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At least 703 records · Page 39

Automated, on-board terrain analysis for precision landings

Advances in space robotics technology hinge to a large extent upon the development and deployment of sophisticated new vision-based methods for automated in-space mission operations and scientific survey. To this end, we have developed a new concept for automated terrain analysis that is based upon a generic image enhancement platform|multi-scale retinex (MSR) and visual servo (VS) processing. This pre-conditioning with the MSR and the vs produces a "canonical" visual representation that is largely independent of lighting variations, and exposure errors. Enhanced imagery is then processed with a biologically inspired two-channel edge detection process, followed by a smoothness based criteria for image segmentation. Landing sites can be automatically determined by examining the results of the smoothness-based segmentation which shows those areas in the image that surpass a minimum degree of smoothness. Though the msr has proven to be a very strong enhancement engine, the other elements of the approach|the vs, terrain map generation, and smoothness-based segmentation|are in early stages of development. Experimental results on data from the Mars Global Surveyor show that the imagery can be processed to automatically obtain smooth landing sites. In this paper, we describe the method used to obtain these landing sites, and also examine the smoothness criteria in terms of the imager and scene characteristics. Several examples of applying this method to simulated and real imagery are shown.

Rahman, Zia-ur↗

Automated On-board Terrain Analysis for Precision Landings

Advances in space robotics technology hinge to a large extent upon the development and deployment of sophisticated new vision-based methods for automated in-space mission operations and scientific survey. To this end, we have developed a new concept for automated terrain analysis that is based upon a generic image enhancement platform-multi-scale Retinex (MSR) and visual servo (VS) processing. This pre-conditioning with the MSR and the VS produces a "canonical" visual representation that is largely independent of lighting variations, and exposure errors. Enhanced imagery is then processed with a biologically inspired two-channel edge detection process, followed by a smoothness based criteria for image segmentation. Landing sites can be automatically determined by examining the results of the smoothness-based segmentation which shows those areas in the image that surpass a minimum degree of smoothness. Though the MSR has proven to be a very strong enhancement engine, the other elements of the approach, the VS, terrain map generation, and smoothness-based segmentation, are in early stages of development. Experimental results on data from the Mars Global Surveyor show that the imagery can be processed to automatically obtain smooth landing sites. In this paper, we describe the method used to obtain these landing sites, and also examine the smoothness criteria in terms of the imager and scene characteristics. Several examples of applying this method to simulated and real imagery are shown.

Rahman, Zia-ur↗

Predicting the Sunspot Cycle

The 11-year sunspot cycle was discovered by an amateur astronomer in 1844. Visual and photographic observations of sunspots have been made by both amateurs and professionals over the last 400 years. These observations provide key statistical information about the sunspot cycle that do allow for predictions of future activity. However, sunspots and the sunspot cycle are magnetic in nature. For the last 100 years these magnetic measurements have been acquired and used exclusively by professional astronomers to gain new information about the nature of the solar activity cycle. Recently, magnetic dynamo models have evolved to the stage where they can assimilate past data and provide predictions. With the advent of the Internet and open data policies, amateurs now have equal access to the same data used by professionals and equal opportunities to contribute (but, alas, without pay). This talk will describe some of the more useful prediction techniques and reveal what they say about the intensity of the upcoming sunspot cycle.

