purpose, CFDRC and NASA LeRC have developed a computational environment to enable coupling between various flow analysis codes at several levels of fidelity. This has been referred to as the Visual Computing Environment (VCE), and is being successfully applied to the analysis of several aircraft engine components. Recently, CFDRC and AFRL/VAAC (WL) have extended the framework and scope of VCE to enable complex multi-disciplinary simulations. The chosen initial focus is on aeroelastic aircraft applications. The developed software is referred to as MDICE-AE, an extensible system suitable for integration of several engineering analysis disciplines. This paper describes the methodology, basic architecture, chosen software technologies, salient library modules, and the current status of and plans for MDICE. A fluid-structure interaction application is described in a separate companion paper.

Kingsley, Gerry↗

Preliminary MIPCC Enhanced F-4 and F-15 Preformance Characteristics for a First Stage Reusable Launch Vehicle

Performance increases in turbojet engines can theoretically be achieved through Mass Injection Pre-Compressor Cooling (MIPCC), a process involving injecting water or oxidizer or both into an afterburning turbojet engine. The injection of water results in pre-compressor cooling, allowing the propulsion system to operate at high altitudes and Mach numbers. In this way, a MIPCC-enhanced turbojet engine could be used to power the first stage of a reusable launch vehicle or be integrated into an existing aircraft that could launch a 100-lbm payload to a reference 100-nm altitude orbit at 28 deg inclination. The two possible candidates for MIPCC flight demonstration that are evaluated in this study are the F-4 Phantom II airplane and the F-15 Eagle airplane (both of McDonnell Douglas, now The Boeing Company, Chicago, Illinois), powered by two General Electric Company (Fairfield, Connecticut) J79 engines and two Pratt & Whitney (East Hartford, Connecticut) F100-PW-100 engines, respectively. This paper presents a conceptual discussion of the theoretical performance of each of these aircraft using MIPCC propulsion techniques. Trajectory studies were completed with the Optimal Trajectories by Implicit Simulation (OTIS) software (NASA Glenn Research Center, Cleveland, Ohio) for a standard F-4 airplane and a standard F-15 airplane. Standard aircraft simulation models were constructed, and the thrust in each was altered in accordance with estimated MIPCC performance characteristics. The MIPCC and production aircraft model results were then reviewed to assess the feasibility of a MIPCC-enhanced propulsion system for use as a first-stage reusable launch vehicle; it was determined that the MIPCC-enhanced F-15 model showed a significant performance advantage over the MIPCC-enhanced F-4 model.

Air Breathing Launch Systems↗

Preliminary MIPCC Enhanced F-4 and F-15 Performance Characteristics for a First Stage Reusable Launch Vehicle

Performance increases in turbojet engines can theoretically be achieved through Mass Injection Pre-Compressor Cooling (MIPCC), a process involving injecting water or oxidizer or both into an afterburning turbojet engine. The injection of water results in pre-compressor cooling, allowing the propulsion system to operate at high altitudes and Mach numbers. In this way, a MIPCC-enhanced turbojet engine could be used to power the first stage of a reusable launch vehicle or be integrated into an existing aircraft that could launch a 100-lbm payload to a reference 100-nm altitude orbit at 28 deg inclination. The two possible candidates for MIPCC flight demonstration that are evaluated in this study are the F-4 Phantom II airplane and the F-15 Eagle airplane (both of McDonnell Douglas, now The Boeing Company, Chicago, Illinois), powered by two General Electric Company (Fairfield, Connecticut) J79 engines and two Pratt & Whitney (East Hartford, Connecticut) F100-PW-100 engines, respectively. This paper presents a conceptual discussion of the theoretical performance of each of these aircraft using MIPCC propulsion techniques. Trajectory studies were completed with the Optimal Trajectories by Implicit Simulation (OTIS) software (NASA Glenn Research Center, Cleveland, Ohio) for a standard F-4 airplane and a standard F-15 airplane. Standard aircraft simulation models were constructed, and the thrust in each was altered in accordance with estimated MIPCC performance characteristics. The MIPCC and production aircraft model results were then reviewed to assess the feasibility of a MIPCC-enhanced propulsion system for use as a first-stage reusable launch vehicle; it was determined that the MIPCC-enhanced F-15 model showed a significant performance advantage over the MIPCC-enhanced F-4 model.

