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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 NTRS1990

Space-time modeling using environmental constraints in a mobile robot system

Grid-based models of a robot's local environment have been used by many researchers building mobile robot control systems. The attraction of grid-based models is their clear parallel between the internal model and the external world. However, the discrete nature of such representations does not match well with the continuous nature of actions and usually serves to limit the abilities of the robot. This work describes a spatial modeling system that extracts information from a grid-based representation to form a symbolic representation of the robot's local environment. The approach makes a separation between the representation provided by the sensing system and the representation used by the action system. Separation allows asynchronous operation between sensing and action in a mobile robot, as well as the generation of a more continuous representation upon which to base actions.

Slack, Marc G.↗

NASA NTRS2010

Optimization of a Multi-Stage ATR System for Small Target Identification

An Automated Target Recognition system (ATR) was developed to locate and target small object in images and videos. The data is preprocessed and sent to a grayscale optical correlator (GOC) filter to identify possible regionsof- interest (ROIs). Next, features are extracted from ROIs based on Principal Component Analysis (PCA) and sent to neural network (NN) to be classified. The features are analyzed by the NN classifier indicating if each ROI contains the desired target or not. The ATR system was found useful in identifying small boats in open sea. However, due to "noisy background," such as weather conditions, background buildings, or water wakes, some false targets are mis-classified. Feedforward backpropagation and Radial Basis neural networks are optimized for generalization of representative features to reduce false-alarm rate. The neural networks are compared for their performance in classification accuracy, classifying time, and training time.

false alarm rate↗

DOE OSTI2026

A unified neural-network framework for nucleon imaging from numerical simulations of QCD

Parton distributions encode the momentum-space structure and, in their generalizations, the spatial tomography of quarks and gluons inside hadrons, the building blocks of visible matter. We present a unified neural-network approach that learns these distributions directly from matrix elements calculated via numerical simulations of quantum chromodynamics (QCD) on the lattice by fitting two complementary inputs simultaneously: data matched to physical quantities via known momentum-space and coordinate-space formalisms. Utilizing data from both methods stabilizes the extraction and mitigates biases that can arise when either is used alone. We validate the method on controlled mock data and apply it to lattice-QCD matrix elements to extract parton distribution functions (PDFs). We show benefits of such an approach for determining the physical quantities. We further extend the framework to zero-skewness generalized parton distributions and demonstrate nucleon tomography within the same neural-network parameterization. Our results provide an adaptable and systematically improvable approach for extracting partonic distributions from Euclidean correlators. It can incorporate polarization, additional channels, and future experimental constraints from current and future facilities, such as the Electron-Ion Collider.

Hadronic Spectroscopy↗

NASA NTRS2011

Finding Mutual Exclusion Invariants in Temporal Planning Domains

We present a technique for automatically extracting temporal mutual exclusion invariants from PDDL2.2 planning instances. We first identify a set of invariant candidates by inspecting the domain and then check these candidates against properties that assure invariance. If these properties are violated, we show that it is sometimes possible to refine a candidate by adding additional propositions and turn it into a real invariant. Our technique builds on other approaches to invariant synthesis presented in the literature, but departs from their limited focus on instantaneous discrete actions by addressing temporal and numeric domains. To deal with time, we formulate invariance conditions that account for both the entire structure of the operators (including the conditions, rather than just the effects) and the possible interactions between operators. As a result, we construct a technique that is not only capable of identifying invariants for temporal domains, but is also able to find a broader set of invariants for non-temporal domains than the previous techniques.

