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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 847 records · Page 47
All sourcesNASA NTRSDOE OSTI
DOE OSTI2017

Free Energy Landscapes of Membrane Transport Proteins

Molecular dynamics (MD) is now a widespread tool for investigating biochemical and biomolecular systems, its prevalence, in no small part, being due to significant advances in computational hardware over the last few decades. Even non-experts can now routinely use MD for protein and nucleic acid structure refinement, studying conformational switching events, and investigating solvation effects due to ligand/drug binding. Nonetheless, the vast majority of simulations being done today utilize only rudimentary algorithmic approaches – so-called “brute force” MD – which only permit access to a small fraction of what the approach has to offer. This is largely because the core algorithm is simple, while advanced techniques can require everything from more sophisticated models and data structures to complicated on-the-fly analysis. A core goal of this early science project is to bring one such advanced MD approach into the broader arena of high-performance computing.In particular, the powerful method of constant-pH MD has long been a relegated to experienced users and specialized model systems. In this work we develop and implement a constant-pH MD algorithm in the NAMD simulation engine making it suitable for deployment on large-scale, next-generation supercomputers as well as ambitious, cutting-edge biological applications. We report,for the first time, constant-pH simulations of a membrane transport protein and use the results to analyze its free energy landscape for ion-selectivity.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS1985

Theoretical and software considerations for general dynamic analysis using multilevel substructured models

The dynamic analysis of complex structural systems using the finite element method and multilevel substructured models is presented. The fixed-interface method is selected for substructure reduction because of its efficiency, accuracy, and adaptability to restart and reanalysis. This method is extended to reduction of substructures which are themselves composed of reduced substructures. The implementation and performance of the method in a general purpose software system is emphasized. Solution algorithms consistent with the chosen data structures are presented. It is demonstrated that successful finite element software requires the use of software executives to supplement the algorithmic language. The complexity of the implementation of restart and reanalysis porcedures illustrates the need for executive systems to support the noncomputational aspects of the software. It is shown that significant computational efficiencies can be achieved through proper use of substructuring and reduction technbiques without sacrificing solution accuracy. The restart and reanalysis capabilities and the flexible procedures for multilevel substructured modeling gives economical yet accurate analyses of complex structural systems.

Schmidt, R. J.↗
NASA NTRS1992

Development of the quasi-procedural method for use in aircraft configuration optimization

The performance of the quasi-procedural analysis system in optimization tasks is investigated. In particular, the quasi-procedural method is applied to the complete mission optimization of a medium-sized transport aircraft using a vortex-lattice aerodynamic model and finite element structural analysis of the wing and the tail. Some modifications and improvements to the system, required in order to complete this task, are described. The performance of the system is compared with that of the standard procedural system, and it is shown that the quasi-procedural approach reduces the analysis required to reach the optimum. The overall cost is shown to be strongly dependent on the analysis architecture and data structure.

Gage, P.↗
DOE OSTI2018

Identification of Selective Dual ROCK1 and ROCK2 Inhibitors Using Structure-Based Drug Design

A HTS campaign identified compound 1, an excellent hit-like molecule to initiate medicinal chemistry efforts to optimize a dual ROCK1 and ROCK2 inhibitor. Substitution (2-Cl, 2-NH 2 , 2-F, 3-F) of the pyridine hinge binding motif or replacement with pyrimidine afforded compounds with a clean CYP inhibition profile. Cocrystal structures of an early lead compound were obtained in PKA, ROCK1, and ROCK2. This provided critical structural information for medicinal chemistry to drive compound design. The structural data indicated the preferred configuration at the central benzylic carbon would be $(R)$, and application of this information to compound design resulted in compound 16. This compound was shown to be a potent and selective dual ROCK inhibitor in both enzyme and cell assays and efficacious in the retinal nerve fiber layer model after oral dosing. This tool compound has been made available through the AbbVie Compound Toolbox. Finally, the cocrystal structures also identified that aspartic acid residues 176 and 218 in ROCK2, which are glutamic acids in PKA, could be targeted as residues to drive both potency and kinome selectivity. Introduction of a piperidin-3-ylmethanamine group to the compound series resulted in compound 58, a potent and selective dual ROCK inhibitor with excellent predicted drug-like properties.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS2000

