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All sourcesNASA NTRSDOE OSTI
DOE OSTI2015

Towards intelligent diagnostic system employing integration of mathematical and engineering model

The development of medical diagnostic system has been one of the main research fields during years. The goal of the medical diagnostic system is to place a nosological system that could ease the diagnostic evaluation normally performed by scientists and doctors. Efficient diagnostic evaluation is essentials and requires broad knowledge in order to improve conventional diagnostic system. Several approaches on developing the medical diagnostic system have been designed and tested since the earliest 60s. Attempts on improving their performance have been made which utilizes the fields of artificial intelligence, statistical analyses, mathematical model and engineering theories. With the availability of the microcomputer and software development as well as the promising aforementioned fields, medical diagnostic prototypes could be developed. In general, the medical diagnostic system consists of several stages, namely the 1) data acquisition, 2) feature extraction, 3) feature selection, and 4) classifications stages. Data acquisition stage plays an important role in converting the inputs measured from the real world physical conditions to the digital numeric values that can be manipulated by the computer system. One of the common medical inputs could be medical microscopic images, radiographic images, magnetic resonance image (MRI) as well as medical signals such as electrocardiogram (ECG) and electroencephalogram (EEG). Normally, the scientist or doctors have to deal with myriad of data and redundant to be processed. In order to reduce the complexity of the diagnosis process, only the significant features of the raw data such as peak value of the ECG signal or size of lesion in the mammogram images will be extracted and considered in the subsequent stages. Mathematical models and statistical analyses will be performed to select the most significant features to be classified. The statistical analyses such as principal component analysis and discriminant analysis as well as mathematical model of clustering technique have been widely used in developing the medical diagnostic systems. The selected features will be classified using mathematical models that embedded engineering theory such as artificial intelligence, support vector machine, neural network and fuzzy-neuro system. These classifiers will provide the diagnostic results without human intervention. Among many publishable researches, several prototypes have been developed namely NeuralPap, Neural Mammo, and Cervix Kit. The former system (NeuralPap) is an automatic intelligent diagnostic system for classifying and distinguishing between the normal and cervical cancerous cells. Meanwhile, the Cervix Kit is a portable Field-programmable gate array (FPGA)-based cervical diagnostic kit that could automatically diagnose the cancerous cell based on the images obtained during sampling test. Besides the cervical diagnostic system, the Neural Mammo system is developed to specifically aid the diagnosis of breast cancer using a fine needle aspiration image.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
NASA NTRS1976

A performance evaluation of various coatings, substrate materials, and solar collector systems

An experimental apparatus was constructed and utilized in conjunction with both a solar simulator and actual sunlight to test and evaluate various solar panel coatings, panel designs, and scaled-down collector subsystems. Data were taken by an automatic digital data acquisition system and reduced and printed by a computer system. The solar collector test setup, data acquisition system, and data reduction and printout systems were considered to have operated very satisfactorily. Test data indicated that there is a practical or useful limit in scaling down beyond which scaled-down testing cannot produce results comparable to results of larger scale tests. Test data are presented as are schematics and pictures of test equipment and test hardware.

Dolan, F. J.↗
NASA NTRS1990

RF/optical interference design for optical intersatellite links

A design approach for the RF/optical link interface for a data relay satellite is described. The flexibility of forward and return links in future data acquisition satellites in handling varying missions and data rates to 1 Gbit/s is considered. Attention is focused on requirements for the NASA Tracking and Data Acquisition System. System components are described including the return link multiplexer, the return link transmultiplexer, the forward link multiplexer, the forward link demultiplexer, and the frontside/backside switch. Ping-pong buffers, which provide rate buffering for each input data stream, are discussed and justification bits, which handle variations due to Doppler shift and local oscillator variation, are considered. The time-division multiplexed streams consist of a unique synchronization word for frame synchronization, and control words associated with each data burst to identify the presence or absence of a justification bit. Redundant data paths are described for both forward and return data streams.

