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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Projective embedding of dynamical systems: Uniform mean field equations

Herein we study embeddings of continuous dynamical systems in larger dimensions via projector operators. We call this technique PEDS, projective embedding of dynamical systems, as the stable fixed point of the original system dynamics are recovered via projection from the higher dimensional space. In this paper we provide a general definition and prove that for a particular type of rank-1 projector operator, the uniform mean field projector, the equations of motion become a mean field approximation of the dynamical system. While in general the embedding depends on a specified variable ordering, the same is not true for the uniform mean field projector. We prove a variety of results on the relationship between the spectrum of the Jacobian for fixed points in the original and in the embedded system. Direct applications of PEDS can be non-convex optimization and machine learning.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Huzinaga projection embedding for efficient and accurate energies of systems with localized spin-densities

We demonstrate the accuracy and efficiency of the restricted open-shell and unrestricted formulation of the absolutely localized Huzinaga projection operator embedding method. Restricted open-shell and unrestricted Huzinaga projection embedding in the full system basis is formally exact to restricted open-shell and unrestricted Kohn–Sham density functional theory, respectively. By utilizing the absolutely localized basis, we significantly improve the efficiency of the method while maintaining high accuracy. Furthermore, the absolutely localized basis allows for high accuracy open-shell wave function methods to be embedded into a closed-shell density functional theory environment. The open-shell embedding method is shown to calculate electronic energies of a variety of systems to within 1 kcal/mol accuracy of the full system wave function result. For certain highly localized reactions, such as spin transition energies on transition metals, we find that very few atoms are necessary to include in the wave function region in order to achieve the desired accuracy. This extension further broadens the applicability of our absolutely localized Huzinaga level-shift projection operator method to include open-shell species. Here, we apply our method to several representative examples, such as spin splitting energies, catalysis on transition metals, and radical reactions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Natural Charge-Transfer Analysis: Eliminating Spurious Charge-Transfer States in Time-Dependent Density Functional Theory via Diabatization, with Application to Projection-Based Embedding

For many types of vertical excitation energies, linear-response time-dependent density functional theory (LR-TDDFT) offers a useful degree of accuracy combined with unrivaled computational efficiency, although charge-transfer excitation energies are often systematically and dramatically underestimated, especially for large systems and those that contain explicit solvent. As a result, low energy electronic spectra of solution-phase chromophores often contain tens to hundreds of spurious charge-transfer states, making LR-TDDFT needlessly expensive in bulk solution. More nefariously, intensity borrowing by the low-energy charge-transfer states can affect intensities of the valence excitations even if those excitation energies are accurate. At higher excitation energies, it is difficult to distinguish spurious CT states from genuine charge-transfer-to-solvent (CTTS) excitations. In this work, we introduce an automated diabatization scheme that enables fast and effective screening of the CTTS acceptor space in bulk solution. Our procedure introduces the concept of “natural charge-transfer orbitals”, which provide a means to isolate characteristic pairs of orbitals that are most likely to participate in a CTTS excitation. The projection of these orbitals onto solvent-centered virtual orbitals provides a criterion for defining the most important solvent molecules in a given excitation. We apply this method to analyze an ab initio molecular dynamics (MD) trajectory of I-(aq) and report the lowest-energy CTTS band in the absorption spectrum. Our results are in excellent agreement with experimental measurements for bulk I-(aq), and only one-third of the water molecules in the I-(H2O)96 simulation cell need to be described with LR-TDDFT in order to obtain excitation energies that are converged to < 0.1 eV. The tools introduced herein will improve the accuracy, efficiency, and usability of LR-TDDFT in solution-phase environments

Carter-Fenk, Kevin D.↗
NASA NTRS1985

The embedded operating system project

The design and construction of embedded operating systems for real-time advanced aerospace applications was investigated. The applications require reliable operating system support that must accommodate computer networks. Problems that arise in the construction of such operating systems, reconfiguration, consistency and recovery in a distributed system, and the issues of real-time processing are reported. A thesis that provides theoretical foundations for the use of atomic actions to support fault tolerance and data consistency in real-time object-based system is included. The following items are addressed: (1) atomic actions and fault-tolerance issues; (2) operating system structure; (3) program development; (4) a reliable compiler for path Pascal; and (5) mediators, a mechanism for scheduling distributed system processes.

