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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 73 records · Page 4

Channel coding in the space station data system network

A detailed discussion of the use of channel coding for error correction, privacy/secrecy, channel separation, and synchronization is presented. Channel coding, in one form or another, is an established and common element in data systems. No analysis and design of a major new system would fail to consider ways in which channel coding could make the system more effective. The presence of channel coding on TDRS, Shuttle, the Advanced Communication Technology Satellite Program system, the JSC-proposed Space Operations Center, and the proposed 30/20 GHz Satellite Communication System strongly support the requirement for the utilization of coding for the communications channel. The designers of the space station data system have to consider the use of channel coding.

Healy, T.↗

A general-purpose method for Pareto optimal placement of flow rate and concentration sensors in networked systems – With application to wastewater treatment plants

The advent of affordable computing, low-cost sensor hardware, and high-speed and reliable communications have spurred installation of ubiquitous sensors in complex engineered systems. However, ensuring reliable data quality remains a challenge. Exploitation of redundancy among sensor signals can help improving the precision of measured variables, detecting the presence of gross errors, and identifying faulty sensors. The cost of sensor ownership, maintenance efforts in particular, can still be cost-prohibitive however. Maximizing the ability to assess and control data quality while minimizing the cost of ownership thus requires a careful sensor placement. To solve this challenge, in this work we develop a generally applicable method to solve the multi-objective sensor placement problem in systems governed by linear and bilinear balance equations. Importantly, the method computes all Pareto-optimal sensor layouts with conventional computational resources and requires no information about the expected sensor quality.

42 ENGINEERING↗

Analysis of Automated Transit Network Systems with Battery-Electric Vehicles in Automated Mobility Districts: Preprint

The paper provides an overview of the insights and findings of the National Renewable Energy Laboratory's (NREL) ongoing research on the implementation of automated mobility districts (AMDs). AMD is a term coined by NREL to describe a geographically defined district or major activity center located in a dense urban setting with mobility applications provided by automated/autonomous vehicle (AV) systems spanning internal circulation and first-mile/last-mile connections to regional transportation hubs. Research over the past five years has focused on understanding the evolution of AMDs, beginning with demonstrations of automated shuttles prior to the pandemic, to more integrated on-demand mobility systems currently in initial stages of deployment. Initial insights and findings from earlier studies include the need for designation of a "jurisdiction having authority," a clear vision of a complete system to provide end-to-end mobility services, and the requisite intelligent infrastructure to complement AV technology. NREL's most recent Phase III research investigates station boarding/alighting (curb) issues, the full electrification of fleets, and the need for a systems engineering methodology (SEM) to properly analyze the complexities resulting from the convergence of automation, on-demand mobility, and electrification of the transit systems within the AMD. The paper reviews the findings of AMD research conducted during Phase I, II, and III, with special emphasis on Phase III results with respect to a descriptive example of the proposed SEM when a "digital twin" analytical model is used to simulate the transport fleet's battery-electric vehicle miles of travel and associated duty cycles through a rigorous analytical assessment with a comprehensive modeling process.

ADVANCED PROPULSION SYSTEMS↗

Machine Learning-Assisted Distribution System Network Reconfiguration Problem

High penetration from volatile renewable energy resources in the grid and the varying nature of loads raise the need for frequent line switching to ensure the efficient operation of electrical distribution networks. Operators must ensure maximum load delivery, reduced losses, and the operation between voltage limits. However, computations to decide the optimal feeder configuration are often computationally expensive and intractable, making it unfavorable for real-time operations. This is mainly due to the existence of binary variables in the network reconfiguration optimization problem. To tackle this issue, we have devised an approach that leverages machine learning techniques to reshape distribution networks featuring multiple substations. This involves predicting the substation responsible for serving each part of the network. Hence, it leaves simple and more tractable Optimal Power Flow problems to be solved. This method can produce accurate results in a significantly faster time, as demonstrated using the IEEE 37-bus distribution feeder. Compared to the traditional optimization-based approaches, a feasible solution is achieved approximately ten times faster for all the tested scenarios.

deep neural networks↗

Rocketsonde repeatability of temperature and wind measurements as obtained from rocketsonde network systems

Variability of temperature and wind data obtained close in time is of particular concern since questions exist on whether this variability is due to natural atmospheric variability or arises from instrumental causes. Previously conducted repeatability tests of the U.S. Loki Datasonde instrument indicated rms differences of 1C in temperature and 3 mps in wind. The newer Super Loki Datasonde instrument reaches apogee 20 km higher (about 82 km) than the older system and attains a higher initial fall velocity, thus the heat exchange effects on the measuring components are different. Data were obtained from routine rocketsonde launchings, available in pairs, with time differences of 12 to 120 minutes. Mean values calculated over the altitude range of 30 to 70 km indicate than an rms difference of 1-2 C in temperature and of 3-4 mps in the zonal and meridional components exist. Additional computations in 5-km altitude layers suggest that rms differences do not exceed 3 C and 7 mps at the highest altitudes.

