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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 1,279 records · Page 71

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NASA NTRS1985

Evaluation of performance characteristics for a space antenna system subjected to stochastic disturbances

Control system synthesis for a large space antenna system is investigated based on stochastic linear optimal control techniques and the minimization of a quadratic Gaussian performance index. Parametric studies indicate that suitable combinations of plant and sensor noise characteristics, and state weighting matrices, can be found to meet the mission RMS pointing requirements. Using a combination of the Kalman filter and linear feedback, an optimal control law for the finite element model of the Hoop/Column structural system without damping is obtained. Removing the hoop-mounted actuator resulted in an increase in the RMS errors, an increased control effort, and an increase in the least damped modal time constant. Removing the hoop-mounted sensor resulted in an RMS error increase and estimator performance degradation, with less system RMS performance degradation than noted for removal of the hoop-mounted actuator.

Ananthakrishnan, S.↗

NASA NTRS2003

The Design and Implementation of Instruments for Low-Frequency Electromagnetic Sounding of the Martian Subsurface

Low-frequency electromagnetic soundings of the subsurface can identify liquid water at depths ranging from hundreds of meters to approx. 10 km in an environment such as Mars. Among the tools necessary to perform these soundings are low-frequency electric and magnetic field sensors capable of being deployed from a lander or rover such that horizontal and vertical components of the fields can be measured free of structural or electrical interference. Under a NASA Planetary Instrument Definition and Development Program (PIDDP), we are currently engaged in the prototype stages of low frequency sensor implementations that will enable this technique to be performed autonomously within the constraints of a lander platform. Once developed, this technique will represent both a complementary and alternative method to orbital radar sounding investigations, as the latter may not be able to identify subsurface water without significant ambiguities. Low frequency EM methods can play a crucial role as a ground truth measurement, performing deep soundings at sites identified as high priority areas by orbital radars. Alternatively, the penetration depth and conductivity discrimination of low-frequency methods may enable detection of subsurface water in areas that render radar methods ineffective. In either case, the sensitivity and depth of penetration inherent in low frequency EM exploration makes this tool a compelling candidate method to identify subsurface liquid water from a landed platform on Mars or other targets of interest.

G T Delory↗

NASA NTRS2018

Development of a Coherent Doppler Lidar for Precision Maneuvering and Landing of Space Vehicles

A coherent Doppler lidar has been developed to address NASA’s need for a high-performance, compact, and cost-effective velocity and altitude sensor onboard its landing vehicles. Future robotic and manned missions to planetary bodies require precise ground-relative velocity vector and altitude data to execute complex descent maneuvers and safe, soft landing at a pre-designated site. This lidar sensor, referred to as a Navigation Doppler Lidar, meets the required performance of landing missions while complying with vehicle size, mass, and power constraints. Operating from over five kilometers altitude, the lidar obtains velocity and range precision measurements with 2 cm/sec and 2 meters, respectively, dominated by the vehicle motion. After a series of flight tests onboard helicopters and rocket-powered free-flyer vehicles, the Navigation Doppler Lidar is now being ruggedized for future missions to various destinations in the solar system.

Amzaherdian, Farzin↗

DOE OSTI2024

Printed Potentiometric Ammonium Sensors for Agriculture Applications

Ammonium (NH 4 + ) concentration is critical to both nutrient availability and nitrogen (N) loss in soil ecosystems but can be highly variable across spatial and temporal scales. For this reason, effectively informing agricultural practices such as fertilizer management and understanding of mechanisms of soil N loss require sensor technologies to monitor ammonium concentrations in real time. Our work investigates the performance of fully printed ammonium ion-selective sensors used in diverse soil environments. Ammonium sensors consisting of a printed ammonium ion-selective electrode and a printed Ag/AgCl reference were fabricated and characterized in aqueous solutions and three different soil types (sand, peat, and clay) under the range of ion concentrations likely to be present in soil (0.01–100 mM). The response of ammonium sensors was further evaluated under variable gravimetric moisture content in the soil to reflect their reliability under field conditions. Ammonium sensors demonstrated a sensitivity of 53.6 ± 5.1 mV/decade when tested in aqueous solution, and a sensitivity of 55.7 ± 11 mV/dec, 57.5 ± 4.1 mV/dec, and 43.7 ± 4 mV/dec was measured in sand, clay, and peat soils, respectively.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2023

