SEARCH · Search NASA

Results for “advanced building construction”

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.

SourceResearch connectionFrom yearThrough year

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 325 records · Page 18

All sources NASA NTRS DOE OSTI

NASA NTRS2013

NASA Sounding Rocket Program Educational Outreach

Educational and public outreach is a major focus area for the National Aeronautics and Space Administration (NASA). The NASA Sounding Rocket Program (NSRP) shares in the belief that NASA plays a unique and vital role in inspiring future generations to pursue careers in science, mathematics, and technology. To fulfill this vision, the NSRP engages in a variety of educator training workshops and student flight projects that provide unique and exciting hands-on rocketry and space flight experiences. Specifically, the Wallops Rocket Academy for Teachers and Students (WRATS) is a one-week tutorial laboratory experience for high school teachers to learn the basics of rocketry, as well as build an instrumented model rocket for launch and data processing. The teachers are thus armed with the knowledge and experience to subsequently inspire the students at their home institution. Additionally, the NSRP has partnered with the Colorado Space Grant Consortium (COSGC) to provide a "pipeline" of space flight opportunities to university students and professors. Participants begin by enrolling in the RockOn! Workshop, which guides fledgling rocketeers through the construction and functional testing of an instrumentation kit. This is then integrated into a sealed canister and flown on a sounding rocket payload, which is recovered for the students to retrieve and process their data post flight. The next step in the "pipeline" involves unique, user-defined RockSat-C experiments in a sealed canister that allow participants more independence in developing, constructing, and testing spaceflight hardware. These experiments are flown and recovered on the same payload as the RockOn! Workshop kits. Ultimately, the "pipeline" culminates in the development of an advanced, user-defined RockSat-X experiment that is flown on a payload which provides full exposure to the space environment (not in a sealed canister), and includes telemetry and attitude control capability. The RockOn! and RockSat-C elements of the "pipeline" have been successfully demonstrated by five annual flights thus far from Wallops Flight Facility. RockSat-X has successfully flown twice, also from Wallops. The NSRP utilizes launch vehicles comprised of military surplus rocket motors (Terrier-Improved Orion and Terrier-Improved Malemute) to execute these missions. The NASA Sounding Rocket Program is proud of its role in inspiring the "next generation of explorers" and is working to expand its reach to all regions of the United States and the international community as well.

Rosanova, G.↗

DOE OSTI2026

Novel additive manufacturing for plasma facing materials ‐ creating a research pathway for minority students

This project addresses two critical and intertwined challenges in fusion energy, namely the shortage of a broadly trained scientific workforce and the lack of scalable manufacturing solutions for plasma-facing components (PFCs). Through a collaboration among Florida International University (FIU), Miami Dade College (MDC), and Purdue University, the project established structured, reproducible educational and research pathways that recruit and advance students from institutions historically outside the fusion energy enterprise, building the human capital that this field urgently needs. The project integrates the complementary research strengths of FIU and Purdue to investigate flash sintering as a transformative processing route for tungsten-based PFCs. Unlike conventional sintering approaches, flash sintering offers rapid densification at significantly reduced thermal budgets, making it a compelling candidate for fabricating complex tungsten geometries that must withstand extreme plasma-facing environments. Systematic experimental and modeling efforts will elucidate the fundamental mechanisms governing microstructure evolution, grain boundary chemistry, and thermomechanical response during flash sintering — knowledge that is presently lacking but essential for translating this technology into reliable manufacturing practice. The convergence of workforce development and cutting-edge manufacturing research positions this project to deliver measurable, durable impact: a pipeline of fusion-ready researchers cultivated through expanded institutional partnerships, and a validated materials processing framework that accelerates domestic readiness for next-generation fusion reactor construction.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2025