Hathaway, David H.↗

Operational Lessons Learned from the Ares I-X Flight Test

The Ares I-X flight test, launched in 2009, is the first test of the Ares I crew launch vehicle. This development flight test evaluated the flight dynamics, roll control, and separation events, but also provided early insights into logistical, stacking, launch, and recovery operations for Ares I. Operational lessons will be especially important for NASA as the agency makes the transition from the Space Shuttle to the Constellation Program, which is designed to be less labor-intensive. The mission team itself comprised only 700 individuals over the life of the project compared to the thousands involved in Shuttle and Apollo missions; while missions to and beyond low-Earth orbit obviously will require additional personnel, this lean approach will serve as a model for future Constellation missions. To prepare for Ares I-X, vehicle stacking and launch infrastructure had to be modified at Kennedy Space Center's Vehicle Assembly Building (VAB) as well as Launch Complex (LC) 39B. In the VAB, several platforms and other structures designed for the Shuttle s configuration had to be removed to accommodate the in-line, much taller Ares I-X. Vehicle preparation activities resulted in delays, but also in lessons learned for ground operations personnel, including hardware deliveries, cable routing, transferred work and custodial paperwork. Ares I-X also proved to be a resource challenge, as individuals and ground service equipment (GSE) supporting the mission also were required for Shuttle or Atlas V operations at LC 40/41 at Cape Canaveral Air Force Station. At LC 39B, several Shuttle-specific access arms were removed and others were added to accommodate the in-line Ares vehicle. Ground command, control, and communication (GC3) hardware was incorporated into the Mobile Launcher Platform (MLP). The lightning protection system at LC 39B was replaced by a trio of 600-foot-tall towers connected by a catenary wire to account for the much greater height of the vehicle. Like Shuttle, Ares I-X will be stacked on a MLP and rolled out to the pad on a Saturn-era crawler-transporter. While Ares I-X was only held in place by the four hold-down posts on its aft skirt during rollout, a new vehicle stabilization system (VSS) attached to the vertical service structure kept the vehicle from undue swaying prior to launch at the pad, LC 39B. Following the launch, the flight test vehicle first stage was recovered with the aid of new parachutes resized to accommodate the five-segment-long first stage, which had a much greater length and mass than the Shuttle s reusable solid rocket boosters. After splashdown, recovery divers exercised extra care when handling the first stage to ensure that the flight data recorders in the fifth segment simulator were not damaged by exposure to sea water. The data recovered from the Ares I-X flight test will be very valuable in verifying the predicted environments and models used to design the vehicle. Lessons learned from Ares I-X will be shared with the Ares Projects through written and verbal reports and through integration of mission team members into the Project workforce.

Davis, Stephan R.↗

Ares I-X: Lessons for a New Era of Spaceflight

Since 2005, the Ares Projects at Marshall Space Flight Center (MSFC) have been developing the Ares I crew launch vehicle and Ares V cargo launch vehicle. On October 28, 2009, the first development flight test of the Ares I crew launch vehicle, Ares I-X, lifted off from a launch pad at Kennedy Space Center (KSC) on successful suborbital flight. Despite the President s intention to cancel the Constellation Program of which Ares is a part, this historic flight has produced a great amount of data and numerous lessons learned for any future launch vehicles. This paper will describe the accomplishments of Ares I-X and the lessons that other programs can glean from this successful mission. Ares I was designed to carry up to four astronauts to the International Space Station (ISS). It also was designed to be used with the Ares V cargo launch vehicle for a variety of missions beyond low-Earth orbit (LEO). The Ares I-X development flight test was conceived in 2006 to acquire early engineering and environment data during liftoff, ascent, and first stage recovery. The test achieved the following primary objectives: Demonstrated control of a dynamically similar, integrated Ares I/Orion, using Ares I relevant ascent control algorithms. Performed an in-flight separation/staging event between a Ares I-similar First Stage and a representative Upper Stage. Demonstrated assembly and recovery of a new Ares I-like First Stage element at KSC. Demonstrated First Stage separation sequencing, and quantify First Stage atmospheric entry dynamics, and parachute performance. Characterized the magnitude of integrated vehicle roll torque throughout First Stage flight.

Davis, Stephan R.↗

Self-Aware Vehicles: Mission and Performance Adaptation to System Health

Advances in sensing (miniaturization, distributed sensor networks) combined with improvements in computational power leading to significant gains in perception, real-time decision making/reasoning and dynamic planning under uncertainty as well as big data predictive analysis have set the stage for realization of autonomous system capability. These advances open the design and operating space for self-aware vehicles that are able to assess their own capabilities and adjust their behavior to either complete the assigned mission or to modify the mission to reflect their current capabilities. This paper discusses the self-aware vehicle concept and associated technologies necessary for full exploitation of the concept. A self-aware aircraft, spacecraft or system is one that is aware of its internal state, has situational awareness of its environment, can assess its capabilities currently and project them into the future, understands its mission objectives, and can make decisions under uncertainty regarding its ability to achieve its mission objectives.