Power System Event Detection Using the Energy Detector: A Performance Analysis

As the grid becomes smarter, the need to accurately detect, predict, and classify waveform phenomena is growing. When it comes to detecting high-frequency behaviors, i.e. transients, it is especially important to employ an event detection system that is able to accurately uncover these types of disturbances that would otherwise be lost with traditional hardware. In this paper, we first present the energy detector; a waveform event detection system that adaptively monitors a signal's energy and picks out high-frequency events that deviate from the nominal state. Secondly, we evaluate the performance of this detector against waveform data that have been corrupted by sensor irregularities. Using Oak Ridge National Laboratory's sensor testbed, we are able to show the results of the detector's performance against events that have been corrupted by three distinct sensor types, and examine how these results change with multiple trials. The results show excellent performance when detecting the beginning of an anomalous event with an average of less than 1% error.

Ekti, Ali Riza↗

DOE OSTI2025

Signal Differentiation of Moving Magnetic Nanoparticles for Enhanced Biodetection and Diagnostics

Magnetic nanoparticles are extensively utilized as markers/signal labelling in various biomedical applications. Detecting and distinguishing magnetic signals from similarly sized moving magnetic nanoparticles in microfluidic systems is crucial yet challenging for biosensing. In this study, we have developed an original method to detect and differentiate magnetic signals from moving superparamagnetic (SPM) and ferrimagnetic (FM) nanoparticles of comparable sizes. Our approach utilizes a highly sensitive magnetic-coil-based sensor that harnesses the combined effects of giant magnetoimpedance (GMI) and an LC-resonance circuit, offering performance superior to that of conventional GMI sensors. Iron oxide nanoparticles, which have similar particle sizes but differing coercivities (zero for SPM and non-zero for FM) or similar zero coercivities but differing particle sizes, flow through the magnetic coil at controlled velocities. Their distinct effects are analyzed through changes in the complex impedance of the sensing system. Our findings provide a unique pathway for utilizing SPM and FM nanoparticles as innovative magnetic markers to identify specific biological entities, thereby expanding their potential applications.

Hwang, Kee Young↗

DOE OSTI2022

Sensor cost-effectiveness analysis for data-driven fault detection and diagnostics in commercial buildings

Data-driven building fault detection and diagnostics (FDD) is heavily dependent on sensors. However, common sensors from Building Automation Systems are not optimized to maximize accuracy in FDD. Installing additional sensors that provide more detailed building system information is key to maximizing the performance of FDD solutions. Here in this paper, we present a sensor cost analysis workflow to quantify the economic implications of installing new sensors for FDD using the concept of sensor threshold marginal cost (STMC). STMC does not represent actual sensor cost. Rather, it represents a target cost based on the economic benefit that would be realized through improved FDD performance and one or more specified economic criteria. We calculate STMCs for multiple possible fault types and use fault prevalence information to aggregate STMCs into a single dollar value to determine the cost-effectiveness of a potential sensor investment. We conducted a case study using Oak Ridge National Laboratory's Flexible Research Platform (FRP) test facility as a reference. The case study demonstrates the feasibility of the analysis and highlights the key cost considerations in sensor selection for FDD. The results also indicate that identifying and installing the few key sensor(s) is critical to cost-effectively improve FDD performance.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

NASA NTRS2008

Sensor Selection and Data Validation for Reliable Integrated System Health Management