Efficient Merge and Insert Operations for Binary Heaps and Trees

Binary heaps and binary search trees merge efficiently. We introduce a new amortized analysis that allows us to prove the cost of merging either binary heaps or balanced binary trees is O(l), in the amortized sense. The standard set of other operations (create, insert, delete, extract minimum, in the case of binary heaps, and balanced binary trees, as well as a search operation for balanced binary trees) remain with a cost of O(log n). For binary heaps implemented as arrays, we show a new merge algorithm that has a single operation cost for merging two heaps, a and b, of O(absolute value of a + min(log absolute value of b log log absolute value of b. log absolute value of a log absolute value of b). This is an improvement over O(absolute value of a + log absolute value of a log absolute value of b). The cost of the new merge is so low that it can be used in a new structure which we call shadow heaps. to implement the insert operation to a tunable efficiency. Shadow heaps support the insert operation for simple priority queues in an amortized time of O(f(n)) and other operations in time O((log n log log n)/f (n)), where 1 less than or equal to f (n) less than or equal to log log n. More generally, the results here show that any data structure with operations that change its size by at most one, with the exception of a merge (aka meld) operation, can efficiently amortize the cost of the merge under conditions that are true for most implementations of binary heaps and search trees.

Kuszmaul, Christopher Lee↗
NASA NTRS2002

Computing Axisymmetric Jet Screech Tones Using Unstructured Grids

The space-time conservation element and solution element (CE/SE) method is used to solve the conservation law form of the compressible axisymmetric Navier-Stokes equations. The equations are time marched to predict the unsteady flow and the near-field screech tone noise issuing from an underexpanded circular jet. The CE/SE method uses an unstructured grid based data structure. The unstructured grids for these calculations are generated based on the method of Delaunay triangulation. The purpose of this paper is to show that an acoustics solution with a feedback loop can be obtained using truly unstructured grid technology. Numerical results are presented for two different nozzle geometries. The first is considered to have a thin nozzle lip and the second has a thick nozzle lip. Comparisons with available experimental data are shown for flows corresponding to several different jet Mach numbers. Generally good agreement is obtained in terms of flow physics, screech tone frequency, and sound pressure level.

Jorgenson, Philip C. E.↗
NASA NTRS2005

Aeroelastic Flight Data Analysis with the Hilbert-Huang Algorithm

This paper investigates the utility of the Hilbert-Huang transform for the analysis of aeroelastic flight data. It is well known that the classical Hilbert transform can be used for time-frequency analysis of functions or signals. Unfortunately, the Hilbert transform can only be effectively applied to an extremely small class of signals, namely those that are characterized by a single frequency component at any instant in time. The recently-developed Hilbert-Huang algorithm addresses the limitations of the classical Hilbert transform through a process known as empirical mode decomposition. Using this approach, the data is filtered into a series of intrinsic mode functions, each of which admits a well-behaved Hilbert transform. In this manner, the Hilbert-Huang algorithm affords time-frequency analysis of a large class of signals. This powerful tool has been applied in the analysis of scientific data, structural system identification, mechanical system fault detection, and even image processing. The purpose of this paper is to demonstrate the potential applications of the Hilbert-Huang algorithm for the analysis of aeroelastic systems, with improvements such as localized/online processing. Applications for correlations between system input and output, and amongst output sensors, are discussed to characterize the time-varying amplitude and frequency correlations present in the various components of multiple data channels. Online stability analyses and modal identification are also presented. Examples are given using aeroelastic test data from the F/A-18 Active Aeroelastic Wing aircraft, an Aerostructures Test Wing, and pitch-plunge simulation.

Brenner, Marty↗
NASA NTRS2006

Aeroelastic Flight Data Analysis with the Hilbert-Huang Algorithm

This report investigates the utility of the Hilbert Huang transform for the analysis of aeroelastic flight data. It is well known that the classical Hilbert transform can be used for time-frequency analysis of functions or signals. Unfortunately, the Hilbert transform can only be effectively applied to an extremely small class of signals, namely those that are characterized by a single frequency component at any instant in time. The recently-developed Hilbert Huang algorithm addresses the limitations of the classical Hilbert transform through a process known as empirical mode decomposition. Using this approach, the data is filtered into a series of intrinsic mode functions, each of which admits a well-behaved Hilbert transform. In this manner, the Hilbert Huang algorithm affords time-frequency analysis of a large class of signals. This powerful tool has been applied in the analysis of scientific data, structural system identification, mechanical system fault detection, and even image processing. The purpose of this report is to demonstrate the potential applications of the Hilbert Huang algorithm for the analysis of aeroelastic systems, with improvements such as localized online processing. Applications for correlations between system input and output, and amongst output sensors, are discussed to characterize the time-varying amplitude and frequency correlations present in the various components of multiple data channels. Online stability analyses and modal identification are also presented. Examples are given using aeroelastic test data from the F-18 Active Aeroelastic Wing airplane, an Aerostructures Test Wing, and pitch plunge simulation.

