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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 55 records · Page 3
All sourcesNASA NTRSDOE OSTI
NASA NTRS2019

Assessment of Upper Body Posture and Shape with Garment-Embedded Flexible Strain Sensors

Spacesuits are critical to performing spacewalks or EVA, however can increase injury risks due to - Spacesuit Fit Concerns: Astronauts come from a diverse population; Improper suit fit will result in persistent contact and mechanical pressure on the body. - Altered Biomechanics: Mechanical constraints and pressurization can make it difficult due to - Reduced range of motion, Reduced strength capability. To improve suit design and mitigate injuries, kinematic and geometric measurements are required during EVA evaluations - Human motions inside a spacesuit may not coincide with the suit motions: Spacesuit configurations do not exactly match with human anatomical joints; Gaps/paddings inside the suit induce lags between human motion and suit motion - Conventional motion capture or 3-D scanning techniques are difficult to use to measure internal motion: Optical occlusions; Volume restrictions; Ferrous magnetic interference.

Vu, Linh↗
NASA NTRS1992

Development of an embedded Fabry Perot Fiber Optic Strain Rosette Sensor (FP-FOSRS)

We investigate the feasibility of utilizing a Fabry-Perot Fiber Optic Strain Rosette Sensor (FP-FOSRS) for the evaluation of the internal strain state of a material system. We briefly describe the manufacturing process for this sensor and point out some potential problem areas. Results of an embedded FP-FOSRS in an epoxy matrix with external resistance strain gauges applied for comparative purposes are presented. We show that the internal and external strain measurements are in close agreement. This work lays the foundation for embedding this sensor in actual composite laminas.

Carman, Gregory P.↗
NASA NTRS1995

Optical fiber sensors for damage analysis in aerospace materials

Under this grant, fiber optic sensors were investigated for use in the nondestructive evaluation of aging aircraft. Specifically, optical fiber sensors for detection and location of impacts on a surface, and for detection of corrosion in metals were developed. The use of neural networks was investigated for determining impact location by processing the output of a network of fiberoptic strain sensors distributed on a surface. This approach employs triangulation to determine location by comparing the arrival times at several sensors, of the acoustic signal generated by the impact. For this study, a neural network simulator running on a personal computer was used to train a network using a back-propagation algorithm. Fiber optic extrinsic Fabry-Perot interferometer (EFPI) strain sensors are attached to or embedded in the surface, so that stress waves emanating from an impact can be detected. The ability of the network to determine impact location by time-or-arrival of acoustic signals was assessed by comparing network outputs with actual experimental results using impacts on a panel instrumented with optical fiber sensors. Using the neural network to process the sensor outputs, the impact location can be inferred to centimeter range accuracy directly from the arrival time data. In addition, the network can be trained to determine impact location, regardless of material anisotropy. Results demonstrate that a back-propagation network identifies impact location for an anisotropic graphite/bismaleimide plate with the same accuracy as that for an isotropic aluminum plate. Two different approaches were investigated for the development of fiber optic sensors for corrosion detection in metals, both utilizing optical fiber sensors with metal coatings. In the first approach, an extrinsic Fabry-Perot interferometric fiber optic strain sensor was placed under tensile stress, and while in the resulting strained position, a thick coating of metal was applied. Due to an increase in the quantity of material, the sensor does not return to its original position upon removal of the applied stress, and some residual strain is maintained within the sensor element. As the metal thickness decreases due to corrosion, this strain is released, providing the sensing mechanism for corrosion detection. In the second approach, photosensitive optical fibers with long period Bragg gratings in the core were coated with metal. The Bragg gratings serve to couple core modes at discrete wavelengths to cladding modes. Since cladding modes interact with the metal coating surrounding the fiber cladding, the specific wavelengths coupled from core to cladding depend on the refractive index of the metal coating. Therefore, as the metal corrodes, the resulting change in index of the coating may be measured by measuring the change in wavelength of the coupled mode. Results demonstrate that both approaches can be successfully used to track the loss in metal coating on the optical fiber sensors due to corrosion.

Schindler, Paul↗
NASA NTRS2000

Characteristics of Extrinsic Fabry-Perot Interferometric (EFPI) Fiber-Optic Strain Gages

The focus of this paper is a comparison of the strain-measuring characteristics of one type of commercially available fiber-optic strain sensor with the performance of conventional resistance strain gages. Fabry-Perot type fiber-optic strain sensors were selected for this testing program. Comparative testing is emphasized and includes load testing at room temperature with apparent strain characterization cryogenically and at elevated temperatures. The absolute accuracy of either of these types of strain gages is not addressed.