Bernardini, Sara↗

NASA NTRS2012

Polyimide Aerogel Thin Films

Polyimide aerogels have been crosslinked through multifunctional amines. This invention builds on "Polyimide Aerogels With Three-Dimensional Cross-Linked Structure," and may be considered as a continuation of that invention, which results in a polyimide aerogel with a flexible, formable form. Gels formed from polyamic acid solutions, end-capped with anhydrides, and cross-linked with the multifunctional amines, are chemically imidized and dried using supercritical CO2 extraction to give aerogels having density around 0.1 to 0.3 g/cubic cm. The aerogels are 80 to 95% porous, and have high surface areas (200 to 600 sq m/g) and low thermal conductivity (as low as 14 mW/m-K at room temperature). Notably, the cross-linked polyimide aerogels have higher modulus than polymer-reinforced silica aerogels of similar density, and can be fabricated as both monoliths and thin films.

Meador, Mary Ann↗

NASA NTRSDate not supplied

In-Situ Alloying of GRCop-42 via Additive Manufacturing: Precipitate Analysis

GRCop-42, a Cu-4at% Cr-2at% Nb alloy, was designed as a high temperature, high strength, high heat flux material for rocket engine combustion chamber liners by NASA Glenn Research Center. In situ alloying of GRCop-42 (ISGRCop-42) using powder bed fusion (PBF) additive manufacturing (AM) takes elemental powders of Cu, Cr, and Nb to be introduced into the PBF environment and develop the GRCop alloy while simultaneously building an AM component. Elemental powders were milled together prior to printing in an effort to facilitate the alloying process. Success of the in situ alloying process may provide lower cost, faster lead times, alloying optimization, and more design freedom in the development of regeneratively-cooled rocket propulsion systems. Evaluation of the ISGRCop-42 was conducted using a phase extraction procedure to isolate the Cr2Nb precipitates from the pure Cu matrix. The isolated precipitates were then examined using x-ray powder diffraction (XRD), scanning electron microscopy (SEM), and energy dispersion spectroscopy (EDS). It was found that ISGRCop-42 successfully and repeatedly formed Cr2Nb at a yield as high as 89% of potential Cr2Nb. Further, it was identified that the preparation of the powder was the most influential factor in alloying success, and the second most influential factor was the laser power.

In Situ alloying↗

DOE OSTI2020

Using Machine Learning to Predict Future Temperature Outputs in Geothermal Systems

Optimizing the power output, and economic value, of geothermal power plants over decades of operation is a major challenge in renewable energy. Optimizing the output requires the ability to predict the mass flow rates and the output temperatures of production wells based on the inputs of injection wells, as well as the time history of the system. Machine Learning (ML) that incorporates the known physics of geothermal systems is one possible solution to this challenge. In this work, we explore the ability of ML algorithms to predict future temperature outputs based on historical data. Considering the challenges with obtaining an empirical dataset from field data that is large enough to enable reliable ML, we propose an alternate approach: developing a high-fidelity reservoir model and using computational resources to build a dataset that enables ML. As a first step towards achieving this goal, we present preliminary results from applying ML to predict the temperature timeseries of simple modeled geothermal systems. We describe the application of relevant state-of-the-art ML approaches, such as the Long Short-Term Memory (LSTM) networks and Convolutional Neural Networks (CNN), to extract temporal structures in the model data. We assess the accuracy of the forecasts we obtain, compare the selected approaches, and share the lessons learned that would inform the process of training and utilizing ML algorithms for larger and more complex geothermal systems.

GEOTHERMAL ENERGY↗

NASA NTRS2024

Interim Measures Work Plan: South Repeater Building: Solid Waste Management Unit 121: Hydraulic Containment and Groundwater Treatment System for Per- and Polyfluoroalkyl Substances: Kennedy Space Center, Florida

