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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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DOE OSTI2023

Visual Brick model authoring tool for building metadata standardization

In this study, the Brick ontology is a unified semantic metadata standard for building assets and their relationships, serving as a key enabler for effective interoperability and automation of building systems and analytics. However, creating a Brick model, in other words, standard semantic metadata based on the Brick ontology for a building dataset, can be a complex task. This paper presents two case studies of the creation of Brick models for real-world residential and commercial building datasets, highlighting the challenges during the Brick model creation process. Additionally, the paper introduces VizBrick, an interactive authoring tool for creating semantic building metadata. VizBrick facilitates the creation of Brick models by providing an intuitive visual interface and interactive capabilities, such as keyword search, automatic mapping suggestions, and recommendations. The use of VizBrick is shown to significantly reduce the time and effort required during the Brick model creation process.

42 ENGINEERING↗

DOE OSTI2021

SILIA: software implementation of a multi-channel, multi-frequency lock-in amplifier for spectroscopy and imaging applications

In this work, we describe a software implementation of a multi-channel, multi-frequency Lock-in Amplifier (SILIA) to extract modulated signals from noisy data distributed over multiple channels of arbitrary number and size. This software implementation emulates the functionality of a multi-channel, multi-frequency lock-in amplifier in a post-processing step following data acquisition. Unlike most traditional lock-in amplifiers, SILIA can work with any number of input channels and is especially useful to analyze data distributed over many channels. We demonstrate the versatility and performance for extracting weak signals in spectroscopy and fluorescence microscopy. We also discuss more general applications and exhibit a method to automatically estimate error from a lock-in result.

47 OTHER INSTRUMENTATION↗

DOE OSTI2021

Ring artifact reduction via multiscale nonlocal collaborative filtering of spatially correlated noise

X-ray micro-tomography systems often suffer severe ring artifacts in reconstructed images. These artifacts are caused by defects in the detector, calibration errors, and fluctuations producing streak noise in the raw sinogram data. In this work, these streaks are modeled in the sinogram domain as additive stationary correlated noise upon logarithmic transformation. Based on this model, a streak removal procedure is proposed where the Block-Matching and 3-D (BM3D) filtering algorithm is applied across multiple scales, achieving state-of-the-art performance in both real and simulated data. Specifically, the proposed fully automatic procedure allows for attenuation of streak noise and the corresponding ring artifacts without creating major distortions common to other streak removal algorithms.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2021

AN AUTOMATED MACHINE LEARNING-GENETIC ALGORITHM FRAMEWORK WITH ACTIVE LEARNING FOR DESIGN OPTIMIZATION

The use of machine learning (ML)-based surrogate models is a promising technique to significantly accelerate simulation-driven design optimization of internal combustion (IC) engines, due to the high computational cost of running computational fluid dynamics (CFD) simulations. However, training the ML models requires hyperparameter selection, which is often done using trial-and-error and domain expertise. Another challenge is that the data required to train these models are often unknown a priori. In this work, we present an automated hyperparameter selection technique coupled with an active learning approach to address these challenges. The technique presented in this study involves the use of a Bayesian approach to optimize the hyperparameters of the base learners that make up a super learner model. In addition to performing hyperparameter optimization (HPO), an active learning approach is employed, where the process of data generation using simulations, ML training, and surrogate optimization is performed repeatedly to refine the solution in the vicinity of the predicted optimum. The proposed approach is applied to the optimization of a compression ignition engine with control parameters relating to fuel injection, in-cylinder flow, and thermodynamic conditions. It is demonstrated that by automatically selecting the best values of the hyperparameters, a 1.6% improvement in merit value is obtained, compared to an improvement of 1.0% with default hyperparameters. Overall, the framework introduced in this study reduces the need for technical expertise in training ML models for optimization while also reducing the number of simulations needed for performing surrogate-based design optimization.

Owoyele, Opeoluwa↗

NASA NTRS1971

Application of Remote Sensing Techniques for Appraising Changes in Wildlife Habitat

An attempt was made to investigate the potential of airborne, multispectral, line scanner data acquisition and computer-implemented automatic recognition techniques for providing useful information about waterfowl breeding habitat in North Dakota. The spectral characteristics of the components of a landscape containing waterfowl habitat can be detected with airborne scanners. By analyzing these spectral characteristics it is possible to identify and map the landscape components through analog and digital processing methods. At the present stage of development multispectral remote sensing techniques are not ready for operational application to surveys of migratory bird habitat and other such resources. Further developments are needed to: (1) increase accuracy; (2) decrease retrieval and processing time; and (3) reduce costs.

