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All sourcesNASA NTRSDOE OSTI
NASA NTRS2004

Real-Time Unsteady Loads Measurements Using Hot-Film Sensors

Several flight-critical aerodynamic problems such as buffet, flutter, stall, and wing rock are strongly affected or caused by abrupt changes in unsteady aerodynamic loads and moments. Advanced sensing and flow diagnostic techniques have made possible simultaneous identification and tracking, in realtime, of the critical surface, viscosity-related aerodynamic phenomena under both steady and unsteady flight conditions. The wind tunnel study reported here correlates surface hot-film measurements of leading edge stagnation point and separation point, with unsteady aerodynamic loads on a NACA 0015 airfoil. Lift predicted from the correlation model matches lift obtained from pressure sensors for an airfoil undergoing harmonic pitchup and pitchdown motions. An analytical model was developed that demonstrates expected stall trends for pitchup and pitchdown motions. This report demonstrates an ability to obtain unsteady aerodynamic loads in real time, which could lead to advances in air vehicle safety, performance, ride-quality, control, and health management.

Mangalam, Arun S.↗
NASA NTRS1989

Modeling, simulation, and analysis of optical remote sensing systems

Remote Sensing of the Earth's resources from space-based sensors has evolved in the past 20 years from a scientific experiment to a commonly used technological tool. The scientific applications and engineering aspects of remote sensing systems have been studied extensively. However, most of these studies have been aimed at understanding individual aspects of the remote sensing process while relatively few have studied their interrelations. A motivation for studying these interrelationships has arisen with the advent of highly sophisticated configurable sensors as part of the Earth Observing System (EOS) proposed by NASA for the 1990's. Two approaches to investigating remote sensing systems are developed. In one approach, detailed models of the scene, the sensor, and the processing aspects of the system are implemented in a discrete simulation. This approach is useful in creating simulated images with desired characteristics for use in sensor or processing algorithm development. A less complete, but computationally simpler method based on a parametric model of the system is also developed. In this analytical model the various informational classes are parameterized by their spectral mean vector and covariance matrix. These class statistics are modified by models for the atmosphere, the sensor, and processing algorithms and an estimate made of the resulting classification accuracy among the informational classes. Application of these models is made to the study of the proposed High Resolution Imaging Spectrometer (HRIS). The interrelationships among observational conditions, sensor effects, and processing choices are investigated with several interesting results.

Kerekes, John Paul↗
DOE OSTI2025

Real-Time Xenon Sensor Analysis Report

Radiotracer release experiments were performed at the Nevada National Security Site in October 2022. The overall experiment was called the RElease ACTivity (REACT) experiment. Twenty-two real-time xenon sensors were deployed for each of four releases. Initial, quick-look analysis results were reported in December 2022. This report reviews the more comprehensive offline analysis effort that was conducted during the remainder of fiscal year 2023 by the Dynamic Networks venture. Improved energy stabilization routines were implemented along with an improved background subtraction routine compared to the original quicklook calculations. The relative detection efficiencies of all real-time sensors were examined. Finally, simulated detector response functions were coupled to two different meteorological models using the measured conditions for the final release (REACT-04) to compare simulated detections with measurements. While there is some agreement between the models and measured data on the detection locations and timing, there is less agreement on the magnitude of those detections. Future sensor and meteorological modeling work will be needed to improve the agreement and to examine the additional releases (REACT-01 through REACT-03).

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
NASA NTRS2004

Real-Time Unsteady Loads Measurements Using Hot-Film Sensors

Several flight-critical aerodynamic problems such as buffet, flutter, stall, and wing rock are strongly affected or caused by abrupt changes in unsteady aerodynamic loads and moments. Advanced sensing and flow diagnostic techniques have made possible simultaneous identification and tracking, in real-time, of the critical surface, viscosity-related aerodynamic phenomena under both steady and unsteady flight conditions. The wind tunnel study reported here correlates surface hot-film measurements of leading edge stagnation point and separation point, with unsteady aerodynamic loads on a NACA 0015 airfoil. Lift predicted from the correlation model matches lift obtained from pressure sensors for an airfoil undergoing harmonic pitchup and pitchdown motions. An analytical model was developed that demonstrates expected stall trends for pitchup and pitchdown motions. This report demonstrates an ability to obtain unsteady aerodynamic loads in real-time, which could lead to advances in air vehicle safety, performance, ride-quality, control, and health management.

