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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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At least 757 records · Page 42
All sourcesNASA NTRSDOE OSTI
NASA NTRS2016

Environmental Enrichment in the ISS Rodent Habitat Hardware System

Responses of animals exposed to microgravity during in-space experiments were reviewed from NASAs and ESA available video recording archives. These documented observation of animal behavior, as well as the range and level of activities during spaceflight, clearly demonstrate that weightlessness conditions and the extreme novelty of the surroundings exert damaging psychological stresses on the inhabitants. In response to a recognized need for in-flight animals to improve their wellbeing we propose to reduce such stresses by shaping and interrelating structures and surroundings to satisfying vital physiological needs of inhabitants. Rodent Habitat Hardware System based housing facility incorporating a tubing network system, to maintain and monitor rodent health environment with advanced accessories has been proposed. The new tubing configuration was found suitable for further incorporation of innovative monitoring technology and accessories in the animal holding habitat unit which allow to monitor in real-time the most valuable health related biological parameter under weightlessness environment of spaceflight.

Orr, Sophie↗
NASA NTRSDate not supplied

From the Interstellar Medium to Ocean Worlds: new challenges for Laboratory Astrophysics

From the Interstellar Medium to Ocean Worlds: new challenges for Laboratory Astrophysics For the past 35+ years, laboratory experiments in Astrophysics have been focusing on identifying and understanding the molecular species and chemistry occurring in interstellar environments, such as the diffuse interstellar medium (ISM) and dense molecular clouds. A significant portion of these laboratory efforts concerns investigations of carbon-based molecules ranging in size from a single carbon atom (e.g., CO, CO2, H2CO) to large polycyclic aromatic hydrocarbon (PAH) molecules potentially consisting of more than one hundred carbon atoms as well as their reactions with H2O and other interstellar species. The laboratory facilities built to conduct these investigations are capable of monitoring the chemistry and measuring the spectra under a wide range of interstellar conditions (e.g., low temperatures and pressures). The past 15 years of space exploration revealed the presence of at least nine other Ocean Worlds, besides Earth, in our Solar System. These worlds include moons and dwarf planets, ice-covered surfaces, subsurface oceans, as well as geysers venting H2O and other compounds, including organics in at least one environment, into space. Although these worlds represent environments that are significantly different from those traditionally considered the realm of Laboratory Astrophysics, their facilities are well situated to provide insight into the chemistry occurring in and around these worlds as well as experimental data for the interpretation of observations from missions visiting these Ocean World. This presentation will discuss the areas where Laboratory Astrophysics can provide experimental data to help understand the chemistry, and mission data of Ocean Worlds, and the challenges research into Ocean Worlds presents to our current facilities and how they can be overcome. Lastly, this presentation will introduce the new ICEE (In-situ Carbon Evolution Experiments) facility at NASA Ames Research Center as an example of how a lab dedicated to Laboratory Astrophysics can adapt itself to also meet the needs for Ocean Worlds research.

Andrew Lige Mattioda↗
DOE OSTI2021

In-situ Photophysical Monitors and Corrective Algorithms for Photovoltaic Film Deposition and Rapid Thermal Processing in Scalable Roll-to-Roll Manufacturing

This project evaluated three photophysics-based approaches for in situ process monitoring of the scalable deposition of perovskite photovoltaic films. Based on stakeholder input and the results of laboratory trials and literature analysis, two techniques, angle resolved elastic light scattering (ARLS) and time-resolved photoluminescence (TRPL) were prototyped and demonstrated with a mixture of simulation, offline and online tests. Also, a hybrid gas flow and humidity control enclosure was constructed and demonstrated to stabilize the ambient conditions around the slot die deposition process and were demonstrated to meet the target humidity control in situ. Due in part to a delayed start and COVID-related lab restrictions and personnel changes, some of the milestones were not met. In spite of these challenges, however, both techniques were prototyped through several iterations and demonstrated significant promise for rapid in line perovskite characterization within the targeted characterization time windows and these techniques are under further development for use in DE-FOA000235:2357-1586. The TRPL system was fully mounted and demonstrated on the scaled slot die roll to roll and sheet coating systems at the Washington Clean Energy Testbeds (WCET). Motivated by significant internal and stakeholder interest, the successful prototyping achieved here, the ongoing need for in-situ characterization for the scale-up of perovskite manufacturing, and the benefits of in situ photophysical characterization for future funded process development research, we are continuing with the principle aims of the project to develop effect in situ photophysical probes for fast analysis of the optoelectronic and structural quality of sheet based and roll to roll process perovskites. TRPLS and ARLS probes proposed in the project are to be completed with external support from the Washington Research Foundation at the WCET. We are currently actively engaged in the acquisition of components and plan to complete and test the probes within three months. It is our intention that these probes will then be used in ongoing perovskite development with our research and commercialization partners including First Solar and other member of the US MAP consortium in future funded development work.

