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 181 records · Page 10
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Real-Time Ammonia and Humidity Monitoring with Ultra-Fast Conductometric Sensors Based on Porphyrin and Phthalocyanine Complexes

Organic semiconductors like porphyrins and phthalocyanines are attracting a wide range of researchers due to their versatile electrical properties and sensing performances in conductometric sensors. In this study, we investigate two types of π-extended porphyrins, which share the same macrocyclic structure but differ in their central metal. These porphyrins are employed as sublayers in bilayer heterojunction devices, with the lutetium bisphthalocyanine complex, LuPc 2 , serving as the common top layer. Remarkably, the central metal in the porphyrin macrocycle significantly influences the solubility of the materials and, consequently, the surface topography of the resulting bilayer heterojunction devices. This structural variation translates into distinct electrical and sensing performances. The device incorporating nickel as metal centre (AM2) demonstrates superior sensitivity towards NH3, with a relative response (RR) of ca. -7% at 90 ppm, an ultra-fast response time of about 9 s, and an impressive limit of detection (LOD) of 250 ppb, whereas, the device that has zinc as metal centre in sublayer (AM3) exhibits RR value of ca. -0.9% at 90 ppm with t 90 of ca. 120 s and LOD of 2 ppm. Both devices are evaluated under randomly varying NH 3 concentration and RH value. The results shows that the AM2-based sensor allows following NH 3 in real-time, while the AM3-based sensor delivers an average concentration over time. On the other hand, the AM2-based sensor exhibits slow kinetics under RH exposure, while the AM3-based sensor precisely mirrors the pattern of random RH changes generated by the software, demonstrating its exceptional responsiveness and accuracy in tracking humidity fluctuations. In conclusion, these findings underscore the critical role of the metal centre in tuning the electrical and sensing properties of the heterojunction devices.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2021

Fabrication of Six Degrees-of-Freedom Hexflex Positioner With Integrated Strain Sensing Using Nonlithographically Based Microfabrication

In this study, a process flow is described for the low cost, flexible fabrication of metal micro-electromechanical systems (MEMS) with high performance integrated sensing. The process is capable of producing new designs in ≈1 week at an average unit cost of <$1 k/device even at batch sizes of ≈1–10, with expected sensing performance limits of about 135 dB over a 10 kHz sensor bandwidth. This is a ≈20× reduction in cost, ≈25× reduction in time, and potentially >30× increase in sensing dynamic range over comparable state-of-the-art compliant nanopositioners. The nonlithographically based microfabrication (NLBM) process is uniquely suited to create high performance nanopositioning architectures which are customizable to the positioning requirements of a range of nanoscale applications. These can significantly reduce the cost of nanomanufacturing research and development, as well as accelerate the development of new processes and the testing of fabrication process chains without excess capital investment. A six degrees-of-freedom (6DOF) flexural nanopositioner with integrated sensing for all 6DOF was fabricated using the newly developed process chain. The fabrication process was measured to have ≈30 μ m alignment. Sensor arm, flexure, and trace widths of 150 μ m, 150 μ m, and 800 μ m, respectively, were demonstrated. Process capabilities suggest lower bounds of 25 μ m, 50 μ m, and 100 μ m, respectively. Dynamic range sensing of 52 dB was demonstrated for the nanopositioner over a 10 kHz sensor bandwidth. Improvements are proposed to approach sensor performance of about 135 dB over a 10 kHz sensor bandwidth.

42 ENGINEERING↗
DOE OSTI2024

Initial PIP-II Beam Current Monitor Fault Case Analyses & Beam Position Monitor Linearity Studies in CST Studio Suite

The use of non-invasive sensors & systems to measure particle beam characteristics is a crucial part of modern accelerator control systems due to their ability to return real time beam data while minimizing negative effects on beam quality. To ensure that one can be reasonably confident these sensors will behave as desired upon be-ing implemented within the beamline, simulations pre-dicting the performance of these sensors under beamline conditions can be used as a valuable tool for checking sensor functionality without a physical test bench. This paper details the design, testing, and results of two sensor models developed using CST Studio Suite soft-ware designed to mimic two sensors to be implemented within the PIP-III beamline: an elliptical, large-aperture beam position monitor (BPM) for which vertical & hori-zontal position signal linearity was analyzed, and an AC current transformer (ACCT) beam current monitor (BCM) used to search for potential fault cases within the BCM and beam pipe flange gaps. Special focus is given to the discovery of linearity variations within the BPM and the use of frequency domain techniques in the BCM fault case analyses.

