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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 685 records · Page 38
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Automated Fire Detection for Industrial Settings with Pretrained Convolutional Networks

Early fire detection in industrial environments is critical to preventing equipment damage, personal injury, and operational disruptions. Traditional smoke detectors, while effective, often experience delays due to the time required for smoke to reach sensors, allowing fires to spread. Manual fire watch operations and human surveillance of camera feeds are resource-intensive and prone to human error. To address these challenges, this paper explores the application of convolutional neural networks for automated fire detection, specifically in industrial settings. By leveraging 11 different pre-trained machine vision models from TensorFlow and enhancing them with transfer learning on a custom-built industrial fire dataset, we optimized fire detection performance. Here, we analyzed each machine vision model architecture in terms of its depth, width, and input image resolution, considering both resource requirements and detection accuracy. We further explored the option of combining multiple models into an ensemble classifier to evaluate whether the performance improvements could justify the much greater computational complexity and other practical impacts. A cost-benefit analysis is presented to evaluate the trade-offs between performance and computational expense. Our findings identify that EfficientNetV2L, specifically tailored for industrial applications, provides the optimal balance between costs involved in training and using the model versus the overall fire detection performance. Additionally, we present a qualitative analysis of model performance using the technique of gradient-based class activation mapping to provide explainability by visualizing model decisions.

artificial intelligence↗
DOE OSTI2023

Autonomous and dynamic precursor selection for solid-state materials synthesis

Abstract Solid-state synthesis plays an important role in the development of new materials and technologies. While in situ characterization and ab-initio computations have advanced our understanding of materials synthesis, experiments targeting new compounds often still require many different precursors and conditions to be tested. Here we introduce an algorithm (ARROWS 3 ) designed to automate the selection of optimal precursors for solid-state materials synthesis. This algorithm actively learns from experimental outcomes to determine which precursors lead to unfavorable reactions that form highly stable intermediates, preventing the target material’s formation. Based on this information, ARROWS 3 proposes new experiments using precursors it predicts to avoid such intermediates, thereby retaining a larger thermodynamic driving force to form the target. We validate this approach on three experimental datasets, containing results from over 200 synthesis procedures. In comparison to black-box optimization, ARROWS 3 identifies effective precursor sets for each target while requiring substantially fewer experimental iterations. These findings highlight the importance of domain knowledge in optimization algorithms for materials synthesis, which are critical for the development of fully autonomous research platforms.

36 MATERIALS SCIENCE↗
NASA NTRS2021

Combined Cycle Engine Large-Scale Inlet for Mode Transition Studies: System Identification Rack Software Design

This report describes the development of the system identification (SysID) rack custom application code. This code is used to automate the system identification experimental processes for the National Aeronautics and Space Administration (NASA) Combined Cycle Engine Large-Scale Inlet for Mode Transition Experiments testbed. This series of experiments took place in the NASA Glenn Research Center (GRC) 10 foot by 10 foot (10x10) Supersonic Wind Tunnel (SWT) test facility. The SysID code was developed to apply command signals to testbed actuators, receive actuator feedback signals, and acquire sensor data which is used to identify the dynamics of the experimental processes. This code development and the process identification experiments were conducted during Phase-2 testing at various operating points. These points were predefined from data collected during the Phase-1 testbed characterization experiments. The developed SysID code was executed on a NASA designed and built real-time data acquisition (DAQ) and controls (SysID) rack. This report focuses on the development of the SysID rack real-time DAQ and control hardware and the custom application code used to automate the system identification process. The implementation of this reliable and efficient data acquisition and controls development tool is demonstrated by presenting an example of experimental data collected to be used for system identification.

