Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “sensor selection”

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 55 records · Page 3
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Sensor Placement Optimization Study for the Built Environment: Next Steps Report

Systems of fixed-position radiation sensors can provide information that assists emergency responders following nuclear incidents. First responder organizations that implement systems of fixed-position sensors face numerous decisions regarding sensor selection, quantity, and placement. Researchers at Pacific Northwest National Laboratory (PNNL) have evaluated the performance of several hypothetical sensor systems during a simulated activation of a radiological dispersal device. Due to technical limitations, PNNL’s analysis was limited to a single location and number of scenarios. This document describes additional research and analysis that would result in improved guidance to first responder organizations considering installation of radiation monitoring systems.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2026

Persistent DynAMICS

Persistent DynAMICS is a lightweight software platform that enables distributed sensing systems to operate as a unified, responsive network. It integrates with existing sensors, data systems, and processing tools as an overlay, without requiring hardware replacement or increasing user burden. As data is collected, the system identifies situations that require additional attention and directs selected sensors to gather more information. For example, if a sensor detects an unusual condition along a pipeline, the system can task nearby sensors or different sensing modalities to confirm the event and focus data collection where it is needed. To support this, the platform forms temporary groups of sensors that work together to address specific objectives. Once complete, these groups are dissolved and resources are reassigned as needed. Communication is handled through an integrated messaging framework with client and server components, enabling reliable operation and data continuity even in low-bandwidth or intermittent connectivity environments.

97 MATHEMATICS AND COMPUTING↗
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 OSTI2025

Synthesis of nanodiamonds encapsulated by zeolitic imidazole framework-8 for quantum sensing applications

Nitrogen vacancy (NV)-containing nanodiamonds are widely used in quantum sensing applications due to their high sensitivity to magnetic fields, relatively low cost, and ability to be initialized, manipulated, and read out at room temperature. Quantum sensing techniques such as optically detected magnetic resonance (ODMR) and spin relaxometry have exploited the sensitivity of the NV nanodiamonds to magnetic fields to detect a range of analytes, such as pH, metal ions, and biomolecules. However, diversifying the sensing targets accessible by NV diamond quantum sensors typically requires careful engineering of the diamond surface chemistry with stimuli-responsive functional groups. Here, a simple protocol for coating NV nanodiamonds with the zeolitic imidazole framework 8 (ZIF-8), a widely used metal-organic framework, is presented. ZIF-8 is a highly porous material that has been used as a selective sensor for gasses, metal ions, and other analytes. The material is well-characterized by x-ray diffraction, transmission electron microscopy, scanning electron microscopy, x-ray photoelectron spectroscopy, and luminescence spectroscopy. Encapsulation of NV nanodiamonds with a porous scaffold such as ZIF-8 provides a promising method for improving the selectivity for the quantum sensing of various analytes. Importantly, the ZIF-8 coating does not impact the luminescence properties of the NV diamond, which is a key readout in ODMR and spin relaxometry sensing approaches. Indeed, the ODMR spectra with and without the ZIF-8 shell is nearly identical. Moreover, the ZIF-8 coating increases the longitudinal spin relaxation time of the NV nanodiamond by a factor of 4 relative to aggregated diamond, a desirable outcome for spin relaxation-based quantum sensing. Metal-organic framework composites with nanodiamonds thus are an exciting strategy for enhancing NV nanodiamond performance in applications such as quantum sensing and quantum-enhanced nuclear magnetic resonance spectroscopy.

nitrogen vacancy nanodiamond↗
DOE OSTI2023

Optimal sensor placement for reconstructing wind pressure field around buildings using compressed sensing

Deciding how to optimally deploy sensors in a large, complex, and spatially extended structure is critical to ensure that the surface pressure field is accurately captured for subsequent analysis and design. In some cases, reconstruction of missing data is required in downstream tasks such as the development of digital twins. Here, this paper presents a data-driven sparse sensor selection algorithm, aiming to provide the most information contents for reconstructing aerodynamic characteristics of wind pressures over tall building structures parsimoniously. The algorithm first fits a set of basis functions to the training data, then applies a computationally efficient QR algorithm that ranks existing pressure sensors in order of importance based on the state reconstruction to this tailored basis. The findings of this study show that the proposed algorithm successfully re- constructs the aerodynamic characteristics of tall buildings from sparse measurement locations, generating stable and optimal solutions across a range of conditions. As a result, this study serves as a promising first step toward leveraging the success of data-driven and machine learning algorithms to supplement traditional genetic algorithms currently used in wind engineering.