Nelson, H. K.↗

NASA NTRS1988

Definition Of Touch-Sensitive Zones For Graphical Displays

Touch zones defined simply by touching, while editing done automatically. Development of touch-screen interactive computing system, tedious task. Interactive Editor for Definition of Touch-Sensitive Zones computer program increases efficiency of human/machine communications by enabling user to define each zone interactively, minimizing redundancy in programming and eliminating need for manual computation of boundaries of touch areas. Information produced during editing process written to data file, to which access gained when needed by application program.

Monroe, Burt L., III↗

NASA NTRS1989

Computer simulation of the mathematical modeling involved in constitutive equation development: Via symbolic computations

Development of new material models for describing the high temperature constitutive behavior of real materials represents an important area of research in engineering disciplines. Derivation of mathematical expressions (constitutive equations) which describe this high temperature material behavior can be quite time consuming, involved and error prone; thus intelligent application of symbolic systems to facilitate this tedious process can be of significant benefit. A computerized procedure (SDICE) capable of efficiently deriving potential based constitutive models, in analytical form is presented. This package, running under MACSYMA, has the following features: partial differentiation, tensor computations, automatic grouping and labeling of common factors, expression substitution and simplification, back substitution of invariant and tensorial relations and a relational data base. Also limited aspects of invariant theory were incorporated into SDICE due to the utilization of potentials as a starting point and the desire for these potentials to be frame invariant (objective). Finally not only calculation of flow and/or evolutionary laws were accomplished but also the determination of history independent nonphysical coefficients in terms of physically measurable parameters, e.g., Young's modulus, was achieved. The uniqueness of SDICE resides in its ability to manipulate expressions in a general yet predefined order and simplify expressions so as to limit expression growth. Results are displayed when applicable utilizing index notation.

Arnold, S. M.↗

NASA NTRS1996

Automated clustering-based workload characterization

The demands placed on the mass storage systems at various federal agencies and national laboratories are continuously increasing in intensity. This forces system managers to constantly monitor the system, evaluate the demand placed on it, and tune it appropriately using either heuristics based on experience or analytic models. Performance models require an accurate workload characterization. This can be a laborious and time consuming process. It became evident from our experience that a tool is necessary to automate the workload characterization process. This paper presents the design and discusses the implementation of a tool for workload characterization of mass storage systems. The main features of the tool discussed here are: (1)Automatic support for peak-period determination. Histograms of system activity are generated and presented to the user for peak-period determination; (2) Automatic clustering analysis. The data collected from the mass storage system logs is clustered using clustering algorithms and tightness measures to limit the number of generated clusters; (3) Reporting of varied file statistics. The tool computes several statistics on file sizes such as average, standard deviation, minimum, maximum, frequency, as well as average transfer time. These statistics are given on a per cluster basis; (4) Portability. The tool can easily be used to characterize the workload in mass storage systems of different vendors. The user needs to specify through a simple log description language how the a specific log should be interpreted. The rest of this paper is organized as follows. Section two presents basic concepts in workload characterization as they apply to mass storage systems. Section three describes clustering algorithms and tightness measures. The following section presents the architecture of the tool. Section five presents some results of workload characterization using the tool.Finally, section six presents some concluding remarks.

Pentakalos, Odysseas I.↗

NASA NTRS2017

Model-Based Thermal System Design Optimization for the James Webb Space Telescope

Spacecraft thermal model validation is normally performed by comparing model predictions with thermal test data and reducing their discrepancies to meet the mission requirements. Based on thermal engineering expertise, the model input parameters are adjusted to tune the model output response to the test data. The end result is not guaranteed to be the best solution in terms of reduced discrepancy and the process requires months to complete. A model-based methodology was developed to perform the validation process in a fully automated fashion and provide mathematical bases to the search for the optimal parameter set that minimizes the discrepancies between model and data. The methodology was successfully applied to several thermal subsystems of the James Webb Space Telescope (JWST). Global or quasiglobal optimal solutions were found and the total execution time of the model validation process was reduced to about two weeks. The model sensitivities to the parameters, which are required to solve the optimization problem, can be calculated automatically before the test begins and provide a library for sensitivity studies. This methodology represents a crucial commodity when testing complex, large-scale systems under time and budget constraints. Here, results for the JWST Core thermal system will be presented in detail.