Campbell, R. H.↗
DOE OSTI2021

Versatile feature learning with graph convolutions and graph structures

Graphs represent real world relationships, and graph embedding projects nodes in a graph to a latent space that can help simplify downstream tasks. Recent development of graph convolutions in deep learning significantly improves the performance of many learning tasks on graphs. Unfortunately, prior embedding methods either do not embed graphs with node features, or fail to produce high-quality embeddings for downstream learning tasks that result in large performance gap in comparison to direct learning on graphs.We present a versatile and effective embedding method, Conv2Vec, for embedding graphs with or without node features. It is based on graph convolutions with objective functions motivated by concepts and structures from classical graph algorithms. Conv2Vec produce high-quality embedding for both plain graphs and graphs with node features for downstream tasks.We evaluate the embeddings generated by Conv2Vec with a transductive node classification task. With the generated embeddings and very simple machine learning approaches, we are able to achieve accuracies similar to those achieved by direct learning with graph convolutions. Interestingly, if we strip the node features from the graph and thus learning an embedding has to rely entirely on the graph topology, node classification with our embedding significantly outperforms direct learning with various graph convolutions. This suggests that structures from classical graph algorithms may play an important role in learning on graphs.

Cong, Guojing↗
DOE OSTI2020

Relativistic two-component projection-based quantum embedding for open-shell systems

In this work, we present a relativistic quantum embedding formalism capable of variationally treating relativistic effects, including scalar-relativity and spin–orbit coupling. We extend density functional theory (DFT)-in-DFT projection-based quantum embedding to a relativistic two-component formalism, where the full spin magnetization vector form is retained throughout the embedding treatment. To benchmark various relativistic embedding schemes, spin–orbit splitting of the nominally t 2g valence manifold of W(CO) 6 , exchange coupling of [(H 3 N) 4 Cr(OH) 2 Cr(NH 3 ) 4 ] 4+ , and the dissociation potential curve of WF 6 are investigated. The relativistic embedding formalism introduced in this work is well suited for efficient modeling of open-shell systems containing late transition metal, lanthanide, and actinide molecular complexes.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS1984

The embedded operating system project

This progress report describes research towards the design and construction of embedded operating systems for real-time advanced aerospace applications. The applications concerned require reliable operating system support that must accommodate networks of computers. The report addresses the problems of constructing such operating systems, the communications media, reconfiguration, consistency and recovery in a distributed system, and the issues of realtime processing. A discussion is included on suitable theoretical foundations for the use of atomic actions to support fault tolerance and data consistency in real-time object-based systems. In particular, this report addresses: atomic actions, fault tolerance, operating system structure, program development, reliability and availability, and networking issues. This document reports the status of various experiments designed and conducted to investigate embedded operating system design issues.

Campbell, R. H.↗
DOE OSTI2025

Projector‐Based Quantum Embedding Study of Iron Complexes

Projection‐based embedding theory (PBET) is used to calculate and assess the challenging spin‐crossover energies for a selection of small Fe‐containing systems by embedding the metal center into the frozen potential of the ligands. MP2, CCSD, and CCSD(T) are embedded in potentials from the SCAN and r 2 SCAN functionals and compared with the canonical values for the constituent methods and previously reported reference values. Considering the PBET calculations as a correction for the underlying DFT, the embedding calculations are able to provided improvement for most cases. In some cases, the PBET methods are able to compensate for limitations in the wave function methods and produce results similar to more rigorous calculations from the literature. For the systems with spin‐crossover energies near zero, the current methodology fails to provide consistent improvement. In conclusion, the isolated recalculation of the electronic structure around the metal center when embedded into a DFT treatment of the ligand field shows promise as a pragmatic and lower cost treatment compared to the canonical treatment of the whole system of the difficult class of spin‐crossover complexes.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS1987

EOS: A project to investigate the design and construction of real-time distributed Embedded Operating Systems

Project EOS is studying the problems of building adaptable real-time embedded operating systems for the scientific missions of NASA. Choices (A Class Hierarchical Open Interface for Custom Embedded Systems) is an operating system designed and built by Project EOS to address the following specific issues: the software architecture for adaptable embedded parallel operating systems, the achievement of high-performance and real-time operation, the simplification of interprocess communications, the isolation of operating system mechanisms from one another, and the separation of mechanisms from policy decisions. Choices is written in C++ and runs on a ten processor Encore Multimax. The system is intended for use in constructing specialized computer applications and research on advanced operating system features including fault tolerance and parallelism.