42 ENGINEERING↗
DOE OSTI2020

Surface-Mediated Interconnections of Nanoparticles in Cellulosic Fibrous Materials toward 3D Sensors

Fibrous materials serve as an intriguing class of 3D materials to meet the growing demands for flexible, foldable, biocompatible, biodegradable, dis- posable, inexpensive, and wearable sensors and the rising desires for higher sensitivity, greater miniaturization, lower cost, and better wearability. The use of such materials for the creation of a fibrous sensor substrate that interfaces with a sensing film in 3D with the transducing electronics is however difficult by conventional photolithographic methods. Here, a highly effective pathway featuring surface-mediated interconnection (SMI) of metal nanoclusters (NCs) and nanoparticles (NPs) in fibrous materials at ambient conditions is demon- strated for fabricating fibrous sensor substrates or platforms. Bimodally distrib- uted gold–copper alloy NCs and NPs are used as a model system to demonstrate the semiconductive-to-metallic conductivity transition, quantized capacitive charging, and anisotropic conductivity characteristics. Upon coupling SMI of NCs/NPs as electrically conductive microelectrodes and surface-mediated assembly (SMA) of the NCs/NPs as chemically sensitive interfaces, the resulting fibrous chemiresistors function as sensitive and selective sensors for gaseous and vaporous analytes. Finally, this new SMI–SMA strategy has significant implications for manufacturing high-performance fibrous platforms to meet the growing demands of the advanced multifunctional sensors and biosensors.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Thermal field reconstruction and compressive sensing using proper orthogonal decomposition

Model order reduction allows critical information about sensor placement and experiment design to be distilled from raw fluid mechanics simulation data. In many cases, sensed information in conjunction with reduced order models can also be used to regenerate full field variables. In this paper, a proper orthogonal decomposition (POD) inferencing method is extended to the modeling and compressive sensing of temperature, a scalar field variable. The method is applied to a simulated, critically stable, incompressible flow over a heated cylinder (Re = 1000) with Prandtl number varying between 0.001 and 50. The model is trained on pressure and temperature data from simulations. Field reconstructions are then generated using data from selected sensors and the POD model. Finally, the reconstruction error is evaluated across all Prandtl numbers for different numbers of retained modes and sensors. The predicted trend of increasing reconstruction accuracy with decreasing Prandtl number is confirmed and a Prandtl number/sensor count error matrix is presented.

Matulis, John↗
DOE OSTI2024

Quantum sensing effect of electron tunneling in DQD/analyte complex

We investigate electron tunneling between quantum dots and molecules to propose a quantum sensor. This sensor consists of double quantum dots (DQD) with energy levels specifically tailored to mirror those of the target analyte. By analyzing the spectral distribution of electron localizations in the DQD system, we can delineate the analyte’s spectrum and deduce its composition by comparing it with a reference sample. To understand electron tunneling dynamics within the DQD/analyte complex, we performed three-dimensional computational modeling applying the effective potential approach to the InAs/GaAs heterostructure. In this modeling, we mimicked the analyte spectrum by utilizing a quantum well characterized by a quasi-discrete spectrum. Our calculations reveal the inherent potential of utilizing this method as a highly sensitive and selective sensor.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2026