Brenner, Martin J.↗
NASA NTRS1994

Software reliability studies

There are many software reliability models which try to predict future performance of software based on data generated by the debugging process. Our research has shown that by improving the quality of the data one can greatly improve the predictions. We are working on methodologies which control some of the randomness inherent in the standard data generation processes in order to improve the accuracy of predictions. Our contribution is twofold in that we describe an experimental methodology using a data structure called the debugging graph and apply this methodology to assess the robustness of existing models. The debugging graph is used to analyze the effects of various fault recovery orders on the predictive accuracy of several well-known software reliability algorithms. We found that, along a particular debugging path in the graph, the predictive performance of different models can vary greatly. Similarly, just because a model 'fits' a given path's data well does not guarantee that the model would perform well on a different path. Further we observed bug interactions and noted their potential effects on the predictive process. We saw that not only do different faults fail at different rates, but that those rates can be affected by the particular debugging stage at which the rates are evaluated. Based on our experiment, we conjecture that the accuracy of a reliability prediction is affected by the fault recovery order as well as by fault interaction.

Hoppa, Mary Ann↗
NASA NTRS2011

Engineering and Scientific Applications: Using MatLab(Registered Trademark) for Data Processing and Visualization

MatLab(TradeMark)(MATrix LABoratory) is a numerical computation and simulation tool that is used by thousands Scientists and Engineers in many countries. MatLab does purely numerical calculations, which can be used as a glorified calculator or interpreter programming language; its real strength is in matrix manipulations. Computer algebra functionalities are achieved within the MatLab environment using "symbolic" toolbox. This feature is similar to computer algebra programs, provided by Maple or Mathematica to calculate with mathematical equations using symbolic operations. MatLab in its interpreter programming language form (command interface) is similar with well known programming languages such as C/C++, support data structures and cell arrays to define classes in object oriented programming. As such, MatLab is equipped with most of the essential constructs of a higher programming language. MatLab is packaged with an editor and debugging functionality useful to perform analysis of large MatLab programs and find errors. We believe there are many ways to approach real-world problems; prescribed methods to ensure foregoing solutions are incorporated in design and analysis of data processing and visualization can benefit engineers and scientist in gaining wider insight in actual implementation of their perspective experiments. This presentation will focus on data processing and visualizations aspects of engineering and scientific applications. Specifically, it will discuss methods and techniques to perform intermediate-level data processing covering engineering and scientific problems. MatLab programming techniques including reading various data files formats to produce customized publication-quality graphics, importing engineering and/or scientific data, organizing data in tabular format, exporting data to be used by other software programs such as Microsoft Excel, data presentation and visualization will be discussed.

Sen, Syamal K.↗
NASA NTRS2013

Towards a Decision Support System for Space Flight Operations

The Mission Operations Directorate (MOD) at the Johnson Space Center (JSC) has put in place a Model Based Systems Engineering (MBSE) technological framework for the development and execution of the Flight Production Process (FPP). This framework has provided much added value and return on investment to date. This paper describes a vision for a model based Decision Support System (DSS) for the development and execution of the FPP and its design and development process. The envisioned system extends the existing MBSE methodology and technological framework which is currently in use. The MBSE technological framework currently in place enables the systematic collection and integration of data required for building an FPP model for a diverse set of missions. This framework includes the technology, people and processes required for rapid development of architectural artifacts. It is used to build a feasible FPP model for the first flight of spacecraft and for recurrent flights throughout the life of the program. This model greatly enhances our ability to effectively engage with a new customer. It provides a preliminary work breakdown structure, data flow information and a master schedule based on its existing knowledge base. These artifacts are then refined and iterated upon with the customer for the development of a robust end-to-end, high-level integrated master schedule and its associated dependencies. The vision is to enhance this framework to enable its application for uncertainty management, decision support and optimization of the design and execution of the FPP by the program. Furthermore, this enhanced framework will enable the agile response and redesign of the FPP based on observed system behavior. The discrepancy of the anticipated system behavior and the observed behavior may be due to the processing of tasks internally, or due to external factors such as changes in program requirements or conditions associated with other organizations that are outside of MOD. The paper provides a roadmap for the three increments of this vision. These increments include (1) hardware and software system components and interfaces with the NASA ground system, (2) uncertainty management and (3) re-planning and automated execution. Each of these increments provide value independently; but some may also enable building of a subsequent increment.

