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This project will focus on diagnostics and quality control understandings of continuously produced FFI membranes [both Anion Exchange Membrane (AEM) and Proton Exchange Membrane (PEM)] and continuously produced FFI electrodes. Optimization of methods and novel quality control techniques will be developed as needed.
Aerospace requirements have engendered the need for instruments for automatic determination of trace impurities in liquid and gaseous systems by in-line continuous operation. These include devices for the automatic sizing and counting of minute particles (below 0.1 mm) is closed liquid and gaseous systems, and the automatic determination of nonvolatile residue in solvents and traces of hydrocarbons dissolved or dispersed in gaseous systems. The principle of operation, and characteristics of instruments, as well as results of experimental testing, are briefly described. Potential industrial applications are also suggested.
Monitoring and regulating the pH of the solution in a bioprocess is one of the key steps in the success of bioreactor operation. An in-line optical pH sensor, based on the optical absorption properties of phenol red present in the medium, was developed and tested in this work for use in NASA space bioreactors based on a rotating wall-perfused vessel system supporting a baby hamster kidney (BHK-21) cell culture. The sensor was tested over three 30-day and one 124-day cell runs. The pH sensor initially was calibrated and then used during the entire cell culture interval. The pH reported by the sensor was compared to that measured by a fiber optically coupled Shimadzu spectrophotometer and a blood gas analyzer. The maximum standard error of prediction for all the four cell runs for development pH sensor against BGA was +/-0.06 pH unit and for the fiber optically coupled Shimadzu spectrophotometer against the blood gas analyzer was +/-0.05 pH unit. The pH sensor system performed well without need of recalibration for 124 days. Copyright 2002 Wiley Periodicals, Inc.
For long-term growth of man1ITlalian cells in perfused bioreactors, it is essential to monitor the concentration of dissolved oxygen (DO) present in the culture medium to quantitate and control level of DO. Continuous measurement of the amount of DO in the cell culture medium in-line under sterile conditions in NASA's perfused bioreactor requires that the oxygen sensor provide increased sensitivity and be sterilizable and nontoxic. Additionally, long-term cell culture experiments require that the calibration be maintained several weeks or months. Although there are a number of sensors for dissolved oxygen on the market and under development elsewhere, very few meet these stringent conditions. An optical oxygen sensor (BOXY) based on dynamic fluorescent quenching and a pulsed blue LED light source was developed in our laboratory to address these requirements. Tris( 4,7 -diphenyl-l, 1 O-phenanthroline )ruthenium(II) chloride is employed as the fluorescent dye indicator. The sensing element consists of a glass capillary (OD 4.0 mm; ID 2.0 mm) coated internally with a thin layer of the fluorescent dye in silicone matrix and overlayed with a black shielding layer. Irradiation of the sensing element with blue light (blue LED with emission maximum at 475 nm) generates a red fluorescence centered at 626 nm. The fluorescence intensity is correlated to the concentration of DO present in the culture medium, following the modified non-linear Stern-Volmer equation. By using a pulsed irradiating light source, the problem of dye-bleaching, which is often encountered in long-term continuous measurements of tIns type, 'is minimized. To date we achieved sensor resolution of 0.3 mmHg at 50 mmHg p02, and 0.6 mmHg at 100 mmHg p02, with a response time of about one minute. Calibration was accomplished in sterile phosphate-buffered saline with a blood-gas analyzer (BGA) measurement as reference. Stand-alone software was also developed to control the sensor and bioreactor as well as to acquire data. Two HOXY sensors with a single calibration were employed to continuously monitor the DO in GTSF-2 medium during a Baby Hamster Kidney (BHK-21) cell culture in a Rotating Wall Perfused Vessel (RWPV) bioreactor for 90 days. HOXY sensors were located at the inlet to and outlet from the bioreactor. One of the sensors was placed between an oxygenator and the inlet to the bioreactor. The dissolved oxygen concentrations determined by both sensors were compared with those measured regularly with the BGA reference. The cell culture was maintained for 110 days. Sensor output was found to correlate well with the BGA data throughout the experiment, where the DO of the medium ranged between 25 and 50 mmHg at the bioreactor outlet and 90-130 mmHg at the bioreactor inlet. Measuring DO with the HOXY sensors versus the BGA reference indicated bias values of -2 mmHg and -15 mmHg, and precision values of +/-3mmHg and +/-16 mmHg at the bioreactor inlet and outlet, respectively.
Ammonia monitor and method of use are disclosed. A continuous, real-time determination of the concentration of ammonia in an aqueous process stream is possible over a wide dynamic range of concentrations. No reagents are required because pH is controlled by an in-line solid-phase base. Ammonia is selectively transported across a membrane from the process stream to an analytical stream to an analytical stream under pH control. The specific electrical conductance of the analytical stream is measured and used to determine the concentration of ammonia.