Molecular To Mesoscale Targeting of Oxoanions with Multi-Tasking Hosts

Achieving a better understanding of anion interactions both in solution and crystalline state was the overarching goal of this project. Anions are everywhere throughout Nature and play important roles in biological and environmental processes. They can be beneficial or deleterious or both in different situations and concentrations. For either reason it is important to have molecules that can bind anions for key needs that benefit society. However, recognition of specific anions is challenging due to the diffuse nature of their negative charge(s) as well as their various shapes and sizes. Understanding the basic properties of anions and how they interact with other molecules and ions in surrounding environments is key to selective recognition. In this project multi-tasking molecules for selective binding of targeted anions were designed to achieve cooperativity and synergism in one rather than multiple host molecules, including (1) cation:anion pair hosts for anions with charges of -2 or greater; (2) pH and redox activated hosts for on-off binding and release; and (3) multiple anion capture in extended host networks. Our design strategy was to combine the use of simple inexpensive building blocks and high yield synthetic pathways to provide economically feasible scale-up for applications. Oxoanions representing multiple shapes and charges were chosen based on having the potential for significant impact on DOE separations needs. Amide/amine-based macrocycles and urea/amine-based chelates and macrocycles with multiple hydrogen bonding sites provided the basic anion-binding frameworks. Successful multi-tasking outcomes were forthcoming in all three tasks. In Task 1, successful ion pair binding for anions with multiple charges was achieved. Furthermore, the ion pair molecules were capable of extended interactions through supramolecular intertwining, like fishing nets for capturing pools of fish (also fitting with Task 3). In Task 2, molecules were synthesized possessing on-off switches. These included a pH sensitive sensor for on-off binding of anions in general, as well as an electrochemical sensor selective for sulfate capture. Three new classes of extended anion host networks capable of binding multiple ions was a major outcome of Task 3. These systems included: anion sensitive, fluorescent organogels; channel-forming macrocycles for studying anion-water including larger macrocyclic cluster sandwiches; and, the offshoot of Task 1, fishing net ion-pair networks for higher valent anions. These strategies can be expanded in the future to other ions and molecules for a better understanding of intermolecular and interionic interactions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Long-Term Infrasound Sensor Calibration and Characterization

Previous testing has shown that infrasound sensors deployed in the field can exhibit notable deviations from their nominal, lab-based calibrations. These variations may be due to changes in environmental conditions, long-term sensor drift, or other unresolved features. In early 2018, we installed two identical infrasound elements with five infrasound sensors at each element (Chaparral M50A, Chaparral M64LN, CEA/Martec MB2005, CEA/Seismowave MB3a, and Hyperion IFS-5113A). These sensors were accepted or under consideration for use in the International Monitoring System network of the Comprehensive Nuclear-Test-Ban Treaty. Each element had all sensors connected to a single digitizer and port to the atmosphere. We also recorded instrument enclosure air temperature and humidity and external air temperature. Using the MB2005 as the reference, we examine the relative sensor response (both magnitude and phase) as a function of time and frequency and compare it with quarterly laboratory calibrations and environmental conditions. Here, we find that the magnitude response for all sensors exhibits some variability in both the lab and field, with the amplitude variations often >5%. The field-based variations are more severe and occur on both long-term (months) and short-term (hours) timescales. Short-term variability correlates with changes in environmental conditions and is considerable (up to 25%) for the Chaparral M50A and noticeable (∼5%) for the French Alternative Energies and Atomic Energy Commission (CEA) MB3a. Long-term magnitude variability for the Chaparral M50A was up to 50% and does not clearly correlate with environmental conditions. The other sensors show some long-term magnitude offsets, but they have relatively stable responses in the conditions we examined. The MB3a also displays some frequency-dependent magnitude variability and shows a minor dependence on temperature. Phase estimates are stable and near zero for all sensors tested. These results strongly suggest sensor response and variability due to environmental conditions should be considered in future infrasound data interpretation and sensor selection and development.