14 SOLAR ENERGY↗
NASA NTRS1990

Mechanistic studies of the CO-oxidation reaction on catalysts for use in long-life CO2 lasers

The catalytic recombination of carbon monoxide and oxygen was studied under conditions expected to be present in a sealed E-beam CO2 laser system. These conditions are typically a gas inlet temperature of 60 C, a substoichiometric CO/O2 ratio of ca. 2.5/1 with an oxygen feed rate of ca. 5 micromoles/s, a carrier gas comprising He, N2 and CO2 in the ratio of 3:2:1, near atmospheric pressure and a gas velocity of 4 m/s. Heterogeneous catalysts, based on precious metal supported on tin oxide, have been coated onto ceramic monoliths and tested for catalytic activity and stability after a reduction/passivation step. Two catalyst systems have been chosen. These are Pt/Pd/SnO2 and Pt/Ru/SnO2. Under the conditions described above, a characteristic decline in catalytic activity is apparent for both systems, and exit gas temperature has been recognized as a sensitive parameter by which to monitor the activity changes. A semilogarithmic plot of exit temperature as a function of time has revealed two distinct processes connected with the decline in activity: one process is associated with reduction of the oxidized precious metal (at Site A), whilst the other is related to the formation and approach to steady-state of an active site at the metal/support interface (Site B).

Dawood, Talat↗
NASA NTRS1989

Reusable rocket engine turbopump health monitoring system, part 3

Degradation mechanisms and sensor identification/selection resulted in a list of degradation modes and a list of sensors that are utilized in the diagnosis of these degradation modes. The sensor list is divided into primary and secondary indicators of the corresponding degradation modes. The signal conditioning requirements are discussed, describing the methods of producing the Space Shuttle Main Engine (SSME) post-hot-fire test data to be utilized by the Health Monitoring System. Development of the diagnostic logic and algorithms is also presented. The knowledge engineering approach, as utilized, includes the knowledge acquisition effort, characterization of the expert's problem solving strategy, conceptually defining the form of the applicable knowledge base, and rule base, and identifying an appropriate inferencing mechanism for the problem domain. The resulting logic flow graphs detail the diagnosis/prognosis procedure as followed by the experts. The nature and content of required support data and databases is also presented. The distinction between deep and shallow types of knowledge is identified. Computer coding of the Health Monitoring System is shown to follow the logical inferencing of the logic flow graphs/algorithms.

Perry, John G.↗
NASA NTRS1993

DSS-13: Using an OSI Process Control Standard for Monitor and Control

The flexibility and robustness of a monitor and control (M&C) system are a direct result of the underlying inter-processor communications architecture. A new architecture for M&C at the Deep Space Communications Complexes (DSCCs) has been developed based on the Manufacturing Message Specification (MMS) process control standard of the Open System Interconnection (OSI) suite of protocols. This architecture has been tested both in a laboratory environment and under operational conditions at the Deep Space Network (DSN) experimental station (DSS-13). The DSS-13 experience in the application of OSI standards to support M&C has been extremely successful. MMS meets the functional needs of the station and provides a level of flexibility and responsiveness previously unknown in that environment.