Rouzky, A. R.↗
DOE OSTI2021

Testing of Instrumentation and Control Sensors and Cables for Small Modular Reactors

As advanced reactor concepts like small modular reactors (SMRs) progress towards design maturity and commercial deployment, it is important to assess their instrumentation and control (I&C) system sensors and cables to assure their safe, reliable, and efficient operation throughout their service lifetimes. The I&C system of any nuclear power plant (NPP) is the central nervous system of the plant and is made up of field devices such as sensors which are connected via cables to analog and/or digital systems. These systems are responsible for control and/or protection of the plant. The performance of I&C sensors and cables is dependent on several factors, including plant operating conditions. In particular, the plant operation can affect the static (accuracy) and dynamic (response) performance of the sensor, whereas the surrounding ambient environment can impact the remaining useful life of the cables, connectors, and other associated components within I&C sensor circuits.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2022

Process prediction and detection of faults using probabilistic bidirectional recurrent neural networks on real plant data

Attaining Industry 4.0 for manufacturing operations requires advanced monitoring systems and real-time data analytics of plant data, among other topics. We propose a Probabilistic Bidirectional Recurrent Network (PBRN) for industrial process monitoring for the early detection of faults. The model is based on a Gated Recurrent Unit (GRU) neural network that allows the model to retain long-term dependencies between sensor data along a time horizon, hence learning the dynamic behavior of the process. To reduce the false-positive detection rate of the model, we compel the model to learn from a highly noisy sensor reading while outputting noise-free sensor outputs. The performance of the proposed model is compared to other data-driven statistical process monitoring schemes using real plant data from an industrial Air Separations Unit (ASU) containing noisy sensor readings. We show that the model can learn from noisy data without reducing its performance. Using two different fault cases, we demonstrate the model’s ability to carry out early fault detection with average false-positive rates of 2.9% and 4.9% for both fault cases. The missed detection rates are 0.1% and 0.2%, respectively.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2022

A digital twin approach to system-level fault detection and diagnosis for improved equipment health monitoring

Automating the task of fault detection and diagnosis is crucial in the effort to reduce the operation and maintenance cost in the nuclear industry. This paper describes a physics-based approach for system-level diagnosis in thermal-hydraulic systems in nuclear power plants. The inclusion of physics information allows for the creation of virtual sensors, which provide improved fault diagnosis capability. The physics information also serves to better constrain diagnostic solutions to the physical domain. As a demonstration, various test cases for fault diagnosis in a high-pressure feedwater system were considered. The use of virtual sensors allows constructing performance models for two first-point feedwater heaters which would not have been possible otherwise due to the limited sensor set. Real-time plant data provided by a utility partner were used to assess the diagnostic approach. The detection of an abnormal event immediate after a plant startup pointed to faulty behaviors in the two first-point feedwater heaters. Further, this double-blind fault diagnosis was subsequently confirmed by the plant operator. In addition, several simulated sensor fault events demonstrated the capability of our algorithms in detecting and discriminating sensor faults.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2025

Acoustic Observations of the OSIRIS-REx Sample Return Capsule Re-Entry from Wendover Airport