Mangalam, Arun S.↗
NASA NTRS2011

C/NOFS Measurements of Magnetic Perturbations in the Low-Latitude Ionosphere During Magnetic Storms

The Vector Electric Field Investigation suite on the C/NOFS satellite includes a fluxgate magnetometer to monitor the Earth s magnetic fields in the low-latitude ionosphere. Measurements yield full magnetic vectors every second over the range of +/-45,000 nT with a one-bit resolution of 1.37 nT (16 bit A/D) in each component. The sensor s primary responsibility is to support calculations of both V x B and E x B with greater accuracy than can be obtained using standard magnetic field models. The data also contain information about large-scale current systems that, when analyzed in conjunction with electric field measurements, promise to significantly expand understanding of equatorial electrodynamics. We first compare in situ measurements with the POMME (Potsdam Magnetic Model of the Earth) model to establish in-flight sensor "calibrations" and to compute magnetic residuals. At low latitudes the residuals are predominately products of the storm time ring current. Since C/NOFS provides a complete coverage of all local times every 97 min, magnetic field data allow studies of the temporal evolution and local time variations of storm time ring current. The analysis demonstrates the feasibility of using instrumented spacecraft in low-inclination orbits to extract a timely proxy for the provisional Dst index and to specify the ring current s evolution.

Le, Guan↗
DOE OSTI2023

On data-driven energy flexibility quantification: A framework and case study

Building energy flexibility is an important resource for a sustainable and resilient power grid, and an important measure to reduce utility costs for building owners. Quantifying energy flexibility for existing buildings can provide critical insights in optimizing their operation. Data-driven methods for building energy modeling and analytics are gaining popularity due to the increasingly available sensor and meter infrastructure, affordable computational resources, and advanced modeling algorithms. However, their application in quantifying the energy flexibility of real buildings is still limited due to the heterogeneous data types and limited data availability. Here, this study proposes a framework for building-level data-driven energy flexibility quantification that considers different levels of data availability and use cases. Two case studies with real building data collected at different scales were conducted to demonstrate the proposed framework for different purposes.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
NASA NTRS2017

Online Multi-Modal Learning and Adaptive Information Trajectory Planning for Autonomous Exploration

In robotic information gathering missions, scientists are typically interested in understanding variables which require proxy measurements from specialized sensor suites to estimate. However, energy and time constraints limit how often these sensors can be used in a mission. Robots are also equipped with cheaper to use navigation sensors such as cameras. In this paper, we explore a challenging planning problem in which a robot is required to learn about a scientific variable of interest in an initially unknown environment by planning informative paths and deciding when and where to use its sensors. To tackle this we present two innovations: a Bayesian generative model framework to automatically learn correlations between expensive science sensors and cheaper to use navigation sensors online, and a sampling based approach to plan for multiple sensors while handling long horizons and budget constraints. Our approach does not grow in complexity with data and is anytime making it highly applicable to field robotics. We tested our approach extensively in simulation and validated it with real data collected during the 2014 Mojave Volatiles Prospector Mission. Our planning algorithm performs statistically significantly better than myopic approaches and at least as well as a coverage-based algorithm in an initially unknown environment while having added advantages of being able to exploit prior knowledge and handle other intricacies of the real world without further algorithmic modifications.

learning↗
NASA NTRS1972

Four-dimensional world-wide atmospheric models (surface to 25 km altitude)

Four-dimensional atmospheric models previously developed for use as input to atmospheric attenuation models are evaluated to determine where refinements are warranted. The models are refined where appropriate. A computerized technique is developed that has the unique capability of extracting mean monthly and daily variance profiles of moisture, temperature, density and pressure at 1 km intervals to the height of 25 km for any location on the globe. This capability could be very useful to planners of remote sensing of earth resources missions in that the profiles may be used as input to the attenuation models that predict the expected degradation of the sensor data. Recommendations are given for procedures to use the four-dimensional models in computer mission simulations and for the approach to combining the information provided by the 4-D models with that given by the global models.