R Thomas↗
NASA NTRS1983

Description of data base management systems activities

One of the major responsibilities of the JPL Computing and Information Services Office is to develop and maintain a JPL plan for providing computing services to the JPL management and administrative community that will lead to improved productivity. The CISO plan to accomplish this objective has been titled 'Management and Administrative Support Systems' (MASS). The MASS plan is based on the continued use of JPL's IBM 3032 Computer system for administrative computing and for the MASS functions. The current candidate administrative Data Base Management Systems required to support the MASS include ADABASE, Cullinane IDMS and TOTAL. Previous uses of administrative Data Base Systems have been applied to specific local functions rather than in a centralized manner with elements common to the many user groups. Limited capacity data base systems have been installed in microprocessor based office automation systems in a few Project and Management Offices using Ashton-Tate dBASE II. These experiences plus some other localized in house DBMS uses have provided an excellent background for developing user and system requirements for a single DBMS to support the MASS program.

Source record↗
NASA NTRS1987

High speed precision motion strategies for lightweight structures

Work during the recording period proceeded along the lines of the proposal, i.e., three aspects of high speed motion planning and control of flexible structures were explored: fine motion control, gross motion planning and control, and automation using light weight arms. In addition, modeling the large manipulator arm to be used in experiments and theory has lead to some contributions in that area. These aspects are reported below. Conference, workshop and journal submissions, and presentations related to this work were seven in number, and are listed. Copies of written papers and abstracts are included.

Book, Wayne J.↗
NASA NTRS1987

Technology - The basis for the past, the key to the future

The relationship between new technology and space missions, and the objectives of the Civil Space Technology Initiative (CSTI) are studied. The CSTI is concerned with technologies for safe and efficient access to space, earth-orbiting operations, and future science missions. The initiative focuses on research in the areas of propulsion, vehicles, information systems, large space structures and their control, power, and automation and robotics. Consideration is given to the development of high-performance engines for next-generation vehicles, booster technology for hybrid and pressure-fed propulsion systems, and a space OTV based on the aerobrake concept. Research involved with the application of automation and robotics to earth-orbiting operations are discussed. The control of flexible structure flight experiment, the use of nuclear systems for space propulsion, and the development of sensor devices and high-rate, high-capacity data systems are examined.

Harris, Leonard A.↗
NASA NTRS1991

A voyage to Mars: A challenge to collaboration between man and machines

A speech addressing the design of man machine systems for exploration of space beyond Earth orbit from the human factors perspective is presented. Concerns relative to the design of automated and intelligent systems for the NASA Space Exploration Initiative (SEI) missions are largely based on experiences with integrating humans and comparable systems in aviation. The history, present status, and future prospect, of human factors in machine design are discussed in relation to a manned voyage to Mars. Three different cases for design philosophy are presented. The use of simulation is discussed. Recommendations for required research are given.

Statler, Irving C.↗
NASA NTRS1995

On the uncertainty in single molecule fluorescent lifetime and energy emission measurements

Time-correlated single photon counting has recently been combined with mode-locked picosecond pulsed excitation to measure the fluorescent lifetimes and energy emissions of single molecules in a flow stream. Maximum likelihood (ML) and least square methods agree and are optimal when the number of detected photons is large however, in single molecule fluorescence experiments the number of detected photons can be less than 20, 67% of those can be noise and the detection time is restricted to 10 nanoseconds. Under the assumption that the photon signal and background noise are two independent inhomogeneous poisson processes, we derive the exact joint arrival time probably density of the photons collected in a single counting experiment performed in the presence of background noise. The model obviates the need to bin experimental data for analysis, and makes it possible to analyze formally the effect of background noise on the photon detection experiment using both ML or Bayesian methods. For both methods we derive the joint and marginal probability densities of the fluorescent lifetime and fluorescent emission. the ML and Bayesian methods are compared in an analysis of simulated single molecule fluorescence experiments of Rhodamine 110 using different combinations of expected background nose and expected fluorescence emission. While both the ML or Bayesian procedures perform well for analyzing fluorescence emissions, the Bayesian methods provide more realistic measures of uncertainty in the fluorescent lifetimes. The Bayesian methods would be especially useful for measuring uncertainty in fluorescent lifetime estimates in current single molecule flow stream experiments where the expected fluorescence emission is low. Both the ML and Bayesian algorithms can be automated for applications in molecular biology.