Garlow, Ronald K.↗
DOE OSTI2021

Integrating Applied Energy and BER Smart Data Capabilities to Develop a DOE Data Fabric for Energy-Water R&D

Focal Area(s): 1) Data acquisition and assimilation enabled by machine learning, AI, and advanced methods including experimental/network design/optimization, unsupervised learning (including deep learning), and hardware-related efforts involving AI (e.g., edge computing). Science Challenge: DOE R&D, including DOE’s Basic Energy Research (BER)’s Environmental Systems Science Division (EESSD) program and DOE’s applied energy research (AER) programs (EERE, FE, and NE) are producers and consumers of Earth systems datasets. This white paper focuses on the first topic area from the call in relation to how crosscutting resources and innovations from DOE’s EESSD and AER can be brought to bear to mutual benefit and more efficient energy-water, Earth system data resources through improved. The overarching challenge posed by this call focuses on how DOE can directly leverage artificial intelligence (AI) to engineer a substantial (paradigm-changing) improvement in Earth System Predictability? While stemming from DOE BER’s EESSD program, this is a challenge that is faced and also being addressed by DOE’s AER programs. Over the past decade plus, FE, EERE, and NE programs have made important strides towards addressing this need. These strides are in many ways highly complementary to EESSD’s MODEX efforts. Energy water systems spanning metocean to groundwater to surface water systems all are data driven whether for basic energy or applied energy. These are remote, multi-variate, complex natural, and in many cases engineered, systems. Key needs and challenges of both EESSD and AER include developing data-focused tools to enhance data search and discovery to fill in knowledge gaps (address sparse data challenge), and rapidly transform datasets, including disparate and multi-source data. Leveraging DOE on-premise computing (HPC, exascale) infrastructure supports the computing-intensive algorithms required to execute these data acquisition and transformation processes to derive enriched knowledge and data, driving AI/ML and big data analytics for these systems. The opportunity lies in combining BER and AER efforts to provide a more robust, advanced, efficient and complete computing data fabric to address energy-water data acquisition and assimilation needs which currently pose significant impediments to AI/ML predictions and research.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2018

Coupling of a High-Resolution Ambient Pressure Drift Tube Ion Mobility Spectrometer to a Commercial Time-of-flight Mass Spectrometer

Ion mobility spectrometry provides information about molecular structures of ions. Hence, high resolving power allows separation of isomers which is of major interest in several applications. In this work, we couple our high-resolution ion mobility spectrometer (IMS) with a resolving power of R{sub p} = 100 to a time-of-flight mass spectrometer (TOF-MS). Besides, the benefit of an increased resolving power such an IMS-MS also helps analyzing and understanding the ionization processes in IMS. Usually, the coupling between IMS and TOF-MS is realized by synchronizing data acquisition of the IMS and MS resulting in two-dimensional data containing ion mobility and mass spectra. However, due to peak widths of less than 100 μs in our high-resolution IMS, this technique is not practicable due to significant peak broadening during the ion transfer into the MS and an insufficient data acquisition rate of the MS. Thus, a novel but simple interface between the IMS and MS has been designed which minimizes ion losses, allows recording of ion mobility at full IMS resolving power, and enables a shuttered transmission of ions into the MS. The interface is realized by replacing the Faraday plate used in IMS by a Faraday grid that is shielded by two additional aperture grids. For demonstration, positive product ions of benzene, toluene, and m-xylene in air are investigated. The IMS is equipped with a radioactive {sup 3}H source. Besides the well-known product ions M{sup +} and M·NO{sup +}, a dimer ion is also observed for benzene and toluene, consisting of two molecules and three further hydrogen atoms. .

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
NASA NTRS1987

A computer controlled signal preprocessor for laser fringe anemometer applications