The Origins, Spectral Interpretation, Resource Identification, and Security‐Regolith Explorer sample return capsule (SRC) re‐entered the Earth’s atmosphere at hypersonic speeds from interplanetary space on 24 September 2023. The current work reports on 18 ground‐based acoustic sensors deployed at Wendover Airport, the same location that the Genesis and Stardust SRC re‐entries were recorded. Four different sensors (Chaparral Physics, Gem, Wilson Engineering Research and Development [WERD], and RedVox) were deployed in close proximity to compare their performance. All the sensors captured an N‐wave signal associated with the SRC re‐entry shock wave followed by a broadband coda. The Chaparral Physics array served as the high‐fidelity reference measurement. The N‐wave signal had a peak‐to‐peak amplitude of 4.07 Pa with a fundamental frequency of 4.98 Hz from 167.5° measured clockwise from north, nearly perpendicular to the SRC trajectory. In addition, high coherence in the coda was shown to be associated reflections from the surrounding mountains. In general, the more economical sensors (Gem, WERD, and RedVox) produced results that were consistent with these observations and sensor specifications. Beamforming with these single sensors arranged as an array showed agreement with the high‐fidelity array to within a couple of degrees. Furthermore, the current high‐fidelity results were compared with the measurements during the Genesis and Stardust SRC re‐entries. All three entries produced a broadband fundamental peak at a frequency that was inversely related to the SRC diameter as well as evidence of reflections from the surrounding topography.

KC, Real J. [Oklahoma State University, Stillwater↗
DOE OSTI2022

Multiplexed Readout for an Experiment with a Large Number of Channels Using Single-Electron Sensitivity Skipper-CCDs

This paper presents the implementation of a multiplexed analog readout electronics system that can achieve single-electron counting using Skipper-CCDs with non-destructive readout. The proposed system allows the best performance of the sensors to be maintained, with sub-electron noise-level operation, while maintaining low-bandwidth data transfer, a minimum number of analog-to-digital converters (ADC) and low disk storage requirement with zero added multiplexing time, even for the simultaneous operation of thousands of channels. These features are possible with a combination of analog charge pile-up, sample and hold circuits and analog multiplexing. The implementation also aims to use the minimum number of components in circuits to keep compatibility with high-channel-density experiments using Skipper-CCDs for low-threshold particle detection applications. Performance details and experimental results using a sensor with 16 output stages are presented along with a review of the circuit design considerations.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2021

Performance Evaluation of Comparative Vacuum Monitoring and Piezoelectric Sensors for Structural Health Monitoring of Rotorcraft Components

