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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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NASA NTRS1978

Multiprocessing tradeoffs and the wind-tunnel simulation problem

The architecture tradeoff issue is discussed, concentrating on an oversimplified version of the multiprocessing aspect. A degree of symmetric multiprocessing is unavoidable; the choice is either complete symmetric multiprocessing or a number of identical pipelines. The processing elements can be geared to do either plane-multiprocessing, or line-multiprocessing. Other important design choices are the number notation, word length, main memory size, cache memory size, and different means to implement data transport.

Chen, T. C.↗

DOE OSTI2026

Coordinated Natural Gas and Electric Planning: Case Studies of Current Approaches and Practices

This paper examines how natural gas and electric utilities across eight U.S. states and two Canadian provinces are beginning to coordinate historically separate planning processes in response to growing system interdependencies, policy mandates, aging infrastructure, and changing customer energy choices. Electricity planning has long relied on robust integrated resource planning frameworks that weigh numerous objectives, risks, and costs. Natural gas planning, on the other hand, is typically less transparent and more narrowly focused on safety and system integrity. As economic, reliability, and policy drivers place new and shared demands on both systems, jurisdictions and utilities are experimenting with approaches such as coordinated forecasting, non pipeline alternatives, and combined planning pilots. A few have issued regulatory or statutory directives for greater data sharing and methodological alignment. Case studies from British Columbia, California, Colorado, Illinois, Massachusetts, Minnesota, New York, Québec, Rhode Island, and Washington illustrate a wide range of approaches to rethinking siloed planning. The paper identifies several common themes across the jurisdictions examined. It provides observations on the methods, processes, and organizational steps that may be needed in the future to address the challenges being faced by states and utilities. Lastly, it identifies some initial steps that states and utilities can consider if they would like to pursue more integrated, cost-effective, policy-aligned energy system planning.

03 NATURAL GAS↗

NASA NTRS1989

Data compression for Eos on-board SAR processor

A lightweight, low-power, real-time data compressor design for the Earth Observing System (Eos) onboard synthetic aperture radar (SAR) processor is presented. The implementation is based on VLSI design of a pipelined binary tree-searched vector quantizer (VQ), utilizing space-qualifiable 1.25-micron CMOS technology. The implementation exploits VLSI system design principles such as the modularity, regular data flow, simple interconnection, localized communication, simple global control, and parallel/pipelined processing. The overall system requires 30 chips with only one VLSI processing element design. The total weight is about 1.2 lbs, with an estimated power dissipation of approximately 4 watts operating at the maximum input data rate. The projected throughput rate exceeds 5 MHz.

Chang, C. Y.↗

NASA NTRSDate not supplied

Seven Years of Bright Meteor Data from the NASA All Sky Fireball Network

The NASA All Sky Fireball Network is a network consisting of 18 all-sky meteor cameras across the continental US. We present a data release of 33,660 bright meteors collected between 2013 and 2019. The released data consists of trajectory, orbit, radiant, shower association, and brightness. We discuss the camera hardware and software used to make the observations, the characteristics of the data, and known error sources. The camera hardware consists of Watec 902H2 Ultimate CCD cameras with a fish-eye lens giving an all-sky field of view. The data is complete until an absolute meteor magnitude of approximately -4, but meteors down to a magnitude of -1 are routinely observed. The cameras are spread across the continental United States in five subnetworks, with each network consisting of two to five cameras. The cameras report to a central server where the data is processed each morning. The network is modeled after the University of Western Ontario’s Southern Ontario Meteor Network. The cameras are running All-sky and Guided Real-time Detection (ASGARD) meteor detection software and analysis pipeline.