Gregory, Irene M.↗

NASA Affordable Vehicle Avionics (AVA)

Small satellites are becoming ever more capable of performing valuable missions for both government and commercial customers. However, currently these satellites can be launched affordably only as secondary payloads. This makes it difficult for the small satellite mission to launch when needed, to the desired orbit, and with acceptable risk. What is needed is a class of low-cost launchers, so that launch costs to low-Earth orbit (LEO) are commensurate with payload costs. Several private and government-sponsored launch vehicle developers are working toward just that-the ability to affordably insert small payloads into LEO. But until now, cost of the complex avionics remained disproportionately high. AVA (Affordable Vehicle Avionics) solves this problem. Significant contributors to the cost of launching nanosatellites to orbit are the avionics and software systems that steer and control the launch vehicles, sequence stage separation, deploy payloads, and telemeter data. The high costs of these guidance, navigation and control (GNC) avionics systems are due in part to the current practice of developing unique, single-use hardware and software for each launch. High-performance, high-reliability inertial sensors components with heritage from legacy launchers also contribute to costs-but can low-cost commercial inertial sensors work just as well? NASA Ames Research Center has developed and tested a prototype low-cost avionics package for space launch vehicles that provides complete GNC functionality in a package smaller than a tissue box (100 millimeters by 120 millimeters by 69 millimeters; 4 inches by 4.7 inches by 2.7 inches), with a mass of less than 0.84 kilogram (2 pounds. AVA takes advantage of commercially available, low-cost, mass-produced, miniaturized sensors, filtering their more noisy inertial data with real-time GPS (Global Positioning Satellite) data. The goal of the AVA project is to produce and light-verify a common suite of avionics and software that deliver affordable, capable GNC and telemetry avionics with application to multiple nanolaunch vehicles at 1 percent of the cost of current state-of-the-art avionics.

space technology↗

Space Technology Game Changing Development: NASA Affordable Vehicle Avionics (AVA)

Common Modular Avionics System for Nanolaunchers Offering Affordable Access to Space Small satellites are becoming ever more capable of performing valuable missions for both government and commercial customers. However, currently these satellites can be launched affordably only as secondary payloads. This makes it difficult for the small satellite mission to launch when needed, to the desired orbit, and with acceptable risk. What is needed is a class of low-cost launchers, so that launch costs to low-Earth orbit (LEO) are commensurate with payload costs. Several private and government-sponsored launch vehicle developers are working toward just that—the ability to affordably insert small payloads into LEO. But until now, cost of the complex avionics remained disproportionately high. AVA solves this problem. Significant contributors to the cost of launching nanosatellites to orbit are the avionics and software systems that steer and control the launch vehicles, sequence stage separation, deploy payloads, and telemeter data. The high costs of these guidance, navigation and control (GNC) avionics systems are due in part to the current practice of developing unique, single use hardware and software for each launch. High-performance, high-reliability inertial sensors components with heritage from legacy launchers also contribute to costs—but can low-cost commercial inertial sensors work just as well?

Aquilina, Rudy↗

PACE OCI Calibration and Geolocation Operational Algorithm Description

This technical report describes the software implementation of the calibration and geolocation processing algorithms for the Ocean Color Instrument (OCI) on the Plankton, Aerosol, Cloud, ocean Ecosystem (PACE) mission. PACE was launched on February 8, 2024. The first Earth-viewing data were collected on February 25, and commissioning was completed on April 5. All PACE science data are acquired and processed by the Science Data Segment (SDS). The first processing stages are Level 0-to-1A and Level 1A-to-1B. The calibration and geolocation processing is performed during the latter stage. The L1B products are the inputs for geophysical retrieval processing (Level 2). This report is organized as follows. The pertinent characteristics of OCI for calibration and geolocation processing are described in Section II. Section III describes the implementation of the geolocation processing algorithms, and the calibration processing is described in Section IV. The Level 1B product format is described in Section V.

Ivona Cetinic↗

A DATA EFFICIENT SPARSE MODELING FRAMEWORK FOR POWER ESTIMATION IN WATER TREATMENT SENSING OPERATIONS

With increasing freshwater scarcity, advanced process design mechanisms such as Closed-Circuit Reverse Osmosis (CCRO) and Digital/Physical Twin systems are gaining traction in water treatment and reuse operations. While digital and physical twin models enable improved system insight and control, their development is often expensive and computationally intensive, requiring large volumes of synthetic or experimental data to characterize underlying process dynamics. This work introduces a sparse surrogate modeling framework to estimate power consumption from measured flow and pressure variables, along with their nonlinear polynomial and interaction expansions. To ensure model reliability and reduce overfitting, a two-stage pipeline is proposed. First, a dynamic data filtering algorithm is employed to remove uninformative observations and transient operational states. Second, a sparse penalized regression technique is applied to select a minimal set of parsimonious features. The proposed model achieves high sparsity, retaining only 7 out of 34 candidate features (≈79.41% sparsity) while delivering a root mean square error (RMSE) of 0.072 on the test dataset.