Deep Point Cloud Building Envelope Segmentation (DeeP-CuBES) using Deep Learning

Building Information Modeling (BIM) plays an important role in building design and construction, particularly for achieving energy-efficient retrofits. Building envelope retrofits using panelized prefabricated system, such as those popularized by the Energiesprong program, need accurate as-built dimensions of facade features (windows, doors, etc.) to achieve the desired thermal and air tightness. Traditionally, building surveying is done manually, resulting in a time-consuming and labor-intensive process. Recently, 3D point clouds from terrestrial LiDAR have been used to automate the generation of as-built dimensions of existing buildings. However, automated BIM using LiDAR relies on solving the point cloud semantic segmentation (PCSS) problem. In this work, we propose a robust pipeline for solving the PCSS problem using deep neural networks, focusing on overcoming challenges posed by imbalanced datasets and complex architectural features. We introduce the first high-density, labeled, and validated building envelope point cloud dataset derived from multiple building scans, specifically curated to tackle challenges in facade-level segmentation. Results from the trained neural networks show that advanced attention-based architectures and incorporating radiometry (light intensity and RGB) features significantly boost segmentation accuracy for windows and doors.

Selvakumar, Balaji [ORNL]↗

NASA NTRS1989

Development and application of nonflammable, high-temperature beta fibers

Recent advances in fiber technology have contributed to the success of the U.S. space program. The inorganic fiber Beta, developed as a result of efforts begun in the early 1960's and heightened following the January 27, 1967 Apollo fire is unique among inorganic and organic fibers. It has been developed into woven, nonwoven, knitted, braided, coated and printed structures. All of these were used extensively for the Apollo, Skylab, Apollo-Soyuz test project, space shuttle, Spacelab, and satellite programs. In addition to being used successfully in the space program, Beta fibers are being used commercially as firesafe fabrics in homes, hospitals, institutions, public buildings, aircraft, and public transportation, wherever total nonflammability is required. One of the most unique applications of the Beta composite structure is the roofing material for the 80,000-seat Detroit Lion's Silverdome and 5 square miles of the Jeddah International Airport in Saudi Arabia. This fiber has been successfully incorporated into 165 major public construction projects around the globe. The United States alone has used more than 12 million square yards of the material. Beta fiber has been used successfully to date and has a promising future with unlimited potential for both space and commercial application. Efforts are currently underway to improve Beta fiber to meet the requirements of extended service life for the Space Station Freedom, lunar outpost, and Mars exploration missions.

Dawn, Frederic S.↗

DOE OSTI2025

Non-destructive structural characterization of graphite components using mechanical resonance and deep learning

As compared to conventional nuclear reactors, microreactors have the potential to significantly reduce construction timelines and capital costs, decreasing the barriers for advanced nuclear reactor technologies. However, the lower power output of these microreactors (typically < 20 MWe) creates challenging economics if operation and maintenance costs cannot be sufficiently reduced. The compact size of these designs presents an opportunity for comprehensive in-situ structural health monitoring to provide real-time feedback in order to reduce operational costs associated with maintenance and downtime. Many microreactor concepts use graphite for both in-core neutron moderation and as a structural material, which has typically required some form of periodic and laborious inspection. This report provides a description and assessment of recent work with graphite to couple acoustic-based experimental measurements and characterization with machine learning models to mature structural health monitoring capabilities and generate benefits for the nuclear microreactor industry. With resilient embedded sensors in development in other programs funded by the US Department of Energy’s Office of Nuclear Energy and elsewhere, the work described herein builds upon previously funded efforts to mature non-destructive testing technology that relates measured vibrational signatures to structural changes, using a combination of new experimental measurements and machine learning processing. Building on past successful demonstrations of predictive workflows to identify structural changes in a hexagonal stainless steel test article with excellent acoustic propagation, we first performed baseline characterization on graphite samples with canonical geometries to ensure compatibility and confidence in the applied techniques for a material with distinctly different mechanical properties. In contrast to efforts in previous years, we worked exclusively with unidirectional vibration data that is more comparable to those expected from the existing embedded sensor technologies which are suitable for deployment in a reactor setting. Established acoustic and modern machine-learning-based characterization approaches were applied to the resulting datasets from these simple geometries. Both approaches were found to be highly capable of detecting even small geometric irregularities amongst nominally identical samples. As such, we then moved to testing these approaches for detection of artificial local stress perturbations introduced into a more complex geometry: a hexagonal block with drilled holes. A main outcome of this work is that a generalizable ML workflow can be used to detect and predict the characteristics of small artificial anomalies in a graphite component with a relevant geometry. While this work was performed using surficial vibration data, we expect the approach to be flexible and viable for other monitoring scenarios, such as those with different arrangements or types of sensor arrays. As compared to previously funded efforts, an existing ML workflow based on neural networks was enhanced through the addition of recently developed Fourier neural operators. As applied to previously collected and new vibration datasets, prediction accuracies of anomaly characterizations were greatly improved with minimal added computational cost. As trained on small durations of vibration data (tens of seconds) collected over a realistic number of locations, the model was able to reliably determine the presence of a subtle stress anomaly and begin to provide location estimates. Such an approach is likely to be viable for more relevant reactor damage scenarios for graphite components, such as progressive crack growth or creep.