Aaron Kingery↗

DOE OSTI2026

Automatic Lane-Level Road Network Extraction from Aerial Imagery for Transportation Digital Twins

Accurate road networks are essential for credible traffic microsimulation and transportation digital twins, yet high-definition maps are often difficult to obtain due to limited availability, high cost, or proprietary restrictions. Some build networks from crowdsourced data, such as OpenStreetMap, but these sources often contain geometric and semantic inconsistencies. Others create networks manually, a process that is labor-intensive and difficult to scale. To address these limitations, this work presents an end-to-end pipeline that automatically extracts georeferenced, lane-level road networks from publicly available high-resolution satellite imagery and converts them into simulation-ready assets. The developed end-to-end pipeline has three primary modules: (1) A computer-vision-based module first detects directed lane geometries and intersection layouts. (2) A heuristic-based topology construction module then identifies approach and exit legs and establishes conflict-free lane-to-lane connections. (3) Finally, an automatic simulation-building module converts the extracted network into standard formats, e.g., OpenDRIVE, and generates routable SUMO networks. The framework supports both complete network construction from scratch and local-scale refinement of existing networks through lane-count correction, transition recovery, and geometric regularization. The proposed pipeline provides a practical pathway to generate traffic simulation networks from satellite imagery, significantly reducing manual reconstruction effort and enabling scalable, continuously updated transportation digital twins.

Guo, Hetian [University of Georgia, Athens] (ORCID↗

NASA NTRS2012

MER Telemetry Processor

MERTELEMPROC processes telemetered data in data product format and generates Experiment Data Records (EDRs) for many instruments (HAZCAM, NAVCAM, PANCAM, microscopic imager, Moessbauer spectrometer, APXS, RAT, and EDLCAM) on the Mars Exploration Rover (MER). If the data is compressed, then MERTELEMPROC decompresses the data with an appropriate decompression algorithm. There are two compression algorithms (ICER and LOCO) used in MER. This program fulfills a MER specific need to generate Level 1 products within a 60-second time requirement. EDRs generated by this program are used by merinverter, marscahv, marsrad, and marsjplstereo to generate higher-level products for the mission operations. MERTELEPROC was the first GDS program to process the data product. Metadata of the data product is in XML format. The software allows user-configurable input parameters, per-product processing (not streambased processing), and fail-over is allowed if the leading image header is corrupted. It is used within the MER automated pipeline. MERTELEMPROC is part of the OPGS (Operational Product Generation Subsystem) automated pipeline, which analyzes images returned by in situ spacecraft and creates level 1 products to assist in operations, science, and outreach.

Lee, Hyun H.↗

NASA NTRS2009

Multi-Mission Automated Task Invocation Subsystem

Multi-Mission Automated Task Invocation Subsystem (MATIS) is software that establishes a distributed data-processing framework for automated generation of instrument data products from a spacecraft mission. Each mission may set up a set of MATIS servers for processing its data products. MATIS embodies lessons learned in experience with prior instrument- data-product-generation software. MATIS is an event-driven workflow manager that interprets project-specific, user-defined rules for managing processes. It executes programs in response to specific events under specific conditions according to the rules. Because requirements of different missions are too diverse to be satisfied by one program, MATIS accommodates plug-in programs. MATIS is flexible in that users can control such processing parameters as how many pipelines to run and on which computing machines to run them. MATIS has a fail-safe capability. At each step, MATIS captures and retains pertinent information needed to complete the step and start the next step. In the event of a restart, this information is retrieved so that processing can be resumed appropriately. At this writing, it is planned to develop a graphical user interface (GUI) for monitoring and controlling a product generation engine in MATIS. The GUI would enable users to schedule multiple processes and manage the data products produced in the processes. Although MATIS was initially designed for instrument data product generation,