The operation of most commercially available laser fringe anemometer (LFA) counter-processors assumes that adjustments are made to the signal processing independent of the computer used for reducing the data acquired. Not only does the researcher desire a record of these parameters attached to the data acquired, but changes in flow conditions generally require that these settings be changed to improve data quality. Because of this limitation, on-line modification of the data acquisition parameters can be difficult and time consuming. A computer-controlled signal preprocessor has been developed which makes possible this optimization of the photomultiplier signal as a normal part of the data acquisition process. It allows computer control of the filter selection, signal gain, and photo-multiplier voltage. The raw signal from the photomultiplier tube is input to the preprocessor which, under the control of a digital computer, filters the signal and amplifies it to an acceptable level. The counter-processor used at Lewis Research Center generates the particle interarrival times, as well as the time-of-flight of the particle through the probe volume. The signal preprocessor allows computer control of the acquisition of these data.Through the preprocessor, the computer also can control the hand shaking signals for the interface between itself and the counter-processor. Finally, the signal preprocessor splits the pedestal from the signal before filtering, and monitors the photo-multiplier dc current, sends a signal proportional to this current to the computer through an analog to digital converter, and provides an alarm if the current exceeds a predefined maximum. Complete drawings and explanations are provided in the text as well as a sample interface program for use with the data acquisition software.

Oberle, Lawrence G.↗
NASA NTRS1974

Assess program: Interactive data management systems for airborne research

Two data systems were developed for use in airborne research. Both have distributed intelligence and are programmed for interactive support among computers and with human operators. The C-141 system (ADAMS) performs flight planning and telescope control functions in addition to its primary role of data acquisition; the CV-990 system (ADDAS) performs data management functions in support of many research experiments operating concurrently. Each system is arranged for maximum reliability in the first priority function, precision data acquisition.

Munoz, R. M.↗
DOE OSTI2017

Simulation of Engine Expansion for Transparent Nozzle Combustion Research

A solenoid valve system and the ability to remotely control devices were added to the transparent nozzle experimental setup. The remote control of the devices allow a user to completely control the experiment via a computer interface. The user can collect data (low speed data acquisition of pressure and temperature and high speed data acquisition of voltage), set injection pressure of the system, and control timing of triggering solenoids, data collection, cameras and injection. The solenoid valve system was shown to work properly and allow for the simulation of engine expansion by cutting off the intake flow of pressure and opening the exhaust flow to a vent. The solenoid valve setup was also shown to help with the problems of splash back and air bubbles forming inside the sack and nozzle tip.

33 ADVANCED PROPULSION SYSTEMS↗
NASA NTRS1976

Applications of the real-time data analysis system in the Ames 40- by 80-foot wind tunnel

The first major overhaul and refurbishment of the Ames 40- by 80-foot wind tunnel since it was put into operation in 1944 was recently completed. A substantial part of this refurbishment was devoted to providing this wind tunnel with a modern real time data acquisition and analysis system to increase the safety, efficiency, and accuracy of experimental investigations in this facility. Background leading to the requirements for the new system, major elements of the system, and some of the applications of the system are summarized. The potential of computerized data acquisition systems for wind tunnels in terms of long term trends in hardware and software costs, and the constraints which must be dealt with to achieve the full potential of computerized data acquisition systems are discussed.

Kelly, M. W.↗
DOE OSTI2022

Sub-10 second fly-scan nano-tomography using machine learning

Abstract X-ray computed tomography is a versatile technique for 3D structure characterization. However, conventional reconstruction algorithms require that the sample not change throughout the scan, and the timescale of sample dynamics must be longer than the data acquisition time to fulfill the stable sample requirement. Meanwhile, concerns about X-ray-induced parasite reaction and sample damage have driven research efforts to reduce beam dosage. Here, we report a machine-learning-based image processing method that can significantly reduce data acquisition time and X-ray dose, outperforming conventional approaches like Filtered-Back Projection, maximum-likelihood, and model-based maximum-a-posteriori probability. Applying machine learning, we achieve ultrafast nano-tomography with sub-10 second data acquisition time and sub-50 nm pixel resolution in a transmission X-ray microscope. We apply our algorithm to study dynamic morphology changes in a lithium-ion battery cathode under a heating rate of 50 o C min −1 , revealing crack self-healing during thermal annealing. The proposed method can be applied to various tomography modalities.

