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At least 775 records · Page 43

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NASA NTRS1986

Thermal sensing of cryogenic wind tunnel model surfaces Evaluation of silicon diodes

Different sensors and installation techniques for surface temperature measurement of cryogenic wind tunnel models were investigated. Silicon diodes were selected for further consideration because of their good inherent accuracy. Their average absolute temperature deviation in comparison tests with standard platinum resistance thermometers was found to be 0.2 K in the range from 125 to 273 K. Subsurface temperature measurement was selected as the installation technique in order to minimize aerodynamic interference. Temperature distortion caused by an embedded silicon diode was studied numerically.

Daryabeigi, K.↗

NASA NTRS1986

Thermal sensing of cryogenic wind tunnel model surfaces - Evaluation of silicon diodes

Daryabeigi, Kamran↗

NASA NTRS2009

Terminal Descent Sensor Simulation

Sulcata software simulates the operation of the Mars Science Laboratory (MSL) radar terminal descent sensor (TDS). The program models TDS radar antennas, RF hardware, and digital processing, as well as the physics of scattering from a coherent ground surface. This application is specific to this sensor and is flexible enough to handle end-to-end design validation. Sulcata is a high-fidelity simulation and is used for performance evaluation, anomaly resolution, and design validation. Within the trajectory frame, almost all internal vectors are represented in whatever coordinate system is used to represent platform position. The trajectory frame must be planet-fixed. The platform body frame is specified relative to arbitrary reference points relative to the platform (spacecraft or test vehicle). Its rotation is a function of time from the trajectory coordinate system specified via dynamics input (file for open loop, callback for closed loop). Orientation of the frame relative to the body is arbitrary, but constant over time. The TDS frame must have a constant rotation and translation from the platform body frame specified at run time. The DEM frame has an arbitrary, but time-constant, rotation and translation with respect to the simulation frame specified at run time. It has the same orientation as sigma0 frame, but is possibly translated. Surface sigma0 has the same arbitrary rotation and translation as DEM frame.

Chen, Curtis W.↗

DOE OSTI2025

Model Development and Analysis of a High-Fidelity Neutron Transport Sensor: The Quadrupole Detector Concept for Measurement of the Neutron Flux Gradient

Accurate reconstruction of the neutron flux distribution within a reactor core is essential for safe and efficient reactor operation. Traditional power shape synthesis in Light Water Reactors relies on hundreds of in-core detectors. However, this approach becomes impractical for Advanced Reactors and Microreactors due to limited space and harsh environments. To address this challenge, we propose a data-driven methodology that combines high-fidelity modeling with real-time ex-core sensor measurements, enabling the reconstruction of core power distribution while minimizing the reliance on intrusive in-core instrumentation. This project began in FY24 and achieved two initial milestones: (1) the definition of a three-year development plan for a Digital Twin framework and (2) the development of high-fidelity neutronics models of the Purdue University Reactor One (PUR-1) using both MCNP6 and OpenMC. The PUR-1 reactor, a zero-power facility, was selected due to its suitability for neutronics-focused modeling and the availability of experimental data for validation. Both models were benchmarked using neutron flux measurements obtained from irradiated gold foils, which were strategically placed within the core during a dedicated campaign in July 2024. This report marks the continuation and completion of those foundational tasks. The OpenMC model has been refined (improved geometric accuracy, expanded cross-section libraries, and refined sampling) and validated using additional experimental data. An updated sensor design—based on quadrupole configuration—was designed to measure both ex-core flux and its spatial gradient. These measurements will serve as inputs to a neural network-based reconstruction algorithm. Finally, the methodology was demonstrated on a two-dimensional test case representative of the heterogeneous material composition of the PUR-1 reactor core. A neural network implementation of the Kirchhoff-Helmholtz integral equation was employed to solve the boundary value problem using peripheral sensor measurements. The preliminary results confirm the strong potential of the proposed approach for accurate and minimally invasive neutron flux reconstruction.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2023

Single molecule insights into interfacial molecular recognition for model electrochemical DNA biosensors