Campbell, R. H.↗
DOE OSTI2022

Electronic and Geometric effects on Photochemistry of Molecules in Well-Defined Environments

Assemblies of molecular switches at surfaces are of great interest for applications in solar energy conversion, optoelectronic and optomechanical devices. Experimental studies have demonstrated that it is possible to optically probe photoactive molecules in well-defined nanoscale environments. To understand these systems, we have developed a polarizable frozen-density embedding (FDEpol) to model the optical properties of molecules adsorbed on metal clusters. We have demonstrated that the FDEpol method can describe the ground state and linear response properties of strongly coupled systems with results that are in good agreement with exact projection based embedding method.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS1986

EOS: A project to investigate the design and construction of real-time distributed embedded operating systems

The EOS project is investigating the design and construction of a family of real-time distributed embedded operating systems for reliable, distributed aerospace applications. Using the real-time programming techniques developed in co-operation with NASA in earlier research, the project staff is building a kernel for a multiple processor networked system. The first six months of the grant included a study of scheduling in an object-oriented system, the design philosophy of the kernel, and the architectural overview of the operating system. In this report, the operating system and kernel concepts are described. An environment for the experiments has been built and several of the key concepts of the system have been prototyped. The kernel and operating system is intended to support future experimental studies in multiprocessing, load-balancing, routing, software fault-tolerance, distributed data base design, and real-time processing.

Campbell, R. H.↗
DOE OSTI2024

Subcellular Feature-Based Classification of α and β Cells Using Soft X-ray Tomography

The dysfunction of α and β cells in pancreatic islets can lead to diabetes. Many questions remain on the subcellular organization of islet cells during the progression of disease. Existing three-dimensional cellular mapping approaches face challenges such as time-intensive sample sectioning and subjective cellular identification. To address these challenges, we have developed a subcellular feature-based classification approach, which allows us to identify α and β cells and quantify their subcellular structural characteristics using soft X-ray tomography (SXT). We observed significant differences in whole-cell morphological and organelle statistics between the two cell types. Additionally, we characterize subtle biophysical differences between individual insulin and glucagon vesicles by analyzing vesicle size and molecular density distributions, which were not previously possible using other methods. These sub-vesicular parameters enable us to predict cell types systematically using supervised machine learning. We also visualize distinct vesicle and cell subtypes using Uniform Manifold Approximation and Projection (UMAP) embeddings, which provides us with an innovative approach to explore structural heterogeneity in islet cells. This methodology presents an innovative approach for tracking biologically meaningful heterogeneity in cells that can be applied to any cellular system.

3D cell mapping↗
NASA NTRS2020

IV&V Assurance Case Design for Artemis II

As human-rated missions like those in NASA’s Artemis program continue to grow in both size and complexity, and the role of software in achieving mission objectives expands dramatically, NASA’s Independent Verification and Validation (IV&V) Teams face evolving challenges in assuring the safety and performance of the safety- and mission-critical embedded software that is essential to landing astronauts on the surface of the Moon by 2024. Key among these challenges is IV&V’s desire to present a cohesive, integrated assurance statement to its stakeholders that encapsulates and summarizes our assurance positions across the integrated Artemis systems and their combined role in support of a safe and successful flight. In order to meet this challenge, the IV&V Teams have begun a transition to using formal assurance case concepts and documentation in the Goal Structuring Notation (GSN) to build an argument in support of software assurance. IV&V recognizes significant benefits to the logical argumentation structure provided by assurance cases and GSN over our current practices for documenting and managing assurance claims. In order to reap these benefits, IV&V is integrating the use of assurance case concepts with our paradigm of follow-the-risk capability based assurance. Because of this, assurance cases created and used by IV&V are distinct from the sort of assurance case created by a development project or embedded software assurance organization. IV&V’s assurance cases depend much less upon standards and regulations, and more on evidence captured by IV&V regarding the environment, requirements, design, and implementation. IV&V constructs an independent network of claims based on an independent decomposition of arguments. Based upon the risk posture of these claims and their associated software and software artifacts, IV&V then develops and executes engineering analyses and testing, which provide evidence to either support or refute the claim. This emerging risk-informed assurance case methodology is being put into practice as IV&V plans for support of the Artemis II mission, the first flight of the Orion capsule and Space Launch System with astronauts on board.

