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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 433 records · Page 24

Design and Assembly Process Implementation for Embedding Passive and Active Components Introduction to IPC-7092

"This presentation describes the design and assembly challenges for implementing passive and active components, in either formed or inserted methodology, into a printed board. The completed structure including internal electronic components is ready for surface mount and/or through-hole component attachment. The multilayered structure becomes a complete product ready for further processing in an assembly process and be made from organic, inorganic (ceramic) or both types of material."

embedded circuitry↗

Model compilation for embedded real-time planning and diagnosis

This paper describes MEXEC, an implemented micro executive that compiles a device model into an interal structure. Not only does this structure facilitate computing the most likely current device mode from n sets of sensor measurements, but it also facilitates generating an n step reconfiguration plan that is most likely not to result in reaching a target mode - if such a plan exists.

embedded real-time planning↗

Analyzing Risks and Vulnerabilities of Various Computer Systems and Undergoing Exploitation using Embedded Devices

Security is one of the most if not the most important areas today. After the several attacks on the United States, security everywhere has heightened from airports to communication among the military branches legionnaires. With advanced persistent threats (APTs) on the rise following Stuxnet, government branches and agencies are required, more than ever, to follow several standards, policies and procedures to reduce the likelihood of a breach. Attack vectors today are very advanced and are going to continue to get more and more advanced as security controls advance. This creates a need for networks and systems to be in an updated, patched and secured state in a launch control system environment. Attacks on critical systems are becoming more and more relevant and frequent. Nation states are hacking into critical networks that might control electrical power grids or water dams as well as carrying out advanced persistent threat (APTs) attacks on government entities. NASA, as an organization, must protect its self from attacks from all different types of attackers with different motives. Although the International Space Station was created, there is still competition between the different space programs. With that in mind, NASA might get attacked and breached for various reasons such as espionage or sabotage. My project will provide a way for NASA to complete an in house penetration test which includes: asset discovery, vulnerability scans, exploit vulnerabilities and also provide forensic information to harden systems. Completing penetration testing is a part of the compliance requirements of the Federal Information Security Act (FISMA) and NASA NPR 2810.1 and related NASA Handbooks. This project is to demonstrate how in house penetration testing can be conducted that will satisfy all of the compliance requirements of the National Institute of Standards and Technology (NIST), as outlined in FISMA. By the end of this project, I hope to have carried out the tasks stated above as well as gain an immense knowledge about compliance, security tools, networks and network devices, as well as policies and procedures.

Penetration Testing↗

Embedded Systems Hardware Integration and Code Development for Maraia Capsule and E-MIST

The cost of sending large spacecraft to orbit makes them undesirable for carrying out smaller scientific missions. Small spacecraft are more economical and can be tailored for missions where specific tasks need to be carried out, the Maraia capsule is such a spacecraft. Maraia will allow for samples of experiments conducted on the International Space Station to be returned to earth. The use of balloons to conduct experiments at the edge of space is a practical approach to reducing the large expense of using rockets. E-MIST is a payload designed to fly on a high altitude balloon. It can maintain science experiments in a controlled manner at the edge of space. The work covered here entails the integration of hardware onto each of the mentioned systems and the code associated with such work. In particular, the resistance temperature detector, pressure transducers, cameras, and thrusters for Maraia are discussed. The integration of the resistance temperature detectors and motor controllers to E-MIST is described. Several issues associated with sensor accuracy, code lock-up, and in-flight reset issues are mentioned. The solutions and proposed solutions to these issues are explained.

capsule↗

CO Adsorption on a Single‐Atom Catalyst Stably Embedded in Graphene

Abstract Confined single metal atoms in graphene‐based materials have proven to be excellent catalysts for several reactions and promising gas sensing systems. However, whether the chemical activity arises from the specific type of metal atom or is a direct consequence of the confinement itself remains unclear.

Chemistry↗

Diffeomorphisms of 4-manifolds with boundary and exotic embeddings

Abstract We define family versions of the invariant of 4-manifolds with contact boundary due to Kronheimer and Mrowka and use these to detect exotic diffeomorphisms of 4-manifolds with boundary. Further, we show the existence of the first example of exotic 3-spheres in a smooth closed 4-manifold with diffeomorphic complements.