This document presents the design details of a granular activated carbon (GAC) hydraulic containment and groundwater treatment system Interim Measures Work Plan for the South Repeater Building site (South Repeater, Solid Waste Management Unit 121), located at John F. Kennedy Space Center (KSC), Florida. The interim measures (IM) treatment area includes the source area and downgradient property boundary, which have been impacted by per- and polyfluoroalkyl substances (PFAS). The objectives of the IM are to treat the source area and mitigate PFAS migration to areas outside of KSC boundaries. This document was prepared by AECOM Technical Services, Inc., for the National Aeronautics and Space Administration under Contract 80KSC019D0010, Task Order 80KSC021F0096. The IM consists of the installation and operation of 19 extraction wells and an associated groundwater treatment system. A total of 13 wells will be installed to a depth of 34 feet below land surface (bls) to target the upper medium-grained sand with shell layer. A total of six wells will be installed to a depth of 56 feet bls to target the lower layer of poorly graded sand with shell fragments. The system will be designed to operate each extraction well simultaneously using submersible pumps at flow rates of 5 or 10 gallons per minute (gpm), excluding one extraction well with a flow rate of 30 gpm. The extracted groundwater will be conveyed to a groundwater treatment system, where it will be treated via GAC prior to disposal via infiltration. To evaluate treatment system performance, baseline groundwater sampling will be conducted prior to treatment system startup. Performance monitoring will be completed quarterly for the first year. A total of eight performance monitoring wells will be installed to a depth of 12 feet bls, and eight performance monitoring wells will be installed to a depth of 30 feet bls. In addition to the installation of 16 performance monitoring wells, 12 existing monitoring wells will be incorporated into the performance monitoring program.

groundwater treatment↗

NASA NTRS2003

An Extraction and Curation Technique for Particles Captured in Aerogel Collectors

In 2006, the STARDUST mission will return samples of cometary, interplanetary and interstellar dust captured in aerogel collectors. The curation strategy (or strategies) for STARDUST remain to be defined. Here we present a technique for curation of particles captured in aerogel which will simultaneously preserve the entire particle track, and could allow for the elemental in situ analysis of both the particle residue at the terminus of the track and any particle residues located along the track. This builds on work that we have previously reported elsewhere.

Westphal, A. J.↗

NASA NTRS2016

Human Mars Landing Site and Impacts on Mars Surface Operations

This paper describes NASA's initial steps for identifying and evaluating candidate Exploration Zones (EZs) and Regions of Interests (ROIs) for the first human crews that will explore the surface of Mars. NASA's current effort to define the exploration of this planet by human crews, known as the Evolvable Mars Campaign (EMC), provides the context in which these EZs and ROIs are being considered. The EMC spans all aspects of a human Mars mission including launch from Earth, transit to and from Mars, and operations on the surface of Mars. An EZ is a collection of ROIs located within approximately 100 kilometers of a centralized landing site. ROIs are areas relevant for scientific investigation and/or development/maturation of capabilities and resources necessary for a sustainable human presence. The EZ also contains one or more landing sites and a habitation site that will be used by multiple human crews during missions to explore and utilize the ROIs within the EZ. With the EMC as a conceptual basis, the EZ model has been refined to a point where specific site selection criteria for scientific exploration and in situ resource utilization can be defined. In 2015 these criteria were distributed to the planetary sciences community and the in situ resource utilization and civil engineering communities as part of a call for EZ proposals. The resulting "First Landing Site/Exploration Zone Workshop for Human Missions to the Surface of Mars" was held in October 2015 during which 47 proposals for EZs and ROIs were presented and discussed. Proposed locations spanned all longitudes and all allowable latitudes (+/- 50 degrees). Proposed justification for selecting one of these EZs also spanned a significant portion of the scientific and resource criteria provided to the community. Several important findings resulted from this Workshop including: (a) a strong consensus that, at a scale of 100 km (radius), multiple places on Mars exist that have both sufficient scientific interest to sustain multiple crews of exploring astronauts, AND potential resource deposits for ISRU indicating the current EZ definition is viable and should be retained for now, (b) new data types (needed for more definitive analysis of EZs) argued strongly for a new orbiter mission, and possibly one or more surface missions, to obtain these data, (c) a general consensus that this Workshop was an excellent start to identifying a place where future human missions to Mars can productively explore this planet and learn to live and work there for the long term. Building on these findings, HEOMD and SMD are: (a) refining the EZ selection criteria and overall selection process to improve on lessons learned from the first EZ workshop, (b) using these proposed locations to develop "reference EZs" for assessment purposes (primarily engineering assessments), (c) gathering data and conducting analyses to better understanding the different potential sources for water, including the ease of extraction and purification, and (d) assessing trends in additional data that are needed to better characterize EZs proposed at the workshop and how these data needs impact the design and operation of future robotic Mars missions.

