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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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All sourcesNASA NTRSDOE OSTI
NASA NTRS2009

NASA Tech Briefs, April 2009

Topics covered include: Direct-Solve Image-Based Wavefront Sensing; Use of UV Sources for Detection and Identification of Explosives; Using Fluorescent Viruses for Detecting Bacteria in Water; Gradiometer Using Middle Loops as Sensing Elements in a Low-Field SQUID MRI System; Volcano Monitor: Autonomous Triggering of In-Situ Sensors; Wireless Fluid-Level Sensors for Harsh Environments; Interference-Detection Module in a Digital Radar Receiver; Modal Vibration Analysis of Large Castings; Structural/Radiation-Shielding Epoxies; Integrated Multilayer Insulation; Apparatus for Screening Multiple Oxygen-Reduction Catalysts; Determining Aliasing in Isolated Signal Conditioning Modules; Composite Bipolar Plate for Unitized Fuel Cell/Electrolyzer Systems; Spectrum Analyzers Incorporating Tunable WGM Resonators; Quantum-Well Thermophotovoltaic Cells; Bounded-Angle Iterative Decoding of LDPC Codes; Conversion from Tree to Graph Representation of Requirements; Parallel Hybrid Vehicle Optimal Storage System; and Anaerobic Digestion in a Flooded Densified Leachbed.

Source record↗
NASA NTRS2008

The Citizens and Remote Sensing Observational Network (CARSON) Guide: Merging NASA Remote Sensing Data with Local Environmental Awareness

"Citizen science" generally refers to observatoinal research and data collection conducted by non-professionals, commonly as volunteers. In the environmental science field, citizen scientists may be involved with local nad regional issues such as bird and wildlife populations, weather, urban sprawl, natural hazards, wetlands, lakes and rivers, estuaries, and a spectrum of public health concerns. Some citizen scientists may be primarily motivated by the intellectual challenge of scientific observations. Citizen scientists may now examine and utilize remote-sensing data related to their particular topics of interest with the easy-to-use NASA Web-based tools Giovanni and NEO, which allow exploration and investigation of a wide variety of Earth remote sensing data sets. The CARSON (Citizens and Remote Sensing Observational Network) Guide will be an online resource consisting of chapters each demonstrating how to utilize Giovanni and NEO to access and analyze specific remote-sensing data. Integrated in each chapter will be descriptions of methods that citizen scientists can employ to collect, monitor, analyze, and share data related to the chapter topic which pertain to environmental and ecological conditions in their local region. A workshop held in August 2008 initiated the development of prototype chapters on water quality, air quality, and precipitation. These will be the initial chapters in the first release of the CARSON Guide, which will be used in a pilot project at the Maryland Science Center in spring 2009. The goal of the CARSON Guide is to augment and enhance citizen scientist environmental research with NASA satellite data by creating a participatory network consisting of motivated individuals, environmental groups and organizations, and science-focused institutions such as museuma and nature centers. Members of the network could potentially interact with government programs, academic research projects, and not-for-profit organizations focused on environmental issues.

Acker, James↗
NASA NTRS2010

Smart Sensor Demonstration Payload

Sensors are a critical element to any monitoring, control, and evaluation processes such as those needed to support ground based testing for rocket engine test. Sensor applications involve tens to thousands of sensors; their reliable performance is critical to achieving overall system goals. Many figures of merit are used to describe and evaluate sensor characteristics; for example, sensitivity and linearity. In addition, sensor selection must satisfy many trade-offs among system engineering (SE) requirements to best integrate sensors into complex systems [1]. These SE trades include the familiar constraints of power, signal conditioning, cabling, reliability, and mass, and now include considerations such as spectrum allocation and interference for wireless sensors. Our group at NASA s John C. Stennis Space Center (SSC) works in the broad area of integrated systems health management (ISHM). Core ISHM technologies include smart and intelligent sensors, anomaly detection, root cause analysis, prognosis, and interfaces to operators and other system elements [2]. Sensor technologies are the base fabric that feed data and health information to higher layers. Cost-effective operation of the complement of test stands benefits from technologies and methodologies that contribute to reductions in labor costs, improvements in efficiency, reductions in turn-around times, improved reliability, and other measures. ISHM is an active area of development at SSC because it offers the potential to achieve many of those operational goals [3-5].

Schmalzel, John↗
NASA NTRS2018

Self-Stabilizing Distributed Symmetric-Fault Tolerant Synchronization Protocol

A network system includes at least one node configured to exchange messages through a set of communication links. Each node includes a synchronizer, a set of monitors in communication with the synchronizer, a physical oscillator and a state timer clock and a local timer clock, each clock being driven by the physical oscillator and having a variable clock value that locally tracks passage of clock time for the node. The network system is configured to execute a synchronization process when a specified condition occurs. Upon receiving a Sync message, each of the nodes is configured to store an incoming Sync message, increment a local timer clock value, or ignore the Sync message based on a local timer clock value associated with an incoming Sync message.