36 MATERIALS SCIENCE↗
NASA NTRS1995

A Unique Facility For Metabolic and Thermoregulatory Studies

A unique exercise facility has been developed and used to perform tipper body ergometry tests for space applications. Originally designed to simulate the muscular, cardiovascular and thermoregulatory responses to working in zero gravity, this facility may be used to conduct basic thermoregulatory investigations applicable to multiple sclerosis patients. An environmental chamber houses the tipper body ergometer and permits control of temperature, air now and humidify. The chamber is a closed system and recirculate-s air after conditioning if. A Cybex Lipper body ergometer has been mounted horizontally on the wall of the environmental chamber. In this configuration, the subject lies underneath the arm crank on a supine seat in order to turn the crank. The supine seat can be removed in order to introduce other equipment into the chamber such as a stool to allow upright arm cranking, or a treadmill to allow walk-run experiments. Physiological and environmental signals are fed into a Strawberry Tree data acquisition system while being monitored and logged using the Workbench software program. Physiological monitoring capabilities include 3-lead EKG using an H-P patient monitor, 5 site skin temperature and core temperature using YSI thermistors, and O2 consumption and CO2 production using AMFTFK Applied Electrochemistry analyzers and sensors. This comprehensive data acquisition set tip allows for calculation of various thermoregulatory indices including heat storage, evaporative heat loss, latent heat loss, and metabolic rate. The current system is capable of adding more data acquisition channels if needed. Some potential studies that could be carried out using the facility include: 1) An investigation into the efficiency of cooling various segments of the body to lower Tc 1-2 F. 2) A series of heat and mass balance studies comparing various LCG configurations.

Williamson, Rebecca C.↗
NASA NTRS1991

The Millimeter-Wave Imaging Radiometer (MIR)

The Millimeter-Wave Imaging Radiometer (MIR) is a new instrument being designed for studies of airborne passive microwave retrieval of tropospheric water vapor, clouds, and precipitation parameters. The MIR is a total-power cross-track scanning radiometer for use on either the NASA ER-2 (high-altitude) or DC-8 (medium altitude) aircraft. The current design includes millimeter-wave (MMW) channels at 90, 166, 183 +/- 1,3,7, and 220 GHz. An upgrade for the addition of submillimeter-wave (SMMW) channels at 325 +/- 1,3,7 and 340 GHz is planned. The nadiral spatial resolution is approximately 700 meters at mid-altitude when operated aboard the NASA ER-2. The MIR consists of a scanhead and data acquisition system, designed for installation in the ER-2 superpod nose cone. The scanhead will house the receivers (feedhorns, mixers, local oscillators, and preamplifiers), a scanning mirror, hot and cold calibration loads, and temperature sensors. Particular attention is being given to the characterization of the hot and cold calibration loads through both laboratory bistatic scattering measurements and analytical modeling. Other aspects of the MIR and the data acquisition system are briefly discussed, and diagrams of the location of the MIR in the ER-2 superpod nosecone and of the data acquisition system are presented.

Gasiewski, A. J.↗
DOE OSTI2016

Identifying Urinary and Serum Exosome Biomarkers for Radiation Exposure Using a Data Dependent Acquisition and SWATH-MS Combined Workflow

Purpose: Early and accurate assessment of radiation injury by radiation-responsive biomarkers is critical for triage and early intervention. Biofluids such as urine and serum are convenient for such analysis. Recent research has also suggested that exosomes are a reliable source of biomarkers in disease progression. In the present study, we analyzed total urine proteome and exosomes isolated from urine or serum for potential biomarkers of acute and persistent radiation injury in mice exposed to lethal whole body irradiation (WBI). Methods and Materials: For feasibility studies, the mice were irradiated at 10.4 Gy WBI, and urine and serum samples were collected 24 and 72 hours after irradiation. Exosomes were isolated and analyzed using liquid chromatography mass spectrometry/mass spectrometry-based workflow for radiation exposure signatures. A data dependent acquisition and SWATH-MS combined workflow approach was used to identify significantly exosome biomarkers indicative of acute or persistent radiation-induced responses. For the validation studies, mice were exposed to 3, 6, 8, or 10 Gy WBI, and samples were analyzed for comparison. Results: A comparison between total urine proteomics and urine exosome proteomics demonstrated that exosome proteomic analysis was superior in identifying radiation signatures. Feasibility studies identified 23 biomarkers from urine and 24 biomarkers from serum exosomes after WBI. Urinary exosome signatures identified different physiological parameters than the ones obtained in serum exosomes. Exosome signatures from urine indicated injury to the liver, gastrointestinal, and genitourinary tracts. In contrast, serum showed vascular injuries and acute inflammation in response to radiation. Selected urinary exosomal biomarkers also showed changes at lower radiation doses in validation studies. Conclusions: Exosome proteomics revealed radiation- and time-dependent protein signatures after WBI. A total of 47 differentially secreted proteins were identified in urinary and serum exosomes. Together, these data showed the feasibility of defining biomarkers that could elucidate tissue-associated and systemic response caused by high-dose ionizing radiation. This is the first report using an exosome proteomics approach to identify radiation signatures.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
NASA NTRS2001