Electrochemical sensors that use surface-immobilized DNA to bind analytes and transduce the binding into electrochemical signals, have the potential for rapid, specific, and sensitive detection of bioanalytes via a compact and portable platform. However, accessing the structure of these surfaces/interfaces at the relevant spatial scale (< 10 nm), which determines the interfacial interactions and ultimately sensing performance, remains an unsolved challenge. Here, we review studies that have used high resolution atomic force microscope imaging and spatial statistical analysis tools to understand crowding interactions between thiolated DNA probes immobilized on gold electrodes and how such interactions impact target binding. We also review related studies that attempt to control the nanoscale spatial arrangement of the immobilized recognition elements to optimize sensing performance. Furthermore, these efforts have led to new advances in understanding of the structure-function relationships of DNA-based electrochemical biosensors to move the field toward rational engineering of these biosensing interfaces.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

NASA NTRS1999

Developing a Fundamental Model for an Integrated GPS/INS State Estimation System with Kalman Filtering

This work will demonstrate the integration of sensor and system dynamic data and their appropriate models using an optimal filter to create a robust, adaptable, easily reconfigurable state (motion) estimation system. This state estimation system will clearly show the application of fundamental modeling and filtering techniques. These techniques are presented at a general, first principles level, that can easily be adapted to specific applications. An example of such an application is demonstrated through the development of an integrated GPS/INS navigation system. This system acquires both global position data and inertial body data, to provide optimal estimates of current position and attitude states. The optimal states are estimated using a Kalman filter. The state estimation system will include appropriate error models for the measurement hardware. The results of this work will lead to the development of a "black-box" state estimation system that supplies current motion information (position and attitude states) that can be used to carry out guidance and control strategies. This black-box state estimation system is developed independent of the vehicle dynamics and therefore is directly applicable to a variety of vehicles. Issues in system modeling and application of Kalman filtering techniques are investigated and presented. These issues include linearized models of equations of state, models of the measurement sensors, and appropriate application and parameter setting (tuning) of the Kalman filter. The general model and subsequent algorithm is developed in Matlab for numerical testing. The results of this system are demonstrated through application to data from the X-33 Michael's 9A8 mission and are presented in plots and simple animations.

Canfield, Stephen↗

NASA NTRSDate not supplied

Data Simulation Using VLIDORT and PCRTM and its Use for Radiometric Calibration of Hyperspectral UV-NIR-SWIR Sensors

Using the vector linearized discrete ordinate radiative transfer model (VLIDORT), a multiple-scattering multi-layer discrete ordinate scattering codes, coupled with a fast principal component (PC) radiative transfer model (PCRTM), we can simulate the radiation fields for hyperspectral UV-NIR-SWIR sensors from 250nm to 2500nm with a very high speed. Since the accurate gas absorptions, molecules and aerosol/cloud particle scatterings, and the surface reflectance have been considered in these simulations, these model data can be used for satellite or airborne sensor design, characterization, or end-to-end system level uncertainty assessment. Comparison of the modelled data with measured results has been a general practice for operational satellite sensor calibrations, such as the Ozone Mapping and Profiler Suite (OMPS) onboard on SNPP and NOAA-20. This presentation will give more details of this simulation system and models. Some examples of the generation of simulations data for CLARREO PathFinder (CPF) and the Surface Biology and Geology (SBG), as well as some examples to use these data for CPF and OMPS radiometric calibration will be presented.

Xiaozhen Xiong↗

NASA NTRS1994

Computer modeling of the sensitivity of a laser water vapor sensor to variations in temperature and air speed