Gerek Whitman↗
NASA NTRS2020

IV&V Assurance Case Design for Artemis II

As human-rated missions like those in NASA's Artemis program continue to grow in both size and complexity, and the role of software in achieving mission objectives expands dramatically, NASA's Independent Verification and Validation (IV&V) Teams face evolving challenges in assuring the safety and performance of the safety- and mission-critical embedded software that is essential to landing astronauts on the surface of the Moon by 2024. Key among these challenges is IV&V's desire to present a cohesive, integrated assurance statement to its stakeholders that encapsulates and summarizes our assurance positions across the integrated Artemis systems and their combined role in support of a safe and successful flight. In order to meet this challenge, the IV&V Teams have begun a transition to using formal assurance case concepts and documentation in the Goal Structuring Notation (GSN) to build an argument in support of software assurance. IV&V recognizes significant benefits to the logical argumentation structure provided by assurance cases and GSN over our current practices for documenting and managing assurance claims. In order to reap these benefits, IV&V is integrating the use of assurance case concepts with our paradigm of follow-the-risk capability based assurance. Because of this, assurance cases created and used by IV&V are distinct from the sort of assurance case created by a development project or embedded software assurance organization. IV&V's assurance cases depend much less upon standards and regulations, and more on evidence captured by IV&V regarding the environment, requirements, design, and implementation. IV&V constructs an independent network of claims based on an independent decomposition of arguments. Based upon the risk posture of these claims and their associated software and software artifacts, IV&V then develops and executes engineering analyses and testing, which provide evidence to either support or refute the claim. This emerging risk-informed assurance case methodology is being put into practice as IV&V plans for support of the Artemis II mission, the first flight of the Orion capsule and Space Launch System with astronauts on board.

Whitman, Gerek↗
NASA NTRS2021

Overview of Dragonfly Entry Aerosciences Measurements (DrEAM)

NASA Ames Research Center (ARC) leads the Dragonfly Entry Aerosciences Measurements (DrEAM) project, which is an aeroshell instrumentation suite on the Dragonfly mission that fulfills the Engineering Science Investigation requirement for the New Frontiers mission. NASA ARC is partnering with NASA Langley Research Center (LaRC) and the German Aerospace Center (DLR) to provide a comprehensive sensor suite, including a DLR-provided Data Acquisition System (DAS). DrEAM will provide key aerothermodynamic data and performance analysis for Dragonfly’s forebody and backshell Thermal Protection System (TPS). Titan’s atmosphere predominantly consists of ni-trogen (~98% by mole) with small amounts of me-thane (~2% by mole) and other trace gases. CN is a strong radiator, and is found in nonequilibrium con-centrations for Titan entry. The accurate modeling of nonequilibrium CN radiation has proven to be a diffi-cult task. Prompted by the Huygens mission, many experimental campaigns and analyses were performed to better understand the aerothermal environments experienced by the probe during Titan entry [1]. How-ever, the Huygens probe carried no heatshield instru-mentation. Therefore, the DrEAM sensor suite will sig-nificantly advance the state-of-the-art not only by documenting the environment and performance of Dragonfly’s entry system but also by making key in situ measurements in Titan’s atmosphere for the first time. Aerothermal environments and TPS response will be measured using sensors whose flight heritage is tak-en from the Mars Entry, Descent, and Landing In-strumentation 2 (MEDLI2) thermocouple plugs and the COMbined Aerothermal and Radiometer Sensor (COMARS) suite [2], with the latter supplied by DLR. The MEDLI2 project used embedded thermocouples to directly measure the in-depth TPS temperature-time history at several locations on the heat shield and backshell of the Mars 2020 entry vehicle. These tem-perature measurements, in turn, can be used to infer surface environments via an inverse analysis proce-dure analogous to that used for MEDLI. For DrEAM, the thermocouple plug subsystem will be known as Dragonfly Sensors for Aero-Thermal Reconstruction (DragSTR). On Schiaparelli, the COMARS suite in-cluded three total surface-mounted heat flux sensors, three pressure sensors, and one radiometer. For DrEAM, the COMARS package will be known as the COmbined Sensor System for Titan Atmosphere (COSSTA). Since the methane concentration in the Titan atmos-phere is directly proportional to the radiative heat flux, the COSSTA measurements will be used to reduce the current uncertainty in the methane volume fraction. Atmospheric density measurements and capsule aero-dynamic data will be obtained through the onboard Inertial Measurement Unit (IMU), supplemented by pressure transducers similar to those used by the MEDLI and MEDLI2 projects. The DrEAM pressure sensors will be known as the Dragonfly Atmospheric Flight Transducers. (DrAFT). The pressure measure-ments, when combined with data from the on-board IMU, will allow for reconstruction of such quantities as vehicle Mach number, freestream density, and atmos-pheric winds. DrAFT measurements will enhance Dragonfly trajectory reconstruction and enable a sepa-ration of the aerodynamics from the atmosphere, as was done for MEDLI [3] and is currently in process for the MEDLI2 flight data set.