Fee, David↗
DOE OSTI2020

Real-time Canister Welding Health Monitoring and Prediction System for Spent Fuel Dry Storage

In this report, the salt mist corrosion testing at controlled temperature was carried out successfully on 304L SS submerged arc welded coupons by Unifog Dispersion Tower at ORNL. Corrosion in-situ monitoring system from Intelligent Automation, Inc. (IAI) was setup in the corrosion test and running smoothly to record signals during the corrosion test. Parts and device selection, sensors attachment, and experimental procedures are discussed. There wasn’t any visible corrosion or crack propagation on the weld coupon after about a month of corrosion testing.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2021

Augmented Monitoring and Condition Assessment Program (AMCAP) - Proof-of-Principle (POP) Mockup for Non-Aluminum Spent Nuclear Fuel Container In-Situ Examinations

A disciplined engineering approach is being followed to develop an engineered system of tooling and sensors, characterization techniques, and deployment subsystems for in-situ inspection of the several container types used for the storage of non-aluminum spent nuclear fuel (NASNF) in L Basin under the Augmented Monitoring and Condition Assessment Program (AMCAP). Inspecting the containers to provide information on their structural condition helps ensure the safe handling and storage of the NASNF containers pending final disposition. This report describes the work performed in the initial two phases of this developmental work, namely the bench scale and proof-of-principle (POP) scale, which focus on sensor selection and the tooling design and fabrication for two remote non-destructive examination (NDE) methods. These methods include visual testing (VT) for a visual examination of the container surfaces and ultrasonic testing (UT) for a n examination to characterize container wall material thickness and flaws.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2022

Applying Acoustic Emission to Large Format Additive Manufacturing

Large format additive manufacturing (AM) is being adapted as a method of producing large structures in a short lead time and cost-effective way. With the growing advancement in AM techniques and application, machine monitoring and part qualification is highly needed. There has been leading research focused on the manufacturing development and feedstock material but minimum research on the structural health monitoring (SHM), defect detection, and nondestructive evaluation (NDE) for large format AM. Scanning large structure using conventional nondestructive testing (NDT) techniques, such as ultrasound or X-ray, and searching for potential defects can be very time consuming, challenging and cost prohibitive. Acoustic emission (AE) is a passive technique that can be used to monitor and locate defect progression in large structures by distributing group of sensors around the part. This research outlines the necessary procedure for implementing AE to AM as a reliability method. The topics this research will display are: (a) Wave propagation/velocity evaluation, (b) an AE attenuation characterization for the anisotropic printed structure and material, (c) background noise measurements of the extruder and gantry system, and (d) assist in optimal sensor selection and placement for monitoring large AM structures with demonstration. This work establishes the foundation for scaling up the SHM-AE system for the large additive platform.

Spencer, Ryan↗
DOE OSTI2021

Variational Information Planning for Sequential Decision Making

We consider the setting of sequential decision making where, at each stage, potential actions are evaluated based on expected reduction in posterior uncertainty, given by mutual information (MI). As MI typically lacks a closed form, we propose an approach which maintains variational approximations of, both, the posterior and MI utility. Our planning objective extends an established variational bound on MI to the setting of sequential planning. The result, variational information planning (VIP), is an efficient method for sequential decision making. We further establish convexity of the variational planning objective and, under conditional exponential family approximations, we show that the optimal MI bound arises from a relaxation of the well-known exponential family moment matching property. Here, we demonstrate VIP for sensor selection, experiment design, and active learning, where it meets or exceeds methods requiring more computation, or those specialized to the task.

Pacheco, Jason↗
DOE OSTI2022

Physics-based modeling and information-theoretic sensor and settings selection for tool wear detection in precision machining

Precision machining of metals is an energy intensive process with applications and impacts across the manufacturing industry. The energy efficiency, product yield, and maintenance of the precision machine require a digital twin that can assist with prognostics and health management. In this report a physics-based model is developed and validated against face milling data, and then used for the timely and precise inference of machining faults that cannot be measured directly. Computer numerical control (CNC) measurements of power and force are used through this physics-based machining model to predict deviations of the outputs of power consumption and cutting forces during normal operation. A model-based fault detection and isolation methodology is applied to determine the optimal (traditional and available) sensor suite and the test settings (admissible input values) that improve the inference of tool wear in face milling. The optimal sensor suite and input test settings are obtained by solving a mixed integer non-linear program that optimizes information-theoretic metrics relevant to the detection and isolation of tool wear from steady-state or transient machining measurements. Dynamic time warping and k—NN classification are then used to validate the robustness of the optimal design for fault detection test design, including the optimal sensor suite.