Currently, there is disagreement among existing methods of determining atmospheric water vapor concentration at dew-points below -40 C. A major source of error is wall effects which result from the necessity of bringing samples into the instruments. All of these instruments also have response times on the order of seconds. NASA Langley is developing a water vapor sensor which utilizes the absorption of the infrared radiation produced by a diode laser to estimate water vapor concentration. The laser beam is directed through an aircraft window to a retroreflector located on an engine. The reflected beam is detected by an infrared detector located near the laser. To maximize signal to noise, derivative signals are analyzed. By measuring the 2f/DC signal and correcting for ambient temperature, atmospheric pressure and air speed (which results in a Doppler shifting of the laser beam), the water vapor concentration can be retrieved. Since this is an in situ measurement there are no wall effects and measurements can be made at a rate of more than 20 per second. This allows small spatial variations of water vapor to be studied. In order to study the sensitivity of the instrument to variations in temperature and air speed, a computer program which generated the 2f, 3f, 4f, DC and 2f/DC signals of the instrument as a function of temperature, pressure and air speed was written. This model was used to determine the effect of errors in measurement of the temperature and air speed on the measured water vapor concentration. Future studies will quantify the effect of pressure measurement errors, which are expected to be very small. As a result of these studied, a retrieval algorithm has been formulated, and will be applied to data taken during the PEM-West atmospheric science field mission. Spectroscopic studies of the water vapor line used by the instrument will be used to refine this algorithm. To prepare for these studies, several lasers have been studied to determine their output frequency range and power.

Tucker, George F.↗

DOE OSTI2020

Data-based and secure switched cyber–physical systems

In this work, we develop a completely model-free moving target defense framework for the detection and mitigation of sensor and/or actuator attacks in cyber–physical systems with dynamics that evolve in discrete-time. We incorporate an intrusion detection mechanism based on an approximate dynamic programming technique that learns the policies for optimal regulation and optimal tracking while simultaneously defending against actuator and sensor attacks in a model-free fashion. Switching rules are leveraged to force proactive and reactive defense mechanisms as well as, guarantee the stability of the equilibrium point. Finally, as a case study, we apply the proposed moving target defense framework to a DC–DC converter that is used in electric vehicles.

42 ENGINEERING↗

DOE OSTI2014

Structural models of the membrane anchors of envelope glycoproteins E1 and E2 from pestiviruses

The membrane anchors of viral envelope proteins play essential roles in cell entry. Recent crystal structures of the ectodomain of envelope protein E2 from a pestivirus suggest that E2 belongs to a novel structural class of membrane fusion machinery. Based on geometric constraints from the E2 structures, we generated atomic models of the E1 and E2 membrane anchors using computational approaches. The E1 anchor contains two amphipathic perimembrane helices and one transmembrane helix; the E2 anchor contains a short helical hairpin stabilized in the membrane by an arginine residue, similar to flaviviruses. A pair of histidine residues in the E2 ectodomain may participate in pH sensing. The proposed atomic models point to Cys987 in E2 as the site of disulfide bond linkage with E1 to form E1–E2 heterodimers. The membrane anchor models provide structural constraints for the disulfide bonding pattern and overall backbone conformation of the E1 ectodomain. - Highlights: • Structures of pestivirus E2 proteins impose constraints on E1, E2 membrane anchors. • Atomic models of the E1 and E2 membrane anchors were generated in silico. • A “snorkeling” arginine completes the short helical hairpin in the E2 membrane anchor. • Roles in pH sensing and E1–E2 disulfide bond formation are proposed for E1 residues. • Implications for E1 ectodomain structure and disulfide bonding pattern are discussed.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

NASA NTRS1987

Sensor-based diagnosis using knowledge of structure and function

A system for fault detection and isolation called LES, developed at the Kennedy Space Center for the Space Shuttle's Launch Processing System, is a well-developed diagnostic system that is simultaneously model-based and sensor-based. This experiment has led to a surprising result: the failure of a sensor can not only be handled in precisely the same way as the failure of any other object, but may present an especially easy case. Classical rule-based diagnostic systems need to find out whether or not their sensors are telling them the truth before they can safely draw inferences from them. By contrast, while LES does treat sensors as a special case, it does so only because there may exist a short cut that allows them to be handled more simply than other objects. LES uses both structural and functional knowledge, and has found cases in which the structural knowledge can be economically replaced by the judicious use of functional relationships; LES' functional relationships are stored in exactly one place, so they must be inverted to determine hypothetical values for possibly faulty objects. The inversion process has been extended to include conditional functions not normally considered to have inverses.