36 MATERIALS SCIENCE↗

DOE OSTI2022

Digitalization of an experimental electrochemical reactor via the smart manufacturing innovation platform

The exponential increase in data produced over the last two decades has revolutionized the way we collect, store, process, analyze, model, and interpret information to improve profitability. Manufacturing is no exception. How- ever, Smart Manufacturing, the digital practice, organization, workforce, and infrastructure transformation for collection and deployment of data and models at scale and at all levels of manufacturing, is a complex, costly, and labor-intensive journey that is still seeing slow adoption. The Clean Energy Smart Manufacturing Innovation Institute (CESMII), a national Manufacturing USA public-private partnership sponsored by the Department of Energy, is addressing this scaled use of data and modeling in manufacturing. CESMII has focused on how to col- lect and use operating data for numerous applications that improve productivity, precision, and performance of manufacturing operations from factory floor to supply chain using process simulation, predictive analytics, mon- itoring and control, and real-time optimization. Because contextualized data are key, CESMII has developed the Smart Manufacturing Innovation Platform (SMIP) to lower the barriers to the data that are needed to accelerate data-based model building, improve data visualization, and more quickly gain insights. Reusable, standards-based ways of doing data collection, ingestion, and contextualization are particularly important for scaling access and use of data. The SMIP uses a standards-based definition and construct for reusable information models called an SM Profile. When an SM Profile is used in conjunction with the SMIP, the SMIP ensures the availability of contextualized, operational data for model building. The present work demonstrates Smart Manufacturing and the application of the SMIP for building several data-centered models for the operation and control of an ex- perimental electrochemical reactor that reduces carbon dioxide (CO 2 ) gas to valuable liquid and gas chemicals, such as alcohols, olefins, and syngas. We describe how the SMIP plays a central role in more effective model building and we demonstrate how the electochemical reactor can be controlled and optimized for the desired products. Use of the SMIP involves the transmission of real-time sensor measurements to a cloud resource so that the operating data are available to all model building experts. The data collection and transmission process is fully automated to greatly reduce the need for manual manipulation of the data. Data-driven machine learning models are used for advanced real-time state estimation, real-time optimization, and model-based feedback control for the reactor. The application models are implemented as a system to monitor the data flow and control the electrochemical reactor with a single visualization interface. SM Profiles are used to demonstrate reusability of the information models for the reactor and the instrumentation. The application packages, algorithms, and user interfaces developed are cast as Docker images in a library to facilitate reusability of the application models.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2021

Towards standardized nuclear reactors: Seismic isolation and the cost impact of the earthquake load case

We report nuclear energy has a key role to play in global decarbonization. Impediments to the widespread deployment of reactors are their projected high capital cost and levelized cost of energy, and time required to analyze, design, license, construct, and commission them. The earthquake load case is a key cost driver for a new build nuclear plant, because near-surface soils and seismic hazard are different at each site, requiring site-specific analysis, design, engineering, qualification, licensing, and regulatory review, essentially making every design First-of-a-Kind (FoaK). To enable deployment at the scale needed for deep decarbonization, the cost and time impact of the seismic load case must be significantly mitigated, and plants must be standardized. Seismic base isolation has been proven to considerably reduce the earthquake response of structures and equipment but has yet to be applied to a nuclear power plant in the United States, in part because the financial impacts, positive or negative, are not known. Because there are no recent non-proprietary data to characterize the influence of the seismic load case on capital cost, it is difficult to confidently quantify the financial benefits of seismic isolation. Scheme-level designs of two fundamentally different advanced reactor buildings were developed to assemble cost data on the influence of the seismic load case. Both buildings were equipped with three bespoke pieces of safety-related equipment and analyzed for incremented levels of earthquake shaking to quantify the seismic penalty on equipment, in terms of vessel weights and horizontal accelerations. Using analysis results, a questionnaire was developed and transmitted to nuclear utilities, reactor developers, engineers, and equipment suppliers to collect cost data on engineering and fabrication costs for these unique pieces of safety-class equipment. Synthesis of the cost data showed that the seismic load case significantly affects the capital cost (sum of engineering and fabrication cost) of safety-class equipment, with engineering costs being comparable to fabrication costs. Standardization of safety-class equipment is made possible by seismic isolation, that is, equipment designed for minimal seismic robustness can resist earthquake shaking at a site of much higher seismic hazard. The average reduction in the capital cost of the safety-related equipment, enabled by seismic isolation, is a factor of two for FoaK equipment and a factor of five for standardized equipment.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