For new access to space systems with challenging mission requirements, effective implementation of integrated system health management (ISHM) must be available early in the program to support the design of systems that are safe, reliable, highly autonomous. Early ISHM availability is also needed to promote design for affordable operations; increased knowledge of functional health provided by ISHM supports construction of more efficient operations infrastructure. Lack of early ISHM inclusion in the system design process could result in retrofitting health management systems to augment and expand operational and safety requirements; thereby increasing program cost and risk due to increased instrumentation and computational complexity. Having the right sensors generating the required data to perform condition assessment, such as fault detection and isolation, with a high degree of confidence is critical to reliable operation of ISHM. Also, the data being generated by the sensors needs to be qualified to ensure that the assessments made by the ISHM is not based on faulty data. NASA Glenn Research Center has been developing technologies for sensor selection and data validation as part of the FDDR (Fault Detection, Diagnosis, and Response) element of the Upper Stage project of the Ares 1 launch vehicle development. This presentation will provide an overview of the GRC approach to sensor selection and data quality validation and will present recent results from applications that are representative of the complexity of propulsion systems for access to space vehicles. A brief overview of the sensor selection and data quality validation approaches is provided below. The NASA GRC developed Systematic Sensor Selection Strategy (S4) is a model-based procedure for systematically and quantitatively selecting an optimal sensor suite to provide overall health assessment of a host system. S4 can be logically partitioned into three major subdivisions: the knowledge base, the down-select iteration, and the final selection analysis. The knowledge base required for productive use of S4 consists of system design information and heritage experience together with a focus on components with health implications. The sensor suite down-selection is an iterative process for identifying a group of sensors that provide good fault detection and isolation for targeted fault scenarios. In the final selection analysis, a statistical evaluation algorithm provides the final robustness test for each down-selected sensor suite. NASA GRC has developed an approach to sensor data qualification that applies empirical relationships, threshold detection techniques, and Bayesian belief theory to a network of sensors related by physics (i.e., analytical redundancy) in order to identify the failure of a given sensor within the network. This data quality validation approach extends the state-of-the-art, from red-lines and reasonableness checks that flag a sensor after it fails, to include analytical redundancy-based methods that can identify a sensor in the process of failing. The focus of this effort is on understanding the proper application of analytical redundancy-based data qualification methods for onboard use in monitoring Upper Stage sensors.

Garg, Sanjay↗

NASA NTRS2019

Testing of Heat Flux Sensors at Cryogenic Temperatures

Normally, in order to characterize multilayer insulation installed onto a test tank, the boil-off of the tank is measured and then heat loads from structural and fluid penetrations are calculated from temperature measurements throughout the system. For the Structural Heat Intercept, Insulation, and Vibration Evaluation Rig testing, it was determined that this approach would have significant uncertainties (over 50%) and that another method was needed to characterize the heat load through the blanket. Heat flux sensors are widely used to measure heat loads and characterize insulation systems at room temperature, however, the heat fluxes measured are usually two orders of magnitude higher than high performance MLI. Three different heat flux sensors were initially checked out on a liquid hydrogen calorimeter. One was chosen for actual implementation and 20 sensors were ordered. Of those sensors, calibration was attempted on 7 of the sensors. The results from testing and calibration are discussed.

cryogenic fluid management↗

NASA NTRS2001

Offering an Array of Improvements

Sensors Unlimited, Inc., with SBIR funding from NASA's Langley Research Center, Goddard Space Flight Center, Marshall Space Flight Center, and the Jet Propulsion Laboratory, developed a monolithic focal plane array for near-infrared imaging. The company developed one- (1- D) and two-dimensional (2-D) imaging arrays consisting of a highly reliable InGaAs p-I-n diode as a photodetector for monitoring a variety of applications, including single element device applications in receivers. The InGaAs 1-D and 2-D arrays have many applications. For example, they monitor the performance of dense wavelength division multiplexing (DWDM) systems- the process of packaging many channels into a single fiber-optic cable. Sensors Unlimited commercially offers its LXTM and LYTM Series InGaAs linear arrays for reliable DWDM performance monitoring. The LX and LY arrays enable instrument module designs with no moving parts, which provides for superior uniformity, and fast, linear outputs that remain stable over a wide temperature range. Innovative technologies derived from the monolithic focal plane array have enabled telecommunication companies to optimize existing bandwidth in their fiber-optic networks in order to support a high volume of network traffic. At the same time, the technologies obtained from the array have the potential for reducing costs, while increasing performance from Sensors Unlimited's current product lines.