Cataldo, Giuseppe↗

NASA NTRS2024

Crew Health and Performance Integrated Data Architecture (CHP-IDA) TechPort May 2024

Future exploration missions to Mars will have increased need for crew autonomy. Crew Health & Performance (CHP) related data on the ISS is currently, manually downlinked and in disparate locations, which limits crew autonomy for future missions. The CHP-IDA project is developing a backend data system platform that grants the ability to seamlessly collect, store, process, and display CHP-related data for exploration missions. This platform allows for integration of data and advanced analytics that offer crew and ground teams better insight into the crew’s health and performance. It also enables applications that can improve the crew’s ability to provide more autonomous medical care during exploration missions. Data will be collected automatically to reduce crew and ground team time and effort and will synchronize across all in-mission vehicles, habitats, and ground as communication delay permits. The Human Research Program’s (HRP) Medical Data Architecture (MDA) project focused on this backend data architecture but for medical data only. The CHP-IDA project, a joint effort between HRP’s Exploration Medical Capability (ExMC) element and the Exploration Medical Integrated Product Team (XMIPT), expands this capability to all relevant CHP-related data. The additional inputs from nutrition, environment, exercise, radiation, and any other relevant sources will give more insight into crew’s health and performance. Currently, the Human Systems Engineering and Integration Division at Johnson Space Center (JSC) is designing the system. The team completed a system requirements review (SRR) in FY22 and now the focus is on core software development, testbed buildup, and use case scenario demonstration. An end-to-end demonstration with multiple data sources across CHP domains is schedule for the end of FY24 where all three focus areas will be displayed. Following this ground demo, the software will be completed, tested, and validated for flight.

Courtney M Schkurko↗

DOE OSTI2021

DISTRIBUTION TRANSFORMER ASSET MONITORING ON THE GRID EDGE USING SMART SENSOR DATA

As new loads such as rooftop photovoltaics, electric vehicles and other distributed energy resources become commonplace on the distribution grid, the stress on already aging assets begins to escalate. This increased loading and changing dynamics can exacerbate failure rates. While traditional monitoring efforts focus on transmission and generation assets, utilities are now beginning to pay close attention to distribution assets in order to increase reliability indices and reduce cost from unexpected outages. This research develops low-cost and scalable methods to monitoring the health of a critical distribution grid asset: the service transformer. Existing methods in literature are either invasive and thus difficult to implement or require the device to be tested offline in an expensive lab setting. Data from the ubiquitous smart meter as well as a novel Bluetooth based transformer monitor are leveraged to automatically notify the utility of deteriorating or damaged transformers. Voltage, temperature, and vibration are some of the signals measured and analyzed by the proposed algorithms to predict transformer failures. Furthermore, these algorithms are designed to keep the implementation and processing costs low by taking advantage of edge computing where possible.

24 POWER TRANSMISSION AND DISTRIBUTION↗

NASA NTRS2007

Video Guidance Sensor and Time-of-Flight Rangefinder

A proposed video guidance sensor (VGS) would be based mostly on the hardware and software of a prior Advanced VGS (AVGS), with some additions to enable it to function as a time-of-flight rangefinder (in contradistinction to a triangulation or image-processing rangefinder). It would typically be used at distances of the order of 2 or 3 kilometers, where a typical target would appear in a video image as a single blob, making it possible to extract the direction to the target (but not the orientation of the target or the distance to the target) from a video image of light reflected from the target. As described in several previous NASA Tech Briefs articles, an AVGS system is an optoelectronic system that provides guidance for automated docking of two vehicles. In the original application, the two vehicles are spacecraft, but the basic principles of design and operation of the system are applicable to aircraft, robots, objects maneuvered by cranes, or other objects that may be required to be aligned and brought together automatically or under remote control. In a prior AVGS system of the type upon which the now-proposed VGS is largely based, the tracked vehicle is equipped with one or more passive targets that reflect light from one or more continuous-wave laser diode(s) on the tracking vehicle, a video camera on the tracking vehicle acquires images of the targets in the reflected laser light, the video images are digitized, and the image data are processed to obtain the direction to the target. The design concept of the proposed VGS does not call for any memory or processor hardware beyond that already present in the prior AVGS, but does call for some additional hardware and some additional software. It also calls for assignment of some additional tasks to two subsystems that are parts of the prior VGS: a field-programmable gate array (FPGA) that generates timing and control signals, and a digital signal processor (DSP) that processes the digitized video images. The additional timing and control signals generated by the FPGA would cause the VGS to alternate between an imaging (direction-finding) mode and a time-of-flight (range-finding mode) and would govern operation in the range-finding mode.

Bryan, Thomas↗

DOE OSTI2015

Compression Algorithm Analysis of In-Situ (S)TEM Video: Towards Automatic Event Detection and Characterization

Precise analysis of both (S)TEM images and video are time and labor intensive processes. As an example, determining when crystal growth and shrinkage occurs during the dynamic process of Li dendrite deposition and stripping involves manually scanning through each frame in the video to extract a specific set of frames/images. For large numbers of images, this process can be very time consuming, so a fast and accurate automated method is desirable. Given this need, we developed software that uses analysis of video compression statistics for detecting and characterizing events in large data sets. This software works by converting the data into a series of images which it compresses into an MPEG-2 video using the open source “avconv” utility [1]. The software does not use the video itself, but rather analyzes the video statistics from the first pass of the video encoding that avconv records in the log file. This file contains statistics for each frame of the video including the frame quality, intra-texture and predicted texture bits, forward and backward motion vector resolution, among others. In all, avconv records 15 statistics for each frame. By combining different statistics, we have been able to detect events in various types of data. We have developed an interactive tool for exploring the data and the statistics that aids the analyst in selecting useful statistics for each analysis. Going forward, an algorithm for detecting and possibly describing events automatically can be written based on statistic(s) for each data type.

