Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “sensor performance”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 1,225 records · Page 68
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

TEAMER: Performance mapping of Re Vision's Persistance PTO

Contains datasets from experimental measurements that were used to validate Re Vision's Persistence PTO's efficiency and performance. These measurements were obtained using a dynamometer test bench setup. The data includes open-circuit voltage and loss measurements to validate machine characteristics, efficiency mapping tests to determine the generator's performance mapping, and efficiency mapping tests to determine the converter's efficiency over the feasible operating range. This data was collected between June 2023 and September 2023. The data was collected at the National Renewable Energy Laboratory's Flatirons Campus, Colorado, United States. The data was collected using NREL's 5-kW dynamometer test bench, equipped with a torque sensor and various voltage and current sensors fed to a dedicated data acquisition system. Units for the data are included in the data file headers for each data series. A text editor or spreadsheet software such as Excel is required to view the *.csv data. The data are also provided in *.mat files. To view data plots, a Matlab script with *.mat files are provided.

16 TIDAL AND WAVE POWER↗
DOE OSTI2022

Development of A Multi-Spectral Pyrometry Sensor for High-Speed Transient Surface-Temperature Measurements in Combustion-Relevant Harsh Environments

Accurate and high-speed transient surface-temperature measurements of combustion devices including internal combustion (IC) engines, gas turbines, etc., provide validation targets and boundary conditions for computational fluid dynamics models, and are broadly relevant to technology advancements such as performance improvement and emissions reduction. Development and demonstration of a multi-infrared-channel pyrometry-based optical instrument for high-speed surface-temperature measurement is described. The measurement principle is based on multi-spectral radiation thermometry (MRT) and uses surface thermal radiation at four discrete spectral regions and a corresponding emissivity model to obtain surface temperature via non-linear least squares (NLLS) optimization. Rules of thumb for specifying the spectral regions and considerations to avoid interference with common combustion products are developed; the impact of these along with linear and non-linear MRT analysis are assessed as a function of temperature and signal-to-noise ratio. A multi-start method to determine the MRT-solution global optimum is described and demonstrated. The resulting multi-channel transient pyrometry instrument is described along with practical considerations including optical-alignment drift, matching intra-channel transient response, and solution-confidence indicators. The instrument demonstrated excellent >97% accuracy and >99% 2-sigma precision over the 400–800 °C range, with ~20 µs (50 kHz, equivalent to 0.2 cad at 2000 RPM IC-engine operation) transient response in the bench validation.

47 OTHER INSTRUMENTATION↗
DOE OSTI2024

Trajectory Shaper: A Solution for Disrupted Cooperative Adaptive Cruise Control

Cooperative adaptive cruise control (CACC) can effectively reduce energy consumption, alleviate traffic congestion, and enhance safety. However, communication-related constraints and uncooperative vehicle users can disrupt CACC during real-world operations, significantly undermining the putative benefits of CACC. To alleviate the negative impacts of disrupted CACC, this study develops the trajectory shaper (TS) methods as backup solutions for two scenarios: (i) communication between vehicles is infeasible, and vehicles execute adaptive cruise control (ACC) using local sensor measurements; (ii) follower vehicles reject forming a cooperative platoon and execute their local distributed controllers using the information attained via communication. When communication is infeasible, a distributed TS is devised on each vehicle to modify the sensor measurements, enabling safe and efficient ACC operations. When communication is available but uncooperative agents are involved, the lead vehicle of the platoon executes a centralized TS to modify the information shared with uncooperative agents, achieving optimal platoon-level performance. The centralized and distributed TSs are implemented based on the model predictive control algorithms to yield optimal modifications on input information. Robustness is also factored to tackle model uncertainties during TS operations to ensure safety and efficiency. Numerical experiments validate the control performance of the proposed TSs.