NASA NTRSDate not supplied

Tours of High-containment and Pristine Facilities in Support of Mars Sample Return (MSR) Sample Receiving Facility (SRF) Definition Studies

During 2019 and 2020, the NASA Tiger Team RAMA (acronym of the authors) toured several high-containment biosafety laboratories and pristine space-mission facilities worldwide to better understand their practices, capabilities, and lessons-learned to aid in planning a Sample Receiving Facility (SRF) in support of Mars Sample Return (MSR). The team also included tours of a manufacturer of mobile and modular high-containment facilities as well as manufacturers of isolators and gloveboxes. In addition, the team visited the European Space Agency (ESA)ultraclean and sterile ISO 3 / airborne molecular contamination -9 (AMC-9) isolator line to clean and assemble the most critical hardware for ESA’s ExoMars Mars Lander System, and researchers developing a novel double-walled isolator (DWI) and robotic handling techniques in support of an MSR SRF. The RAMA team visits covered several construction modalities for an MSR SRF: (1) a new traditional fixed facility; (2) use of an existing fixed Biosafety Level 4(BSL-4) facility; (3) a novel modular BSL-4 approach; and (4) a hybrid combination of fixed, modular, and existing facilities. A new fixed facility approach can be tailored to MSR’s needs and is the approach used by all U.S. BSL-4 laboratories constructed to date. However, this approach could be the most expensive modality, take the longest to implement (8-12 years), and have significant programmatic risk of delay. The utilization of an existing BSL-4 facility may be possible depending on the final contamination control and science requirements for the MSR SRF. Due to the internal dimensions of the labs visited and facility structural requirements, it is unlikely that any modification can be made to the facility to meet cleanliness requirements. Furthermore, due to possible construction delays, possible capacity issues, and potential cross contamination vectors from in-house select agents, there may also be significant programmatic risks for sharing an existing facility. Another approach is building a contemporary modular facility. This is a novel approach that has recently been used for a BSL-3/3Ag facilities. The modular elements would be installed in a traditional building or shell structure. A modular facility has many advantages over a traditional fixed facility with lower costs, shorter design/construction/ commissioning schedule, and flexibility for easier retrofits and future expansion. Lastly, a hybrid approach of combining the use of either: (1) a modular facility inside a new fixed facility or (2) a modular and/or fixed BSL-4 annex in conjunction with an existing BSL-4 space should be considered. The advantage of a hybrid approach is that the facility could leverage the strengths of other approaches. Beyond facility construction approaches, the RAMA team investigated technologies and techniques for isolating and handling Martian samples in pristine environments. For example, ESA has been studying and developing a DWI breadboard along with other sample-handling technologies. The research and development investment for clean, remote manipulation and robotics at the start of the facility design phase would be beneficial to the SRF. Additionally, under-standing the lessons learned from Thales Alenia Space during the construction and operation of the most advanced state-of-the-art precision cleaning, sterilization, and assembly glovebox isolators ever developed for spacecraft hardware are also critical for the SRF. The RAMA team lays out a summary of the 18 facilities toured, and includes 43 observations,18 findings, and 22 areas of possible follow-up that the RAMA team and others could pursue to enable further findings. The observations and findings illustrate that constructing an MSR SRF would combine the complexity of both high-containment and pristine facilities, and merging these technologies would be challenging, but achievable.