Brown, Emery N.↗
NASA NTRS1996

On the Uncertainty in Single Molecule Fluorescent Lifetime and Energy Emission Measurements

Time-correlated single photon counting has recently been combined with mode-locked picosecond pulsed excitation to measure the fluorescent lifetimes and energy emissions of single molecules in a flow stream. Maximum likelihood (ML) and least squares methods agree and are optimal when the number of detected photons is large, however, in single molecule fluorescence experiments the number of detected photons can be less than 20, 67 percent of those can be noise, and the detection time is restricted to 10 nanoseconds. Under the assumption that the photon signal and background noise are two independent inhomogeneous Poisson processes, we derive the exact joint arrival time probability density of the photons collected in a single counting experiment performed in the presence of background noise. The model obviates the need to bin experimental data for analysis, and makes it possible to analyze formally the effect of background noise on the photon detection experiment using both ML or Bayesian methods. For both methods we derive the joint and marginal probability densities of the fluorescent lifetime and fluorescent emission. The ML and Bayesian methods are compared in an analysis of simulated single molecule fluorescence experiments of Rhodamine 110 using different combinations of expected background noise and expected fluorescence emission. While both the ML or Bayesian procedures perform well for analyzing fluorescence emissions, the Bayesian methods provide more realistic measures of uncertainty in the fluorescent lifetimes. The Bayesian methods would be especially useful for measuring uncertainty in fluorescent lifetime estimates in current single molecule flow stream experiments where the expected fluorescence emission is low. Both the ML and Bayesian algorithms can be automated for applications in molecular biology.

Brown, Emery N.↗
NASA NTRS2002

Light Microscopy Module: On-Orbit Microscope Planned for the Fluids Integrated Rack on the International Space Station

The Light Microscopy Module (LMM) is planned as a remotely controllable, automated, on-orbit facility, allowing flexible scheduling and control of physical science and biological science experiments within the Fluids Integrated Rack (FIR) on the International Space Station. Initially four fluid physics experiments in the FIR will use the LMM the Constrained Vapor Bubble, the Physics of Hard Spheres Experiment-2, Physics of Colloids in Space-2, and Low Volume Fraction Entropically Driven Colloidal Assembly. The first experiment will investigate heat conductance in microgravity as a function of liquid volume and heat flow rate to determine, in detail, the transport process characteristics in a curved liquid film. The other three experiments will investigate various complementary aspects of the nucleation, growth, structure, and properties of colloidal crystals in microgravity and the effects of micromanipulation upon their properties.

Motil, Susan M.↗
NASA NTRSDate not supplied

Evaluation of a Traditional Regression Model Term Selection Process for Balance Calibration Data Sets

Key elements of a traditional regression model term selection process for the analysis of wind tunnel strain-gage balance calibration data are discussed. The traditional process is sometimes applied when regression models of the gage outputs are needed and an analyst does not have access to a term selection algorithm. In principle, the traditional process identifies supported regression model terms of a gage output by combining an analyst's subject- matter knowledge with a visual examination of selected plots of the calibration loads. Twelve empirical rules are listed that may be used to select regression model terms. Data from the manual calibration of a force balance is used to illustrate the application of the traditional term selection process. The data example shows that the traditional process can become very complex. Its successful application highly depends on an analyst's experience and skills. Therefore, it is suggested to replace the traditional term selection process with an automated term selection algorithm. Then, objective metrics are systematically applied during the term selection that make the identification of the regression model more repeatable and less dependent on an analyst's personal skills.