Source record↗

DOE OSTI2020

Nonlinear modeling and performance analysis of cracked beam microgyroscopes

Cracks constitute a common structural defect in microelectromechanical systems that may arise during manufacturing, mechanical fatigue, or shock loading. Areas weakened by cracks increase the flexibility of the microstructure. Furthermore, depending on the crack severity, the increased flexibility can cause dramatic changes in the static and dynamic behaviors of electrically actuated MEMS. In this study, a numerical investigation of the depth and location of multiple edge cracks on the performance of beam microgyroscopes is conducted. Applying the Griffith strain energy release theorem for an edge crack, the vibrational characteristics of microgyroscopes with multiple cracks including the static deflection, natural frequencies, and mode shapes are studied analytically. Then, the differential quadrature method is employed to model the nonlinear dynamic behaviors of the cracked gyroscope system. Cracks initiated along the driving or sensing directions of the microgyroscope are found to have differing effects on its nonlinear dynamic response. This numerical study reveals that the onset of severe single cracks or a series of multiple cracks can significantly affect the sensitivity of the microgyroscope to base rotations and therefore leads to a degradation in the performance of the damaged MEMS sensor. This study also shows that a potential design approach for broadband microgyroscope systems manufactured with cracks can be proposed.

42 ENGINEERING↗

DOE OSTI2024

STOPGAP—A time-of-flight extension for the Belle II TOP barrel PID system

The Belle II barrel region is instrumented with the Time of Propagation (TOP) particle identification system. Due to its mechanical design, the individual TOP modules do not overlap, leaving a gap of around 2 cm between them in the azimuthal direction. This leads to a 6%–9% drop in acceptance, depending on the track’s momentum. We propose a solution to remedy these gaps by instrumenting them with fast silicon detectors to directly measure the time-of-flight of traversing particles. We present here a simulation study discussing the performance requirements and the possible sensor technologies, and we demonstrate that such a project could be realized with novel, fast monolithic CMOS sensors, or alternatively AC-LGAD sensors, both of which are expected to reach MIP timing resolutions of down to 50 ps or better.

Hartbrich, Oskar↗

DOE OSTI2023

Development of diamond-based diagnostics for next-generation XFELs

The composition and performance of three different diamond sensor based pass-through diagnostics are presented. A position-sensitive quadrant sensor was designed and characterized using the XPP beam at the SLAC LCLS, demonstrating a generated-charge resolution of 0.025 pC and a position sensitivity of 2 μm, measurable pulse-by-pulse at a repetition rate of up to 50 MHz. A compact signal path capable of repetition rates up to 1 GHz was used to characterize the charge collection properties of diamond sensors as a function of the density of electron-hole pairs created within the sensor, finding a limit of approximately 10 16 electron-hole pairs per cm 3 beyond which the collection efficiency and time began to degrade. Finally, a proposed scheme for measuring ionizing radiation at multi-GHz rates is presented, along with results preliminarily demonstrating signal transport capability in excess of 5 GHz.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2022

Predicting battery capacity from impedance at varying temperature and state of charge using machine learning

Prediction of battery health from electrochemical impedance spectroscopy (EIS) data can enable rapid measurement of battery state in real-world applications without using additional sensors or time-consuming performance measurements. However, deconvoluting the effect of capacity, state of charge, and temperature on EIS response is complicated analytically. Here, various machine-learning models, such as linear, Gaussian process, random forest, and artificial neural network regression, are utilized to predict capacity from EIS using hundreds of capacity, direct current (DC) resistance, and EIS measurements recorded under varying conditions of health, temperature, and state of charge (SOC). Several feature extraction and selection methods from traditional electrochemical analysis and statistical modeling are explored using machine-learning pipelines. EIS data from just two frequencies can accurately predict capacity, and interrogation shows that the optimal set of frequencies is not usually intuitive. Best results are achieved with an ensemble model, which predicts battery capacity with a mean absolute error of 1.9% on data from unobserved cells.