Hoffman, Stephen J.↗

NASA NTRSDate not supplied

Method Development for In-situ Detection of Latent Herpesvirus DNA from Saliva using Nanopore Sequencing

Research toward latent herpesvirus reactivation has been intensively addressed through Space Shuttle and International Space Station (ISS) investigations. This work has provided the understanding that persistent reactivation of herpesviruses from asymptomatic crew can be detected through viral shedding in saliva, urine, and blood. Occasionally, viral reactivation from the latency stage can pose a threat to crew health (clinical manifestation) before, during, and after flight missions. Furthermore, previous work detailing correlations with immunity indicate that monitoring viral reactivation could be implemented to assess potential immune dysfunction. While in-flight monitoring is desirable, there is no well-established procedure or method for real-time evaluations, and research to date has relied on postflight, ground-based analysis. The development of portable molecular technologies like the miniPCR™ (miniPCR Bio) thermal cycler and the MinION™ sequencer (Oxford Nanopore Technologies) have confirmed that real-time monitoring is possible in extreme and low resource environments. These devices, combined with simple sample preparation methods, have been used to demonstrate bacterial identification onboard the ISS, as well as rapid viral detection in remote locations on Earth. The work here builds upon previous molecular advancements onboard the ISS toward the development and validation of a spaceflight-compatible method for viral detection from crew samples. Several herpesviruses can be detected in saliva, which provides a non-invasive means to collect samples for monitoring. While the basis for this method lies in previous spaceflight investigations, key points for method optimization include DNA extraction from saliva, viral primer selection, and bioinformatic processes for data analysis. To increase viral yield, numerous DNA extraction methods have been evaluated and will be discussed in detail. For initial development and testing, varicella-zoster virus (VZV) is being targeted though open reading frame 51 and 63 (ORF51, ORF63), as the replication origin-binding protein is highly expressed during latency. Optimization of the thermal cycling parameters has resulted in the ability to test the entire process. The full method has been tested with both viral VZV DNA standards and saliva spiked with varying concentrations of VZV. Viral sequence data were mapped to the reference sequence using minimap2. Prior to mapping, DNA sequencing reads were filtered for length and quality, barcodes were removed, and alignment identity calculated. Following further assessments, statistics were compared across multiple sequencing experiments and are being used to determine the success of the protocols. Forward work will include the incorporation of herpes simplex virus 1 (HSV-1) and Epstein-Barr virus (EBV) primers as well as the validation of results to the terrestrial qPCR standard assay. Upon full validation of the developed method, saliva will be collected from 20 healthy subjects and spiked with viral DNA. These samples will be split and assayed with the MinION and standard qPCR assay.

Hang N Nguyen↗

NASA NTRSDate not supplied

Extraction of Thruster Plume Ion Population Trends From Retarding Potential Analyzer Data

Characterization of ion plume impingement effects on spacecraft surfaces requires knowledge of the ion energy distributions in the thruster plume. Retarding potential analyzers are a convenient diagnostic that provide measurements of the ion voltage distributions. This work presents an attempt to extract additional information via fitting multiple Maxwellian distributions to the diagnostic traces. Tracking the trends of the fitted ion populations across varying facility pressure, angular location, and thruster operating conditions offers further insight into the makeup of the plume plasma and the behavior of the ion energies as a function of those parameters. This approach provides supporting evidence in establishing margins and building further confidence in the plume modeling validation process.