MIPCC Reusable Launch Vehicle↗

Querying Semi-Structured Data

The amount of data of all kinds available electronically has increased dramatically in recent years. The data resides in different forms, ranging from unstructured data in the systems to highly structured in relational database systems. Data is accessible through a variety of interfaces including Web browsers, database query languages, application-specic interfaces, or data exchange formats. Some of this data is raw data, e.g., images or sound. Some of it has structure even if the structure is often implicit, and not as rigid or regular as that found in standard database systems. Sometimes the structure exists but has to be extracted from the data. Sometimes also it exists but we prefer to ignore it for certain purposes such as browsing. We call here semi-structured data this data that is (from a particular viewpoint) neither raw data nor strictly typed, i.e., not table-oriented as in a relational model or sorted-graph as in object databases. As will seen later when the notion of semi-structured data is more precisely de ned, the need for semi-structured data arises naturally in the context of data integration, even when the data sources are themselves well-structured. Although data integration is an old topic, the need to integrate a wider variety of data- formats (e.g., SGML or ASN.1 data) and data found on the Web has brought the topic of semi-structured data to the forefront of research. The main purpose of the paper is to isolate the essential aspects of semi- structured data. We also survey some proposals of models and query languages for semi-structured data. In particular, we consider recent works at Stanford U. and U. Penn on semi-structured data. In both cases, the motivation is found in the integration of heterogeneous data.

DATA MANAGEMENT↗

Distributed Neural Representation for Reactive In Situ Visualization

Implicit neural representations (INRs) have emerged as a powerful tool for compressing large-scale volume data. This opens up new possibilities for in situ visualization. However, the efficient application of INRs to distributed data remains an underexplored area. Here, in this work, we develop a distributed volumetric neural representation and optimize it for in situ visualization. Our technique eliminates data exchanges between processes, achieving state-of-the-art compression speed, quality and ratios. Our technique also enables the implementation of an efficient strategy for caching large-scale simulation data in high temporal frequencies, further facilitating the use of reactive in situ visualization in a wider range of scientific problems. We integrate this system with the Ascent infrastructure and evaluate its performance and usability using real-world simulations.

Wu, Qi↗

Development of Control System Functional Capabilities within the IES Plug-and-Play Simulation Environment

The concept of an Integrated Energy System (IES) is meant to combine different energy technologies in synergistic ways to achieve a more secure and economical energy supply. The RAVEN-based HYBRID framework is used to find the optimal installed capacity and the optimal economical dispatch of each component of the IES. A new RAVEN (Risk Analysis Virtual ENvironment) plugin for grid and capacity optimization (HERON) has been developed for optimizing the production variables of the IES given the demand profile. Currently, only the limits that affect the production variables and their corresponding time rates of change are considered (explicit constraints). However, other variables are additionally subject to constraints, but the associated limits are not accounted for (implicit constraints). In particular, for the power dispatch problem, the optimization algorithm takes into account the limits on the electrical power output and the corresponding hourly power variations but does not consider other constraints on process variables whose response effects the service life of the IES. This report describes a scheme that allows accounting for implicit constraints without increasing the size of the optimization problem. The Reference Governor (RG) algorithm is traditionally used for enforcing state and control constraints by modifying the set-point trajectories supplied to the feedback regulators. In our application, the RG is coupled within an iterative loop with the HERON-power dispatcher to generate optimal trajectories that ensure the operational constraints are met. A data-driven procedure to derive a representation of the dynamics of the controlled system was developed. First, the variables that represented the state of the system are selected (PCA-based approach), and then state-space representation matrices are derived from the collected measurements (DMDc algorithm). A preliminary version of the developed workflow based on Linear Time Invariant matrices was assessed by adopting a two-unit test case. More sophisticated versions of this workflow foreseeing the on-line derivation of system matrices will be deployed in FY 2021. Finally, a “plug-and-play” library of controllers and state observers was developed in Dymola. Some aspects of the current configuration of the IES unit components, e.g., the encapsulation of the control schemes into dedicated blocks, are consistent with the “plug-and-play” philosophy. Other features, e.g., the system buses collecting the input and the output variables, are not. For this reason, once listed and described the limits of the current configuration, necessary modifications to the plant model interface are presented. As a test-case, the interfaces of the SES model in the RAVEN-based HYBRID framework were reworked accordingly, and two different control schemes were applied to the same plant model.

24 POWER TRANSMISSION AND DISTRIBUTION↗