Stockett, Michael H.↗
NASA NTRS1993

Using Manufacturing Message Specification for Monitor and Control at Venus

The flexibility and robustness of a monitor and control (M&C) system are a direct result of the underlying inter-processor communications architecture. A new architecture for M&C at the Deep Space Communications Complexes (DSCCs) has been developed based on the Manufacturing Message Specification (MMS) process control standard of the Open System Interconnection (OSI) suite of protocols. This architecture has been tested both in a laboratory environment and under operational conditions at the Deep Space Network (DSN) experimental Venus station (DSS-13). The Venus experience in the application of OSI standards to support M&C has been extremely successful. MMS meets the functional needs of the station and provides a level of flexibility and responsiveness previously unknown in that environment...

Stockett, Michael H.↗
NASA NTRS2005

Optically Stimulated Electron Emission Contamination Monitor and Method

An apparatus and method for performing quality inspections on a test surface based on optically stimulated emission of electrons. In one embodiment, the apparatus comprises a device for producing optical radiation having a plurality of different spectrum lines, selecting at least one of the spectrum lines, and directing the selected spectrum line to the test surface, and circuitry for detecting a current of photoelectrons emitted from the test surface, generating a signal indicative of photoelectron current, and for indicating a condition of quality based on the generated signal indicative of the photoelectron current. In one embodiment, the method comprises producing optical radiation having a plurality of different spectrum lines, selecting at least one of the spectrum lines and directing the selected spectrum line to the test surface, detecting a current of photoelectrons emitted from the test surface and generating a signal indicative of photoelectron current, and indicating a condition of quality based on the generated signal indicative of the photoelectron current.

Christopher S Welch↗
DOE OSTI2023

Machine-learning-based, online estimation of ceramic’s microstructure upon the laser spot brightness during laser sintering

The ceramic microstructure strongly influences its properties. During manufacturing, the online monitoring of microstructure is critical to ensure the desired material properties. So far, the microstructure on the relevant scale is usually characterized offline using scanning electron microscopy (SEM), which is time and cost-consuming. In this work, we demonstrate a cost-effective, machine learning (ML)-based approach to simulate the SEM micrographs in real-time from the laser spot brightness. We experimentally observed a strong correlation between the laser spot brightness and the corresponding microstructure at the exact locations. The brightness values obtained from thermal emission images and the corresponding SEM micrographs were used in the training datasets. The ML algorithm was a style-based conditional generative adversarial network (CGAN). After training, the ML model could generate high-fidelity microstructure images within 0.1 seconds based on in-situ captured brightness at the laser sintering spot. We used the average grain sizes as the metric to evaluate the accuracy of the ML-predicted micrographs. Here, the ML-predicted microstructures were in good agreement, with less than 5% in difference from the real SEM images. In conclusion, we demonstrate the cost-effective, online microstructure estimation during laser sintering with a simple setup (a camera, a regular computer, and the ML model).

08 HYDROGEN↗
DOE OSTI2022

Development of fast-running eighth core nodal solution

A fast-running, eighth-core solution technique has been developed for the quick core calculations in ANC, the Westinghouse core analysis code based on the nodal expansion method, and the BEACON{sup TM} Core Monitoring System (BEACON). This technique, referred to as 'Fast Eighth' (Fast8), enables users to obtain satisfactory macroscopic core calculation results such as reactivity, axial offset and assembly power much more quickly than calculations performed in the standard full-core or quarter-core geometry. Fast8 uses three techniques: folding the radial geometry into eighth-core geometry, reducing the axial geometry into a coarse axial mesh geometry, and smearing the spacer grids into nodes on-the-fly after the first calculation in the standard geometry. These geometry adjustments in Fast8 contribute to the reduction of the number of neutronic and material nodes while maintaining the reaction rates in each node. The axial mesh condition dependency in Fast8 is investigated in a xenon transient calculation in single assembly geometry, and the Fast8 maximum axial mesh size is determined based on these results. Fast8 is then applied to the load swing calculation, and the results are compared with the reference, full-core geometry, solution. The critical boron concentration and axial offset of Fast8 show good agreement with the reference solutions, and that Fast8 is a good technique for obtaining macroscopic core calculation results in significantly shorter time. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2022

Hybrid data-driven and model-informed online tool wear detection in milling machines