Schmidlin, F. J.↗

Global positioning system network analysis with phase ambiguity resolution applied to crustal deformation studies in California

An efficient algorithm is developed for multisession adjustment of GPS data with simultaneous orbit determination and ambiguity resolution. Application of the algorithm to the analysis of data from a five-year campaign in progress in southern and central California to monitor tectonic motions using observations by GPS satellites, demonstrates improvements in estimates of station position and satellite orbits when the phase ambiguities are resolved. Most of the phase ambiguities in the GPS network were resolved, particularly for all the baselines of geophysical interest in California.

Dong, Da-Nan↗

Network, system, and status software enhancements for the autonomously managed electrical power system breadboard. Volume 1: Project summary

This volume (1 of 4) gives a summary of the original AMPS software system configuration, points out some of the problem areas in the original software design that this project is to address, and in the appendix collects all the bimonthly status reports. The purpose of AMPS is to provide a self reliant system to control the generation and distribution of power in the space station. The software in the AMPS breadboard can be divided into three levels: the operating environment software, the protocol software, and the station specific software. This project deals only with the operating environment software and the protocol software. The present station specific software will not change except as necessary to conform to new data formats.

Mckee, James W.↗

Network, system, and status software enhancements for the autonomously managed electrical power system breadboard. Volume 3: Commands specification

This volume (3 of 4) contains the specification for the command language for the AMPS system. The volume contains a requirements specification for the operating system and commands and a design specification for the operating system and command. The operating system and commands sits on top of the protocol. The commands are an extension of the present set of AMPS commands in that the commands are more compact, allow multiple sub-commands to be bundled into one command, and have provisions for identifying the sender and the intended receiver. The commands make no change to the actual software that implement the commands.

Mckee, James W.↗

Network, system, and status software enhancements for the autonomously managed electrical power system breadboard. Volume 4: Graphical status display

This volume (4 of 4) contains the description, structured flow charts, prints of the graphical displays, and source code to generate the displays for the AMPS graphical status system. The function of these displays is to present to the manager of the AMPS system a graphical status display with the hot boxes that allow the manager to get more detailed status on selected portions of the AMPS system. The development of the graphical displays is divided into two processes; the creation of the screen images and storage of them in files on the computer, and the running of the status program which uses the screen images.

Mckee, James W.↗

Multi-layer holographic bifurcative neural network system for real-time adaptive EOS data analysis

Optical data processing techniques have the inherent advantage of high data throughout, low weight and low power requirements. These features are particularly desirable for onboard spacecraft in-situ real-time data analysis and data compression applications. The proposed multi-layer optical holographic neural net pattern recognition technique will utilize the nonlinear photorefractive devices for real-time adaptive learning to classify input data content and recognize unexpected features. Information can be stored either in analog or digital form in a nonlinear photorefractive device. The recording can be accomplished in time scales ranging from milliseconds to microseconds. When a system consisting of these devices is organized in a multi-layer structure, a feed forward neural net with bifurcating data classification capability is formed. The interdisciplinary research will involve the collaboration with top digital computer architecture experts at the University of Southern California.

Liu, Hua-Kuang↗

Multi-layer holographic bifurcative neural network system for real-time adaptive EOS data analysis

Optical data processing techniques have the inherent advantage of high data throughout, low weight and low power requirements. These features are particularly desirable for onboard spacecraft in-situ real-time data analysis and data compression applications. the proposed multi-layer optical holographic neural net pattern recognition technique will utilize the nonlinear photorefractive devices for real-time adaptive learning to classify input data content and recognize unexpected features. Information can be stored either in analog or digital form in a nonlinear photofractive device. The recording can be accomplished in time scales ranging from milliseconds to microseconds. When a system consisting of these devices is organized in a multi-layer structure, a feedforward neural net with bifurcating data classification capability is formed. The interdisciplinary research will involve the collaboration with top digital computer architecture experts at the University of Southern California.

Liu, Hua-Kuang↗

LDCM Ground System. Network Lesson Learned

This slide presentation reviews the Landsat Data Continuity Mission (LDCM) and the lessons learned in implementing the network that was assembled to allow for the acquisition, archiving and distribution of the data from the Landsat mission. The objective of the LDCM is to continue the acquisition, archiving, and distribution of moderate-resolution multispectral imagery affording global, synoptic, and repetitive coverage of the earth's land surface at a scale where natural and human-induced changes can be detected, differentiated, characterized, and monitored over time. It includes a review of the ground network, including a block diagram of the ground network elements (GNE) and a review of the RF design and testing. Also included is a listing of the lessons learned.

Gal-Edd, Jonathan↗