Cheng, Cecilia S.↗

NASA NTRS2023

High-Rate Delay Tolerant Networking (HDTN) User Guide Version 1.0

Delay Tolerant Networking (DTN) has been identified as a key technology to enable and facilitate the development and growth of future space networks. Classically, space communications networks are collections of disparate links that are manually managed either point-to-point or use space relays. The accelerating accessibility of space enables a new scaling of space nodes, yet both the manual management of configurations and scheduling and the lack of structure connecting links precisely prohibit scaling. This challenge gives rise to newer and larger classes of communications needs that are met by DTN, which must overcome the disconnection, disruption, latency, and mobility featured in space communications systems. DTN joins the underlying links as an overlay, and can be made to communicate over any protocol stack. The core actions of DTN are store, carry, and forward, where data are stored instead of dropped if there is no immediately available outduct. It does this by taking the DTN unit of data, bundles, and providing necessary layers to adapt these bundles to the underlying transport protocols of choice; these are called convergence layers. DTN's Bundle Protocol (BP) can then be used on top of terrestrial protocol stacks, such as TCP/IP, as well as protocols for space, such as LTP/AOS, all in the same network. For emphasis it is noted that bundles can be of essentially any size, and hence this convergence to lower layers of choice is necessary. Existing DTN implementations have operated in constrained environments with limited resources, resulting in low data speeds. However, as various technologies have advanced, data transfer rates and efficiency have advanced, which has pushed the need for a DTN implementation for ground systems and for spacecraft that is performance-oriented in order to not impose an unnecessary bottleneck. High-rate Delay Tolerant Networking (HDTN) takes advantage of modern hardware platforms to substantially reduce latency and improve throughput compared to today’s DTN operations. The HDTN implementation maintains interoperability with existing deployments of DTN that conform to IETF RFCs 4838, 5050, and 9171. At the same time, HDTN defines a new data format better suited to higher-rate operation. It defines and adopts a massively parallel pipelined and message-oriented architecture, allowing the system to scale gracefully as its resources increase. HDTN’s architecture also supports hooks to replace various processing pipeline elements with specialized hardware accelerators. This offers improved Size, Weight, and Power (SWaP) characteristics while reducing development complexity and cost.

Delay Tolerant Networking↗

NASA NTRS2024

High-Rate Delay Tolerant Networking (HDTN) User Guide Version 1.3.0

Delay Tolerant Networking↗

NASA NTRS2012

Interactive 3D Mars Visualization

The Interactive 3D Mars Visualization system provides high-performance, immersive visualization of satellite and surface vehicle imagery of Mars. The software can be used in mission operations to provide the most accurate position information for the Mars rovers to date. When integrated into the mission data pipeline, this system allows mission planners to view the location of the rover on Mars to 0.01-meter accuracy with respect to satellite imagery, with dynamic updates to incorporate the latest position information. Given this information so early in the planning process, rover drivers are able to plan more accurate drive activities for the rover than ever before, increasing the execution of science activities significantly. Scientifically, this 3D mapping information puts all of the science analyses to date into geologic context on a daily basis instead of weeks or months, as was the norm prior to this contribution. This allows the science planners to judge the efficacy of their previously executed science observations much more efficiently, and achieve greater science return as a result. The Interactive 3D Mars surface view is a Mars terrain browsing software interface that encompasses the entire region of exploration for a Mars surface exploration mission. The view is interactive, allowing the user to pan in any direction by clicking and dragging, or to zoom in or out by scrolling the mouse or touchpad. This set currently includes tools for selecting a point of interest, and a ruler tool for displaying the distance between and positions of two points of interest. The mapping information can be harvested and shared through ubiquitous online mapping tools like Google Mars, NASA WorldWind, and Worldwide Telescope.

Powell, Mark W.↗

NASA NTRS1995

Pipeline synthetic aperture radar data compression utilizing systolic binary tree-searched architecture for vector quantization

A system for data compression utilizing systolic array architecture for Vector Quantization (VQ) is disclosed for both full-searched and tree-searched. For a tree-searched VQ, the special case of a Binary Tree-Search VQ (BTSVQ) is disclosed with identical Processing Elements (PE) in the array for both a Raw-Codebook VQ (RCVQ) and a Difference-Codebook VQ (DCVQ) algorithm. A fault tolerant system is disclosed which allows a PE that has developed a fault to be bypassed in the array and replaced by a spare at the end of the array, with codebook memory assignment shifted one PE past the faulty PE of the array.