Precision machining tool wear is responsible for low product throughput and quality. Monitoring the tool wear online is vital to prevent degradation in machining quality. However, direct real-time tool wear measurement is not practical. This paper presents residual-based anomaly detection models, combining a hybrid model comprised of a physics-based model and a data-driven model (a decision tree or a neural network) to predict signals of interest (e.g., power or forces) under nominal conditions, followed by Page’s cumulative sum test for detecting tool wear on-line using the computer numerical control machine measurements. The most informative features are ranked using dynamic programming and its approximation variants from real-time measurements and machine settings, such as the width of cut, depth of cut, feed rate and spindle speed, that serve as inputs to the predictive models. The baseline nominal model is incrementally updated with experimental data via a gradient boosted adaptation model to generate the residuals that account for discrepancies between the actual machine data under normal conditions and the baseline nominal model predictions. The hybrid model is validated against 20 Mazak milling machine experimental tests and one Haas run-to-failure experiment. The proposed anomaly detector is applied to synthetic data from simulations of the physics-based model at different operating conditions, measurement noise levels, and tool wear levels, and the methods were able to achieve an overall 92% accuracy in data with 1% noise. The anomaly detection methods based on hybrid model reduced the false alarms of either the data-driven or physical-based models alone, and are found to be capable of good online detection of tool wear.

42 ENGINEERING↗
DOE OSTI2024

Enhancing Data Quality Monitoring at CMS with Interactive Visualization Tools and Automated Reference Run Selection

Current data quality monitoring (DQM) tools at CMS offer granularity limited to per-run analysis. Consequently, issues manifesting at the per-lumisection level can go unnoticed or, even if detectable, often lead to the classification of the whole run as bad, resulting in unnecessary data loss. Additionally, shifters have to evaluate a large set of monitoring elements during their long shifts, increasing the probability of human errors or overlooked problems. In this contribution, we present ongoing work on the development of tools that will provide shifters with an accessible, granularity-enhanced view of DQM data through interactive and dynamic visualizations. Furthermore, we introduce a reference run selection tool currently under development, which will automate the selection based on data-taking conditions and will offer a curated set of training data for machine learning models that will be used for the partial automation of the offline data certification process. These endeavors will be integrated into the DIALS website, enabling enhancements in data certification accuracy and improving the accessibility of DQM at CMS.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
NASA NTRS1974

Preliminary results of ERTS-investigations by W-German investigations

Results are presented of West German investigations into multidisciplinary geoscientific experiments in central Germany and the Alps, and hydrogeological investigations in the Pampa of Argentina based on ERTS-1 data. The main goals of the investigation were achieved. The studies have given a good idea of the possibilities and limitations of ERTS imagery depending on the objectives in question and on the geographical conditions of the areas under investigation. Even in the well known region of central Europe, ERTS has proven its ability of improving present knowledge. In fields such as pollution monitoring and regional planning the satellite techniques should have distinct practical value. For any regional study of less known areas, the value of ERTS imagery can hardly be overestimated.

Muehlfeld, R.↗
NASA NTRS1976

Microbiology studies in the Space Shuttle

Past space microbiology studies have evaluated three general areas: microbe detection in extraterrestrial materials; monitoring of autoflora and medically important species on crewmembers, equipment, and cabin air; and in vitro evaluations of isolated terrestrial species carried on manned and unmanned spaceflights. These areas are briefly reviewed to establish a basis for presenting probable experiment subjects applicable to the Space Shuttle era. Most extraterrestrial life detection studies involve visitations to other heavenly bodies. Although this is not applicable to the first series of Shuttle flights, attempts to capture meteors and spores in space could be important. Human pathogen and autoflora monitoring will become more important with increased variety among crewmembers. Inclusion of contaminated animal and plant specimens in the space lab will necessitate inflight evaluation of cross-contamination and infection potentials. The majority of Shuttle microbiology studies will doubtless fall into the third study area. Presence of a space lab will permit a whole range of experimentation under conditions similar to these experienced in earth-based laboratories. The recommendations of various study groups are analyzed, and probable inflight microbiological experiment areas are identified for the Life Sciences Shuttle Laboratory.

