Deep Lynx Matlab Adapter
The Deep Lynx MATLAB Adapter is a Python application that connects the Deep Lynx data warehouse with any MATLAB simulation.
Wilsdon, KatherineN [Idaho National Laboratory] (0↗
SEARCH · Engineering Papers
Results for “Deep Lynx”
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.
Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.
Deep Lynx Data Historian
This software is intended to facilitate the ingestion of data from some data historian into Deep Lynx. A data historian in this instance is any location where sensor and operational data from some live asset is gathered. The data can be either manual retrieved by this software or the data historian source can push to a listening endpoint provided by this software.
Browning, JerenM↗
Real-Time Optimization Workflow Status Update
Economically optimal and safe operation of integrated energy systems (IES) requires optimization at many different time scales. A real-time optimization (RTO) workflow will attempt to maximize revenue and minimize operational costs on a time scale of minutes to hours. Such a workflow requires the use of a digital twin (DT), which is a virtual representation of a physical system. The DT is updated using real-time data from the physical system, and serves as a model in an optimization framework. The optimization results are then sent back to the physical system to complete the loop. This report details the progress made in developing building blocks for a DT/RTO framework. The Risk Analysis Virtual Environment (RAVEN) platform within the Framework for Optimization of Resources and Economics (FORCE) tool suite can perform many of the tasks required for building a DT and performing RTO. The first item of this report details RAVEN enhancements that enable RAVEN workflows to be run in various environments. Data communication between the physical system and its DT is essential for successful RTO. This includes preprocessing real-time data, loading data into a data warehouse, and querying the stored data. The second section of this report describes the progress made in implementing an adapter in Python in order for Deep Lynx to handle the data communication. Typical dispatch optimization frameworks are built on linear programming (LP). The prototype RTO workflow developed in this report uses an LP problem as a part of a receding-horizon- or economic model predictive control (EMPC) based optimization. The third section of this report details the framework of an RTO workflow in which the system consists of a simple electrical storage device. A DT can be built from a reduced-order model (ROM). Integrating a ROM into a typical LP optimization framework has been challenging because most optimization packages require the user to write algebraic expressions for the system model. The final section of this report shows how an externally built RAVEN ROM can be integrated in an RTO framework by using the Python package Pyomo. This demonstrates the RTO workflow capability from a software-only perspective and is an important step in demonstrating the capability to implement an RTO workflow for a physical system.
97 MATHEMATICS AND COMPUTING↗
Initial results from a ROSAT deep survey in Lynx
Preliminary results from a deep (70 ksec) Rosat survey of the high galactic latitude selected area Lynx.3A are presented. Lynx.3A sensitivity was previously studied in both the optical radio, with deep Westerbork surveys and deep multicolor Charge Couple Device (CCD) images form the Palomar 200 inch Four-Shooter. About 70 x-ray sources were detected within the central 40 foot diameter region of the Position Sensitive Proportional Counter (PSPC), observed surface densities of approximately 200 x-ray sources/sq deg are suggested, and these x-ray sources alone account for approximately 30 percent of the cosmic x-ray background (0.9 to 2.2 keV). An initial look at the observed x-ray logN - logS curve is presented, but a detailed assessment requires further study. The 4 sigma limit of about 7 times 10 to the minus 15th power erg/s.sq cm (0.5 to 2.0 keV) is considerably deeper then the Einstein deep surveys, and of comparable sensitivity to the deepest current Rosat surveys. Cross correlation with our Four Shooter optical catalogs yields at least one likely optical candidate for nearly all of the Rosat x-ray sources; a number of the likely optical identifications have colors of quasi-stellar objects (and stellar PSF), but in other cases galaxies/groups are also viable candidates.
Anderson, S. F.↗
Cyote Insights
CyOTE Insights leverages React, Vite, Typescript, Tailwind, and Daisy UI for the Graphical User Interface. It was designed in a particular style with a dark mode and a light mode. All code is broken down into components and reusable wrapper components for efficiency. All data is stored in Deep Lynx as a central data repository using an ontology based schema. The application serves as a main endpoint for the data in the COREII and CyOTE programs. The main purpose of the application is to display historical attack data in the Operational Technology space. At the time of this writing, it supports 27 historical attack reports compiled from OSINT sources. All of the data is publicly available, but what this application offers is the ability to see many years worth of publications in a detailed dashboard. It will also support future reports that are written using the other applications in the COREII program.
Pluth, AdamJ [Idaho National Laboratory (INL), Ida↗
Massive star formation in a gravitationally-lensed H II galaxy at z=3.357
The Lynx arc, with a redshift of 3.357, was discovered during spectroscopic follow-up of the z=0.570 cluster RX J0848+4456 from the ROSAT Deep Cluster Survey. The arc is characterized by a very red R - K color and strong, narrow emission lines.
star formation gravitationally-lensed↗
Development of Space-Flight Compatible Room-Temperature Electronics for the Lynx X-Ray Microcalorimeter
We are studying the development of space-flight compatible room-temperature electronics for the Lynx x-ray microcalorimeter (LXM) of the Lynx mission. The baseline readout technique for the LXM is microwave SQUID multiplexing. The key modules at room temperature are the RF electronics module and the digital electronics and event processor (DEEP). The RF module functions as frequency converters and mainly consists of local oscillators and I/Q mixers. The DEEP performs demultiplexing and event processing, and mainly consists of field-programmable gate arrays, ADCs, and DACs. We designed the RF electronics and DEEP to be flight ready, and estimated the power, size, and mass of those modules. There are two boxes each for the RF electronics and DEEP for segmentation, and the sizes of the boxes are 13 in: × 13 in: × 9 in: for the RF electronics and 15.5 in: × 11.5 in: × 9.5 in: for the DEEP. The estimated masses are 25.1 kg∕box for the RF electronics box and 24.1 kg∕box for the DEEP box. The maximum operating power for the RF electronics is 141 W or 70.5 W∕box, and for the DEEP box is 615 W or 308 W∕box. The overall power for those modules is 756 W. We describe the detail of the designs as well as the approaches to the estimation of resources, sizes, masses, and powers.
Sakai, Kazuhiro↗