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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 181 records · Page 10
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Optical device for in-line and real-time monitoring of microorganisms

A multi-wavelength laser diode based optical sensor system capable of monitoring the dynamics and physiological changes of a microorganism culture in real-time. The microorganism culture from a microorganism production chamber is pumped to a flow chamber. Laser diodes emit light at certain wavelengths through the flow chamber, which is sensed by photodiodes. A laser control circuitry is operatively connected to the laser diodes and a signal conditioning circuitry is operatively connected to the photodiodes. A microprocessor reads and records voltage signals corresponding to the wavelengths. A data acquisition system converts said voltage signals into measurements of biological parameters, which are displayed on a graphical user interface and allow a user to monitor the measurements in real time.

47 OTHER INSTRUMENTATION↗
DOE OSTI2022

Reflective long period grating

A reflection mode sensor system may include an optical fiber core and an optical fiber cladding. A first long period grating (LPG) may be positioned along the optical fiber core having a first grating period, a second LPG may be positioned along the optical fiber core having a second grating period, and a third LPG may be positioned along the optical fiber core having a third grating period. The grating periods may enable sensing of multiple parameters simultaneously. A metal coating may be applied to an end facet of the combined optical fiber core and optical fiber cladding. The metal coating may also cover a side surface of the optical fiber cladding along a length from the end facet. The metal coating may include a paste applied to the optical fiber core and the optical fiber cladding, where the paste has been cured, and includes a metal.

47 OTHER INSTRUMENTATION↗
DOE OSTI2023

Proton exchange membrane material and methods of making the same

Hydrocarbon proton exchange membranes are disclosed that are composed of a material including a hydrophobic main chain, and acidic side chains. The main chain includes a polyaryl structure that is substantially free of ether linkages and also includes a fluoromethyl substituted carbon. The acidic side chains include a hydrocarbon tether terminated by a strongly acidic group, such as a fluoroalkyl sulfonate group. Chemical stability of the material is increased by removing the ether linkages from the main chain. The hydrophobic main chain and substantially hydrophilic side chains create a phase-separated morphology that affords enhanced transport of protons and water across the membrane even at low relative humidity levels. These materials are advantageous as membranes for use in fuel cells, redox flow batteries, water hydrolysis systems, sensors, electrochemical hydrogen compressors, actuators, water purifiers, gas separators, etc.

Bae, Chulsung↗
DOE OSTI2023

Online monitoring using cloud-based applications.

Online monitoring using cloud-based applications presentation. Enabling online monitoring using cloud services will require additional sensors, systems and choices.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2025

Infrastructure-Based Cooperative Perception at a Traffic Intersection: Overview and Challenges

Traffic intersections are crucial and challenging nodes in transportation networks where multiple lanes of vehicles and pedestrians converge. About one-quarter of traffic fatalities and about one-half of all traffic injuries in the United States happen at traffic intersections . Effective management of these intersections is important to ensure safety and efficiency of all users - vehicles, pedestrians, cyclists, and vulnerable road users (VRUs). With advancements in sensor perception technologies such as radar, light detection and ranging (lidar), and cameras, traffic intersections are developing into dynamic and data-rich environments. By using these data to create a real-time digital twin, we can enable real-time data-driven decision making and a range of applications such as sharing perception information to connected vehicles (CVs) and connected autonomous vehicles (CAVs), safety affirmative signaling, and curb optimizing to improve efficiency and enhance safety.This paper presents an overview of the concept and examines the challenges involved in implementing an infrastructure-based cooperative perception engine at a traffic intersection. In addition to outlining the physical components, this study also addresses important challenges involved in a multi-sensor system. We present results from deploying the National Renewable Energy Laboratory's (NREL's) Infrastructure Perception and Control (IPC) mobile trailer at a traffic intersection in the city of Colorado Springs, Colorado, USA that employed multiple radars and lidars to capture the data. This study provides necessary practical learning for the Cooperative Driving Automation (CDA) and traffic engineering communities for next-generation infrastructure-based cooperative perception that promises improvements in signal control for optimized traffic flow, among other applications, and documents findings for ongoing research and development efforts in other areas.