The costs associated with the increasing maintenance and surveillance needs of aging structures are rising at an unexpected rate. Multi-site fatigue damage, hidden cracks in hard-to-reach locations, disbonded joints, erosion, impact, and corrosion are among the major flaws encountered in today’s extensive fleet of aging aircraft and space vehicles. Aircraft maintenance and repairs represent about a quarter of a commercial fleet’s operating costs. The application of Structural Health Monitoring (SHM) systems using distributed sensor networks can reduce these costs by facilitating rapid and global assessments of structural integrity. The use of in-situ sensors for real-time health monitoring can overcome inspection impediments stemming from accessibility limitations, complex geometries, and the location and depth of hidden damage. Reliable, structural health monitoring systems can automatically process data, assess structural condition, and signal the need for human intervention. The ease of monitoring an entire on-board network of distributed sensors means that structural health assessments can occur more often, allowing operators to be even more vigilant with respect to flaw onset. SHM systems also allow for condition-based maintenance practices to be substituted for the current time-based or cycle-based maintenance approach thus optimizing maintenance labor. The Federal Aviation Administration has conducted a series of SHM validation and certification programs intended to comprehensively support the evolution and adoption of SHM practices into routine aircraft maintenance practices. This report presents one of those programs involving a Sandia Labs-aviation industry effort to move SHM into routine use for aircraft maintenance. The Airworthiness Assurance NDI Validation Center (AANC) at Sandia Labs, in conjunction with Sikorsky, Structural Monitoring Systems Ltd., Anodyne Electronics Manufacturing Corp., Acellent Technologies Inc., and the Federal Aviation Administration (FAA) carried out a trial validation and certification program to evaluate Comparative Vacuum Monitoring (CVM) and Piezoelectric Transducers (PZT) as a structural health monitoring solution to specific rotorcraft applications. Validation tasks were designed to address the SHM equipment, the health monitoring task, the resolution required, the sensor interrogation procedures, the conditions under which the monitoring will occur, the potential inspector population, adoption of CVM and PZT systems into rotorcraft maintenance programs and the document revisions necessary to allow for their routine use as an alternate means of performing periodic structural inspections. This program addressed formal SHM technology validation and certification issues so that the full spectrum of concerns, including design, deployment, performance and certification were appropriately considered. Sandia Labs designed, implemented, and analyzed the results from a focused and statistically relevant experimental effort to quantify the reliability of a CVM system applied to Sikorsky S-92 fuselage frame application and a PZT system applied to an S-92 main gearbox mount beam application. The applications included both local and global damage detection assessments. All factors that affect SHM sensitivity were included in this program: flaw size, shape, orientation and location relative to the sensors, as well as operational and environmental variables. Statistical methods were applied to performance data to derive Probability of Detection (POD) values for SHM sensors in a manner that agrees with current nondestructive inspection (NDI) validation requirements and is acceptable to both the aviation industry and regulatory bodies. The validation work completed in this program demonstrated the ability of both CVM and PZT SHM systems to detect cracks in rotorcraft components. It proved the ability to use final system response parameters to provide a Green Light/Red Light (“GO” – “NO GO”) decision on the presence of damage. In additional to quantifying the performance of each SHM system for the trial applications on the S-92 platform, this study also identified specific methods that can be used to optimize damage detection, guidance on deployment scenarios that can affect performance and considerations that must be made to properly apply CVM and PZT sensors. These results support the main goal of safely integrating SHM sensors into rotorcraft maintenance programs. Additional benefits from deploying rotorcraft Health and Usage Monitoring Systems (HUMS) may be realized when structural assessment data, collected by an SHM system, is also used to detect structural damage to compliment the operational environment monitoring. The use of in-situ sensors for health monitoring of rotorcraft structures can be a viable option for both flaw detection and maintenance planning activities. This formal SHM validation will allow aircraft manufacturers and airlines to confidently make informed decisions about the proper utilization of CVM and PZT technology. It will also streamline future regulatory actions and formal certification measures needed to assure the safe application of SHM solutions.

42 ENGINEERING↗
DOE OSTI2021

High-Fluence Active Irradiation and Combined Effects Testing of Sapphire Optical Fiber Distributed Temperature Sensors - ASI Project Summary

The goal of this work is to investigate the performance of sapphire optical fiber temperature sensors and develop clad sapphire optical fibers for in-pile instrumentation. This work tests the distributed sensing performance of sapphire sensors by using optical backscatter reflectometry methods under combined radiation/temperature effects and high fluence. A series of irradiations will be completed to evaluate the effect of irradiation on sapphire optical fiber temperature sensors and to determine an operational limit for the sensors.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2025

Dielectric Engineering of ZnO@ZIF‐8 for High‐Performance Triboelectric Nanogenerators and Self‐Powered Humidity Sensors

Porous metal oxide–metal-organic framework (MO x @MOF) hybrids offer synergistic effects that enhance surface charge density, electronic structure, and textural properties, making them ideal for self-powered sensing applications. Here, uniform, and pinhole-free ternary porous ZnO–PTFE@ZIF-8 hybrid films are developed on room-temperature co-sputtered ZnO–polytetrafluoroethylene (PTFE) composite films, where ZnO serves as a self-sacrificial precursor to precisely regulate ZIF-8 (Zn-MeIm 2 ) growth through solvothermal methods. The resulting TENG achieves a high output power density of 0.67 mW cm −2 , attributed to the synergistic effects of fluorine-rich PTFE and methyl-functionalized ZIF-8, which enhance surface charge density and dielectric response. By tuning PTFE content in the ZnO–PTFE composite, the dielectric constant and triboelectric output is optimized. The ZP60@ZIF-8-based device also demonstrates excellent humidity sensing performance, with a wide detection range (20–99% RH) and ultrahigh sensitivity (R V % of 19 900%, R I % of 19 325% at 99% RH). These results position ZP@ZIF-8-based TENGs as promising platforms for next-generation self-powered sensors and smart wearable electronics.