John T. Yim↗

NASA NTRS2017

Building an Economical and Sustainable Lunar Infrastructure to Enable Lunar Industrialization

A new concept study was initiated to examine the architecture needed to gradually develop an economical, evolvable and sustainable lunar infrastructure using a public/private partnerships approach. This approach would establish partnership agreements between NASA and industry teams to develop a lunar infrastructure system that would be mutually beneficial. This approach would also require NASA and its industry partners to share costs in the development phase and then transfer operation of these infrastructure services back to its industry owners in the execution phase. These infrastructure services may include but are not limited to the following: lunar cargo transportation, power stations, communication towers and satellites, autonomous rover operations, landing pads and resource extraction operations. The public/private partnerships approach used in this study leveraged best practices from NASA's Commercial Orbital Transportation Services (COTS) program which introduced an innovative and economical approach for partnering with industry to develop commercial cargo services to the International Space Station. This program was planned together with the ISS Commercial Resupply Services (CRS) contracts which was responsible for initiating commercial cargo delivery services to the ISS for the first time. The public/private partnerships approach undertaken in the COTS program proved to be very successful in dramatically reducing development costs for these ISS cargo delivery services as well as substantially reducing operational costs. To continue on this successful path towards installing economical infrastructure services for LEO and beyond, this new study, named Lunar COTS (Commercial Operations and Transport Services), was conducted to examine extending the NASA COTS model to cis-lunar space and the lunar surface. The goals of the Lunar COTS concept are to: 1) develop and demonstrate affordable and commercial cis-lunar and surface capabilities, such as lunar cargo delivery and surface power generation, in partnership with industry; 2) incentivize industry to establish economical and sustainable lunar infrastructure services to support NASA missions and initiate lunar commerce; and 3) encourage creation of new space markets for economic growth and benefit. A phased-development approach was also studied to allow for incremental development and demonstration of capabilities needed to build a lunar infrastructure. This paper will describe the Lunar COTS concept goals, objectives and approach for building an economical and sustainable lunar infrastructure. It will also describe the technical challenges and advantages of developing and operating each infrastructure element. It will also describe the potential benefits and progress that can be accomplished in the initial phase of this Lunar COTS approach. Finally, the paper will also look forward to the potential of a robust lunar industrialization environment and its potential effect on the next 50 years of space exploration.

Zuniga, Allison F.↗

DOE OSTI2022

Approaches for effective negative pressure isolation space control to minimize airborne transmission of contaminants in residential homes

Controlling airborne transmission of contaminants including respired viruses such as SARS-CoV-2 is necessary to protect occupants living in the same house with a contagious person. The effectiveness of interventions requiring minor efforts that create a negative pressure isolation zone (IZ) for a contagious person has yet to be systematically tested for residential homes. In this study, ASHRAE Standard 170, which offers guidance for negative pressure isolation space control in healthcare facilities, was used in developing practical and attainable recommendations for residential single-family homes. The relative effectiveness of several control strategies was evaluated through experimentally conducting 17 different test cases in a manufactured single-family house laboratory. These cases were designed based on various heating, ventilation and air-conditioning (HVAC) operating scenarios, intervention measures including closing the IZ door and/or sealing over supply and return air grilles in the IZ, and utilization of bathroom exhaust or portable window fans for pressure control. Four out of 17 test cases were identified as having the potential for strong containment with adequate depressurization in the IZ. The most effective IZ depressurization was achieved through continuously operating the exhaust fan in the bathroom attached to the IZ, by installing a portable window fan that extracted air out of the IZ, and a portable room air conditioner with the AC unit exhaust duct installed in one of the IZ windows.

Construction & Building Technology↗

NASA NTRS1994

Optical-Correlator Neural Network Based On Neocognitron

Multichannel optical correlator implements shift-invariant, high-discrimination pattern-recognizing neural network based on paradigm of neocognitron. Selected as basic building block of this neural network because invariance under shifts is inherent advantage of Fourier optics included in optical correlators in general. Neocognitron is conceptual electronic neural-network model for recognition of visual patterns. Multilayer processing achieved by iteratively feeding back output of feature correlator to input spatial light modulator and updating Fourier filters. Neural network trained by use of characteristic features extracted from target images. Multichannel implementation enables parallel processing of large number of selected features.