ADVANCED PROPULSION SYSTEMS,MATHEMATICS AND COMPUT↗
DOE OSTI2024

Guided cold atom inertial sensors with membrane integrated photonics on atom trap integrated platforms

A guided cold-atom inertial sensor system comprises an atom trap integrated platform, a laser system, a magnetic field system, a control system, and a computing system. The laser system and magnetic field system are adapted to form a magneto-optical trap (MOT) about a suspended waveguide of the atom trap integrated platform made of membrane integrated photonics. After loading cold atoms from a MOT, the photonic atom trap integrated platform generates one-dimensional guided atoms with an evanescent field optical dipole trap (EF-ODT) along the optical waveguide to create guided atomic accelerometers/gyroscopes. Motion of atomic wavepackets in a superposition state is created along the guided atom geometry by way of state-dependent momentum kicks. The light-pulse sequence of guided atom interferometry splits, redirects, and recombines atomic wavepackets, which allows measurement of atom interference fringes sensitive to inertial forces via a probe laser.

Lee, Jongmin↗
DOE OSTI2021

(Poster) TRIPWIRE: Multi-modal Distributed Sensing For Repository Verification

Poster submission. This project is developing and demonstrating a multi-modal sensor system, TRIPWIRE, for containment verification in inaccessible radiological and nuclear waste repositories. The TRIPWIRE system will continuously monitor ionizing radiation, electromagnetic fields and vibration in the vicinity of emplaced nuclear materials buried in a repository, reporting on disturbances with a real-time alarm control station.

98 - NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL↗
DOE OSTI2023

Fact Sheet - Long-length Scintillating Fibers for Radiation Detection

As the world looks to underground geological repositories for storing nuclear waste, technologies to safeguard the material are needed. An example of a project that developed a new technology is Tripwire. Tripwire proposes a multi-sensor system approach for geological spent nuclear fuel repositories that relies of radiation, vibration, and electromagnetic detection. Tripwire was developed by the Applied Radiation Measurements and Systems (ARMS) group at INL and sponsored by the National Nuclear Security Administration (NNSA). The ARMS group performs research and development, testing and evaluation, operational support, and training focused on applied ionizing radiation detection and measurement. Application areas include nuclear engineering for advanced reactors and fuel cycle operations, nuclear nonproliferation, nuclear counterproliferation, nuclear forensics, and arms control and disarmament.

46 - INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AN↗
DOE OSTI2024

Techniques for incorporating sensors into apparatuses and systems

Methods of placing sensors in structures may involve placing first particles including a first material of the structure on or above a support surface. Second particles including a second, different material may be dispersed among the first particles at least within a transition region of the structure proximate to a location where a sensor is to be supported by the structure. A sensor may be placed in the location. The first particles of the first material may be fused to one another and to the second particles of the second material to form the structure with the sensor supported by the structure.

van Rooyen, Isabella J.↗
DOE OSTI2022

Sensing units including a radio-frequency sensor, and related systems, devices, and methods

Systems, devices, and methods related to generating and/or transmitting sensor measurement data are described. A device may include a first conductive pad positioned on a first surface of a substrate. The device may also include a second conductive pad positioned on a second, opposite surface of the substrate. Further, the device may include an inductive coil coupled between the first electrical pad and the second electrical pad. Also, the device may include a third conductive pad positioned on a third surface of the substrate and configured to couple to a sensor. The device may include a fourth conductive pad positioned on a fourth surface of the substrate and configured to couple to the sensor. The device may be configured to wirelessly transmit a signal.

Smith, James A.↗
DOE OSTI2021

Sensor impacts on building and HVAC controls: A critical review for building energy performance

Building operations rely heavily on control systems and sensors. This paper provides a sophisticated literature review on sensor systems in building/HVAC systems, particularly in the context of controls, and their impacts on energy efficiency and thermal comfort. This study aims to understand the previous and current research and identify future research opportunities on this subject. The reviewed sensor systems were used for heuristic rule-based controls, local controls, and advanced optimal controls for existing and emerging technologies. Five major aspects of sensors are reviewed here: control loops for sensors, sensor types, sensor locations, sensor data, and a sensor impact evaluation framework. To augment the literature review, comprehensive standardized interviews were also conducted with relevant industry experts and practitioners. These interviews were designed and performed to (1) identify significant factors for selecting sensor sets and current undergoing issues, (2) identify potential improvements in sensor configuration/deployment, and (3) integrate expert (e.g., researcher, building operation practitioner) knowledge and experiences to develop structured use-case scenarios. Researchers collected and analyzed 31 interview responses for this paper.