EDL↗
DOE OSTI2020

Faster Johnson–Lindenstrauss transforms via Kronecker products

The Kronecker product is an important matrix operation with a wide range of applications in signal processing, graph theory, quantum computing and deep learning. In this work, we introduce a generalization of the fast Johnson–Lindenstrauss projection for embedding vectors with Kronecker product structure, the Kronecker fast Johnson–Lindenstrauss transform (KFJLT). The KFJLT reduces the embedding cost by an exponential factor of the standard fast Johnson–Lindenstrauss transform’s cost when applied to vectors with Kronecker structure, by avoiding explicitly forming the full Kronecker products. Here, we prove that this computational gain comes with only a small price in embedding power: consider a finite set of $p$ points in a tensor product of $d$ constituent Euclidean spaces $\bigotimes _{k=d}^{1}{\mathbb{R}}^{n_k}$, and let $N = \prod _{k=1}^{d}n_k$. With high probability, a random KFJLT matrix of dimension $m \times N$ embeds the set of points up to multiplicative distortion $(1\pm \varepsilon )$ provided $m \gtrsim \varepsilon ^{-2} \, \log ^{2d - 1} (p) \, \log N$. We conclude by describing a direct application of the KFJLT to the efficient solution of large-scale Kronecker-structured least squares problems for fitting the CP tensor decomposition.

Kronecker structure↗
DOE OSTI2024

Signature analysis of high-throughput transcriptomics screening data for mechanistic inference and chemical grouping

Abstract High-throughput transcriptomics (HTTr) uses gene expression profiling to characterize the biological activity of chemicals in in vitro cell-based test systems. As an extension of a previous study testing 44 chemicals, HTTr was used to screen an additional 1,751 unique chemicals from the EPA’s ToxCast collection in MCF7 cells using 8 concentrations and an exposure duration of 6 h. We hypothesized that concentration-response modeling of signature scores could be used to identify putative molecular targets and cluster chemicals with similar bioactivity. Clustering and enrichment analyses were conducted based on signature catalog annotations and ToxPrint chemotypes to facilitate molecular target prediction and grouping of chemicals with similar bioactivity profiles. Enrichment analysis based on signature catalog annotation identified known mechanisms of action (MeOAs) associated with well-studied chemicals and generated putative MeOAs for other active chemicals. Chemicals with predicted MeOAs included those targeting estrogen receptor (ER), glucocorticoid receptor (GR), retinoic acid receptor (RAR), the NRF2/KEAP/ARE pathway, AP-1 activation, and others. Using reference chemicals for ER modulation, the study demonstrated that HTTr in MCF7 cells was able to stratify chemicals in terms of agonist potency, distinguish ER agonists from antagonists, and cluster chemicals with similar activities as predicted by the ToxCast ER Pathway model. Uniform manifold approximation and projection (UMAP) embedding of signature-level results identified novel ER modulators with no ToxCast ER Pathway model predictions. Finally, UMAP combined with ToxPrint chemotype enrichment was used to explore the biological activity of structurally related chemicals. The study demonstrates that HTTr can be used to inform chemical risk assessment by determining in vitro points of departure, predicting chemicals’ MeOA and grouping chemicals with similar bioactivity profiles.

Toxicology↗
NASA NTRS2010

FAILSAFE Health Management for Embedded Systems

The FAILSAFE project is developing concepts and prototype implementations for software health management in mission- critical, real-time embedded systems. The project unites features of the industry-standard ARINC 653 Avionics Application Software Standard Interface and JPL s Mission Data System (MDS) technology (see figure). The ARINC 653 standard establishes requirements for the services provided by partitioned, real-time operating systems. The MDS technology provides a state analysis method, canonical architecture, and software framework that facilitates the design and implementation of software-intensive complex systems. The MDS technology has been used to provide the health management function for an ARINC 653 application implementation. In particular, the focus is on showing how this combination enables reasoning about, and recovering from, application software problems.

Horvath, Gregory A.↗