Mars Sample Return↗

NASA NTRS2007

Kilopixel Pop-Up Bolometer Arrays for the Atacama Cosmology Telescope

The recently deployed Atacama Cosmology Telescope (ACT) anticipates first light on its kilopixel array of close-packed transition-edge-sensor bolometers in November of 2007. The instrument will represent a full implementation of the next-generation, large format arrays for millimeter wave astronomy that use superconducting electronics and detectors. Achieving the practical construction of such an array is a significant step toward producing advanced detector arrays for future SOFIA instruments. We review the design considerations for the detector array produced for the ACT instrument. The first light imager consists of 32 separately instrumented 32-channel pop-up bolometer arrays (to create a 32x32 filled array of mm-wave sensors). Each array is instrumented with a 32-channel bias resistor array, Nyquist filter array, and time-division SQUID multiplexer. Each component needed to be produced in relatively large quantities with suitable uniformity to meet tolerances for array operation. An optical design was chosen to maximize absorption at the focal plane while mitigating reflections and stray light. The pop-up geometry (previously implemented with semiconducting detectors and readout on the SHARC II and HAWC instruments) enabled straightforward interface of the superconducting bias and readout circuit with the 2D array of superconducting bolometers. The array construction program balanced fabrication challenges with assembly challenges to deliver the instrument in a timely fashion. We present some of the results of the array build and characterization of its performance.

Chervenak, J. A.↗

NASA NTRS2024

Pliocene Model Intercomparison Project Phase 3 (PlioMIP3) – Science Plan and Experimental Design

The Pliocene Model Intercomparison Project (PlioMIP) was initiated in 2008. Over two phases PlioMIP has helped co-ordinate the experimental design and publication strategy of the community, which has included an increasing number of climate models and modelling groups from around the world. It has engaged with palaeoenvironmental scientists to foster new data synthesis supporting the construction of new model boundary conditions, as well as to facilitate new data-model comparisons. The work has advanced our understanding of Pliocene climates and environments, enhanced our knowledge regarding the ability of complex climate and Earth System models to accurately simulate climate change, and helped to refine our estimates of how sensitive the climate system is to forcing conditions. In this community protocol paper, we outline the scientific plan for PlioMIP Phase 3 (PlioMIP3). This plan provides the required guidance to participating modelling groups from around the world to successfully set up and perform PlioMIP3 climate model experiments. The project is open to new participants from the scientific community (both from the climate modelling and geosciences communities). In PlioMIP3, we retain the PlioMIP2 Core experiments (Eoi 400 , E 280 ) and extend the Core requirements to include either an experiment focussed on the Early Pliocene or an alternative Late Pliocene simulation (or both). These additions (a) allow a comparison of Early and Late Pliocene warm intervals and help build research connections and synergy with the MioMIP (Miocene Model Intercomparison Project - also known as DeepMIP-Miocene) and PlioMioVAR projects (Pliocene-Miocene Variability Working Group), and (b) create an alternative time slice simulation for 3.205 Ma (MIS KM5c) through removal of some of the largest palaeogeographic differences introduced between PlioMIP1 and 2 resulting in minimal land-sea mask variations from the modern. In addition, we present ten optional experiments designed to enhance our assessment of climate sensitivity and to explore the uncertainty in greenhouse gas-related forcing. For the first time, we introduce orbital sensitivity experiments into the science plan, as well as simulations incorporating dynamic vegetation-climate feedbacks and an experiment designed to examine the potential significance of East Antarctic Ice Sheet boundary condition uncertainty. These changes enhance palaeo-to-future scientific connections and enable an exploration of the significance of palaeogeographic uncertainties on climate simulations.

Climate modelling↗

DOE OSTI2025

High-performance windows improve thermal survivability of occupants during cold snaps

