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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 541 records · Page 30
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

An Intelligent Adaptable Monitoring Package. Final Report

The “Intelligent Adaptable Monitoring Package” project was a four-year effort that demonstrated the feasibility of integrated sensing packages at tidal and wave energy sites. Such integration is generally required by the breadth of sensors required to understand environmental effects at marine energy sites and the operational difficulty of deploying, maintaining, and recovering such sensors. Over the course of the project, the Adaptable Monitoring Package (AMP) was deployed in multiple settings, each corresponding to a project budget period: - Budget Period 1: Demonstration of cabled deployment at Pacific Northwest National Laboratory’s Marine Science Laboratory. The deployment highlighted AMP hardware endurance over a 4-month deployment in a tidally-dominated environment and laid the groundwork for machine learning algorithms to detect and classify targets present in active sonar data. - Budget Period 2: Demonstration of an autonomous deployment at PacWave South off the coast of Newport, Oregon. The deployment highlighted the stability of AMP hardware and software, with the autonomous package collecting data on a duty cycle over a 1.5-month deployment. - Budget Period 3: Demonstration of an autonomous deployment powered by a wave energy converter at the U.S. Navy’s Wave Energy Test Site. The deployment highlighted the potential of wave energy to power ocean observatories and led to the development of machine learning algorithms to detect and classify targets in optical camera data. In aggregate, this project’s greatest success was demonstrating the AMP’s flexibility in a range of deployment scenarios. Each budget period represented a “first of a kind” demonstration of integrated instrumentation – cabled AMP, autonomous AMP, wave-energy powered AMP – and each deployment helped to identify and set goals for the next. Further, despite the exploratory nature of these deployments, each one achieved high system up-time and proved that flexible integration of multiple sensors in a single package represents a viable strategy for marine energy environmental monitoring. The key lessons learned from the project are: - Without continuous power, either from a shore cable or in situ source, many of the benefits of integration are lost (If continuous power is not available, the ability to detect rare events is lost, as is the ability to minimize the risk of behavioral changes through adaptive sensing. However, even on a duty cycle, there is still value in being able to acquire synchronous data from multiple sensors.); and - Observations from a moving platform present substantially greater data processing challenges than those from stationary platforms. Finally, these deployments also demonstrate an important truth: successful integration alone does not guarantee that relevant data are collected. To grow the knowledge base about environmental interactions with marine energy converters, integrated systems, like the AMP, need to include the right sensor mix and connect the data pipelines to effective processing algorithms. These deployments establish a strong foundation for future collaborations with the environmental research community: not only to understand the environmental effects of marine energy, but also to improve our general ability to study life in the sea.

16 TIDAL AND WAVE POWER↗
DOE OSTI2021

Machine Learning Guided Operational Intelligence from Synchrophasors (Final Report)

Schweitzer Engineering Laboratories (SEL) and Oregon State University (OSU) received over 27 terabytes of electrical power system phasor measurement unit (PMU) data for the Eastern, Western, and ERCOT interconnections. The dataset includes measurements spread across 446 PMUs from early 2016 to mid 2018 depending on the interconnect. The full dataset was split into a training and test (holdout) dataset by PNNL. All data was received in the Apache Parquet format. The overarching goal of this project is to develop and execute a strategy to mitigate data anomalies, perform analysis on the dataset, and detect anomalous events in the data.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2022

AOI.1 Application of Artificial Intelligence techniques enabling coal fired power plants the ability to achieve higher efficiency, improved availability, and increased reliability of their operations (Final Report)

During this effort, SparkCognition with support from the Electric Power Research Institute (EPRI) was tasked with applying artificial intelligence (AI) to improve the reliability, efficiency, and safety of operations at a coal-fired plant. By implementing AI techniques, like machine learning (ML), it is believed that operators can leverage existing data sources to gain more insights such as advanced warning of machine degradation. With enough lead time, a reliability engineer can take action to minimize, or even avoid, impact to production. To complete this work effort, SparkCognition developed and refined an ML-based model using sensor data for a Steam Turbine unit at a host site. The models were deployed in an online, web-based solution that allows users to visualize model outputs and supporting data. The final solution, based on SparkCognition’s proprietary software platform called SparkPredict®, was shared with EPRI who completed an online evaluation of results to determine the solution’s ability to detect actionable events.

20 FOSSIL-FUELED POWER PLANTS↗
DOE OSTI2022

Detection of Damage Inducing Impact Events in Vibration Test Fixtures Using Holder Exponents

The Shock and Vibration team within the Test Engineering group at Los Alamos National Laboratory (LANL) aids in the development and qualification of weapon systems for the United States Department of Energy (DOE). Performing tests that replicate shock and vibration environments representative of a weapon’s lifetime is critical in ensuring safety, survivability, and reliability. A key factor in shock and vibration testing is accurate representation of the weapon’s boundary conditions in its end use configuration. The boundary conditions representative of a reentry body in flight are particularly difficult to replicate on an electrodynamic shaker. When executing shock and vibration tests on a reentry body, two system axes are tested with the system in a cantilevered configuration. This cantilevered testing configuration results in a moment load being applied to the system while undergoing vibration environments. A special fixture, known as the Flex-Web, was developed to decouple this moment load from the reentry body in order to more accurately represent real world boundary conditions while replicating flight environments.