Spiegler, D. B.↗
NASA NTRS1986

Design considerations for flight test of a fault inferring nonlinear detection system algorithm for avionics sensors

The modifications to the design of a fault inferring nonlinear detection system (FINDS) algorithm to accommodate flight computer constraints and the resulting impact on the algorithm performance are summarized. An overview of the flight data-driven FINDS algorithm is presented. This is followed by a brief analysis of the effects of modifications to the algorithm on program size and execution speed. Significant improvements in estimation performance for the aircraft states and normal operating sensor biases, which have resulted from improved noise design parameters and a new steady-state wind model, are documented. The aircraft state and sensor bias estimation performances of the algorithm's extended Kalman filter are presented as a function of update frequency of the piecewise constant filter gains. The results of a new detection system strategy and failure detection performance, as a function of gain update frequency, are also presented.

Caglayan, A. K.↗
NASA NTRS1986

Design considerations for flight test of a fault inferring nonlinear detection system algorithm for avionics sensors

This paper summarizes the modifications made to the design of a fault inferring nonlinear detection system (FINDS) algorithm to accommodate flight computer constraints and the resulting impact on the algorithm performance. An overview of the flight data-driven FINDS algorithm is presented. This is followed by a brief analysis of the effects of modifications to the algorithm on program size and execution speed. Significant improvements in estimation performance for the aircraft states and normal operating sensor biases, which have resulted from improved noise design parameters and a new steady-state wind model, are documented. The aircraft state and sensor bias estimation performances of the algorithm's extended Kalman filter are presented as a function of update frequency of the piecewise constant filter gains. The results of a new detection system strategy and failure detection performance, as a function of an update frequency, are also presented.

Caglayan, A. K.↗
NASA NTRS1991

Optical and mechanical response of high temperature optical fiber sensors

The National Aerospace Plane (NASP) will experience temperatures as high as 2500 F at critical locations in its structure. Optical fiber sensors were proposed as a means of monitoring the temperature in these critical regions by either bonding the optical fiber to, or embedding the optical fiber in, metal matrix composite (MMC) components. Unfortunately, the anticipated NASP temperature ranges exceed the glass transition region of the optical fiber glass. The attempt is made to define the operating temperature range of optical fiber sensors from both optical and mechanical perspectives. A full non-linear optical analysis was performed by modeling the optical response of an isolated sensor cyclically driven through the glass transition region.

Sirkis, Jim↗
NASA NTRS1989

Model reduction in the physical coordinate system

In the dynamics modeling of a flexible structure, finite element analysis employs reduction techniques, such as Guyan's reduction, to remove some of the insignificant physical coordinates, thus producing a dynamics model that has smaller mass and stiffness matrices. But this reduction is limited in the sense that it removes certain degrees of freedom at a node points themselves in the model. From the standpoint of linear control design, the resultant model is still too large despite the reduction. Thus, some form of the model reduction is frequently used in control design by approximating a large dynamical system with a fewer number of state variables. However, a problem arises from the placement of sensors and actuators in the reduced model, because a model usually undergoes, before being reduced, some form of coordinate transformations that do not preserve the physical meanings of the states. To correct such a problem, a method is developed that expresses a reduced model in terms of a subset of the original states. The proposed method starts with a dynamic model that is originated and reduced in finite element analysis. Then the model is converted to the state space form, and reduced again by the internal balancing method. At this point, being in the balanced coordinate system, the states in the reduced model have no apparent resemblance to those of the original model. Through another coordinate transformation that is developed, however, this reduced model is expressed by a subset of the original states.