strain-gage balance↗
NASA NTRS2021

SoMo: Fast and Accurate Simulations of Continuum Robots in Complex Environments

Engineers and scientists often rely on their intuition and experience when designing soft robotic systems. The development of performant controllers and motion plans for these systems commonly requires time-consuming iterations on hardware. We present the SoMo (Soft Motion) toolkit, a software framework that makes it easy to instantiate and control typical continuum manipulators in an accurate physics simulator. SoMo introduces a standardized and human-readable description format for continuum manipulators. It leverages this description format and the Bullet physics engine to enable fast and accurate simulations of soft and soft-rigid hybrid robots in environments with complex contact interactions. This allows users to vary design and control parameters across simulations with minimal effort. We compare the capabilities of SoMo to other physics simulators and highlight the benefits and accuracy of SoMo by demonstrating the agreement between simulation and real-world experiments on several examples; these include an in-hand manipulation task with continuum fingers, an automated exploration of how to design soft fingers for precision grasping, and a brief snake locomotion study. Overall, SoMo provides an accessible way for designers of soft robotic hardware and control systems to gain access to a simulation-accelerated workflow.

Moritz A. Graule↗
DOE OSTI2024

Lightning and Radar Measures of Mixed-Phase Updraft Variability in Tracked Storms during the TRACER Field Campaign in Houston, Texas

Properties of 7488 thunderstorms are summarized for June–September 2022 during the Tracking Aerosol Convection Interactions Experiment (TRACER) field campaign Houston, Texas, using polarimetric weather radar and VHF 3D Lightning Mapping Array data. Automated tracking of storms linked each instrument’s measurements to a data-defined, time-evolving storm footprint. Within each storm, the depth and magnitude of episodic columns of radar differential reflectivity and specific differential phase quantified the prevalence of updrafts that activated mixed-phase precipitation pathways. Lightning measurements further distinguished the degree of rimed precipitation formation: the fraction of tracks with lightning varied from day to day and cells with lightning had stronger polarimetric columns. Track-level correlation of the lightning flash rate with radar polarimetric measures had substantial spread, showing that lightning provides an additional signal of mixed-phase precipitation processes that can complement future studies of thermodynamic and aerosol controls on cloud microphysics in the Houston region.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

AToM: Advanced Tokamak Modeling Environment

Stability constraints play an important role in integrated modeling. The global plasma stability and macro-instabilities such as internal kink modes, neoclassical tearing modes, and edge localized perturbations limit the plasma performance and can result in large-scale transient events and plasma disruptions. These macro-instabilities can be also beneficial to the plasma performance. For example, the peeling models often lead to the edge localized modes (ELMs). However, the formation of stationary edge harmonic oscillations (EHOs) due to nonlinear interaction of peeling modes can result in a transition to the Quiescent H-mode (QH-mode) without ELMs. The profiles predicted with transport models need to be refined using the MHD stability constraints. This is important especially for transient and nonlinear stages of discharges such as ramp-up access to hybrid and steady state operation, and L- to H-mode transition as well as transition to the QH-mode. Several stability and MHD codes are already included in the OMFIT framework. These codes include BALOO, ELITE, GATO, M3DC1, MARS, and NIMROD. However, the verifications of stability constraints are currently mostly excluded from transport modeling workflows. The only exception is the EPED module which includes the ELITE predictions to limit the pedestal height. Here, we improved the OMFIT workflow to include stability calculations. Including the stability conditions to the integrated modeling workflow improved the robustness of the predictive modeling discharges. Being implemented in the workflow, the stability conditions can be also used for the stability analysis of experimental data. This improved the physics understanding of various discharge scenarios and can be used in experiment planning.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
NASA NTRS2012

Gene Expression Measurement Module (GEMM) - A Fully Automated, Miniaturized Instrument for Measuring Gene Expression in Space