Exposure to low indoor air temperature is a major contributor to temperature-related mortality during extreme cold events, especially when power outages disrupt operation of space heating systems. This study explores the impact of high-performance windows on the thermal resilience of residential buildings during extreme cold weather and grid power outages, as well as their long-term benefits through energy efficiency and reduced risk of property damage. Building performance simulations were conducted for reference residential buildings in three construction vintages and two major U.S. cities located in cold climate zones, considering two types of extreme cold events: short and severe, and long and milder. Our research found that even houses compliant with current energy codes struggle to maintain safe indoor temperatures for more than a few hours during power outages, necessitating rapid evacuations. High-performance windows can extend the thermal survivability time by up to 3.8 days within a 7-day cold snap and significantly reduce risk of bursting frozen water pipes, depending on the building’s insulation and infiltration level, cold event severity, and occupant vulnerability. This extended thermal safety time is crucial in scenarios where reduced mobility complicates emergency responses in senior housing. In addition to boosting thermal resilience, upgrading older homes with high-performance windows can reduce heating energy consumption by over 18% and cooling energy by 15%. Our findings highlight the need to incorporate thermal resilience assessments into new designs or major retrofits, including the use of typical and extreme weather scenarios and advanced technologies like high-performance windows.

Krelling, Amanda F↗

DOE OSTI2024

What to expect when you're expecting engagement: Delivering procedural justice in large-scale solar energy deployment

Community engagement in the planning process to build large-scale solar (LSS) projects can win local support and advance procedural justice. However, an understanding of community engagement in current LSS development is lacking. Using responses from a U.S. nationwide survey (n = 979) of residential neighbors living within 3 miles (4.8 km) of completed LSS projects (i.e. “solar neighbors”) and project details from the U.S. Large-Scale Solar Photovoltaic Database (USPVDB), this study seeks to answer the following questions: How are solar neighbors' perceptions of community engagement associated with their attitudes toward their LSS projects? How do solar neighbors' perceptions of community engagement compare to their expectations? And, how do neighbors explain what they perceived about the planning process? We answer these questions using mixed methods, including regression modeling, a new gap analysis technique, and qualitative coding. We find that higher perceived engagement is associated with more positive attitudes toward the project, even when controlling for respondents who acted in opposition. Supporters and opponents alike expect more engagement than they perceived and information about projects both before construction and after operation is lacking. Awareness and engagement expectations increase at certain project size and proximity thresholds. However, most neighbors expect the public to offer input during engagement, but not make decisions. We contextualize these findings with explanatory comments from respondents.

14 SOLAR ENERGY↗

NASA NTRS2015

Resource Prospector (RP) - Early Prototyping and Development

The Resource Prospector (RP) is an In-Situ Resource Utilization (ISRU) technology demonstration mission under study by the NASA Human Exploration and Operations Mission Directorate's (HEOMD) Advanced Exploration Systems (AES) Division. The mission, currently planned to launch in 2020, will demonstrate extraction of oxygen from lunar regolith to validate ISRU capability. The mission will address key Strategic Knowledge Gaps (SKGs) for robotic and human exploration to the Moon, Near Earth Asteroids (NEAs), and ultimately Mars, as well as meet the strategic goals of the Global Exploration Roadmap (GER), offered by the International Space Exploration Coordination Group (ISECG). In this roadmap, the use of local resources is specifically addressed relating to human exploration. RP will provide knowledge to inform the selection of future mission destinations, support the development of exploration systems, and reduce the risk associated with human exploration. Expanding human presence beyond low-Earth orbit to asteroids and Mars will require the maximum possible use of local materials, so-called in-situ resources. The moon presents a unique destination to conduct robotic investigations that advance ISRU capabilities, as well as providing significant exploration and science value. Lunar regolith contains useful resources such as oxygen, water, silicon, and light metals, like aluminum and titanium. Oxygen can be separated from the regolith for life support (breathable air), or used to create rocket propellant (oxidizer). Regolith can be used to protect against radiation exposure, be processed into solar cells, or used to manufacture construction materials such as bricks and glass. RP will characterize the constituents and distribution of water and other volatiles at the poles of the Moon, enabling innovative uses of local resources, in addition to validating ISRU capabilities. This capability, as well as a deeper understanding of regolith, will be valuable in the exploration of near-Earth asteroids (NEAs) and Mars. In order to reduce risk and explore system designs, the RP project is attempting two-fold approaches to development as it looks towards flight. We continue to explore flight planning, requirements, and interfaces definition by using Engineering Test Units (ETUs), looking towards lunar deployment, while also using fiscal year 2015 to develop, build and test an earth-terrestrial prototype rover and payload system. This terrestrial prototype, called "RP15", is built to both inform the system design, and to be a partnership advocacy tool for this unique mission. RP15 must be affordable within the resource and time constraints of fiscal year 2015, while working to the following Needs, Goals, and Objectives provided by HEOMD/AES: 1. Demonstrate rover mobility in a 1g environment 2. The Surface Segment (prototype rover + payload system) shall represent the flight system concept with as much fidelity as affordable (limited by cost and schedule) - Surface Segment shall be the approximate size/dimension/footprint -Surface Segment shall package all the expected devices (instruments, systems, etc.), even if some facets are mocked-up due to time/cost constraints -Overall Surface Segment fidelity negotiable to make achievable 3. Priority should be given to illustrating mission functionality over support functionality, which exists solely to support mission functionality This paper will provide an overview of RP project developments, including the design and build, capturing the development and initial integrated testing of RP15 in relevant environments.