Building control↗
DOE OSTI2023

Development of a Multi Sensor Data Science System for Monitoring a Solvent Extraction Process

Idaho National Laboratory is designing and constructing a solvent extraction test bed, Beartooth, as part of a nuclear fuel cycle stewardship initiative. The test bed will provide facilities and equipment for testing novel extraction processes and give early career scientists opportunities to gain skills in performing separations chemistry. The test bed is being uniquely designed to enable machine learning capabilities for the characterization of chemical process operations. One of the intentions of incorporating machine learning methods is to provide process operators with enhanced situational awareness for the optimization of separations techniques and possible detection of a diversion event. As a result, the objective of this Laboratory Directed Research and Development project is to develop a multi-sensor data collections system and implement machine learning techniques on signals from an existing centrifugal contactor cascade to identify equipment usage and process events. This presentation will provide an overview of sensors used and experiments conducted to date.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2022

Multi-Sensor Data Acquisition System for Process Monitoring

Idaho National Laboratory is building a new nuclear fuel cycle test bed. This fuel cycle test bed named “Beartooth” will give researchers the opportunity to study the nuclear fuel cycle process. The process operations include the use of centrifugal contactors and process flow for the purification of special nuclear material recovery in used fuel. This new research facility has the need to use non-traditional measurement sensors to determine the state-of-health of the solvent extraction process. These non-traditional sensors can also enhance nuclear nonproliferation supervision and other activities. The non-traditional sensors include accelerometers, acoustic, current, flow, colorimetric, temperature, pH and conductivity. The challenge behind deploying all these sensors, is the need for fast and reliable data collection. The data acquisition system (DAQ) needs to be capable of recording up to 12 accelerometers and/or acoustic microphones simultaneously at rates up to 12.8 kSamples/second/channel. This requires the need for a strong architecture and data collection solution. This summary identifies the system architecture, DAQ, and sensors needed to support non-traditional measurements in a solvent extraction process.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2021

Landscape-scale characterization of Arctic tundra vegetation composition, structure, and function with a multi-sensor unoccupied aerial system

The Arctic is experiencing some of the most rapid climate change on Earth, with strong impacts on tundra ecosystems that are characterized by high land-surface and vegetation heterogeneity. Previous studies have explored this complexity using satellite remote sensing, however these typically coarse spatial resolution data have generally missed sub-pixel heterogeneity, leaving critical gaps in our understanding of tundra vegetation dynamics from the community to landscape scales. To address these gaps, we collected very high-resolution (1-5 cm) optical, structural, and thermal data at three low-Arctic tundra sites on the Seward Peninsula, Alaska, using a multi-sensor unoccupied aerial system (UAS). We examined the application of these data to studying tundra vegetation dynamics, by quantifying (1) canopy height and thermoregulation (leaf-air temperature) of representative plant functional types (PFTs), (2) fine-scale patterns of vegetation composition across landscapes, and (3) impacts of fine-scale vegetation composition on landscape-scale variation of canopy height and thermoregulation. Our results show that deciduous tall shrubs (those that can potentially grow >2 m) had a strong cooling effect, with canopy temperatures significantly lower than local air temperatures and other PFTs. Increased cover of tall shrubs also had the potential to reduce the cover of low-stature PFTs across the landscape, potentially associated with their closed canopy (i.e., increased light competition) and strong thermoregulation. To understand the connections between fine-scale vegetation composition and large-scale ecosystem processes, we produced a random forest model which showed that fine-scale PFT composition accounted for 86.8% and 74.2% of the landscape-scale variation in canopy height and thermoregulation, respectively. These findings highlight the importance of spatially detailed characterization of tundra PFTs to improve our ecological understanding and model representation of tundra vegetation, also transcend our study to show the need for continued collection of similar datasets to better understand the impacts of surface heterogeneity on the mapping and modeling of tundra ecosystem dynamics, as well as assist with conservation management and biodiversity monitoring strategies.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Comprehensive AI-based System for Control, Sensor Estimation, and Fault Detection of Cascaded Multilevel Inverters