42 ENGINEERING↗
DOE OSTI2022

Data Fusion via Neural Network Entropy Minimization for Target Detection and Multi-Sensor Event Classification

Broadly applicable solutions to multimodal and multisensory fusion problems across domains remain a challenge because effective solutions often require substantive domain knowledge and engineering. The chief questions that arise for data fusion are in when to share information from different data sources, and how to accomplish the integration of information. The solutions explored in this work remain agnostic to input representation and terminal decision fusion approaches by sharing information through the learning objective as a compound objective function. The objective function this work uses assumes a one-to-one learning paradigm within a one-to-many domain which allows the assumption that consistency can be enforced across the one-to-many dimension. The domains and tasks we explore in this work include multi-sensor fusion for seismic event location and multimodal hyperspectral target discrimination. We find that our domain- informed consistency objectives are challenging to implement in stable and successful learning because of intersections between inherent data complexity and practical parameter optimization. While multimodal hyperspectral target discrimination was not enhanced across a range of different experiments by the fusion strategies put forward in this work, seismic event location benefited substantially, but only for label-limited scenarios.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2023

Low Energy LArTPC Signal Detection Using Anomaly Detection

Extracting low-energy signals from LArTPC detectors is useful, for example, for detecting supernova events or calibrating the energy scale with argon-39. However, it is difficult to efficiently extract the signals because of noise. We propose using a 1DCNN to select wire traces that have a signal. This efficiently suppresses the background while still being efficient for the signal. This is then followed by a 1D autoencoder to denoise the wire traces. At that point the signal waveform can be cleanly extracted. In order to make this processing efficient, we implement the two networks on an FPGA. In particular we use hls4ml to produce HLS from the Keras models for both the 1DCNN and the autoencoder. We deploy them on an AMD/Xilinx Alveo U55C using the Vitis software platform.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2024

Investigation of cosmic ray impact on transmon qubits with different materials through fast decay detection at Fermilab’s SQMS laboratory

Noise sources affecting superconducting qubits, such as cosmic rays and ambient gamma radiation, have garnered attention for their potential impact. These radiations deposit energy in the qubit's substrate, generating high-energy phonons that break Cooper pairs, leading to the formation of quasi-particles. When these quasi-particles tunnel across Josephson junctions, they induce qubit de-excitation, causing relaxation errors. In this study, we employ a fast feedback mechanism for performing qubit reset to detect decay events with high time resolution. This capability along with frequency multiplexed readout allows us to explore error correlations across time and space. Transmon qubits, manufactured within the Superconducting Quantum Materials and Systems (SQMS) center [1], are investigated at the above-ground lab. We study the impact of cosmic rays on qubits with different encapsulations, geometries, and locations on the same or different chips. We present preliminary findings and discuss the implications for the performance of contemporary quantum hardware.

Roy, Tanay↗
DOE OSTI2024

Deep Learning for Fish Identification from Sonar Data (CRADA 481 Final Report)

In eastern regions of the United States, the American eel is a species of management and regulatory concern because of significant population declines, despite the species’ previous abundance in all tributaries of rivers flowing into the Atlantic Ocean. The American eel is also a candidate for listing under the U.S. Endangered Species Act. While hydropower construction and operation are only one of several factors contributing to this population decline, such a listing could impose additional regulatory challenges for a large number of hydropower projects. In this CRADA project, we improved technologies for identifying migrating eels with the goal of reducing the cost and time required for future American eel hydropower impact assessment and mitigation studies, while maintaining accuracy. We built on results from a previous FOA project (FOA# DE-FOA-0001662), led by the Electric Power Research Institute (EPRI), which developed a highly accurate, deep-learning method for identifying migrating eels from imaging sonar data. The current study aimed to further optimize this deep-learning model, originally designed for image classification, and to develop an object detection software capable of identifying fish from sonar videos in real time, enabling the detection of events like fish migrations and specific species, such as the American eel, at hydropower dams. The data conversion algorithms were packaged as software with a graphical user interface, and the software is evaluated by external collaborators. We focused on the American eel in this project and explored the transferability of the developed deep learning models to the sea lamprey, given the similar body shape and swimming behavior between the two species.

13 HYDRO ENERGY↗
DOE OSTI2026

Teleseismic Network Association with GENIE

In this report we investigate adapting the Graph Neural Interpretation Engine (GENIE), an associator developed for three-component dense monitoring networks, to regional to teleseismic association using a sparse network of array stations. We expand GENIE’s input features to include first-P detection time, azimuth, and slowness estimates. Additionally, we include a probability of detection (PDET) term which measures a station’s likelihood of detecting an event. To assess each feature’s relative importance, we train four models, each using an increasing set of node features and find that the PDET models perform the best. We define two measures of event complexity which demonstrate that all GENIE model versions perform better than the standard backprojection stack.