Zhou, Anye [ORNL] (ORCID:0000000301455579)↗
DOE OSTI2023

Data-Driven Discovery of Linear Molecular Probes with Optimal Selective Affinity for PFAS in Water

Approaches to tackle the wide and growing variety of highly persistent per- and polyfluoroalkyl substances (PFAS) are of pressing global need because of their detrimental human health effects, such as cancer, birth defects, and hormone imbalance. Sensitive, selective, and easy-to-use real-time sensors to monitor and detect PFAS and sorbents to extract them are critical to meeting government-mandated environmental concentrations. In this work, we combine all-atom molecular dynamics simulations, enhanced sampling, deep representational learning, and Bayesian optimization to perform high-throughput virtual screening for highly sensitive and selective molecular probes. Our molecular design space consists of 3850 linear hydrocarbon chains with varying degrees of halogenation with and without amine- and phosphine-based headgroups. By employing a data-driven search process, we efficiently explore the molecular design space to optimize the sensitivity to perfluorooctanesulfonic acid (PFOS) as a prototypical PFAS analyte and selectivity relative to a sodium dodecyl sulfate (SDS) interferent. We calculate 504 Gibbs free energies of probe-analyte and probe-interferent interactions and identify probes with PFOS association free energies of up to (-ΔG PFOS ) = 9.8 ± 0.2 kJ/mol and selectivities relative to SDS of (-ΔΔG PFOS–SDS ) = 3.1 ± 1.5 kJ/mol. A C 11 Br 23 P(CH 3 ) 2 probe containing 11 backbone brominated carbons and a tertiary phosphine headgroup possesses the most sensitive binding constant to PFOS within the defined search space of K b PFOS = 177.4 ± 12.7, and a semibrominated probe C 5 H 11 C 7 Br 14 N(CH 3 ) 2 containing 12 backbone carbons and a tertiary amine headgroup possesses the highest selectivity relative to SDS of K b PFOS /K b SDS = 4.6 ± 1.7. A retrospective analysis of our data to extract interpretable design rules reveals that the sensitivity of linear hydrogenated probes increases by approximately 1 kJ/mol per C–C bond. The addition or removal of halogen atoms and amine or phosphine headgroups produces nonmonotonic changes in both sensitivity and selectivity with changes to the sensitivity of up to 2.5 kJ/mol. Finally, this work places empirical limitations on the performance of a wide range of linear probes for PFOS detection and offers a generic strategy for high-throughput computational screening to promote selective and sensitive binding.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Analyzing Data Privacy for Edge Systems

Internet-of-Things (IoT)-based streaming applications are all around us. Currently, we are transitioning from IoT processing being performed on the cloud to the edge. While moving to the edge provides significant networking efficiency benefits, IoT edge computing creates significant data privacy concerns. We propose a methodology that can successfully privacy protect the continual data streams generated by sensors on the edge device. We implement local differential privacy on streaming data and incorporate Bayesian inference and Gaussian process to evaluate the privacy policy. We demonstrate our methodology on a real-world smart meter testbed and identify the optimal privacy protection settings.

Kotevska, Olivera↗
DOE OSTI2023

Phase retrieval using Gaussian basis functions

A wavefront map of arbitrary aperture can be represented by a sum of Gaussian basis functions. Its performance is compared here to other representation methods such as orthonormal polynomials and Fourier modes. Gaussian basis functions can be applied to phase retrieval of high-frequency wavefront maps. Experiments show good agreement with direct measurements by a wavefront sensor. Finally, optimum measurement conditions are discussed based on the statistics of wavefront properties.

47 OTHER INSTRUMENTATION↗
DOE OSTI2022

Forward silicon vertex/tracking detector design and R$\&$D for the future Electron-Ion Collider

The proposed high-luminosity high-energy Electron-Ion Collider (EIC) will provide a clean environment to precisely study several fundamental questions in the fields of high-energy and nuclear physics . A low material budget and high granularity silicon vertex/tracking detector is critical to carry out a series of hadron and jet measurements at the future EIC especially for the heavy flavor product reconstruction or tagging. The conceptual design of a proposed forward silicon tracking detector with the pseudorapidity coverage from 1.2 to 3.5 has been developed in integration with different magnet options and the other EIC detector sub-systems. The tracking performance of this detector enables precise heavy flavor hadron and jet measurements in the hadron beam going direction. The detector R&D for the proposed silicon technology candidates: Low Gain Avalanche Diode (LGAD) and radiation hard depleted Monolithic Active Pixel Sensor (MALTA), which can provide good spatial and timing resolutions, is underway. Bench test results of the LGAD and MALTA prototype sensors will be discussed.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2021

Measurement report: Properties of aerosol and gases in the vertical profile during the LAPSE-RATE campaign