Chang, Chi-Yung↗

DOE OSTI2025

SITCOMTN-162: Testing the implementation of Metadetection and Cell-Based Coadds on Abell 360 LSSTComCam data

The purpose of this technote is to test the technical quality of LSSTComCam commissioning data, specifically the Rubin_SV_38_7 field, by utilizing cell-based coadds and Metadetection by measuring the tangential and cross weak lensing shear profiles of the massive cluster Abell 360 (called A360 throughout the technote). The process entails generating the cell-based coadds for Metadetection to run on, identifying and removing cluster member galaxies, applying quality cuts, calibrating the shear measurements, and validation. Cell-based coadds and Metadetection are both currently in the process of being implemented within the LSST Science Pipelines at the time of this technote. There is substantial technical value in attempting a difficult measurement prior to full implementation. Measuring the tangential shear around A360 will showcase the current abilities of these algorithms, as well as highlight where work is still needed. As seen from the resulting shear profile of A360, the cell-based coadds and Metadetection are able to work in tandem to produce a shear catalog and resulting reduced shear profile. This technote is one part of a series studying A360 in order to both stress test the commissioning camera and demonstrate the technical capabilities of the Vera Rubin Observatory. We study the quality of the PSF modeling and impact it can have on cluster WL in [Combet et al., 2025], implementation of cell-based coadds and subsequent use for Metadetect [Sheldon et al., 2023] in this technote, photometric calibration in (in prep), source selection and photometric redshifts in [Adari et al., 2025], use of Anacal [Li et al., 2024] to produce a cluster shear profile in [Li et al., 2025], and background subtraction in this field and Fornax in [Zhou et al., 2025].

79 ASTRONOMY AND ASTROPHYSICS↗

NASA NTRS1990

A parallel pipelined architecture for a digital multicarrier demodulator

A parallel pipelined architecture is presented for demultiplexing and demodulating SCPC/FDMA channels in real time. Specific algorithms are selected for each of the operations necessary for multicarrier demodulation. The selection is made based on their suitability for implementation into parallel-pipelined and sharing schemes. The demodulator is programmable and uses a single hardware module which is shared among all the channels for the recovery of clock, carrier, and data, resulting in large savings of power and hardware. The system is suitable for onboard processing of signals in satellites where power and area requirements are critical. The design is illustrated for the specific case of processing 800 FDMA channels at 64 kb/s each.

Fernandes, P. J.↗

NASA NTRS1995

Algorithms for parallel flow solvers on message passing architectures

The purpose of this project has been to identify and test suitable technologies for implementation of fluid flow solvers -- possibly coupled with structures and heat equation solvers -- on MIMD parallel computers. In the course of this investigation much attention has been paid to efficient domain decomposition strategies for ADI-type algorithms. Multi-partitioning derives its efficiency from the assignment of several blocks of grid points to each processor in the parallel computer. A coarse-grain parallelism is obtained, and a near-perfect load balance results. In uni-partitioning every processor receives responsibility for exactly one block of grid points instead of several. This necessitates fine-grain pipelined program execution in order to obtain a reasonable load balance. Although fine-grain parallelism is less desirable on many systems, especially high-latency networks of workstations, uni-partition methods are still in wide use in production codes for flow problems. Consequently, it remains important to achieve good efficiency with this technique that has essentially been superseded by multi-partitioning for parallel ADI-type algorithms. Another reason for the concentration on improving the performance of pipeline methods is their applicability in other types of flow solver kernels with stronger implied data dependence. Analytical expressions can be derived for the size of the dynamic load imbalance incurred in traditional pipelines. From these it can be determined what is the optimal first-processor retardation that leads to the shortest total completion time for the pipeline process. Theoretical predictions of pipeline performance with and without optimization match experimental observations on the iPSC/860 very well. Analysis of pipeline performance also highlights the effect of uncareful grid partitioning in flow solvers that employ pipeline algorithms. If grid blocks at boundaries are not at least as large in the wall-normal direction as those immediately adjacent to them, then the first processor in the pipeline will receive a computational load that is less than that of subsequent processors, magnifying the pipeline slowdown effect. Extra compensation is needed for grid boundary effects, even if all grid blocks are equally sized.