Chao, Tien-Hsin↗

DOE OSTI2023

Low power and privacy preserving sensor platform for occupancy detection

A low-cost, low-power, stand-alone sensor platform having a visible-range camera sensor, a thermopile array, a microphone, a motion sensor, and a microprocessor that is configured to perform occupancy detection and counting while preserving the privacy of occupants. The platform is programmed to extract shape/texture from images in spatial domain; motion from video in time domain; and audio features in frequency domain. Embedded binarized neural networks are used for efficient object of interest detection. The platform is also programmed with advanced fusion algorithms for multiple sensor modalities addressing dependent sensor observations. The platform may be deployed for (i) residential use in detecting occupants for autonomously controlling building systems, such as HVAC and lighting systems, to provide energy savings, (ii) security and surveillance, such as to detect loitering and surveil places of interest, (iii) analyzing customer behavior and flows, (iv) identifying high performing stores by retailers.

Velipasalar, Senem↗

DOE OSTI2025

Measuring thermal curing induced shrinkage of material extrusion based additive manufacturing silicone elastomer lattices by X-ray computed tomography

Thermal curing induces shrinkage in material extrusion based additive manufacturing silicone elastomer samples, resulting in discrepancies between as printed and final geometries. Knowing the extent to which the samples change in shape and size allows us to make appropriate modifications to the printing design to better control the geometry of the samples. We present an X-ray computed tomography (CT) based approach to determine filament-level shrinkage due to thermal curing of silicone elastomer samples printed with direct ink writing (DIW). The approach relies on custom-designed build plates that are resistant to the elevated curing temperatures and that have sufficiently distinct X-ray absorption characteristics from the silicone elastomer to ensure adequate segmentation of the latter in X-ray imaging data. We implement the approach to evaluate shrinkage in DIW ‘log pile’ samples with three distinct strand arrangements and demonstrate of how filament-level information can be extracted from the X-ray CT data.

Additive manufacturing↗

DOE OSTI2023

PiCAM: A Raspberry Pi-based open-source, low-power camera system for monitoring plant phenology in Arctic environments

Time-lapse cameras have been widely used as a tool to monitor the timing of seasonal vegetation growth. These simple, relatively inexpensive systems can provide high-frequency observations of leaf development and demography which are critical data sets needed to characterize plant phenology from species to landscapes. This is important for understanding how plants are responding to global changes, as well as for validating satellite-derived phenology products. However, in remote regions including the high-latitude Arctic, deploying time-lapse cameras could be challenging. The remoteness and lack of widespread power and telecommunications infrastructure limit options for the installation, maintenance and retrieval of data and equipment, and make it difficult for cameras to survive in extreme weather (e.g. long cold winters). To improve our understanding of Arctic phenology, new technologies are required to address these challenges. Here, we present a novel, low-power, compact, lightweight time-lapse camera system, called power-interval camera automation module (PiCAM). The PiCAM was designed with explicit consideration to simplify deployment (i.e. without a need for external power supplies) of camera systems and to address the challenges of camera survival in harsh Arctic environments. In this paper, we describe the design, setup and technical details of the PiCAM and provide a roadmap for how to build and operate these systems. As proof of concept, we deployed 26 PiCAMs at three low-Arctic tundra sites on the Seward Peninsula, Alaska in early August 2021 for characterizing Arctic plant phenology. Of the 26 PiCAMs, 70% remained active at the point of our revisit in late July 2022 despite the extreme winter temperatures they experienced (< –30°C, heavy snow cover). We extracted key plant phenology metrics from the PiCAMs and captured strong differences across key Arctic plant species. We showed that the PiCAM has the potential to be widely used for monitoring plant phenology across the broader Arctic region, addressing the need for ground-based understanding of Arctic phenological diversity to develop knowledge of plant response to climate change and to validate remote sensing products.

54 ENVIRONMENTAL SCIENCES↗