Abstract. Unmanned aerial systems (UASs) are increasingly being used as observation platforms for atmospheric applications. The Lower Atmospheric Process Studies at Elevation – a Remotely-piloted Aircraft Team Experiment (LAPSE-RATE) in Alamosa, Colorado, USA, on 14–20 July 2018 investigated and validated different UASs, measurement sensors and setup configurations. Flight teams from the Finnish Meteorological Institute (FMI) and Kansas State University (KSU) participated in LAPSE-RATE to measure and investigate properties of aerosol particles and gases in the lower atmosphere. During the experiment, the performance of different UAS configurations were investigated and confirmed to operate reliably, resulting in a scientifically sound observational dataset. As an example, concentration of aerosols – including two new particle formation events, CO2 and water vapor, and meteorological parameters in the atmospheric vertical profile were measured during the short experiment. Such observations characterizing atmospheric phenomena of this specific environment would have not been possible in any other way and, thus, demonstrate the power of UASs as new, promising tools in atmospheric and environmental research.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

A Flexible and Generic Functional Mock-up Unit Based Threat Injection Framework for Grid-interactive Efficient Buildings: A Case Study in Modelica

Grid-interactive efficient buildings (GEBs) have been considered as an important asset to support the power grid reliability by utilizing the demand flexibility offered by GEBs. GEBs are enabled by advances in sensors and controls, and the communication between building equipment, whole buildings, and the grid. The integration of different building technologies and network-based communication system makes GEBs vulnerable to passive threats such as equipment failure and active threats such as cyber-attacks. Modeling and simulation is an effective way to evaluate the impact of threats on the system performance. This paper proposes a generic and flexible threat injection framework for commonly-used building energy simulators such as EnergyPlus and Modelica to support threat modeling and evaluation. This framework leverages functional mock-up unit (FMU) to develop a general modeling interface for threat injection and simulation. A numerical case study using Modelica as a building energy simulator is conducted to demonstrate the capability of the framework for supporting single/multiple-order threat modeling and simulation of a GEB. Four threats and their combinations are injected on a Modelica-based threat-free building energy and control system, including operating supply fan at its full speed, remotely cycling the chiller on and off, blocking the chiller from receiving the chilled water supply temperature setpoints, and hijacking the global zone air temperature setpoint. Simulation results show that the cyber-attack that leads to short-term signal blocking has small effects on the system operation due to the "self-healing" feature of the heating, ventilation, and air-conditioning (HVAC) interactive control system. The threat that takes control of resetting the global zone air temperature setpoints has the most adverse impact on the system energy use, peak power demand, thermal comfort and the provision of demand flexibility. The combination of four threats have aggregative effects on the system but the effects are less than the additive effects of the individual threat.

Fu, Yanyang↗
DOE OSTI2023

Snapshot multispectral imaging using a diffractive optical network

Abstract Multispectral imaging has been used for numerous applications in e.g., environmental monitoring, aerospace, defense, and biomedicine. Here, we present a diffractive optical network-based multispectral imaging system trained using deep learning to create a virtual spectral filter array at the output image field-of-view. This diffractive multispectral imager performs spatially-coherent imaging over a large spectrum, and at the same time, routes a pre-determined set of spectral channels onto an array of pixels at the output plane, converting a monochrome focal-plane array or image sensor into a multispectral imaging device without any spectral filters or image recovery algorithms. Furthermore, the spectral responsivity of this diffractive multispectral imager is not sensitive to input polarization states. Through numerical simulations, we present different diffractive network designs that achieve snapshot multispectral imaging with 4, 9 and 16 unique spectral bands within the visible spectrum, based on passive spatially-structured diffractive surfaces, with a compact design that axially spans ~72 λ m , where λ m is the mean wavelength of the spectral band of interest. Moreover, we experimentally demonstrate a diffractive multispectral imager based on a 3D-printed diffractive network that creates at its output image plane a spatially repeating virtual spectral filter array with 2 × 2 = 4 unique bands at terahertz spectrum. Due to their compact form factor and computation-free, power-efficient and polarization-insensitive forward operation, diffractive multispectral imagers can be transformative for various imaging and sensing applications and be used at different parts of the electromagnetic spectrum where high-density and wide-area multispectral pixel arrays are not widely available.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Nematic transitions in iron pnictide superconductors imaged with a quantum gas