In this paper, an Artificial Intelligence-based (AI) system is proposed for an 11-level cascaded H-bridge multilevel inverter (MLI) with the aims of harmonic suppression and reliability enhancement. The system consists of three seamlessly integrated Neural Networks (NNs). First, a multilayer perceptron is used to generalize the optimal switching angles for selective harmonic elimination under non-equal DC voltages. Next, an autoencoder NN estimates the voltage sensor readings to address potential drifting. Finally, a perceptron NN detects inverter faults based solely on the output voltage of the MLI. Simulation scenarios were evaluated, and the results show that the proposed system provides a comprehensive solution for the robust operation of the MLI. The proposed solution is capable of minimizing the targeted harmonics orders with minimal impact on the fundamental voltage, even when the voltage sensor drifts. Furthermore, the inverter under fault conditions was successfully identified.

Rezende da Costa Reis Kimpara, Renata↗
DOE OSTI2023

Presentation: Sensor Anomaly Detection for Nuclear Reactor Systems Utilizing Linear Regression and K-Means Unsupervised Machine Learning: An overview of methods and results

This presentation is a culmination of work which has occurred over the course of a 10-week internship. Anomaly detection methods must be both robust enough to detect subtle anomalies yet not so sensitive to report false positives, which would result significant loss of revenue. Methods currently being developed for autonomous systems are often pursuing a Digital Twin method, which will look at the entire system and model it as a whole. This presentation, however, focuses less on direct application to an NPP, rather acting as a proof of concept for the methods developed. For the project, we look to develop methods to analyze steady-state data and report anomalies.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2020

A Multi-Sensor Unoccupied Aerial System Improves Characterization of Vegetation Composition and Canopy Properties in the Arctic Tundra

Changes in vegetation distribution, structure, and function can modify the canopy properties of terrestrial ecosystems, with potential consequences for regional and global climate feedbacks. In the Arctic, climate is warming twice as fast as compared to the global average (known as ‘Arctic amplification’), likely having stronger impacts on arctic tundra vegetation. In order to quantify these changes and assess their impacts on ecosystem structure and function, methods are needed to accurately characterize the canopy properties of tundra vegetation types. However, commonly used ground-based measurements are limited in spatial and temporal coverage, and differentiating low-lying tundra plant species is challenging with coarse-resolution satellite remote sensing. The collection and processing of multi-sensor data from unoccupied aerial systems (UASs) has the potential to fill the gap between ground-based and satellite observations. To address the critical need for such data in the Arctic, we developed a cost-effective multi-sensor UAS (the ‘Osprey’) using off-the-shelf instrumentation. The Osprey simultaneously produces high-resolution optical, thermal, and structural images, as well as collecting point-based hyperspectral measurements, over vegetation canopies. In this paper, we describe the setup and deployment of the Osprey system in the Arctic to a tundra study site located in the Seward Peninsula, Alaska. We present a case study demonstrating the processing and application of Osprey data products for characterizing the key biophysical properties of tundra vegetation canopies. In this study, plant functional types (PFTs) representative of arctic tundra ecosystems were mapped with an overall accuracy of 87.4%. The Osprey image products identified significant differences in canopy-scale greenness, canopy height, and surface temperature among PFTs, with deciduous low to tall shrubs having the lowest canopy temperatures while non-vascular lichens had the warmest. The analysis of our hyperspectral data showed that variation in the fractional cover of deciduous low to tall shrubs was effectively characterized by Osprey reflectance measurements across the range of visible to near-infrared wavelengths. Therefore, the development and deployment of the Osprey UAS, as a state-of-the-art methodology, has the potential to be widely used for characterizing tundra vegetation composition and canopy properties to improve our understanding of ecosystem dynamics in the Arctic, and to address scale issues between ground-based and airborne/satellite observations.

54 ENVIRONMENTAL SCIENCES↗