Vanderwijngaart, Rob F.↗

DOE OSTI2026

Persistent DynAMICS

Persistent DynAMICS is a lightweight software platform that enables distributed sensing systems to operate as a unified, responsive network. It integrates with existing sensors, data systems, and processing tools as an overlay, without requiring hardware replacement or increasing user burden. As data is collected, the system identifies situations that require additional attention and directs selected sensors to gather more information. For example, if a sensor detects an unusual condition along a pipeline, the system can task nearby sensors or different sensing modalities to confirm the event and focus data collection where it is needed. To support this, the platform forms temporary groups of sensors that work together to address specific objectives. Once complete, these groups are dissolved and resources are reassigned as needed. Communication is handled through an integrated messaging framework with client and server components, enabling reliable operation and data continuity even in low-bandwidth or intermittent connectivity environments.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2026

Techno Economic Analysis for Production of Renewable Natural Gas and Value-Added Chemicals from Forest Biomass Residues (CRADA Final Report)

West Biofuels - in collaboration with the University of California San Diego, the University of California Davis, the National Laboratory of the Rockies (NLR), the Colorado School of Mines’ Center for Hydrate Research, Placer County Air Pollution Control District, the Sierra Business Council, and the Southern California Gas Company (SoCalGas)-will demonstrate an innovative pathway to convert forest biomass to renewable gas (RG). The project, Production of Pipeline Grade Renewable Natural Gas and Value-Added Chemicals from Forest Biomass Residues, will utilize an existing pilot-scale gasification system and data and lessons learned from a lab-scale catalytic reactor design, develop, and demonstrate an integrated pilot-scale RG process with a scaled-up catalytic reactor and hydrate-based gas separation process. This robust and simple process uses a commercial proven gasifier, a commercially available catalyst that can tolerate gas contaminants, and a gas separation process that simplifies the downstream processing. Current testing has shown that the process can yield a large amount of methane rich renewable gas in addition to a mixture of propanol, ethanol and other higher alcohols and the relative amounts can be controlled by shifting the process conditions. This process is novel and groundbreaking because the product mixture of RG and valuable alcohols byproducts makes RG production economically feasible at $\$$12 per million British thermal units (MMBtu) or less using forest biomass from high hazard zones.

09 BIOMASS FUELS↗

NASA NTRS2018

Automated Semantic Segmentation for Volumetric Cardiovascular Feature Quantification and Pathology Assessment

We present a pipeline method that curtails the expense and observer bias of manual cardiac evaluation by combining semantic segmentation and disease classification as a fully automatic processing pipeline. The initial element consists of a 2D U-Net convolutional neural network architecture for voxel-wise segmentation of the myocardium and ventricular cavities. The results of the segmentation were used to compute a comprehensive volumetric feature matrix that captured diagnostic clinical procedure data and that was used to model a cardiac pathology classifier.Our approach evaluated anonymized parasternal MRI cardiac images from a database of 100 patients (4 pathology groups, 1 healthy group, 20 patients per group) examined at the University Hospital of Dijon. We achieved top average Dice index scores of 0.939, 0.849, 0.886 for structure segmentation of the left ventricle (LV), right ventricle (RV) and myocardium respectively. A 5-ary pathology classification accuracy of 90% was recorded on an independent test set using our trained model.

Lindsey, Tony↗

NASA NTRSDate not supplied

ArcjetCV: a new machine learning application for extracting time-resolved recession measurements from arc jet test videos

Arc jet Computer Vision (ArcjetCV) is a software application built to automate analysis of arc jet ground test video footage. This includes tracking material recession, sting arm motion, and the shock-material standoff distance. This provides a new capability to resolve and validate new physics associated with non-linear processes. This is an essential step to reduce testing, modeling, and validation uncertainties for heatshield material performance. ArcjetCV uses several types of machine learning (convolutional neural net: CNN, decision tree: DT, k-means unsupervised clustering: KM) to automate the video processing pipeline. These include inferring the start/stop of time segments of interest (1D CNN), measuring the time-dependent 2D recession of the material samples (2D CNN, DT), measuring the time-dependent shock standoff distance (2D CNN, DT), and post-processing cleaning of the recession data (KM). The software also provides a graphical user interface for ease of use. The results of using this tool on arc jet videos show non-linear time-dependent effects can be important for certain materials.

machine learning↗