Mukherjee, Subrata [ORNL] (ORCID:0000000309930338)↗

All Systems Go: Regional Collaborations for Scaling AEC Innovation: Preprint

The high and rising cost of preserving and delivering housing in the U.S. requires changes to existing practices of finance, design, and construction. Innovative methods such as industrialized construction could offer the means to address housing undersupply while reducing delivery costs, operational costs and material waste in the building industry, but they face challenges to success and to scale. Simultaneously, construction and cleantech innovators themselves face skepticism from the traditional entrepreneurial ecosystem such as incubators and accelerators while attempting to navigate systems level challenges. To respond to this need, various public and private sector stakeholders have launched initiatives to support innovative companies. These include nonprofits such as Terner Labs and Ivory Innovations offering curated programming to architecture, engineering, and construction (AEC) startups; housing developers in Minnesota and California "bundling" multiple projects together to reach economies of scale with a consistent project team; public and private sector entities developing "catalogues" of pre-approved home designs in the U.S. and Canada. This exploratory paper documents several of these emerging ecosystem-development efforts to support innovative housing approaches, characterizing them by leading stakeholder and intervention strategy based on publicly available information. The paper finds that these initiatives share similar high level goals but vary in implementation, reflecting different stakeholder priorities, regional market and policy dynamics, and housing typologies. The early stage of these efforts offer limited data for comparing actual outcomes, but the paper highlights common qualitative themes and identifies opportunities for further research and potential coordination among these efforts.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

SCOUT Nozzle Data Book

Available analyses and material property information are summarized relevant to the design of four rocket motor nozzles currently incorporated in the four solid propellant rocket stages of the NASA SCOUT launch vehicle. The nozzles discussed include those for the following motors: (1) first stage - Algol IIIA; (2) second stage - Castor IIA; (3) third stage - Antares IIA; and (4) fourth stage - Altair IIIA. Separate sections for each nozzle provide complete data packages. Information on the Antares IIB motor which had limited usage as an alternate motor for the third stage is included.

Shieds, S.↗

Toward Real-Time Analysis of Synchrotron Micro-Tomography Data: Accelerating Experimental Workflows with AI and HPC

ynchrotron light sources are routinely used to perform imaging experiments. In this paper, we review the relevant computational stages, identify bottlenecks, and highlight future opportunities to streamline data acquisition for experimental microscopy workflows. We demonstrate our preliminary exploration with an end-to-end scientific workflow on Summit based on micro-computed tomography data. Computational elements include: 1) reconstruction of volumetric image data; 2) denoising with deep neural networks; and 3) non-local means based segmentation and quantitative analysis.

Mcclure, James↗

LandScan Mosaic

The LandScan program at Oak Ridge National Laboratory (ORNL), in collaboration with the National Geospatial-Intelligence Agency (NGA), continues to deliver the most accurate and up to date global, high resolution gridded population data. Additionally, the latest advancements in the LandScan HD methodology led to reduced latency in development of rapid updates for geopolitical events. With momentum towards reporting more up to date population estimates, feedback from the user community expressed interest in reporting population estimates in ranges - whether to express a level of uncertainty or confirm to leadership and stakeholders the modeled data are estimates. Building upon the need to understand uncertainty or confidence in the modeled data and report ranges at the global scale, LandScan Mosaic was developed. LandScan Mosaic represents the next generation of high-resolution population modeling, building upon the established success of previous LandScan HD iterations. While LandScan HD employed a deterministic big data fusion approach, LandScan Mosaic enhances this methodology by integrating advanced machine learning techniques to impute missing, yet crucial, population model parameters. This advancement allows for probabilistic modeling of building occupancy and population distribution, incorporating uncertainty quantification through Monte Carlo sampling methods. By combining big data fusion with machine learning-driven imputation and stochastic modeling, LandScan Mosaic provides a more comprehensive and robust representation of population dynamics. LandScan Mosaic will be following the in the footsteps of its longstanding counterpart LandScan Global and releasing a global gridded population raster, at the 3-arcsecond resolution. This technical report documents the current stage of development of LandScan Mosaic, detailing the methodologies and data sources behind the modeling. Stakeholders are encouraged to use this document as an authoritative reference for insight into Mosaic’s data development processes. However, readers should note that LandScan Mosaic remains in a late-stage research and development phase, and methodologies and data presented here are subject to refinements ahead of the anticipated global release in Summer 2025. Feedback and inquiries from users and stakeholders are welcomed as we continue to refine and enhance this important population resource.