Meshkat, Leila↗
NASA NTRS2013

Towards a decision support system for space flight operations

The Mission Operations Directorate (MOD) at the Johnson Space Center (JSC) has put in place a Model Based Systems Engineering (MBSE) technological framework for the development and execution of the Flight Production Process (FPP). This framework has provided much added value and return on investment to date. This paper describes a vision for a model based Decision Support System (DSS) for the development and execution of the FPP and its design and development process. The envisioned system extends the existing MBSE methodology and technological framework which is currently in use. The MBSE technological framework currently in place enables the systematic collection and integration of data required for building an FPP model for a diverse set of missions. This framework includes the technology, people and processes required for rapid development of architectural artifacts. It is used to build a feasible FPP model for the first flight of spacecraft and for recurrent flights throughout the life of the program. This model greatly enhances our ability to effectively engage with a new customer. It provides a preliminary work breakdown structure, data flow information and a master schedule based on its existing knowledge base. These artifacts are then refined and iterated upon with the customer for the development of a robust end-to-end, high-level integrated master schedule and its associated dependencies. The vision is to enhance this framework to enable its application for uncertainty management, decision support and optimization of the design and execution of the FPP by the program. Furthermore, this enhanced framework will enable the agile response and redesign of the FPP based on observed system behavior. The differences between the anticipated system behavior and the observed behavior may be due to the processing of tasks internally, or due to external factors such as changes in program requirements or conditions associated with other organizations that are outside of MOD. The paper provides a roadmap for the four increments of this vision. These increments include (1) the existing capabilities (2) hardware and software system components and interfaces with the NASA ground system, (3) uncertainty management and (4) re-planning and automated execution. Each of these increments provides value independently; but some may also enable building of a subsequent increment.

Ruszkowski, James↗
DOE OSTI2026

Hybrid Quantum–Classical Graph Transformers for Efficient Sentiment Analysis

Quantum Machine Learning (QML) offers a promising paradigm that leverages quantum computing principles to develop efficient and expressive models for learning from complex and structured data. Recent advances in natural language processing (NLP) and artificial intelligence (AI) have demonstrated capabilities in understanding, generating, and reasoning over linguistic and multimodal information. In this work, we present the Quantum Graph Transformer (QGT), a hybrid quantum–classical architecture that extends graph transformer capabilities through quantum self-attention. The QGT models variable-length sentences as token graphs, where both the embedding encoding and the self-attention mechanisms are implemented using parameterized quantum circuits (PQCs), enabling efficient contextual learning with significantly fewer trainable parameters. We train QGT using both fully connected and 𝑘 -nearest-neighbor graph structures and evaluate it on five benchmark sentiment-classification datasets. Experimental results show that QGT consistently achieves higher or comparable accuracy to existing quantum NLP models and outperforms a Classical Graph Transformer (CGT) baseline with identical architecture, achieving 29.4 × fewer parameters while requiring 3–5 × fewer samples to reach comparable performance. These findings highlight the potential of graph-based quantum models as scalable and data-efficient architectures for natural language understanding.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
NASA NTRS1989

Turbulence control in wall flows

Most of the detailed turbulence-structure data available pertain only to the simplest cases, involving zero pressure-gradient boundary layers and free-shear layers, and indicate that each disparate geometry possesses its own set of dominant nonlinear instabilities. Various boundary/input conditions act to modify these instabilities for low input levels; for stronger inputs, the basic instability modes/structures sustaining the turbulence field may be altered. Steady-state inputs are noted to be extremely effective in altering turbulence structures, in the directions of either amplification or diminution.