Taylor, G. R.↗
NASA NTRS1976

Display/control requirements for automated VTOL aircraft

A systematic design methodology for pilot displays in advanced commercial VTOL aircraft was developed and refined. The analyst is provided with a step-by-step procedure for conducting conceptual display/control configurations evaluations for simultaneous monitoring and control pilot tasks. The approach consists of three phases: formulation of information requirements, configuration evaluation, and system selection. Both the monitoring and control performance models are based upon the optimal control model of the human operator. Extensions to the conventional optimal control model required in the display design methodology include explicit optimization of control/monitoring attention; simultaneous monitoring and control performance predictions; and indifference threshold effects. The methodology was applied to NASA's experimental CH-47 helicopter in support of the VALT program. The CH-47 application examined the system performance of six flight conditions. Four candidate configurations are suggested for evaluation in pilot-in-the-loop simulations and eventual flight tests.

Hoffman, W. C.↗
NASA NTRS2022

Hybrid data-driven and model-informed online tool wear detection in milling machines

Precision machining tool wear is responsible for low product throughput and quality. Monitoring the tool wear online is vital to prevent degradation in machining quality. However, direct real-time tool wear measurement is not practical. This paper presents residual-based anomaly detection models, combining a hybrid model comprised of a physics-based model and a data-driven model (a decision tree or a neural network) to predict signals of interest (e.g., power or forces) under nominal conditions, followed by Page’s cumulative sum test for detecting tool wear on-line using the computer numerical control machine measurements. The most informative features are ranked using dynamic programming and its approximation variants from real-time measurements and machine settings, such as the width of cut, depth of cut, feed rate and spindle speed, that serve as inputs to the predictive models. The baseline nominal model is incrementally updated with experimental data via a gradient boosted adaptation model to generate the residuals that account for discrepancies between the actual machine data under normal conditions and the baseline nominal model predictions. The hybrid model is validated against 20 Mazak milling machine experimental tests and one Haas run-to-failure experiment. The proposed anomaly detector is applied to synthetic data from simulations of the physics-based model at different operating conditions, measurement noise levels, and tool wear levels, and the methods were able to achieve an overall 92% accuracy in data with 1% noise. The anomaly detection methods based on hybrid model reduced the false alarms of either the data-driven or physical-based models alone, and are found to be capable of good online detection of tool wear.

Online anomaly detection↗
NASA NTRS1988

Hierarchical representation and machine learning from faulty jet engine behavioral examples to detect real time abnormal conditions

The theoretical basis and operation of LEBEX, a machine-learning system for jet-engine performance monitoring, are described. The behavior of the engine is modeled in terms of four parameters (the rotational speeds of the high- and low-speed sections and the exhaust and combustion temperatures), and parameter variations indicating malfunction are transformed into structural representations involving instances and events. LEBEX extracts descriptors from a set of training data on normal and faulty engines, represents them hierarchically in a knowledge base, and uses them to diagnose and predict faults on a real-time basis. Diagrams of the system architecture and printouts of typical results are shown.

Gupta, U. K.↗
DOE OSTI2024

Remote Sensing Detection of Growing Season Freeze-Induced Defoliation of Montane Quaking Aspen (Populus tremuloides) in Southern Utah, USA

Growing season freeze events pose a threat to quaking aspen (Populus tremuloides Michx.), leading to canopy defoliation, reduced vigor, and increased mortality, especially for declining montane populations western North America. Detecting the spatial distribution and progression of this damage is challenging due to limited in situ observations in this region. This study represents the first attempt to comprehensively resolve the spatial extent of freeze-induced aspen canopy damage in southern Utah using multispectral remote sensing data. We developed an approach to detect the spatial and temporal dynamics of freeze-damaged aspen stands, focusing on a freeze event from 8–9 June 2020 in southern Utah. By integrating medium- (~250 to 500 m) and high-resolution (~10 m) satellite data, we employed the Normalized Difference Vegetation Index (NDVI) to compare post-freeze conditions with historical norms and pre-freeze conditions. Our analysis revealed NDVI reductions of 0.10 to 0.40 from pre-freeze values and a second flush recovery. We introduced a pixel-based method to evaluate freeze vulnerability, establishing a strong correlation (R values 0.78 to 0.82) between the onset of the first flush (NDVI > 0.50) and the accumulation of 100 growing degree days (GDD). These methods support the potential for retrospective assessments, proactive forest monitoring, and forecasting future risks.

54 ENVIRONMENTAL SCIENCES↗