Scarl, Ethan A.↗

NASA NTRS2012

Characterization Approaches to Place Invariant Sites on SI-Traceable Scales

The effort to understand the Earth's climate system requires a complete integration of remote sensing imager data across time and multiple countries. Such an integration necessarily requires ensuring inter-consistency between multiple sensors to create the data sets needed to understand the climate system. Past efforts at inter-consistency have forced agreement between two sensors using sources that are viewed by both sensors at nearly the same time, and thus tend to be near polar regions over snow and ice. The current work describes a method that would provide an absolute radiometric calibration of a sensor rather than an inter-consistency of a sensor relative to another. The approach also relies on defensible error budgets that eventually provides a cross comparison of sensors without systematic errors. The basis of the technique is a model-based, SI-traceable prediction of at-sensor radiance over selected sites. The predicted radiance would be valid for arbitrary view and illumination angles and for any date of interest that is dominated by clear-sky conditions. The effort effectively works to characterize the sites as sources with known top-of-atmosphere radiance allowing accurate intercomparison of sensor data that without the need for coincident views. Data from the Advanced Spaceborne Thermal Emission and Reflection and Radiometer (ASTER), Enhanced Thematic Mapper Plus (ETM+), and Moderate Resolution Imaging Spectroradiometer (MODIS) are used to demonstrate the difficulties of cross calibration as applied to current sensors. Special attention is given to the differences caused in the cross-comparison of sensors in radiance space as opposed to reflectance space. The radiance comparisons lead to significant differences created by the specific solar model used for each sensor. The paper also proposes methods to mitigate the largest error sources in future systems. The results from these historical intercomparisons provide the basis for a set of recommendations to ensure future SI-traceable cross calibration using future missions such as CLARREO and TRUTHS. The paper describes a proposed approach that relies on model-based, SI-traceable predictions of at-sensor radiance over selected sites. The predicted radiance would be valid for arbitrary view and illumination angles and for any date of interest that is dominated by clear-sky conditions. The basis of the method is highly accurate measurements of at-sensor radiance of sufficient quality to understand the spectral and BRDF characteristics of the site and sufficient historical data to develop an understanding of temporal effects from changing surface and atmospheric conditions.

Thome, Kurtis↗

NASA NTRS2021

Evaluation of 18 Satellite- and Model-Based Soil Moisture Products Using in Situ Measurements From 826 Sensors

Information about the spatiotemporal variability of soil moisture is critical for many purposes, including monitoring of hydrologic extremes, irrigation scheduling, and prediction of agricultural yields. We evaluated the temporal dynamics of 18 state-of-the-art (quasi-)global near-surface soil moisture products, including six based on satellite retrievals, six based on models without satellite data assimilation (referred to hereafter as “open-loop” models), and six based on models that assimilate satellite soil moisture or brightness temperature data. Seven of the products are introduced for the first time in this study: one multi-sensor merged satellite product called MeMo (Merged soil Moisture) and six estimates from the HBV (Hydrologiska Byråns Vattenbalansavdelning) model with three precipitation inputs (ERA5, IMERG, and MSWEP) with and without assimilation of SMAPL3E satellite retrievals, respectively. As reference, we used in situ soil moisture measurements between 2015 and 2019 at 5 cm depth from 826 sensors, located primarily in the USA and Europe. The 3-hourly Pearson correlation (R) was chosen as the primary performance metric. We found that application of the Soil Wetness Index (SWI) smoothing filter resulted in improved performance for all satellite products. The best-to-worst performance ranking of the four single-sensor satellite products was SMAPL3E SWI , SMOS SWI , AMSR2 SWI , and ASCAT SWI , with the L-band-based SMAPL3E SWI (median R of 0.72) outperforming the others at 50 % of the sites. Among the two multi-sensor satellite products (MeMo and ESA-CCI SWI ), MeMo performed better on average (median R of 0.72 versus 0.67), probably due to the inclusion of SMAPL3E SWI . The best-to-worst performance ranking of the six open-loop models was HBV-MSWEP, HBV-ERA5, ERA5-Land, HBV-IMERG, VIC-PGF, and GLDAS-Noah. This ranking largely reflects the quality of the precipitation forcing. HBV-MSWEP (median R of 0.78) performed best not just among the open-loop models but among all products. The calibration of HBV improved the median R by +0.12 on average compared to random parameters, highlighting the importance of model calibration. The best-to-worst performance ranking of the six models with satellite data assimilation was HBV-MSWEP+SMAPL3E, HBV-ERA5+SMAPL3E, GLEAM, SMAPL4, HBV-IMERG+SMAPL3E, and ERA5. The assimilation of SMAPL3E retrievals into HBV-IMERG improved the median R by +0.06, suggesting that data assimilation yields significant benefits at the global scale.