42 ENGINEERING↗
DOE OSTI2024

Tailoring the d-band center on Ru 1 Cu single-atom alloy nanotubes for boosting electrochemical non-enzymatic glucose sensing

The development of cost-effective and highly efficient electrocatalysts is critical to help electrochemical non-enzymatic sensors achieve high performance. Here, in this work, a new class of catalyst, Ru single atoms confined on Cu nanotubes as a single-atom alloy (Ru 1 Cu NTs), with a unique electronic structure and property, was developed to construct a novel electrochemical non-enzymatic glucose sensor for the first time. The Ru 1 Cu NTs with a diameter of about 24.0 nm showed a much lower oxidation potential (0.38 V) and 9.0-fold higher response (66.5 μA) current than Cu nanowires (Cu NWs, oxidation potential 0.47 V and current 7.4 μA) for glucose electrocatalysis. Moreover, as an electrochemical non-enzymatic glucose sensor, Ru1Cu NTs not only exhibited twofold higher sensitivity (54.9 μA mM −1 cm −2 ) and wider linear range (0.5–8 mM) than Cu NWs, but also showed a low detection limit (5.0 μM), excellent selectivity, and great stability. According to theoretical calculation results, the outstanding catalytic and sensing performance of Ru 1 Cu NTs could be ascribed to the upshift of the d-band center that helped promote glucose adsorption. This work presents a new avenue for developing highly active catalysts for electrochemical non-enzymatic sensors.

electrochemistry↗
DOE OSTI2023

Materials for Gamma Radiation Sensors

Sensors used for spectroscopic measurements of gamma radiation are most often scintillator or semiconductor materials. An overview is provided in this chapter on the materials and development techniques used in producing spectroscopic gamma radiation sensors. Challenges that prevent a perfect sensor are discussed along with the reasons why some sensor materials are ubiquitous despite their performance limitations. The types of sensors commonly used as detectors are discussed along with their key physical properties and electronic characteristics. Materials commonly utilized in radiation detectors are then reviewed to highlight how sensor materials have advanced since the earliest gamma detectors were developed

Johns, Paul M.↗
DOE OSTI2021

Nanocoral Ag for nonenzymatic glucose detection at extremely low operational potential

Silver (Ag) metal has excellent antibacterial properties, which makes it an ideal candidate for nonenzymatic glucose sensing devices. However, Ag nonenzymatic glucose sensors function at significantly high operating potential and suffer from poor selectivity. Here, we report that nanocoral reduced Ag (R-Ag) based nonenzymatic glucose sensors can be operated at potential as low as 0.1 V vs. Ag/AgCl and exhibits more than one order magnitude higher sensitivity in comparison to the Ag film. The R-Ag sensors can detect glucose in a wide range of concentrations varying from 100 u M to 2.5 mM linearly. Finally, the R-Ag sensors are also very robust, as performance remains unchanged even if sensors are stored under ambient conditions for 45 days.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Tailored Graphene Micropatterns by Wafer-Scale Direct Transfer for Flexible Chemical Sensor Platform

2D materials, such as graphene, exhibit great potential as functional materials for numerous novel applications due to their excellent properties. The grafting of conventional micropatterning techniques on new types of electronic devices is required to fully utilize the unique nature of graphene. However, the conventional lithography and polymer-supported transfer methods often induce the contamination and damage of the graphene surface due to polymer residues and harsh wet-transfer conditions. In this work, a novel strategy to obtain micropatterned graphene on polymer substrates using a direct curing process is demonstrated. Employing this method, entirely flexible, transparent, well-defined self-activated graphene sensor arrays, capable of gas discrimination without external heating, are fabricated on 4 in. wafer-scale substrates. Finite element method simulations show the potential of this patterning technique to maximize the performance of the sensor devices when the active channels of the 2D material are suspended and nanoscaled. This study contributes considerably to the development of flexible functional electronic devices based on 2D materials.