Iida, Nobuo↗

Embedded symmetric positive semi-definite machine-learned elements for reduced-order modeling in finite-element simulations with application to threaded fasteners

Here, we present a machine-learning strategy for finite element analysis of solid mechanics wherein we replace complex portions of a computational domain with a data-driven surrogate. In the proposed strategy, we decompose a computational domain into an “outer” coarse-scale domain that we resolve using a finite element method (FEM) and an “inner” fine-scale domain. We then develop a machine-learned (ML) model for the impact of the inner domain on the outer domain. In essence, for solid mechanics, our machine-learned surrogate performs static condensation of the inner domain degrees of freedom. This is achieved by learning the map from displacements on the inner-outer domain interface boundary to forces contributed by the inner domain to the outer domain on the same interface boundary. We consider two such mappings, one that directly maps from displacements to forces without constraints, and one that maps from displacements to forces by virtue of learning a symmetric positive semi-definite (SPSD) stiffness matrix. We demonstrate, in a simplified setting, that learning an SPSD stiffness matrix results in a coarse-scale problem that is well-posed with a unique solution. We present numerical experiments on several exemplars, ranging from finite deformations of a cube to finite deformations with contact of a fastener-bushing geometry. We demonstrate that enforcing an SPSD stiffness matrix drastically improves the robustness and accuracy of FEM–ML coupled simulations, and that the resulting methods can accurately characterize out-of-sample loading configurations with significant speedups over the standard FEM simulations.

97 MATHEMATICS AND COMPUTING↗

Machine learning for arbitrary single-qubit rotations on an embedded device

Here, in this study, we present a technique for using machine learning (ML) for single-qubit gate synthesis on field-programmable logic for a superconducting transmon-based quantum computer based on simulated studies. Our approach is multi-stage. We first “bootstrap” a model based on simulation with access to the full state vector for measuring gate fidelity. We next present an algorithm, named adapted randomized benchmarking (ARB), for fine-tuning the gate on hardware based on measurements of the devices. We also present techniques for deploying the model on programmable devices with care to reduce the required resources. While the techniques here are applied to a transmon-based computer, many of them are portable to other architectures.

97 MATHEMATICS AND COMPUTING↗

Development and evaluation of a multi-functional heat pump with embedded thermal storage

We developed and tested a novel multi-functional packaged vertical heat pump designed for multi-family buildings, capable of providing space cooling, space heating, water heating, and energy storage integration. The system employs a 3-speed scroll compressor and supports energy-efficient cooling and heating across different ambient conditions, while utilizing both indoor and outdoor air sources for water heating. Key performance metrics include an integrated energy efficiency ratio of 18.0 for cooling, a heating seasonal performance factor of 10.0, and a coefficient of performance (COP) of 2.1 for heating in cold climates down to −15 ˚C. Additionally, the system delivers an annual water heating COP greater than 4.0, with outstanding performance in combined space cooling and water heating modes, achieving a total COP of 8.8 by recovering condenser waste heat. The heat pump also demonstrated thermal energy storage capabilities, integrating with phase change material systems to store heating and cooling energy. Furthermore, this versatile system offers a promising solution for improving energy efficiency and sustainability in multi-family buildings, providing high-performance heating, cooling, and water heating across a range of climates.

COP↗

ECLEIRS: Exact conservation law embedded identification of reduced states for parameterized nonlinear conservation laws from sparse and noisy data

Multi-query applications such as parameter estimation, uncertainty quantification and design optimization for parameterized partial differential equation (PDE) systems are expensive. While reduced/latent state dynamics approaches for parameterized PDEs offer a viable alternative, these approaches rely on high-quality data and struggle with highly sparse spatiotemporal noisy measurements typically obtained from experiments. Furthermore, there is no guarantee that these models satisfy governing physical conservation laws. In this article, we propose a reduced state dynamics approach, referred to as ECLEIRS, that embeds exact conservation in the solution and flux representation by utilizing a space-time divergence-free neural network formulation. We compare ECLEIRS with other reduced state dynamics approaches, those that do not enforce any physical constraints and those with physics-informed loss functions, for three shock-propagation problems: 1-D advection, 1-D Burgers and 2-D Euler equations. In conclusion, the numerical experiments conducted in this study demonstrate that ECLEIRS provides the most accurate prediction of dynamics for unseen parameters even in the presence of highly sparse and noisy data.

97 MATHEMATICS AND COMPUTING↗