Resistance Spot Welding (RSW) is a critical process in the automotive industry, valued for its cost-effectiveness, short cycle time, and robustness. However, achieving consistent high-quality joints remains challenging due to the complex interplay of various factors, like materials, processes, and manufacturing uncertainties, etc. Under the collaborative project between Oak Ridge National Laboratory (ORNL) and General Motors (GM), we have developed a robust and expansible machine learning (ML) framework aimed at enhancing quality control in RSW. By harnessing the power of machine learning, we have developed the ability to ensure every aspect of the welding process, from the initial process design stage to the final weld joint quality. The framework operates by analyzing a variety of data streams, including in-line process signals, process parameters, materials, and postprocessed weld joint data. Through this analysis, the models have been trained to detect deviations from optimal quality standards, leveraging their ability to identify signature data patterns and anomalies within in-line signals and construct complex correlations between these signals and weld quality parameters. Meanwhile, the machine learning framework is designed to adapt to a variety of materials, including high strength steels and aluminum alloys, etc. Its flexible architecture facilitates the incorporation of diverse data sources and features, enabling precise modeling and prediction across a broad range of material properties and weld quality variables. The expansible ML frameworks represent a promising transformation in weld quality monitoring and control, empowering industry to achieve high levels of efficiency, consistency, and reliability in manufacturing.
Resistance Spot Welding (RSW) is a critical process in the automotive industry, valued for its cost-effectiveness, short cycle time, and robustness. However, achieving consistent high-quality joints remains challenging due to the complex interplay of various factors, like materials, processes, and manufacturing uncertainties, etc. Under the collaborative project between Oak Ridge National Laboratory (ORNL) and General Motors (GM), we have developed a robust and expansible machine learning (ML) framework aimed at enhancing quality control in RSW. By harnessing the power of machine learning, we have developed the ability to ensure every aspect of the welding process, from the initial process design stage to the final weld joint quality. The framework operates by analyzing a variety of data streams, including in-line process signals, process parameters, materials, and postprocessed weld joint data. Through this analysis, the models have been trained to detect deviations from optimal quality standards, leveraging their ability to identify signature data patterns and anomalies within in-line signals and construct complex correlations between these signals and weld quality parameters. Meanwhile, the machine learning framework is designed to adapt to a variety of materials, including high strength steels and aluminum alloys, etc. Its flexible architecture facilitates the incorporation of diverse data sources and features, enabling precise modeling and prediction across a broad range of material properties and weld quality variables. The expansible ML frameworks represent a promising transformation in weld quality monitoring and control, empowering industry to achieve high levels of efficiency, consistency, and reliability in manufacturing.
Effective quality control (QC) for manufacturing proton exchange membrane water electrolysis (PEMWE) components is critical to enabling widespread adoption of the technology for hydrogen generation. This study investigates X-ray radiography as a novel, high-throughput, potentially in-line QC technique for detecting defects and assessing material property distributions in titanium-based porous transport layers (PTLs) which constitute a crucial component of low temperature PEMWE stacks. We obtain radiographs of a set of fifteen PTLs and model their absorbance of the broadband radiation as a second-order polynomial to account for the non-monoenergetic radiation source used in this study. The resulting model serves as a basis for predicting the areal density and porosity distributions of the PTLs. We find radiography successful in detecting multiple instances of defects, including holes/depressions, cracks, and excess material on the surface or in the pores of the material, demonstrating its potential as a robust in-line QC tool for PTL manufacturing.
An in-line, three element, large diameter, optical display lens is disclosed which has a front convex-convex element, a central convex-concave element, and a rear convex-convex element. The lens, used in flight simulators, magnifies an image presented on a television monitor and, by causing light rays leaving the lens to be in essentially parallel paths, reduces eye strain of the simulator operator.