Hylke E. Beck↗

NASA NTRS1990

A model for the space shuttle main engine high pressure oxidizer turbopump shaft seal system

A simple static model is presented which solves for the flow properties of pressure, temperature, and mass flow in the Space Shuttle Main Engine pressure Oxidizer Turbopump Shaft Seal Systems. This system includes the primary and secondary turbine seals, the primary and secondary turbine drains, the helium purge seals and feed line, the primary oxygen drain, and the slinger/labyrinth oxygen seal pair. The model predicts the changes in flow variables that occur during and after failures of the various seals. Such information would be particularly useful in a post flight situation where processing of sensor information using this model could identify a particular seal that had experienced excessive wear. Most of the seals in the system are modeled using simple one dimensional equations which can be applied to almost any seal provided that the fluid is gaseous. A failure is modeled as an increase in the clearance between the shaft and the seal. Thus, the model does not attempt to predict how the failure process actually occurs (e.g., wear, seal crack initiation). The results presented were obtained using a FORTRAN implementation of the model running on a VAX computer. Solution for the seal system properties is obtained iteratively; however, a further simplified implementation (which does not include the slinger/labyrinth combination) was also developed which provides fast and reasonable results for most engine operating conditions. Results from the model compare favorably with the limited redline data available.

Paxson, Daniel E.↗

NASA NTRS2013

Pressure-Sensitive Paints Advance Rotorcraft Design Testing

The rotors of certain helicopters can spin at speeds as high as 500 revolutions per minute. As the blades slice through the air, they flex, moving into the wind and back out, experiencing pressure changes on the order of thousands of times a second and even higher. All of this makes acquiring a true understanding of rotorcraft aerodynamics a difficult task. A traditional means of acquiring aerodynamic data is to conduct wind tunnel tests using a vehicle model outfitted with pressure taps and other sensors. These sensors add significant costs to wind tunnel testing while only providing measurements at discrete locations on the model's surface. In addition, standard sensor solutions do not work for pulling data from a rotor in motion. "Typical static pressure instrumentation can't handle that," explains Neal Watkins, electronics engineer in Langley Research Center s Advanced Sensing and Optical Measurement Branch. "There are dynamic pressure taps, but your costs go up by a factor of five to ten if you use those. In addition, recovery of the pressure tap readings is accomplished through slip rings, which allow only a limited amount of sensors and can require significant maintenance throughout a typical rotor test." One alternative to sensor-based wind tunnel testing is pressure sensitive paint (PSP). A coating of a specialized paint containing luminescent material is applied to the model. When exposed to an LED or laser light source, the material glows. The glowing material tends to be reactive to oxygen, explains Watkins, which causes the glow to diminish. The more oxygen that is present (or the more air present, since oxygen exists in a fixed proportion in air), the less the painted surface glows. Imaged with a camera, the areas experiencing greater air pressure show up darker than areas of less pressure. "The paint allows for a global pressure map as opposed to specific points," says Watkins. With PSP, each pixel recorded by the camera becomes an optical pressure tap. "Instead of having 100 or 200 pressure taps, you can have in theory several million, up to whatever the resolution of your camera is." Watkins explains that typical wind tunnel testing requires two models: one with very little instrumentation, and a pressure model with a significant amount of sensors applied. "If you can make all of your measurements on one model with PSP, you've decreased your model costs by at least a factor of two and preferably your testing costs by about that much," he says. PSP technology has been around for almost 20 years, but a PSP solution for gathering instantaneous dynamic pressure data from surfaces moving at high speeds, such as rotor blades, was not available until a NASA partnership led to a game-changing innovation.

