Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “Data processing”

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.

At least 19 records
All sourcesNASA NTRSDOE OSTI
NASA NTRS1967

Space sciences data processing.

Data processing and reduction on board spacecraft and on ground using generalized information system

SPACECRAFT INSTRUMENTATION↗
NASA NTRS1976

Efficient computer algorithms for infrared astronomy data processing

Data processing techniques to be studied for use in infrared astronomy data analysis systems are outlined. Only data from space based telescope systems operating as survey instruments are considered. Resulting algorithms, and in some cases specific software, will be applicable for use with the infrared astronomy satellite (IRAS) and the shuttle infrared telescope facility (SIRTF). Operational tests made during the investigation use data from the celestial mapping program (CMP). The overall task differs from that involved in ground-based infrared telescope data reduction.

Pelzmann, R. F., Jr.↗
NASA NTRS1992

Future Goddard data processing and data distribution systems

This paper discusses the current systems used at the Goddard Space Flight Center for processing spacecraft data, as well as the future system prospects. While current systems rely significantly on minicomputers, future systems will emphasize workstations. Space data formats will become more structured, and the increased application of space data standards will permit greater flexibilities in ground data processing, data distribution and savings in mission and data operations.

Koschmeder, Louis A.↗
DOE OSTI2025

MCPC Friction Stir Welding (FSW) Process Data

Processing parameters and machine log data for the MCPC LDRD Agile investment is collected material samples processed. This dataset captures the selected processing parameters, machine logs captured during material processing, and descriptions of how characterization samples were extracted from processed plates of material. The collect characterization data is captured in other datasets.

316 Stainless Steel↗
NASA NTRS1973

Analyses of requirements for computer control and data processing experiment subsystems: Image data processing system (IDAPS) software description (7094 version), volume 2

A description of each of the software modules of the Image Data Processing System (IDAPS) is presented. The changes in the software modules are the result of additions to the application software of the system and an upgrade of the IBM 7094 Mod(1) computer to a 1301 disk storage configuration. Necessary information about IDAPS sofware is supplied to the computer programmer who desires to make changes in the software system or who desires to use portions of the software outside of the IDAPS system. Each software module is documented with: module name, purpose, usage, common block(s) description, method (algorithm of subroutine) flow diagram (if needed), subroutines called, and storage requirements.

Source record↗
DOE OSTI2024

Performance Analysis of Data Processing in Distributed File Systems with Near Data Processing

In the era of big data, the escalating volume and velocity of data generation pose significant challenges in data processing. Traditional systems like Spark and Hadoop manage the increasing amount and velocity of data by improving data placement and processing speeds. However, they face inherent limitations due to the essential data movement required for processing. In this paper, we explore the Skyhook framework, a novel extension of the Ceph distributed system, which significantly reduces the need for data movement. We present an extensive case study using the Skyhook framework, applying it with the TPC-H and K-means clustering algorithms. More specifically, we leverage the TPC-H benchmark to distinguish between CPU-intensive and I/O-intensive tasks. We explore the integration of K-means clustering into SQL, coupled with a near-data processing system to offload the computational burden of the K-means clustering algorithm to storage nodes. We conduct a comprehensive performance evaluation of distributed data processing applications across three processing approaches: traditional layout (baseline), optimized layout, and near-data processing. Additionally, we introduce the use of the FIO tool to simulate real-world system workloads, enabling the measurement of performance metrics such as average latency and CPU utilization. Our research is a significant advance in understanding how to optimize data processing systems to meet the demands of the modern data landscape.

Hou, Shiyue↗
NASA NTRS1999

System-on-Chip Data Processing and Data Handling Spaceflight Electronics

This paper presents a methodology and a tool set which implements automated generation of moderate-size blocks of customized intellectual property (IP), thus effectively reusing prior work and minimizing the labor intensive, error-prone parts of the design process. Customization of components allows for optimization for smaller area and lower power consumption, which is an important factor given the limitations of resources available in radiation-hardened devices. The effects of variations in HDL coding style on the efficiency of synthesized code for various commercial synthesis tools are also discussed.

Kleyner, I.↗
NASA NTRS2011

Graphical Language for Data Processing

A graphical language for processing data allows processing elements to be connected with virtual wires that represent data flows between processing modules. The processing of complex data, such as lidar data, requires many different algorithms to be applied. The purpose of this innovation is to automate the processing of complex data, such as LIDAR, without the need for complex scripting and programming languages. The system consists of a set of user-interface components that allow the user to drag and drop various algorithmic and processing components onto a process graph. By working graphically, the user can completely visualize the process flow and create complex diagrams. This innovation supports the nesting of graphs, such that a graph can be included in another graph as a single step for processing. In addition to the user interface components, the system includes a set of .NET classes that represent the graph internally. These classes provide the internal system representation of the graphical user interface. The system includes a graph execution component that reads the internal representation of the graph (as described above) and executes that graph. The execution of the graph follows the interpreted model of execution in that each node is traversed and executed from the original internal representation. In addition, there are components that allow external code elements, such as algorithms, to be easily integrated into the system, thus making the system infinitely expandable.

Alphonso, Keith↗
NASA NTRS1972

Data processing 2: Advancements in large scale data processing systems for remote sensing

The development of large scale data processing systems for remote sensing is studied by evaluating: (1) the suitability of several sensor types with regard to producing data required for multispectral machine analysis; (2) various types of data preprocessing necessary to prepare such data for analysis; and (3) transfer of machine processing techniques for earth resources data to user community.

Landgrebe, D. A.↗