In recent years, security monitoring of public places and critical infrastructure has heavily relied on the widespread use of cameras, raising concerns about personal privacy violations. To balance the need for effective security monitoring with the protection of personal privacy, we explore the potential of optical fiber sensors for this application. This article proposes FiberFlex, an intelligent and distributed fiber sensor system. Ultizing Field Programmable Gate Arrays (FPGA) high-level synthesis (HLS) acceleration, FiberFlex offers real-time pedestrian detection by co-designing the entire pipeline of optical signal acquisition, processing, and recognition networks based on the principles of optical fiber sensing. As a promising alternative to traditional camera-based monitoring systems, FiberFlex achieves pedestrian detection by analyzing the vibration patterns caused by pedestrian footsteps, enabling security monitoring while preserving individual privacy. FiberFlex comprises three modules: First , fiber-optic sensing system: A fiber-optic distributed acoustic sensing (DAS) system is built and used to measure the ground vibration waves generated by people walking. Second , algorithms: We first collect the training data by measuring the ground vibration waves, label the data, and use the data to train the neural network models to perform pedestrian recognition. Third , hardware accelerators: We use HLS tools to design hardware modules on FPGA for data collection and pre-processing and integrate them with the downstream neural network accelerators to perform in-line real-time pedestrian detection. The final detection results are sent back from FPGA to the host CPU. We implement our system FiberFlex with the in-house built DAS system and AMD/Xilinx Kintex7 FPGA KC705 board and verify the whole system using the real-world collected data. We conduct recognition tests on five test subjects of varying ages, heights, and weights in a fixed sensing area. Each subject experienced 20 real-time recognition tests using their daily walking habits, and the subjects were given adequate rest between tests. After 100 tests on five test subjects, the overall real-time recognition accuracy exceeded \(88.0\%\) . The whole system uses 55 W of power, 33 W in the optical DAS system and 22 W in the FPGA. Relying on its end-to-end interdisciplinary design, FiberFlex seamlessly combines fiber-optic sensors with FPGA accelerators to enable low-power real-time security monitoring without compromising privacy, making it a valuable addition to the existing security monitoring network. According to FiberFlex, more valuable research can be conducted in the future, such as fall monitoring for the elderly, migration of identification networks between different application scenarios, and improvement of anti-interference performance in more complex environments. In future perception networks, where the “eyes” are not feasible, let’s use fiber optic touch instead.
Laser-induced breakdown spectroscopy (LIBS) is being developed as an analytical monitoring tool for molten salt reactor (MSR) systems. A mobile LIBS platform was configured on a small-scale salt vessel (~100 g of salt) and then transported 0.6 km to successfully monitor an engineering-scale pumped salt loop (~100 kg of salt). Several studies on monitoring salt aerosols, hydrogen isotopes, and noble gases were performed on the small-scale system. All these studies were then implemented for monitoring various tests on the engineering-scale loop. Aerosolized salts from both the storage tank and pump bowl were monitored using LIBS to assess bulk salt analyte ratios (Mg, Na, K) and evaluate impurities (H, O, Ca). In addition to monitoring salt aerosols, LIBS was used in tandem with a residual gas analyzer (RGA) and a Raman spectroscopy system to detect hydrogen isotopes as they were sparged through and subsequently depleted from the loop storage tank. Lastly, a similar test with noble gases (100 ppm Kr, 1000 ppm Xe) was performed, in which LIBS demonstrated a faster response than the RGA used in-line. The tests and results are summarized in this report with detailed publications to follow. Key takeaways are listed in the conclusion of the report.
A fiber-optic visible–near-infrared (vis–NIR) absorption spectroscopy and flow sensor system has been developed for near-real-time tracking of Nd mass in the effluent stream from a column in a fume hood. The approach leverages two unique data streams and a partial least-squares regression (PLSR) model trained on vis–NIR absorption spectra of Nd(III) (0–1.5 M) in 1 M HNO 3 . In-line volumetric flow rate and vis–NIR spectra are measured in sequence after a chromatography column. The time stamps from each data stream are then synchronized, which allows integrated volumes to be combined with Nd(III) molarities predicted by a PLSR model to accurately calculate the Nd mass flowing through the column. This integrated measurement provides instantaneous mass flow and accumulates these data over time to obtain the total mass processed. The methodology developed in this study contributes critical technical infrastructure to improve monitoring capabilities to support chemical separations and the production of strategic materials and isotopes.
A capacitance/dielectric sensor was designed, constructed, and used to measure in real time the in-situ water concentration in a desiccant water bed. Measurements were carried out with two experimental setups: (1) passing nitrogen through a humidity generator and allowing the gas stream to become saturated at a measured temperature and pressure, and (2) injecting water via a syringe pump into a nitrogen stream. Both water vapor generating devices were attached to a downstream vertically-mounted water capture bed filled with 19.5 g of Moisture Gone desiccant. The sensor consisted of two electrodes: (1) a 1/8" dia stainless steel rod placed in the middle of the bed and (2) the outer shell of the stainless steel bed concentric with the rod. All phases of the water capture process (background, heating, absorption, desorption, and cooling) were monitored with capacitance. The measured capacitance was found to vary linearly with the water content in the bed at frequencies above 100 kHz indicating dipolar motion dominated the signal; below this frequency, ionic motion caused nonlinearities in the water concentration/capacitance relationship. The desiccant exhibited a dielectric relaxation whose activation energy was lowered upon addition of water indicating either a less hindered rotational motion or crystal reorientation.