Hare, David A.↗
NASA NTRS2013

Longitudinally Jointed Edge-Wise Compression HoneyComb Composite Sandwich Coupon Testing And Fe Analysis: Three Methods of Strain Measurement, And Comparison

Three distinct strain measurement methods (i.e., foil resistance strain gages, fiber optic strain sensors, and a three-dimensional digital image photogrammetry that gives full field strain and displacement measurements) were implemented to measure strains on the back and front surfaces of a longitudinally jointed curved test article subjected to edge-wise compression testing, at NASA Goddard Space Flight Center, according to ASTM C364. The pre-test finite element analysis (FEA) was conducted to assess ultimate failure load and predict strain distribution pattern throughout the test coupon. The predicted strain pattern contours were then utilized as guidelines for installing the strain measurement instrumentations. The foil resistance strain gages and fiber optic strain sensors were bonded on the specimen at locations with nearly the same analytically predicted strain values, and as close as possible to each other, so that, comparisons between the measured strains by strain gages and fiber optic sensors, as well as the three-dimensional digital image photogrammetric system are relevant. The test article was loaded to failure (at ~167 kN), at the compressive strain value of ~10,000 micro epsilon. As a part of this study, the validity of the measured strains by fiber optic sensors is examined against the foil resistance strain gages and the three-dimensional digital image photogrammetric data, and comprehensive comparisons are made with FEA predictions.

Farrokh, Babak↗
NASA NTRS2007

Optical Fiber Distributed Sensing Structural Health Monitoring (SHM) Strain Measurements Taken During Cryotank Y-Joint Test Article Load Cycling at Liquid Helium Temperatures

This paper outlines cryogenic Y-joint testing at Langley Research Center (LaRC) to validate the performance of optical fiber Bragg grating strain sensors for measuring strain at liquid helium temperature (-240 C). This testing also verified survivability of fiber sensors after experiencing 10 thermal cool-down, warm-up cycles and 400 limit load cycles. Graphite composite skins bonded to a honeycomb substrate in a sandwich configuration comprised the Y-joint specimens. To enable SHM of composite cryotanks for consideration to future spacecraft, a light-weight, durable monitoring technology is needed. The fiber optic distributed Bragg grating strain sensing system developed at LaRC is a viable substitute for conventional strain gauges which are not practical for SHM. This distributed sensing technology uses an Optical Frequency Domain Reflectometer (OFDR). This measurement approach has the advantage that it can measure hundreds of Bragg grating sensors per fiber and the sensors are all written at one frequency, greatly simplifying fiber manufacturing. Fiber optic strain measurements compared well to conventional strain gauge measurements obtained during these tests. These results demonstrated a high potential for a successful implementation of a SHM system incorporating LaRC's fiber optic sensing system on the composite cryotank and other future cryogenic applications.

Allison, Sidney G.↗
NASA NTRS2005

Improved Method of Manufacturing SiC Devices

The phrase, "common-layered architecture for semiconductor silicon carbide" ("CLASSiC") denotes a method of batch fabrication of microelectromechanical and semiconductor devices from bulk silicon carbide. CLASSiC is the latest in a series of related methods developed in recent years in continuing efforts to standardize SiC-fabrication processes. CLASSiC encompasses both institutional and technological innovations that can be exploited separately or in combination to make the manufacture of SiC devices more economical. Examples of such devices are piezoresistive pressure sensors, strain gauges, vibration sensors, and turbulence-intensity sensors for use in harsh environments (e.g., high-temperature, high-pressure, corrosive atmospheres). The institutional innovation is to manufacture devices for different customers (individuals, companies, and/or other entities) simultaneously in the same batch. This innovation is based on utilization of the capability for fabrication, on the same substrate, of multiple SiC devices having different functionalities (see figure). Multiple customers can purchase shares of the area on the same substrate, each customer s share being apportioned according to the customer s production-volume requirement. This makes it possible for multiple customers to share costs in a common foundry, so that the capital equipment cost per customer in the inherently low-volume SiC-product market can be reduced significantly. One of the technological innovations is a five-mask process that is based on an established set of process design rules. The rules provide for standardization of the fabrication process, yet are flexible enough to enable multiple customers to lay out masks for their portions of the SiC substrate to provide for simultaneous batch fabrication of their various devices. In a related prior method, denoted multi-user fabrication in silicon carbide (MUSiC), the fabrication process is based largely on surface micromachining of poly SiC. However, in MUSiC one cannot exploit the superior sensing, thermomechanical, and electrical properties of single-crystal 6H-SiC or 4H-SiC. As a complement to MUSiC, the CLASSiC five-mask process can be utilized to fabricate multiple devices in bulk single-crystal SiC of any polytype. The five-mask process makes fabrication less complex because it eliminates the need for large-area deposition and removal of sacrificial material. Other innovations in CLASSiC pertain to selective etching of indium tin oxide and aluminum in connection with multilayer metallization. One major characteristic of bulk micromachined microelectromechanical devices is the presence of three-dimensional (3D) structures. Any 3D recesses that already exist at a given step in a fabrication process usually make it difficult to apply a planar coat of photoresist for metallization and other subsequent process steps. To overcome this difficulty, the CLASSiC process includes a reversal of part of the conventional flow: Metallization is performed before the recesses are etched.