Source record↗

NASA NTRS1991

Analysis of simulated image sequences from sensors for restricted-visibility operations

A real time model of the visible output from a 94 GHz sensor, based on a radiometric simulation of the sensor, was developed. A sequence of images as seen from an aircraft as it approaches for landing was simulated using this model. Thirty frames from this sequence of 200 x 200 pixel images were analyzed to identify and track objects in the image using the Cantata image processing package within the visual programming environment provided by the Khoros software system. The image analysis operations are described.

Kasturi, Rangachar↗

DOE OSTI2016

Multi-omics approach identifies molecular mechanisms of plant-fungus mycorrhizal interaction

In mycorrhizal symbiosis, plant roots form close, mutually beneficial interactions with soil fungi. Before this mycorrhizal interaction can be established however, plant roots must be capable of detecting potential beneficial fungal partners and initiating the gene expression patterns necessary to begin symbiosis. To predict a plant root – mycorrhizal fungi sensor systems, we analyzed in vitro experiments of Populus tremuloides (aspen tree) and Laccaria bicolor (mycorrhizal fungi) interaction and leveraged over 200 previously published transcriptomic experimental data sets, 159 experimentally validated plant transcription factor binding motifs, and more than 120-thousand experimentally validated protein-protein interactions to generate models of pre-mycorrhizal sensor systems in aspen root. These sensor mechanisms link extracellular signaling molecules with gene regulation through a network comprised of membrane receptors, signal cascade proteins, transcription factors, and transcription factor biding DNA motifs. Modeling predicted four pre-mycorrhizal sensor complexes in aspen that interact with fifteen transcription factors to regulate the expression of 1184 genes in response to extracellular signals synthesized by Laccaria. Predicted extracellular signaling molecules include common signaling molecules such as phenylpropanoids, salicylate, and, jasmonic acid. Lastly, this multi-omic computational modeling approach for predicting the complex sensory networks yielded specific, testable biological hypotheses for mycorrhizal interaction signaling compounds, sensor complexes, and mechanisms of gene regulation.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2025

Analysis and optimization of seismic monitoring networks with Bayesian optimal experimental design

SUMMARY Monitoring networks increasingly aim to assimilate data from a large number of diverse sensors covering many sensing modalities. Bayesian optimal experimental design (OED) seeks to identify data, sensor configurations or experiments which can optimally reduce uncertainty and hence increase the performance of a monitoring network. Information theory guides OED by formulating the choice of experiment or sensor placement as an optimization problem that maximizes the expected information gain (EIG) about quantities of interest given prior knowledge and models of expected observation data. Therefore, within the context of seismo-acoustic monitoring, we can use Bayesian OED to configure sensor networks by choosing sensor locations, types and fidelity in order to improve our ability to identify and locate seismic sources. In this work, we develop the framework necessary to use Bayesian OED to optimize a sensor network’s ability to locate seismic events from arrival time data of detected seismic phases at the regional-scale. This framework requires five elements: (i) A likelihood function that describes the distribution of detection and traveltime data from the sensor network, (ii) A prior distribution that describes a priori belief about seismic events, (iii) A Bayesian solver that uses a prior and likelihood to identify the posterior distribution of seismic events given the data, (iv) An algorithm to compute EIG about seismic events over a data set of hypothetical prior events, (v) An optimizer that finds a sensor network which maximizes EIG. Once we have developed this framework, we explore many relevant questions to monitoring such as: how to trade off sensor fidelity and earth model uncertainty; how sensor types, number and locations influence uncertainty; and how prior models and constraints influence sensor placement.

58 GEOSCIENCES↗