Intelligent Systems for Self-Healing Electronics

For long duration missions it is imperative to be able to monitor and record critical information. The data acquisition systems used must therefore be fault tolerant. This usually meant having redundant copies of critical channels. Since each channel usually consists of various components, the parts count, cost, weight and complexity of the system could be very high. The Advanced Data Acquisition System (ADAS) has been developed as a proof of concept. The purpose was to demonstrate an architecture where individual spare parts can replace defective ones to repair a channel. By so doing entire channels do not need replication. This reduces the need of total redundancy and reduces the parts count. This has the added feature that in addition to spare parts, good components of a failed channel can be used as spares in another channel. In addition to reducing parts count and cost, this configuration, with an intelligent decision maker, can improve the reliability of the overall system. Another unique feature of ADAS is that it uses reconfigurable analog filters. These components can be programmed, by the smart system to meet the specific needs of the part they are to replace. This way one part can serve as spare for many different components. The hardware was built and now serves as a platform for developing intelligent algorithms. Another related project was a wireless data acquisition system. I was invited to participate in the meetings and issue suggestions. A brief description of this system will also be included.

Latino, Carl D.↗
NASA NTRS2003

Development and Flight Testing of an Adaptable Vehicle Health-Monitoring Architecture

Development and testing of an adaptable wireless health-monitoring architecture for a vehicle fleet is presented. It has three operational levels: one or more remote data acquisition units located throughout the vehicle; a command and control unit located within the vehicle; and a terminal collection unit to collect analysis results from all vehicles. Each level is capable of performing autonomous analysis with a trained adaptable expert system. The remote data acquisition unit has an eight channel programmable digital interface that allows the user discretion for choosing type of sensors; number of sensors, sensor sampling rate, and sampling duration for each sensor. The architecture provides framework for a tributary analysis. All measurements at the lowest operational level are reduced to provide analysis results necessary to gauge changes from established baselines. These are then collected at the next level to identify any global trends or common features from the prior level. This process is repeated until the results are reduced at the highest operational level. In the framework, only analysis results are forwarded to the next level to reduce telemetry congestion. The system's remote data acquisition hardware and non-analysis software have been flight tested on the NASA Langley B757's main landing gear.

Woodard, Stanley E.↗
NASA NTRSDate not supplied

NSCOR for Evaluating Risk Factors and Biomarkers for Adaptation and Resilience to Spaceflight: Emotional Valence and Social Processes in ICC/ICE Environments