The Scanning Quantum Cryogenic Atom Microscope (SQCRAMscope) uses an atomic Bose–Einstein condensate to measure magnetic fields emanating from solid-state samples. The quantum sensor does so with unprecedented d.c. sensitivity at micrometre resolution, from room to cryogenic temperatures. An additional advantage of the SQCRAMscope is the preservation of optical access to the sample so that magnetometry imaging of, for example, electron transport may be performed in concert with other imaging techniques. Here, we apply this multimodal imaging capability to the study of nematicity in iron pnictide high-temperature superconductors, where the relationship between electronic and structural symmetry breaking resulting in a nematic phase is under debate. We combine the SQCRAMscope with an in situ microscope that measures optical birefringence near the surface. This enables simultaneous and spatially resolved detection of both bulk and near-surface manifestations of nematicity via transport and structural deformation channels, respectively. By performing local measurements of emergent resistivity anisotropy in iron pnictides, we observe sharp, nearly concurrent transport and structural transitions. More broadly, these measurements demonstrate the SQCRAMscope’s ability to reveal important insights into the physics of complex quantum materials.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2023

Fast neutron radiography-based on single-photon digital photosensor: concept and demonstration

For decades, fast neutron radiography performed using pulse-counting detectors employed PMTs coupled to plastic scintillator pixel arrays. SiPM-based systems are now sought to replace fragile PMTs, but conventional, “analog” SiPMs suffer from intrinsic limitations which limit their achievable performance. Among these limitations, a complete analog readout and digitizer chain is required, a counterintuitive approach when considering that the single-photon avalanche diode (SPAD), the basic unit cell of SiPMs, is a Boolean detector providing digital detection at the sensor level. This paper outlines a new concept for neutron radiography instrumentation by using photon-to-digital converters (PDCs, aka digital SiPMs), a fully digital solution to sense the scintillation light.

Pratte, Jean-Francois↗
DOE OSTI2020

Hylia: Time-Series Library for Network Operations (Hylia) v1

The ability to analyze time-series data in network operations is critical to ensure optimal operations and management in wide area networks, sensor networks, and cloud networks. Hylia is a collection of multiple time-series prediction algorithms designed specifically to work with network monitoring data sets such as SNMP, NETFLOW and other monitoring data. It is designed to recognize these features and perform the extrapolation of the data.

Kiran, Mariam↗
DOE OSTI2020

Tardigrade: Summary (LL20-AM-sensor)

Tardigrade is an effort to create small, passive remote sensor for material detection and identification. The microbolometer based sensor design uses custom bandpass filter bands combined with tuned thermal expansion materials in a ruggedized lens housing to provide passive mechanical correction for optical changes across a wide temperature range. This requires developing computational tools to model and predict thermal performance of meta-materials composed of multiple structured base materials and void-space, along with matching and developing 3D print technology to demonstrate the housing. Current efforts in the project are in 3 areas: material design algorithm development (transitioning into full 3D material design space), multi-material additive manufacturing process exploration, and sensor/optics design and engineering.

42 ENGINEERING↗
DOE OSTI2022

High-Resolution Floating Solar PV Data

This dataset contains over two years of 1-minute resolution data collected from four floating solar sites, as well as data from a land-based PV system co-located with one of the floating sites. The dataset includes highly granular module temperature measurements - five modules per floating site, with three sensors per module, totaling 15 module temperature sensors per floating site. In addition to the module temperature data, meteorological data collected at the floating sites is also included, along with traditional PV system-level parameters. The data is intended for analysis of solar energy production, efficiency, and performance degradation over time. For information about the data file usage see the "README" resource below. See "Metadata File" for information about individual files and other metadata information.

Array↗
DOE OSTI2024

The Influence of Microstructure on TCR for Inkjet-Printed Resistive Temperature Detectors Fabricated Using AgNO 3 /Ethylene-Glycol-Based Inks

This study investigated the influence of microstructure on the performance of Ag inkjet-printed, resistive temperature detectors (RTDs) fabricated using particle-free inks based on a silver nitrate (AgNO 3 ) precursor and ethylene glycol as the ink solvent. Specifically, the temperature coefficient of resistance (TCR) and sensitivity for sensors printed using inks that use monoethylene glycol (mono-EG), diethylene glycol (di-EG), and triethylene glycol (tri-EG) and subjected to a low-pressure argon (Ar) plasma after printing were investigated. Scanning electron microscopy (SEM) confirmed previous findings that microstructure is strongly influenced by the ink solvent, with mono-EG inks producing dense structures, while di- and tri-EG inks produce porous structures, with tri-EG inks yielding the most porous structures. RTD testing revealed that sensors printed using mono-EG ink exhibited the highest TCR (1.7 × 10 -3 /°C), followed by di-EG ink (8.2 × 10 -4 /°C) and tri-EG ink (7.2 × 10 -4 /°C). These findings indicate that porosity exhibits a strong negative influence on TCR. Sensitivity was not strongly influenced by microstructure but rather by the resistance of RTD. The highest sensitivity (0.84 Ω/°C) was observed for an RTD printed using mono-EG ink but not under plasma exposure conditions that yield the highest TCR.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Quantum-cascade-laser-absorption-spectroscopy diagnostic for temperature, pressure, and NO X 2 Π 1/2 at 500 kHz in shock-heated air at elevated pressures