The capability to measure gene expression on board spacecraft opens the door to a large number of high-value experiments on the influence of the space environment on biological systems. For example, measurements of gene expression will help us to understand adaptation of terrestrial life to conditions beyond the planet of origin, identify deleterious effects of the space environment on a wide range of organisms from microbes to humans, develop effective countermeasures against these effects, and determine the metabolic bases of microbial pathogenicity and drug resistance. These and other applications hold significant potential for discoveries in space biology, biotechnology, and medicine. Supported by funding from the NASA Astrobiology Science and Technology Instrument Development Program, we are developing a fully automated, miniaturized, integrated fluidic system for small spacecraft capable of in-situ measurement of expression of several hundreds of microbial genes from multiple samples. The instrument will be capable of (1) lysing cell walls of bacteria sampled from cultures grown in space, (2) extracting and purifying RNA released from cells, (3) hybridizing the RNA on a microarray and (4) providing readout of the microarray signal, all in a single microfluidics cartridge. The device is suitable for deployment on nanosatellite platforms developed by NASA Ames' Small Spacecraft Division. To meet space and other technical constraints imposed by these platforms, a number of technical innovations are being implemented. The integration and end-to-end technological and biological validation of the instrument are carried out using as a model the photosynthetic bacterium Synechococcus elongatus, known for its remarkable metabolic diversity and resilience to adverse conditions. Each step in the measurement process-lysis, nucleic acid extraction, purification, and hybridization to an array-is assessed through comparison of the results obtained using the instrument with those from standard laboratory protocols. Once developed, the system can be used with minor modifications for multiple experiments on different platforms in space, including extension to higher organisms and microbial monitoring. A proposed version of GEMM that is capable of handling both microbial and tissue samples on the International Space Station will be briefly summarized.

Pohorille, Andrew↗
DOE OSTI2022

Electron energy loss spectroscopy database synthesis and automation of core-loss edge recognition by deep-learning neural networks

Abstract The ionization edges encoded in the electron energy loss spectroscopy (EELS) spectra enable advanced material analysis including composition analyses and elemental quantifications. The development of the parallel EELS instrument and fast, sensitive detectors have greatly improved the acquisition speed of EELS spectra. However, the traditional way of core-loss edge recognition is experience based and human labor dependent, which limits the processing speed. So far, the low signal–noise ratio and the low jump ratio of the core-loss edges on the raw EELS spectra have been challenging for the automation of edge recognition. In this work, a convolutional-bidirectional long short-term memory neural network (CNN-BiLSTM) is proposed to automate the detection and elemental identification of core-loss edges from raw spectra. An EELS spectral database is synthesized by using our forward model to assist in the training and validation of the neural network. To make the synthesized spectra resemble the real spectra, we collected a large library of experimentally acquired EELS core edges. In synthesize the training library, the edges are modeled by fitting the multi-Gaussian model to the real edges from experiments, and the noise and instrumental imperfectness are simulated and added. The well-trained CNN-BiLSTM network is tested against both the simulated spectra and real spectra collected from experiments. The high accuracy of the network, 94.9%, proves that, without complicated preprocessing of the raw spectra, the proposed CNN-BiLSTM network achieves the automation of core-loss edge recognition for EELS spectra with high accuracy.

36 MATERIALS SCIENCE↗
NASA NTRS1992

Space Station Freedom restructure impacts on technology experiment accommodation

This is a follow up to NASA Technical Memorandum (TM) 102766; it provides an overview of the Office of Aeronautics and Space Technology (OAST) Space Station Freedom (SSF) Technology Development Payload Program, reviews the OAST SSF resource requirements, and contrasts the requirements with the resources that are available to OAST since the restructure of SSF. A discussion of the issues as well as conclusions and recommendations, is provided. It is concluded that, even after adjustments to the OAST traffic model to reflect restructure, some resources will be inadequate even at the 20 percent allocation level. It is also concluded that bartering resources among U.S. users and international partners, and increasing the level of automation may be viable solutions to the resource constraint problem. The final conclusion is that, to facilitate the performance of technology experiments on SSF, OAST should fund SSF experiments and update its traffic model as soon as possible, and should provide technical and programmatic assistance to technology experiment developers.

Avery, Don E.↗