2D materials, Graphene, Microscale patterning, Che↗
DOE OSTI2020

A Novel Simulation-Based Framework for Sensor Error Impact Analysis in Smart Building Systems: A Case Study for a Demand-Controlled Ventilation System

Sensors are one of the fundamental components for sensor-rich controls in buildings but are prone to different errors. Existing studies show that sensor errors hold a place among top-priority faults in building systems. Before we take countermeasures to mitigate the sensor errors, it is vital to prioritize key sensors and quantify the collective impacts of concurrent sensor errors. In response to this, a simulation-based methodology is introduced to conduct a comprehensive sensor error impact analysis in building systems, which adds a stochastic sensor prioritization through a sensitivity analysis on top of a commonly used deterministic sensor error quantification. The synergies of these two parts help better interpret the sensor error impacts on building energy consumption, ventilation performance, thermal comfort, etc. A sensor-rich CO2-based Demand-Controlled Ventilation system is used as a case study to demonstrate the viability of the methodology as a proof-of-the-concept. The results show that the energy savings potential and ventilation performance are mostly influenced by the accuracy of the AHU outdoor airflow sensors. The accuracy of zone level airflow sensors has a negligible impact on both energy savings and ventilation performance. The accuracy of zone CO2 sensors has more influence on the ventilation performance compared with the accuracy of zone airflow sensors. Compared with the baseline case with zero errors, the largest deviation percentages could reach 16.90% and 94.32%, respectively, in terms of the Heating, Ventilation, and Air-Conditioning (HVAC) annual energy consumption and the Outdoor Air Ratio (OAR) when multiple key sensors suffer from normal error intensities simultaneously.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2021

Spectral Effects in Albedo and Rearside Irradiance Measurement for Bifacial Performance Estimation

We investigate the impact of spectral dependence of ground surface reflectivity on albedo and rearside irradiance measurements necessary for bifacial photovoltaic (PV) module performance estimation and monitoring. Because PV modules are spectrally selective, albedo and irradiance measurements performed with common irradiance sensors may require spectral mismatch corrections when used for performance prediction. We investigate via simulation the differences in spectrally responsive albedo measured with thermopile pyranometers and crystalline silicon PV reference cells in comparison to a typical crystalline-silicon bifacial PV module. Simulations are performed for nine different representative ground surface materials using simulated solar spectra together with spectral reflectivity data distributed with the SMARTS simulation software. For the materials considered, the results show that albedo spectral mismatch relative to the bifacial module is distributed over a range of ±9.2% for thermopile pyranometers versus only ±3.7% for a typical PV reference cell. We consider the impact of this spectrally-responsive albedo mismatch on bifacial PV module rearside irradiance measurements. Using synthesized rearside spectral irradiance distributions, we find that for the nine different ground surface materials the predicted rearside irradiance measurement deviates from the effective irradiance observed by the PV module by on the order of 16.5 W/m 2 for the pyranometer and 3.6 W/m 2 for the PV reference cell. We discuss the implications for bifacial albedo and irradiance measurement.

41 EE - Solar Energy Technologies Office (EE-4S)↗
DOE OSTI2023

Sensor Fusion-Based Vehicle Detection and Tracking Using a Single Camera and Radar at a Traffic Intersection

Recent advancements in sensor technologies, in conjunction with signal processing and machine learning, have enabled real-time traffic control systems to adapt to varying traffic conditions. This paper introduces a new sensor fusion approach that combines data from a single camera and radar to achieve cost-effective and efficient vehicle detection and tracking. Initially, vehicles are independently detected and classified using the camera and radar. Then, the constant-velocity model within a Kalman filter is employed to predict vehicle locations, while the Hungarian algorithm is used to associate these predictions with sensor measurements. Finally, vehicle tracking is accomplished by merging kinematic information from predictions and measurements through the Kalman filter. A case study conducted at an intersection demonstrates the effectiveness of the proposed sensor fusion method for traffic detection and tracking, including performance comparisons with individual sensors.

47 OTHER INSTRUMENTATION↗