Exposure to microgravity during human spaceflight needs to be better understood as the human exploration of space requires longer duration missions. It is known that long term exposure to microgravity causes bone loss. Measuring the calcium and other metabolic byproducts in a crew member s urine can evaluate the effectiveness of bone loss countermeasures. The International Space Station (ISS) Urine Monitoring System (UMS) is an automated urine collection device designed to collect urine, separate the urine and air, measure the void volume, and allow for syringe sampling. Accurate measuring and minimal cross-contamination is essential to determine bone loss and the effectiveness of countermeasures. The ISS UMS provides minimal cross-contamination (<0.7 mL urine) and has volume accuracy of 2% between 100 to 1000 mL urine voids. Designed to provide a non-invasive means to collect urine samples from crew members, the ISS UMS operates in-line with the Node 3 Waste and Hygiene Compartment (WHC). The ISS UMS has undergone modifications required to interface with the WHC, including material changes, science algorithm improvements, and software platform revisions. Integrated functional testing was performed to determine the pressure drop, air flow rate, and the maximum amount of fluid capable of being discharged from the UMS to the WHC. This paper will detail the results of the science and the functional integration tests.
The problems associated with blending of the AMK additive with Jet A, and the base fuel effects on AMK properties are addressed. The results from the evaluation of some of the quality control techniques for AMK are presented. The principal conclusions of this investigation are: significant compositional differences for base fuel (Jet A) within the ASTM specification DI655; higher aromatic content of the base fuel was found to be beneficial for the polymer dissolution at ambient (20 C) temperature; using static mixer technology, the antimisting additive (FM-9) is in-line blended with Jet A, producing AMK which has adequate fire-protection properties 15 to 20 minutes after blending; degradability of freshly blended and equilibrated AMK indicated that maximum degradability is reached after adequate fire protection is obtained; the results of AMK degradability as measured by filter ratio, confirmed previous RAE data that power requirements to decade freshly blended AMK are significantly higher than equilibrated AMK; blending of the additive by using FM-9 concentrate in Jet A produces equilibrated AMK almost instantly; nephelometry offers a simple continuous monitoring capability and is used as a real time quality control device for AMK; and trajectory (jet thurst) and pressure drop tests are useful laboratory techniques for evaluating AMK quality.
For detection, identification and characterization of crude oil we combine several optical methods of remote sensing of crude oil films and emulsions (coherent fringe projection illumination (CFP), holographic in-line interferometry (HILI), and laser induced fluorescence). These methods allow the three-dimensional characterization of oil spills, important for practical applications. Combined methods of CFP and HILI are described in the frame of coherent superposition of partial interference patterns. It is shown, that in addition to detection/identification laser illumination in the green-blue region can also degrade oil slicks. Different types of surfaces contaminated by oil spills are tested: oil on the water, oil on the flat solid surfaces and oil on the curved surfaces of pipes. For the detection and monitoring of the laser-induced oil degradation in pipes, coherent fiber bundles were used. Both continuous-wave (CW) and pulsed lasers are tested using pump-probe schemes. This finding suggests that properly structured laser clean-up can be an alternative environmentally-friendly method of decontamination, as compared to the currently used chemical methods that are dangerous to environment.
A prototype bismuth propellant feed and control system was constructed and tested. An electromagnetic pump was used in this system to provide fine control of the hydrostatic pressure, and a new type of in-line flow sensor was developed to provide an accurate, real-time measurement of the mass flow rate. High-temperature material compatibility was a driving design requirement for the pump and flow sensor, leading to the selection of macor for the main body of both components. Post-test inspections of both components revealed no cracks or leaking in either. In separate proof-of-concept experiments, the pump produced a linear pressure rise as a function of current that compared favorably with theoretical pump pressure predictions, with a pressure of 10 kPa at 30 A. Flow sensing was successfully demonstrated in a bench-top test using gallium as a substitute liquid metal. A real-time controller was successfully used to control the entire system, simultaneously monitoring all power supplies and performing data acquisition duties.
Two prototype bismuth propellant feed systems were constructed and operated in conjunction with a propellant vaporizer. One system provided bismuth to a vaporizer using gas pressurization but did not include a means to measure the flow rate. The second system incorporated an electromagnetic pump to provide fine control of the hydrostatic pressure and a new type of in-line flow sensor that was developed for accurate, real-time measurement of the mass flow rate. High-temperature material compatibility was a driving design requirement for the pump and flow sensor, leading to the selection of Macor for the main body of both components. Posttest inspections of both components revealed no degradation of the material. The gas pressurization system demonstrated continuous pressure control over a range from zero to 200 torr. In separate proof-of-concept experiments, the electromagnetic pump produced a linear pressure rise as a function of current that compared favorably with theoretical pump pressure predictions, producing a pressure rise of 10 kPa at 30 A. Preliminary flow sensor operation indicated a bismuth flow rate of 6 mg/s with an uncertainty of plus or minus 6%. An electronics suite containing a real-time controller was successfully used to control the entire system, simultaneously monitoring all power supplies and performing data acquisition duties.