Space exploration class missions, such as a mission to Mars, will require optimization of human performance, adaptability, and resilience. This NASA Specialized Center of Research (NSCOR) utilizes the NIMH Research Domain Criteria (RDoC) framework to identify biological and behavioral markers of individual social adaptation and emotional resilience (as well as vulnerability) to spaceflight-relevant stressors such as living in extended isolation. The overarching goal of this NSCOR is to obtain novel information to help identify biomarkers of individuals who are resilient and/or adaptable to the stressors of isolated, confined, and controlled (ICC) and isolated, confined, and extreme (ICE) environments.A total of N=90 healthy adult astronaut surrogates are being studied in three spaceflight-analog environments: (1) n=40 healthy adults in the Isolation and Confinement Analog Research Unit (ICARUS), an ICC at the University of Pennsylvania, during 7-day missions, for a target total of 280 subject days; (2) n=32 healthy adult astronaut surrogates studied in NASA’s Human Exploration Research Analog (HERA), an ICC at Johnson Space Center during 45-day missions, for a target total of 2,112 subject days; and (3) n=18 healthy adults in the Alfred-Wegener-Institute’s Neumayer Station III, an ICE in Antarctica, during 14-month missions, for a target total of 7,560 subject days. Dr. Nindl’s Laboratory at the University of Pittsburgh is analyzing a priori selected protein biomarkers in blood, saliva, and urine. Complementary rodent models of exposure to early life stressors, confinement, and isolation are being evaluated at Dr. Hensch’s Laboratory to further validate the neurobehavioral and biological findings from the human studies.Given the inconsistency and varied definition of resilience/adaptation in the scientific literature, the NSCOR team developed a composite resilience/adaptation measure that reflects the most relevant outcomes to resilience/adaptation across psychosocial and neurobehavioral functions, as well as neurocognitive and spaceflight-relevant operational performance. To achieve this, group consensus was attained from subject matter experts to produce a rank-order of importance for each input variable. The final resilience/adaptation score included 36 variables that were collected across spaceflight analogs. As of 10/1/2021, the NSCOR project acquired data on n=27 subjects at ICARUS, n=16 at HERA, and n=18 at Neumayer. The COVID-19 pandemic delayed data acquisition at ICARUS and HERA.Among subjects studied to date, 99% of neural and neurobehavioral data (e.g., neuroimaging for structure and function, behavioral measures) as well as blood, saliva, and urine for biochemical assays have been acquired. For rodent models, Dr. Hensch’s laboratory has established biochemical and behavioral parameters reflecting confinement stress in social networks of mice for comparison to stress responses in the human spaceflight analog environments.Group social behaviors were measured with a Social Network Analysis (SNA) approach to define objective parameters associated with sociability and its plasticity by sex. This analytic approach may help identify a network of individuals who are more effective teammates or more likely to generate new social relationships. Data acquisition, biomarker assessment, and data quality control will continue through September 2022.

D F Dinges↗
DOE OSTI2016

Development of a CO 2 Chemical Sensor for Downhole CO 2 Monitoring in Carbon Sequestration