Lunar↗

DOE OSTI2025

Building workflows for an interactive human-in-the-loop automated experiment (hAE) in STEM-EELS

Exploring the structural, chemical, and physical properties of matter on the nano- and atomic scales has become possible with the recent advances in aberration-corrected electron energy-loss spectroscopy (EELS) in scanning transmission electron microscopy (STEM). However, the current paradigm of STEM-EELS relies on the classical rectangular grid sampling, in which all surface regions are assumed to be of equal a priori interest. However, this is typically not the case for real-world scenarios, where phenomena of interest are concentrated in a small number of spatial locations, such as interfaces, structural and topological defects, and multi-phase inclusions. One of the foundational problems is the discovery of nanometer- or atomic-scale structures having specific signatures in EELS spectra. Herein, we systematically explore the hyperparameters controlling deep kernel learning (DKL) discovery workflows for STEM-EELS and identify the role of the local structural descriptors and acquisition functions in experiment progression. In agreement with the actual experiment, we observe that for certain parameter combinations the experiment path can be trapped in the local minima. We demonstrate the approaches for monitoring the automated experiment in the real and feature space of the system and knowledge acquisition of the DKL model. Based on these, we construct intervention strategies defining the human-in-the-loop automated experiment (hAE). This approach can be further extended to other techniques including 4D STEM and other forms of spectroscopic imaging. The hAE library is available on Github at https://github.com/utkarshp1161/hAE/tree/main/hAE.

Pratiush, Utkarsh [Univ. of Tennessee, Knoxville, ↗

NASA NTRS2006

Data Integration Support for Data Served in the OPeNDAP and OGC Environments

NASA is coordinating a technology development project to construct a gateway between system components built upon the Open-source Project for a Network Data AcceSs Protocol (OPeNDAP) and those made available made available via interfaces specified by the Open Geospatial Consortium (OGC). This project is funded though the Advanced Collaborative Connections for Earth-Sun System Science (ACCESS) Program and is a NASA contribution to the Committee on Earth Satellites (CEOS) Working Group on Information Systems and Services (WGISS). The motivation for the project is the set of data integration needs that have been expressed by the Coordinated Enhanced Observing Period (CEOP), an international program that is addressing the study of the global water cycle. CEOP is assembling a large collection in situ and satellite data and mode1 results from a wide variety of sources covering 35 sites around the globe. The data are provided by systems based on either the OPeNDAP or OGC protocols but the research community desires access to the full range of data and associated services from a single client. This presentation will discuss the current status of the OPeNDAP/OGC Gateway Project. The project is building upon an early prototype that illustrated the feasibility of such a gateway and which was demonstrated to the CEOP science community. In its first year as an ACCESS project, the effort has been has focused on the design of the catalog and data services that will be provided by the gateway and the mappings between the metadata and services provided in the two environments.