The design, validation, and application of a quantum-cascade-laser-absorption-spectroscopy diagnostic for measuring gas temperature, pressure, and nitric oxide (NO) in high-temperature air are presented. A distributed-feedback quantum-cascade laser (QCL) centered near 1976 c m − <#comment/> 1 was used to scan across two transitions of NO in its ground electronic state ( X 2 Π <#comment/> 1 / 2 ). A measurement rate of 500 kHz was achieved using a single QCL by: (1) performing current modulation through a bias-tee, and (2) targeting closely spaced transitions with a large difference in lower-state energy. The diagnostic was validated in a mixture of 95% argon and 5% NO, which was shock-heated to ≈ <#comment/> 2000 to 3700 K. The average mean percent differences between laser-absorption-spectroscopy (LAS) measurements and predictions from shock-jump relations for temperature, pressure, and NO mole fraction were 3.1%, 4.1%, and 6.5%, respectively. The diagnostic was then applied to characterize shock-heated air at high temperatures (up to ≈ <#comment/> 5500 K ) and high pressures (up to 12 atm) behind either incident or reflected shocks. The LAS measurements were compared to theoretical predictions from shock-jump relations, pressure sensors mounted in the wall of the shock tube, and equilibrium values of the NO mole fraction. The average mean percent differences between LAS measurements and their aforementioned reference values were 3.2%, 10.8%, and 10.4% for temperature, pressure, and NO mole fraction, respectively. Last, a comparison between a measured NO mole fraction time history and a time-stepped homogeneous reactor simulation performed using two different chemical kinetics mechanisms is presented.

Gilvey, Jonathan J. (ORCID:0000000317664383)↗
DOE OSTI2025

Technical Assessment of the Application of Digital Twin and Prognostic Tools for Condition Monitoring

This report was prepared for the U.S. Nuclear Regulatory Commission (NRC) to present use cases of the application of advanced technologies toward meeting the current and future regulatory requirements for maintenance and condition monitoring of structures, systems, and components (SSCs). The advanced technologies considered in this work, collectively referred to as digital twin (DT) technologies, are advanced sensors and instrumentation, data analytics, machine learning and artificial intelligence (ML/AI), and physics-based models. The report presents two use cases of reactor coolant pumps (RCPs) and heat pipes in nuclear power plants (NPPs) with technical and regulatory considerations and opportunities in using advanced technologies for conditional monitoring. Key findings from the exploration of these considerations are as follows: - Uncertainties in sensor data and model predictions must be rigorously addressed through validation and verification processes - Regulatory compliance is paramount, necessitating data driven models to be developed in line with existing codes and standards, as well as considering potential future guidelines for advanced reactors - Explainability and transparency in ML/AI models are essential for developing operator trust and regulatory review, including methods that enhance the interpretability of complex data-driven predictions - Condition monitoring programs must be evaluated for their effectiveness in reducing maintenance-preventable function failures (MPFF) and aligning with plant performance criteria - The deployment of advanced technologies for condition monitoring could lead to a transition from periodic to continuous monitoring, thereby optimizing maintenance schedules - Collaborative efforts between industry stakeholders, regulatory bodies, and technology developers are crucial for the successful adoption of advanced technologies for condition monitoring systems in nuclear facilities In summary, the introduction of advanced technologies into condition monitoring programs represents a significant leap forward in the domain of NPP maintenance. By harnessing the capabilities of advanced sensors, data analytics, and ML/AI, NPP operators can transition from a time-based to a condition-based maintenance approach. This shift can potentially enhance the reliability and safety of critical plant components while optimizing maintenance efforts and minimizing unnecessary outages. The NRC is continuing to explore the regulatory aspects of advanced technologies as part of inservice inspection and inservice testing (ISI and IST) programs by pursuing additional research in this technical area.

22 - GENERAL STUDIES OF NUCLEAR REACTORS↗