47 OTHER INSTRUMENTATION↗
NASA NTRS1972

Design of a specialized computer for on-line monitoring of cardiac stroke volume

The design of a specialized analog computer for on-line determination of cardiac stroke volume by means of a modified version of the pressure pulse contour method is presented. The design consists of an analog circuit for computation and a timing circuit for detecting necessary events on the pressure waveform. Readouts of arterial pressures, systolic duration, heart rate, percent change in stroke volume, and percent change in cardiac output are provided for monitoring cardiac patients. Laboratory results showed that computational accuracy was within 3 percent, while animal experiments verified the operational capability of the computer. Patient safety considerations are also discussed.

Webb, J. A., Jr.↗
NASA NTRS1972

Modification to the MED and LED source-encoding circuitry for the IMP H and J spacecraft

The circuitry and fabrication changes made on the MED and LED electronics cards for the IMP H and J are reported. Except for the noted changes, the circuitry and module-matrix arrangement is essentially the same as the IMP-1 electronics cards described. In addition, analysis of the IMP-1 transmitted data indicated the desirability of incorporating additional coincident-event threshold detection levels to further discriminate between received particles.

Garrahan, N. M.↗
NASA NTRS1974

Observations at Mercury encounter by the plasma science experiment on Mariner 10

A fully developed bow shock and magnetosheath were observed near Mercury, providing unambiguous evidence for a strong interaction between Mercury and the solar wind. Inside the sheath there is a distinct region analogous to the magnetosphere or magnetotail of earth, populated by electrons with lower density and higher temperature than the electrons observed in the solar wind or magnetosheath. At the time of encounter, conditions were such that a perpendicular shock was observed on the inbound leg and a parallel shock was observed on the outbound leg of the trajectory, and energetic plasma electron events were detected upstream from the outbound shock crossing. The interaction is most likely not atmospheric, but the data clearly indicate that the obstacle to solar wind flow is magnetic, either intrinsic or induced.

Ogilvie, K. W.↗
NASA NTRS1975

Radiation protection and instrumentation

Radiation was found not to be an operational problem during the Apollo program. Doses received by the crewmen of Apollo missions 7 through 17 were small because no major solar-particle events occurred during those missions. One small event was detected by a radiation sensor outside the Apollo 12 spacecraft, but no increase in radiation dose to the crewmen inside the spacecraft was detected. Radiation protection for the Apollo program was focused on both the peculiarities of the natural space radiation environment and the increased prevalence of manmade radiation sources on the ground and onboard the spacecraft. Radiation-exposure risks to crewmen were assessed and balanced against mission gain to determine mission constraints. Operational radiation evaluation required specially designed radiation detection systems onboard the spacecraft in addition to the use of satellite data, solar observatory support, and other liaison. Control and management of radioactive sources and radiation-generating equipment was important in minimizing radiation exposure of ground-support personnel, researchers, and the Apollo flight and backup crewmen.

J. Vernon Bailey↗
NASA NTRS1977

Auroral kilometric radiation as an indicator of auroral magnetic disturbances

Satellite low-frequency radio measurements have shown that auroral kilometric radiation, an intense radio emission from the earth's auroral regions, is closely associated with auroral and magnetic disturbances. In this paper a detailed investigation of this relationship is presented, using the auroral electrojet (AE) index as an indicator of auroral magnetic disturbances and radio measurements from the Imp 6 spacecraft. This study indicates that the mean power flux of the 178-kHz radiation tends to be proportional to the 1.2 power of (AE) for AE more than 100 gamma and, with less certainty, to the square of (AE) for AE less than 100 gamma. The correlation coefficient between log AE and the logarithm of the power flux is 0.514. Occasionally, a kilometric radiation event is detected which is not detected by the ground magnetometer stations, even though an auroral substorm is in progress. This study shows that the remote detection of kilometric radio emissions from the earth can be used as a reasonably reliable indicator of auroral substorm activity.

Voots, G. R.↗
NASA NTRS1977

An ancient divergence among the bacteria

The 16S ribosomal RNZs from two species of met methanogenic bacteria, the mesophile Methanobacterium ruminantium and the thermophile Methanobacterium thermoautotrophicum, have been characterized in terms of the oligonucleotides produced by digestion with T1 ribonuclease. These two organisms are found to be sufficiently related that they can be considered members of the same genus or family. However, they bear only slight resemblance to 'typical' Procaryotic genera; such as Escherichia, Bacillus and Anacystis. The divergence of the methanogenic bacteria from other bacteria may be the most ancient phylogenetic event yet detected - antedating considerably the divergence of the blue green algal line for example, from the main bacterial line.

Balch, W. E.↗