25 ENERGY STORAGE↗

DOE OSTI2021

Advanced Materials for Energy-Water Systems: The Central Role of Water/Solid Interfaces in Adsorption, Reactivity, and Transport

The structure, chemistry, and charge of interfaces between materials and aqueous fluids play a central role in determining properties and performance of numerous water systems. Sensors, membranes, sorbents, and heterogeneous catalysts almost uniformly rely on specific interactions between their surfaces and components dissolved or suspended in the water-and often the water molecules themselves-to detect and mitigate contaminants. Deleterious processes in these systems such as fouling, scaling (inorganic deposits), and corrosion are also governed by interfacial phenomena. Despite the importance of these interfaces, much remains to be learned about their multiscale interactions. Developing a deeper understanding of the molecular- and mesoscale phenomena at water/solid interfaces will be essential to driving innovation to address grand challenges in supplying sufficient fit-for-purpose water in the future. In this Review, we examine the current state of knowledge surrounding adsorption, reactivity, and transport in several key classes of water/solid interfaces, drawing on a synergistic combination of theory, simulation, and experiments, and finally, provide an outlook for prioritizing strategic research directions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2022

Formation Mechanism of Flower-like Polyacrylonitrile Particles

Flower-like polyacrylonitrile (PAN) particles have shown promising performance for numerous applications, including sensors, catalysis, and energy storage. However, the detailed formation process of these unique structures during polymerization has not been investigated. Here, we elucidate the formation process of flower-like PAN particles through a series of in situ and ex situ experiments. We have the following key findings. First, lamellar petals within the flower-like particles were predominantly orthorhombic PAN crystals. Second, branching of the lamellae during the particle formation arose from PAN's fast nucleation and growth on pre-existing PAN crystals, which was driven by the poor solubility of PAN in the reaction solvent. Third, the particles were formed to maintain a constant center-to-center distance during the reaction. The separation distance was attributed to strong electrostatic repulsion, which resulted in the final particles' spherical shape and uniform size. Lastly, we employed the understanding of the formation mechanism to tune the PAN particles' morphology using several experimental parameters including incorporating comonomers, changing temperature, adding nucleation seeds, and adjusting the monomer concentration. Here these findings provide important insights into the bottom-up design of advanced nanostructured PAN-based materials and controlled polymer nanostructure self-assemblies.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2023

Digital Twin Technology (“Morpheus”) for Optimized Building Operations [SWR-22-74]

The electrification of buildings is an important step to reducing greenhouse gas emissions across all industries. The management of increasingly electrified buildings is a complex pursuit, and there remains a need for cost-effective software capable of handling the computational burden required of such complexity. Through a partnership with Dallas Fort Worth (DFW) Airport, researchers at NREL have developed a digital twin modeling framework to optimize building operations, called Morpheus. Pairing predictive control with automatic fault detection and diagnostics, Morpheus decreases energy expenditures, costs, and faults for large facilities. Additionally, Morpheus employs artificial intelligence to continuously improve its performance using information provided by sensor systems, human experts with deep industry domain knowledge, and even from other similar machines or fleets of machines. Coupling this novel energy-management software with other digital twins, such as NREL’s Athena software for mobility operations, enables robust decision-making for asset and space management. The implementation of Morpheus at DFW has resulted in significantly improved HVAC system operations and reduced both peak power and overall energy consumption. This enhanced functionality comes at a more affordable price than previously developed digital twins and can be customized for other facilities’ geometries to provide optimal, individualized control of a facility’s energy consumption.

Chinde, Venkatesh↗

DOE OSTI2023

Dipole-lattice nanoparticle resonances in finite arrays

We investigate how the periodic lattices define the collective optical characteristics of the silicon and titanium nanoparticle arrays. We examine the effects of dipole lattice on the resonances of optical nanostructures, including those made of lossy materials, such as titanium. Our approach involves employing coupled-electric-magnetic-dipole calculations for finite-size arrays, as well as lattice sums for effectively infinite arrays. Our model shows that the convergence to the infinite-lattice limit is faster when the resonance is broad, requiring fewer array particles. Our approach differs from previous works by altering the lattice resonance through modifications in the array period. We observed that a higher number of nanoparticles is necessary to achieve convergence to the infinite-array limit. Additionally, we observe that the lattice resonances excited next to higher diffraction orders (such as second order) converge more quickly toward the ideal case of an infinite array than the lattice resonances related to the first diffraction order. This work reports on the significant advantages of using a periodic arrangement of lossy nanoparticles and the role of collective excitation in enhancing response from transition metals, such as titanium, nickel, tungsten, and so on. The periodic arrangement of nanoscatterers allows for the excitation of strong dipoles, boosting the performance of nanophotonic devices and sensors by improving the strength of localized resonances.

36 MATERIALS SCIENCE↗