97 MATHEMATICS AND COMPUTING↗

Performance of the 19XB 10-Stage Axial-Flow Compressor with Altered Blade Angles

Previous performance data of the 19XB axial-flow compressor indicated that the outlet guide vanes and possibly the inlet guide vanes were stalling. Calculations were made to determine if these adverse conditions could be eliminated and if the manufacturer's design specifications could be more nearly approached by altering the blade angles of the first few compression stages as well as the outlet guide vanes. With the blade angles altered, experimental data were taken at compressor speeds of 8500 to 17,000 rpm with inlet-air conditions of 7.4 inches of mercury absolute and 59 0 F. The temperature-rise efficiency increased with speed from 0.70 at 8500 rpm to 0.74 at 13,600 rpm and dropped gradually to 0.70 at 17,000 rpm. At the design speed of 17,000 rpm, the pressure ratio at the peak efficiency point was 3.63. The maximum pressure ratio at design speed was 4.15 at an equivalent weight flow of 29.8 pounds per second. The altered compressor operated very .near the design specifications of pressure ratio and equivalent weight flow. At the high speeds, the peak adiabatic temperature-rise efficiency was increased 0.02 to 0,06 by altering the blade angles. The peak pressure ratio was increased 0.29 at design speed (17,000 rpm) and 0.05 and 0.13 at 11,900 and 13,600 rpm, respectively. The equivalent weight flow through the altered compressor was reduced 2 pounds per second at 15,300 and 17,000 rpm, as was expected from the design calculations. As extreme caution was taken not to surge the compressor violently, the point of minimum air flow may not have been reached in the present investigation and in a previous investigation. A true comparison of the pressure ratios obtained at the high speeds therefore cannot be made.

Downing, Richard M.↗

The Marine and Hydrokinetic ToolKit (MHKiT) for Data Quality Control and Analysis [Slides]

The ability to collect, ingest, condition, reduce, quality control, process, visualize, and store data in a standardized way is critical at all stages of Marine Energy (ME) research and technology/project development. MHKiT is an open-source, standardized suite of ME data processing functions that provides the ability to ingest, condition, reduce, quality control, process, visualize and store ME data. MHKiT is developed in both Python and Matlab.

16 TIDAL AND WAVE POWER↗

Scientific ballooning payload termination loads

NASA's high altitude balloon borne scientific payloads are typically suspended from a deployed flat circular parachute. At flight termination, the recovery train is pyrotechnically separated at the parachute apex and balloon nadir interface. The release of elastic energy stored in the parachute at zero initial vertical velocity in the rarefied atmosphere produces high canopy opening forces that subject the gondola to potentially damaging shock loads. Data from terminations occurring at altitudes to 40 km with payloads up to 2500 kg on parachutes up to 40 m in diameter are presented. Measured loads are markedly larger than encountered via packed parachute deployment for similar canopy loadings. Canopy inflation is significantly suppressed in the early stages and then accelerated during final blossoming. Data interpretation and behavioral phenomena are discussed along with proposed shock attenuation techniques.

Robbins, E.↗

The role of phenology in statistical crop acreage measurement

In order to achieve market acceptance, the accuracy of remote sensing systems needs to be increased from the historically achieved average level of approximately 80-85% to 96-98%, i.e., by a factor of at least three, preferably five. A theory of discrimination is developed based on the fine-grained spectral data from LACIE supersites. It is shown that significant improvements in discrimination accuracy are possible by exploiting the differentials of crop spectra occurring between different phenologic stages. The major effects of such techniques on data system design are examined with respect to recurrence frequency, data volume, and information extraction.

Castruccio, P. A.↗