Yae, K. Harold↗
NASA NTRS1995

Effects of yaw and pitch motion on model attitude measurements

This report presents a theoretical analysis of the dynamic effects of angular motion in yaw and pitch on model attitude measurements in which inertial sensors were used during wind tunnel tests. A technique is developed to reduce the error caused by these effects. The analysis shows that a 20-to-1 reduction in model attitude measurement error caused by angular motion is possible with this technique.

Tcheng, Ping↗
NASA NTRS2009

NASA Orbital Debris Engineering Model ORDEM2008 (Beta Version)

This is an interim document intended to accompany the beta-release of the ORDEM2008 model. As such it provides the user with a guide for its use, a list of its capabilities, a brief summary of model development, and appendices included to educate the user as to typical runtimes for different orbit configurations. More detailed documentation will be delivered with the final product. ORDEM2008 supersedes NASA's previous model - ORDEM2000. The availability of new sensor and in situ data, the re-analysis of older data, and the development of new analytical techniques, has enabled the construction of this more comprehensive and sophisticated model. Integrated with the software is an upgraded graphical user interface (GUI), which uses project-oriented organization and provides the user with graphical representations of numerous output data products. These range from the conventional average debris size vs. flux magnitude for chosen analysis orbits, to the more complex color-contoured two-dimensional (2-D) directional flux diagrams in terms of local spacecraft pitch and yaw.

Stansbery, Eugene G.↗
NASA NTRS2000

Robust Fault Detection for Aircraft Using Mixed Structured Singular Value Theory and Fuzzy Logic

The purpose of fault detection is to identify when a fault or failure has occurred in a system such as an aircraft or expendable launch vehicle. The faults may occur in sensors, actuators, structural components, etc. One of the primary approaches to model-based fault detection relies on analytical redundancy. That is the output of a computer-based model (actually a state estimator) is compared with the sensor measurements of the actual system to determine when a fault has occurred. Unfortunately, the state estimator is based on an idealized mathematical description of the underlying plant that is never totally accurate. As a result of these modeling errors, false alarms can occur. This research uses mixed structured singular value theory, a relatively recent and powerful robustness analysis tool, to develop robust estimators and demonstrates the use of these estimators in fault detection. To allow qualitative human experience to be effectively incorporated into the detection process fuzzy logic is used to predict the seriousness of the fault that has occurred.

Collins, Emmanuel G.↗
NASA NTRS2001

Use of Remotely-Sensed Rainfall Data in Global Modeling and Data Assimilation

Precipitation observations derived from microwave sensors available from the Tropical Rainfall Measuring Mission (TRMM) and the proposed Global Precipitation Mission (GPM) can provide crucial information needed for improving global modeling, data assimilation, and numerical weather prediction. New methodologies are being developed at NASA to make effective use of this new data type in these applications. Currently, global analyses contain significant errors in primary hydrological fields such as precipitation and evaporation, especially in the tropics. We show that assimilating 6-h averaged TRMM rainfall retrievals improves not only the hydrological cycle but also key climate parameters such as clouds, radiation, and the upper tropospheric moisture in the analysis produced by the Goddard Earth Observing System (GEOS) Data Assimilation System. The improved analysis also leads to improved short-range forecasts in the tropics. The above results were obtained using a variational assimilation procedure that uses rainfall observations to derive moisture and temperature tendency corrections every 6 hours to compensate for errors arising from imperfect initial conditions and deficiencies in the model physics. We will describe a developmental path towards using space-borne rainfall data to empirically estimate and correct for state-dependent systematic errors in parameterized model physics. The study provides a demonstration of the potential of using remote-sensed rainfall data from microwave instruments to improve the 4-dimensional global datasets for climate analysis and numerical weather prediction.