42 ENGINEERING↗
DOE OSTI2020

Selective Sampling for Sensor Type Classification in Buildings

A key barrier to applying any smart technology to a building is the requirement of locating and connecting to the necessary resources among the thousands of sensing and control points, i.e., the metadata mapping problem. Existing solutions depend on exhaustive manual annotation of sensor metadata --- a laborious, costly, and hardly scalable process. To reduce the amount of manual effort required, this paper presents a multi-oracle selective sampling framework to leverage noisy labels from information sources with unknown reliability such as existing buildings, which we refer to as weak oracles, for metadata mapping. This framework involves an interactive process, where a small set of sensor instances are progressively selected and labeled for it to learn how to aggregate the noisy labels as well as to predict sensor types. Two key challenges arise in designing the framework, namely, weak oracle reliability estimation and instance selection for querying. To address the first challenge, we develop a clustering-based approach for weak oracle reliability estimation to capitalize on the observation that weak oracles perform differently in different groups of instances. For the second challenge, we propose a disagreement-based query selection strategy to combine the potential effect of a labeled instance on both reducing classifier uncertainty and improving the quality of label aggregation. We evaluate our solution on a large collection of real-world building sensor data from 5 buildings with more than 11,000 sensors of 18 different types. The experiment results validate the effectiveness of our solution, which outperforms a set of state-of-the-art baselines.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗
DOE OSTI2021

Characterization of a selective, zero power sensor for distributed sensing of hydrogen in energy applications

The use of hydrogen as a clean and renewable energy source is increasing rapidly for both vehicle and stationary applications. There are safety concerns for the locations in which hydrogen is made, used, and transported (i.e., pipelines and tanker trucks). Sensors are needed to comply with safety regulations and to enable a smooth and safe rollout of hydrogen as an alternative energy. However, hydrogen sensors do not yet exist that have the combined features of small size and low power for easy deployment coupled with high-volume manufacturability and low cost. This is necessary to accommodate the emerging fixed and mobile markets while retaining critical metrological metrics, including measurement range, detection limits, selectivity, fast response, stability, and long lifetime. An amperometric gas sensor for hydrogen (AGS) has been developed using an innovative manufacturing method. The sensor was designed using scalable fabrication strategies based on “Printed Electronics” (PE) methodology which are compatible with large-scale production. Prototype sensors were batch fabricated with multiple individual elements on a substrate compatible in size with a standard 8-inch wafer to enable high-volume, low-cost manufacturing, thereby leveraging PE and semiconductor fabrication infrastructure. This novel AGS was instrumented with control circuitry and evaluated for hydrogen detection in the range of 0–5000 ppmv H2 in air. Specific performance evaluations included assessment of the sensor measurement range, repeatability, and selectivity.

08 HYDROGEN↗
DOE OSTI2022

Flexible CO 2 Sensor Architecture with Selective Nitrogen Functionalities by One‐Step Laser‐Induced Conversion of Versatile Organic Ink

Abstract Nitrogen‐containing carbons (NC) are a class of sustainable materials for selective CO 2 adsorption. A versatile concept is introduced to fabricate flexible NC‐based sensor architectures for room‐temperature sensing of CO 2 in a one‐step laser conversion of primary films cast from abundant precursors. By the unidirectional energy impact in conjunction with depth‐dependent attenuation of the laser beam, a layered sensor heterostructure with a porous transducer and active sensor layer is formed. Comprehensive microscopic and spectroscopic cross‐sectional analyses confirm the preservation of the high content of imidazolic nitrogen in the sensor. The performance is optimized in terms of material morphology, chemical composition, and surface chemistry to achieve a linear relative resistive response of up to Δ R / R 0 = −14.3% (10% of CO 2 ). Thermodynamic analysis yields Δ ads H values of −35.6 and 34.1 kJ·mol −1 for H 2 O and CO 2 , respectively. The sensor is operable even in humid environments (e.g., ∆ R / R 0,RH = 80% = 0.53%) and shows good performance upon strong mechanical deformation.

flexible gas sensors↗