McDonald, Kenneth R.↗

DOE OSTI2021

UIR-Net: Object Detection in Infrared Imaging of Thermomechanical Processes in Automotive Manufacturing

Thermomechanical processes (TMPs) such as resistance spot welding (RSW) and hot stamping are widely used in automotive manufacturing. Recent advancement in sensing technology has led to an increasing adoption of thermographic cameras to capture the infrared (IR) radiation of a metal part (or component of a part) during its thermomechanical processing or immediately after the process when the part is still hot. Detecting the object(s) of interest from raw IR images is an essential step in analyzing these data. Deep learning (DL) has been a recent success for object detection (OD), but the application of DL-based OD for industrial IR images in manufacturing is largely lagging behind. The major contribution of this work, which is also the distinction from previous OD studies, is the capability of building the OD model with unlabeled IR images, i.e., imaging data without accurate information indicating the object position. Here, the architecture of Unsupervised IR Image Net (UIR-Net) is designed to accommodate the unique characteristics of IR images from TMPs in manufacturing. This study presents a novel method for OD in unlabeled IR images from TMPs. The proposed method, called UIR-Net, consists of two components: label generation and DL model construction. Two case studies from automotive manufacturing, RSW and hot stamping, are reported to demonstrate the feasibility and effectiveness of the proposed method.

42 ENGINEERING↗

NASA NTRS2002

Louisiana NASA EPSCoR Project

In 1994, the National Aeronautics and Space Administration issued a Cooperative Agreement (CA) to the State of Louisiana, through the Louisiana Board of Regents (BOB), for the performance of scientific research under the Experimental Program to Stimulate Competitive Research (EPSCoR) Project. Originally constructed as a three-year program with an optional two-year follow on, this federal-state partnership culminated on 31 October 2001, including two CA extensions. The total value of the project reached $3.3M in NASA funding, matched by $2.75M in BOB funds, and supplemented by several million dollars in institutional contributions. Three Research Clusters comprised the state-wide research effort coupled with scientific/technical management and a teacher involvement component. The three research clusters addressed the Enterprises of Space Science, Earth Science and Aerospace Technology with research in High Energy Astrophysics, the Global Carbon Cycle, and Propulsion. Ten universities, over two dozen faculty, over 150 students and numerous support personnel were involved. All of the scientific and technical objectives were met or exceeded. In aggregate, the clusters generated about $18M in outside support, better than a 2:1 return on investment (better than 5:1 considering only the NASA investment). Moreover, two of the clusters have advanced to the level of applying for major NSF research center designation. This project was a trial of the model of building research infrastructure through mentoring. While not completely successful, the results at the smaller institutions were, none the less, positive. Faculty were engaged in major research and involved their students. Administrations improved their capabilities to handle grants and contracts. Faculty release time was granted, research space was provided and, in some cases, equipment was made available for the research. Some of the faculty at these schools have remained involved in research and/or formed collaborations for new endeavors, demonstrating that the mentoring model can be successful.

Wefel, John P.↗

NASA NTRS2016

NH11B-1726: FrankenRaven: A New Platform for Remote Sensing

Small, modular aircraft are an emerging technology with a goal to maximize flexibility and enable multi-mission support. This reports the progress of an unmanned aerial system (UAS) project conducted at the NASA Ames Research Center (ARC) in 2016. This interdisciplinary effort builds upon the success of the 2014 FrankenEye project to apply rapid prototyping techniques to UAS, to develop a variety of platforms to host remote sensing instruments. In 2016, ARC received AeroVironment RQ-11A and RQ-11B Raven UAS from the US Department of the Interior, Office of Aviation Services. These aircraft have electric propulsion, a wingspan of roughly 1.3m, and have demonstrated reliability in challenging environments. The Raven airframe is an ideal foundation to construct more complex aircraft, and student interns using 3D printing were able to graft multiple Raven wings and fuselages into FrankenRaven aircraft. Aeronautical analysis shows that the new configuration has enhanced flight time, payload capacity, and distance compared to the original Raven. The FrankenRaven avionics architecture replaces the mil-spec avionics with COTS technology based upon the 3DR Pixhawk PX4 autopilot with a safety multiplexer for failsafe handoff to 2.4 GHz RC control and 915 MHz telemetry. This project demonstrates how design reuse, rapid prototyping, and modular subcomponents can be leveraged into flexible airborne platforms that can host a variety of remote sensing payloads and even multiple payloads. Modularity advances a new paradigm: mass-customization of aircraft around given payload(s). Multi-fuselage designs are currently under development to host a wide variety of payloads including a zenith-pointing spectrometer, a magnetometer, a multi-spectral camera, and a RGB camera. After airworthiness certification, flight readiness review, and test flights are performed at Crows Landing airfield in central California, field data will be taken at Kilauea volcano in Hawaii and other locations.

remote sensing↗