Hou, Arthur↗
DOE OSTI2018

NDT System for Metal Components in Concrete Structures (Final Report)

Steel reinforcements embedded within concrete can corrode and crack, leading to weakening of the structures, and existing NDT (non-destructive testing) techniques do not provide the full picture. Condition assessment is critical in evaluating these structures in order to ensure safe, long-term operation of the nuclear power plants. Improved NDT techniques are needed as the nation’s generating stations age and require action based on increasingly critical inspection data. The power industry uses eddy current test (ECT) during in-service inspections to detect and monitor defects such as cracks and corrosion in metals, particularly metal pipes. However, the detection of defects in the reinforcing steel embedded in concrete is far more challenging for numerous reasons. Primary among them is the concrete layer’s thickness, which prevents the ability to have a close proximity between sensor and metallic sample. One solution to this problem is to create a higher sensitivity technique which can inspect at depth, with good spatial resolution and excellent directional sensitivity, to isolate the metal buried deep in the concrete and characterize defects in the metal. The goal of the phase II research program was to study and develop a new reinforced concrete NDT technology based on anisotropic magnetoresistive (AMR) sensors designed specifically for ECT of steel reinforcements in concrete. The first technical objective was to demonstrate the capability of inspecting steel reinforcement structures, including metal rebar and tensioning cable at or below 6” of depth embedded in concrete. Another objective was to be able to confidently identify multiple layers of reinforcements at varying depths. In addition, the technique needed to be able to provide condition assessment of the metal, providing data on the structure and positioning of the steel members, material loss, and detection of the presence of breaks. An important part of the research and development was aimed at achieving superior performance compared to existing technology. The ability to detect corrosion breaks in unbonded multi-wire and multi-strand tendons was another important objective. The final objective that led to a successful program was to build a complete prototype portable scanning system capable of demonstrating the probe performance in the field. All of these objectives were met, which provided data for the system development work going forward. RMD worked with the engineering firm Simpson Gumpertz & Heger to develop a detailed problem definition for concrete structures and the necessary sensor specifications. In addition, we developed finite element simulation models for the eddy current based NDT system through the analysis of the electromagnetic (EM) properties of sample materials and the orientation of the transmitter, sensor array (receivers), metal, and intervening materials like concrete and air. Based on the modeling and specifications, we designed and fabricated prototype sensor modules. We then acquired and fabricated test samples to characterize and optimize the sensors. Finally, we built a complete prototype for testing on actual concrete structures. This new NDT technology has high promise for greatly improving capabilities in the inspection of steel reinforcements within concrete structures, such as rebar, liners, anchors, and prestressing cables. This method could be valuable in the maintenance of nuclear power plants, and many other structures critical to our nation’s infrastructure.

42 ENGINEERING↗
DOE OSTI2016

Development and evaluation of virtual refrigerant mass flow sensors for fault detection and diagnostics

Refrigerant mass flow rate is an important measurement for monitoring equipment performance and enabling fault detection and diagnostics. However, a traditional mass flow meter is expensive to purchase and install. A virtual refrigerant mass flow sensor (VRMF) uses a mathematical model to estimate flow rate using low-cost measurements and can potentially be implemented at low cost. This study evaluates three VRMFs for estimating refrigerant mass flow rate. The first model uses a compressor map that relates refrigerant flow rate to measurements of inlet and outlet pressure, and inlet temperature measurements. The second model uses an energy-balance method on the compressor that uses a compressor map for power consumption, which is relatively independent of compressor faults that influence mass flow rate. The third model is developed using an empirical correlation for an electronic expansion valve (EEV) based on an orifice equation. The three VRMFs are shown to work well in estimating refrigerant mass flow rate for various systems under fault-free conditions with less than 5% RMS error. Each of the three mass flow rate estimates can be utilized to diagnose and track the following faults: 1) loss of compressor performance, 2) fouled condenser or evaporator filter, 3) faulty expansion device, respectively. For example, a compressor refrigerant flow map model only provides an accurate estimation when the compressor operates normally. When a compressor is not delivering the expected flow due to a leaky suction or discharge valve or other internal fault, the energy-balance or EEV model can provide accurate flow estimates. In this paper, the flow differences provide an indication of loss of compressor performance and can be used for fault detection and diagnostics.

Kim, Woohyun↗