Okojie, Robert S.↗
NASA NTRS2014

Virtual Deformation Control of the X-56A Model with Simulated Fiber Optic Sensors

A robust control law design methodology is presented to stabilize the X-56A model and command its wing shape. The X-56A was purposely designed to experience flutter modes in its flight envelope. The methodology introduces three phases: the controller design phase, the modal filter design phase, and the reference signal design phase. A mu-optimal controller is designed and made robust to speed and parameter variations. A conversion technique is presented for generating sensor strain modes from sensor deformation mode shapes. The sensor modes are utilized for modal filtering and simulating fiber optic sensors for feedback to the controller. To generate appropriate virtual deformation reference signals, rigid-body corrections are introduced to the deformation mode shapes. After successful completion of the phases, virtual deformation control is demonstrated. The wing is deformed and it is shown that angle-ofattack changes occur which could potentially be used to an advantage. The X-56A program must demonstrate active flutter suppression. It is shown that the virtual deformation controller can achieve active flutter suppression on the X-56A simulation model.

Suh, Peter M.↗
NASA NTRS2013

Virtual Deformation Control of the X-56A Model with Simulated Fiber Optic Sensors

A robust control law design methodology is presented to stabilize the X-56A model and command its wing shape. The X-56A was purposely designed to experience flutter modes in its flight envelope. The methodology introduces three phases: the controller design phase, the modal filter design phase, and the reference signal design phase. A mu-optimal controller is designed and made robust to speed and parameter variations. A conversion technique is presented for generating sensor strain modes from sensor deformation mode shapes. The sensor modes are utilized for modal filtering and simulating fiber optic sensors for feedback to the controller. To generate appropriate virtual deformation reference signals, rigid-body corrections are introduced to the deformation mode shapes. After successful completion of the phases, virtual deformation control is demonstrated. The wing is deformed and it is shown that angle-of-attack changes occur which could potentially be used to an advantage. The X-56A program must demonstrate active flutter suppression. It is shown that the virtual deformation controller can achieve active flutter suppression on the X-56A simulation model.

Modal Filter↗
NASA NTRS2016

Probabilistic Damage Characterization Using the Computationally-Efficient Bayesian Approach

This work presents a computationally-ecient approach for damage determination that quanti es uncertainty in the provided diagnosis. Given strain sensor data that are polluted with measurement errors, Bayesian inference is used to estimate the location, size, and orientation of damage. This approach uses Bayes' Theorem to combine any prior knowledge an analyst may have about the nature of the damage with information provided implicitly by the strain sensor data to form a posterior probability distribution over possible damage states. The unknown damage parameters are then estimated based on samples drawn numerically from this distribution using a Markov Chain Monte Carlo (MCMC) sampling algorithm. Several modi cations are made to the traditional Bayesian inference approach to provide signi cant computational speedup. First, an ecient surrogate model is constructed using sparse grid interpolation to replace a costly nite element model that must otherwise be evaluated for each sample drawn with MCMC. Next, the standard Bayesian posterior distribution is modi ed using a weighted likelihood formulation, which is shown to improve the convergence of the sampling process. Finally, a robust MCMC algorithm, Delayed Rejection Adaptive Metropolis (DRAM), is adopted to sample the probability distribution more eciently. Numerical examples demonstrate that the proposed framework e ectively provides damage estimates with uncertainty quanti cation and can yield orders of magnitude speedup over standard Bayesian approaches.

Warner, James E.↗