Bushnell, Dennis M.↗
DOE OSTI2023

Tiling Framework for Heterogeneous Computing of Matrix based Tiled Algorithms

Tiling matrix operations can improve the load balancing and performance of applications on heterogeneous computing resources. Writing a tile-based algorithm for each operation with a traditional, hand-tuned tiling approach that uses for loops in C/C++ is cumbersome and error prone. Moreover, it must enable and support the heterogeneous memory management of data objects and also explore architecture-supported, native, tiled-data transfer APIs instead of copying the tiled data to continuous memory before the data transfer. The tiling framework provides a tiled data structure for heterogeneous memory mapping and parameterization to a heterogeneous task specification API. We have integrated our tiled framework into MatRIS (Math kernels library using IRIS). IRIS is a heterogeneous run-time framework with a heterogeneous programming model, memory model, and task execution model. Experiments reveal that the tiled framework for BLAS operations has improved the programmability of tiled BLAS and improved performance by ~20% when compared against the traditional method that copies the data to continuous memory locations for heterogeneous computing.

Miniskar, Narasinga Rao↗
NASA NTRS1990

CCSDS - An approach to the definition of common standards for space data and information systems

The Consultative Committee for Space Data Systems (CCSDS) was formed in 1982 to develop common space system data structures, protocols, and interfaces which would facilitate mutual international support and interoperability. It soon emerged that CCSDS's activities exerted synergistic forces on systems development efforts. Currently, CCSDS is composed of both member-status and observer-status agencies; while only one member agency is admitted from any one country, multiple additional agencies may participate as observers. CCSDS recommendations to date have identified a common architectural approach for the handling and processing of space data.

Greene, Edward P.↗
DOE OSTI2025

EV-ELM (Electric Vehicle Policies with the Energy Language Model) [SWR-25-156]

Electric Vehicle Policies with the Energy Language Model (EV-ELM) leverages previous work using Large Language Models (LLMs) to find, download, and parse policy information related to energy infrastructure. In this application, we use LLMs to find policy documents related to the permitting and installation of electric vehicle charging infrastructure. This software contains the code to find, download, and parse these documents, while a related data record in the Open Energy Data Initiative (OEDI) will include the resulting output dataset that can be used for downstream analysis. The EV-ELM repository contains code for the EV-ELM project, which focuses on retrieving and processing EV permitting processes using large language models. The project is composed of two pipelines: (1) a web scraping pipeline for discovering and downloading EV permitting documents, and (2) a document parsing and extraction pipeline that processes the downloaded files to produce structured data. The web scraping pipeline is designed to extract relevant information from various websites, while the document parsing pipeline processes and analyzes the extracted documents to derive meaningful insights. Both pipelines depend on the NLR elm repository, which provides essential tools and functionalities for handling and processing the data. The web scraping pipeline is a modified version of the ordinance_gpt example within the elm repository. It has been adapted to fit the specific requirements of the EV-ELM project, ensuring that it effectively captures and processes the necessary information related to EV permitting.

Olson, Reid [National Laboratory of the Rockies (N↗
NASA NTRS1999

Structured Course Objects in a Digital Library

We are developing an Undergraduate Digital Library Framework (UDLF) that will support creation/archiving of courses and reuse of existing course material to evolve courses. UDLF supports the publication of course materials for later instantiation for a specific offering and allows the addition of time-dependent and student-specific information and structures. Instructors and, depending on permissions, students can access the general course materials or the materials for a specific offering. We are building a reference implementation based on NCSTRL+, a digital library derived from NCSTRL. Digital objects in NCSTRL+ are called buckets, self-contained entities that carry their own methods for access and display. Current bucket implementations have a two level structure of packages and elements. This is not a rich enough structure for course objects in UDLF. Typically, courses can only be modeled as a multilevel hierarchy and among different courses, both the syntax and semantics of terms may vary. Therefore, we need a mechanism to define, within a particular library, course models, their constituent objects, and the associated semantics in a flexible, extensible way. In this paper, we describe our approach to define and implement these multilayered course objects. We use XML technology to emulate complex data structures within the NCSTRL+ buckets. We have developed authoring and browsing tools to manipulate these course objects. In our current implementation a user downloading an XML based course bucket also downloads the XML-aware tools: an applet that enables the user to edit or browse the bucket. We claim that XML provides an effective means to represent multi-level structure of a course bucket.

Maly, K.↗