Geologic storage of carbon dioxide (CO 2 ) has been proposed as a viable means for reducing anthropogenic CO 2 emissions. The means for geological sequestration of CO 2 is injection of supercritical CO 2 underground, which requires the CO 2 to remain either supercritical, or in solution in the water/brine present in the underground formation. However, there are aspects of geologic sequestration that need further study, particularly in regards to safety. To date, none of the geologic sequestration locations have been tested for storage integrity under the changing stress conditions that apply to the sequestration of very large amounts of CO 2 . Establishing environmental safety and addressing public concerns require widespread monitoring of the process in the deep subsurface. In addition, studies of subsurface carbon sequestration such as flow simulations, models of underground reactions and transports require a comprehensive monitoring process to accurately characterize and understand the storage process. Real-time information about underground CO 2 movement and concentration change is highly helpful for: (1) better understanding the uncertainties present in CO 2 geologic storage; (2) improvement of simulation models; and (3) evaluation of the feasibility of geologic CO 2 storage. Current methods to monitor underground CO 2 storage include seismic, geoelectric, isotope and tracer methods, and fluid sampling analysis. However, these methods commonly resulted low resolution, high cost, and the inability to monitor continuously over the long time scales of the CO 2 storage process. A preferred way of monitoring in-situ underground CO 2 migration is to continuous measure CO 2 concentration change in brine during the carbon storage process. An approach to obtain the real time information on CO 2 concentration change in formation solution is highly demanded in carbon storage to understand the CO 2 migration subsurface and to answer the public safety problem. The objective of the study is to develop a downhole CO 2 sensor that can in-situ, continuously monitor CO 2 concentration change in deep saline. The sensor is a Severinghaus-type CO 2 sensor with small size, which renders it can be embedded in monitoring well casing or integrated with pressure/temperature transducers, enabling the development of “smart” wells. The studies included: (1) prepare and characterize metal-oxide electrodes. Test the electrodes response to pH change. Investigate different ions and brine concentration effects on the electrode’s performance. Study the stability of the electrode in brine solution; (2) fabricate a downhole CO 2 sensor with the metal-oxide electrodes prepared in the laboratory. Test the performance of the CO 2 sensor in brine solutions. Study high pressure effects on the performance of the sensor; (3) design and conduct CO 2 /brine coreflooding experiments with the CO2 sensor. Monitor CO 2 movement along the core and test the performance of the sensor in coreflooding tests. Develop a data acquisition system that can digitize the sensor’s output voltage. Our completed research has resulted in deep understanding of downhole CO 2 sensor development and CO 2 monitoring in CO 2 storage process. The developed downhole CO 2 sensor included a metal-oxide electrode, a gas-permeable membrane, a porous steel cup, and a bicarbonate-based internal electrolyte solution. Iridium oxide-based electrode was prepared and used for preparation the CO 2 sensor. The prepared iridium oxide-based electrode displayed a linearly response to pH change. Different factors such as different ions and ions concentration, temperature, and pressure effects on the electrode performance on pH response were investigated. The results indicated that the electrode exhibited a good performance even in high salt concentration of produced water. To improve the electrode performance under high pressure, IrO 2 nanoparticles with the particle size in the range of 1-2 nm were prepared and electrodeposited on stainless steel substrate by cyclic voltammetry. It was observed that the thin film of iridium oxide was formed on the substrate surface and such iridium oxide-based electrode displayed excellent performance under high pressure for longer term. A downhole CO 2 sensor with the iridium oxide-based electrode was prepared. The working principle of the CO 2 sensor is based on the measurement of the pH change of the internal electrolyte solution caused by the hydrolysis of CO 2 and then determination of the CO 2 concentration in water. The prepared downhole CO 2 sensor had the size of diameter of 0.7 in. and length of 1.5 in. The sensor was tested under the pressures of 500 psi, 2,000 psi, and 3,000 psi. A linear correlation was observed between the sensor potential change and dissolved CO 2 concentration in water. The response time of the CO 2 sensor was in the range of 60-100 minutes. Further tests indicated that the CO 2 sensor exhibited good reproducibility under high pressure. A CO 2 /brine coreflooding system was constructed to simulate the real-world CO 2 storage process. The prepared downhole CO 2 sensor was loaded in the system to monitor CO 2 movement during CO 2 /brine coreflooding test. The results indicated that the sensor could detect CO 2 movement in the tests. Further studies showed that the sensor could be recovered by brine flooding after CO 2 /brine flushed the core. The results of the coreflooding tests demonstrated that the sensor had potential application for CO 2 monitoring in carbon sequestration. A data acquisition system for the downhoe CO 2 sensor was developed and coded. The system converted the sensor output signal into digital data and transported the data from downhole to wellhead surface. The data acquisition system was tested and evaluated in the laboratory with the prepared sensor for data collection.

36 MATERIALS SCIENCE↗
NASA NTRS1995

Particle fallout/activity sensor

A particle fallout/activity sensor measures relative amounts of dust or other particles which collect on a mirror in an area to be monitored. The sensor includes a sensor module and a data acquisition module, both of which can be operated independently of one another or in combination with one another. The sensor module includes a housing containing the mirror, an LED assembly for illuminating the mirror and an optical detector assembly for detecting light scattered off of the mirror by dust or other particles collected thereon. A microprocessor controls operation of the sensor module's components and displays results of a measurement on an LCD display mounted on the housing. A push button switch is also mounted on the housing which permits manual initiation of a measurement. The housing is constructed of light absorbing material, such as black delrin, which minimizes detection of light by the optical detector assembly other than that scattered by dust or particles on the mirror. The data acquisition module can be connected to the sensor module and includes its own microprocessor, a timekeeper and other digital circuitry for causing the sensor module to make a measurement periodically and send the measurement data to the data acquisition module for display and storage in memory for later retrieval and transfer to a separate computer. The time tagged measurement data can also be used to determine the relative level of activity in the monitored area since this level is directly related to the amount of dust or particle fallout in the area.

Curtis, Ihlefeld M.↗