algorithm analysis↗

DOE OSTI2024

Bayesian stability and force modeling for uncertain machining processes

Accurately simulating machining operations requires knowledge of the cutting force model and system frequency response. However, this data is collected using specialized instruments in an ex-situ manner. Bayesian statistical methods instead learn the system parameters using cutting test data, but to date, these approaches have only considered milling stability. This paper presents a physics-based Bayesian framework which incorporates both spindle power and milling stability. Initial probabilistic descriptions of the system parameters are propagated through a set of physics functions to form probabilistic predictions about the milling process. The system parameters are then updated using automatically selected cutting tests to reduce parameter uncertainty and identify more productive cutting conditions, where spindle power measurements are used to learn the cutting force model. The framework is demonstrated through both numerical and experimental case studies. Results show that the approach accurately identifies both the system natural frequency and cutting force model.

42 ENGINEERING↗

DOE OSTI2016

Alert Triage v 0.1 beta

In the cyber security operations of a typical organization, data from multiple sources are monitored, and when certain conditions in the data are met, an alert is generated in an alert management system. Analysts inspect these alerts to decide if any deserve promotion to an event requiring further scrutiny. This triage process is manual, time-consuming, and detracts from the in-depth investigation of events. We have created a software system that uses supervised machine learning to automatically prioritize these alerts. In particular we utilize active learning to make efficient use of the pool of unlabeled alerts, thereby improving the performance of our ranking models over passive learning. We have demonstrated the effectiveness of our system on a large, real-world dataset of cyber security alerts.

Doak, JustinE.↗

NASA NTRS1987

Image processing system to analyze droplet distributions in sprays

An image processing system was developed which automatically analyzes the size distributions in fuel spray video images. Images are generated by using pulsed laser light to freeze droplet motion in the spray sample volume under study. This coherent illumination source produces images which contain droplet diffraction patterns representing the droplets degree of focus. The analysis is performed by extracting feature data describing droplet diffraction patterns in the images. This allows the system to select droplets from image anomalies and measure only those droplets considered in focus. Unique features of the system are the totally automated analysis and droplet feature measurement from the grayscale image. The feature extraction and image restoration algorithms used in the system are described. Preliminary performance data is also given for two experiments. One experiment gives a comparison between a synthesized distribution measured manually and automatically. The second experiment compares a real spray distribution measured using current methods against the automatic system.

Bertollini, Gary P.↗

NASA NTRS1989

Hubble Space Telescope Design Engineering Knowledgebase (HSTDEK)

The research covered here pays specific attention to the development of tools to assist knowledge engineers in acquiring knowledge and to assist other technical, engineering, and management personnel in automatically performing knowledge capture as part of their everyday work without adding any extra work to what they already do. Requirements for data products, the knowledge base, and methods for mapping knowledge in the documents onto the knowledge representations are discussed, as are some of the difficulties of capturing in the knowledge base the structure of the design process itself, along with a model of the system designed. The capture of knowledge describing the interactions of different components is also discussed briefly.

Johannes, James D.↗

NASA NTRS1995

Investigation of registration algorithms for the automatic tile processing system

The Robotic Tile Inspection System (RTPS), under development in NASA-KSC, is expected to automate the processes of post-flight re-water-proofing and the process of inspection of the Shuttle heat absorbing tiles. An important task of the robot vision sub-system is to register the 'real-world' coordinates with the coordinates of the robot model of the Shuttle tiles. The model coordinates relate to a tile data-base and pre-flight tile-images. In the registration process, current (post-flight) images are aligned with pre-flight images to detect the rotation and translation displacement required for the coordinate systems rectification. The research activities performed this summer included study and evaluation of the registration algorithm that is currently implemented by the RTPS, as well as, investigation of the utility of other registration algorithms. It has been found that the current algorithm is not robust enough. This algorithm has a success rate of less than 80% and is, therefore, not suitable for complying with the requirements of the RTPS. Modifications to the current algorithm has been developed and tested. These modifications can improve the performance of the registration algorithm in a significant way. However, this improvement is not sufficient to satisfy system requirements. A new algorithm for registration has been developed and tested. This algorithm presented very high degree of robustness with success rate of 96%.

Tamir, Dan E.↗