Malekpour, Mahyar R.↗
NASA NTRS2020

GRACE Improves Seasonal Groundwater Forecast Initialization Over the United States

We evaluate the impact of Gravity Recovery and Climate Experiment data assimilation (GRACE-DA) on seasonal hydrological forecast initialization over the United States, focusing on groundwater storage. GRACE-based terrestrial water storage (TWS) estimates are assimilated into a land surface model for the2003–16 period. Three-month hindcast (i.e., forecast of past events) simulations are initialized using states from the reference (no data assimilation) and GRACE-DA runs. Differences between the two initial hydrological condition (IHC) sets are evaluated for two forecast techniques at 305 wells where depth to water table measurements are available. Results show that using GRACE-DA-based IHC improves seasonal groundwater forecast performance in terms of both RMSE and correlation. While most regions show improvement, degradation is common in the High Plains, where withdrawals for irrigation practices affect groundwater variability more strongly than the weather variability, which demonstrates the need for simulating such activities. These findings contribute to recent efforts toward an improved U.S. drought monitoring and forecast system.

Augusto Getirana↗
NASA NTRSDate not supplied

Li-ion Battery Aging with Hybrid Physics-Informed Neural Networks and Fleet-wide Data

In this work, we propose a hybrid model for Li-ion battery discharge and aging prediction that leverages fleet-wide data to predict future capacity drops.The model is built upon an hybrid approach merging physics-based and empirical equations, as well as neural network models in a recurrent neural network cell. The hybrid physics-informed neural network can predict voltage discharge cycles given the loading profile, and estimate the used capacity of the battery under random-loading conditions by tracking aging parameters connected to the residual capacity of the battery. By merging information on the battery aging parameters with existing fleet-wide aging data, the model can predict the future residual capacity of the battery that is being monitored, and therefore enable predictions of voltage discharge curves far ahead in the battery life cycle. We validated the approach using the NASA Prognostics Data Repository Battery data-set, which contains experimental data on Li-ion batteries discharged at random loading conditions in a controlled environment. The approach also allows the identification of discrepancies between the battery aging trend and the trend observed at the fleet level, so that batteries behaving differently from the rest of the fleet can be subject to closer monitoring and further testing to refine predictions.

PINN↗
DOE OSTI2013

Risk and Performance Analyses Supporting Closure of WMA C at the Hanford Site in Southeast Washington

The Office of River Protection under the U.S. Department of Energy (DOE) is pursuing closure of the Single-Shell Tank (SST) Waste Management Area (WMA) C as stipulated by the Hanford Federal Facility Agreement and Consent Order (HFFACO) under federal requirements and work tasks will be done under the State-approved closure plans and permits. An initial step in meeting the regulatory requirements is to develop a baseline risk assessment representing current conditions based on available characterization data and information collected at the WMA C location. The baseline risk assessment will be supporting a Resource Conservation and Recovery Act of 1976 (RCRA) Field Investigation (RFI)/Corrective Measures Study (CMS) for WMA closure and RCRA corrective action. Complying with the HFFACO conditions also involves developing a long-term closure Performance Assessment (PA) that evaluates human health and environmental impacts resulting from radionuclide inventories in residual wastes remaining in WMA C tanks and ancillary equipment. This PA is being developed to meet the requirements necessary for closure authorization under DOE Order 435.1 and Washington State Hazardous Waste Management Act. To meet the HFFACO conditions, the long-term closure risk analysis will include an evaluation of human health and environmental impacts from hazardous chemical inventories along with other performance Comprehensive Environmental Response, Compensation, and Liability Act Appropriate and Applicable Requirements (CERCLA ARARs) in residual wastes left in WMA C facilities after retrieval and removal. This closure risk analysis is needed to needed to comply with the requirements for permitted closure. Progress to date in developing a baseline risk assessment of WMA C has involved aspects of an evaluation of soil characterization and groundwater monitoring data collected as a part of the RFI/CMS and RCRA monitoring. Developing the long-term performance assessment aspects has involved the construction of detailed numerical models of WMA C using the Subsurface Transport Over Multiple Phases (STOMP©) computer code, the development of a technical approach for abstraction of a range of representative STOMP© simulations into a system-level model based on the GoldSim© system-level model software.The STOMP©-based models will be used to evaluate local-scale impacts and closed facility performance over a sufficient range of simulations to allow for development of the system-level model of the WMA C. The GoldSim©-based system-level model will be used to evaluate overall sensitivity of modeled parameters and the estimate the uncertainty in potential future impacts from a closed WMA C facility.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
NASA NTRS2007

Potential of VIIRS Data for Regional Monitoring of Gypsy Moth Defoliation: Implications for Forest Threat Early Warning System

A NASA RPC (Rapid Prototyping Capability) experiment was conducted to assess the potential of VIIRS (Visible/Infrared Imager/Radiometer Suite) data for monitoring non-native gypsy moth (Lymantria dispar) defoliation of forests. This experiment compares defoliation detection products computed from simulated VIIRS and from MODIS (Moderate Resolution Imaging Spectroradiometer) time series products as potential inputs to a forest threat EWS (Early Warning System) being developed for the USFS (USDA Forest Service). Gypsy moth causes extensive defoliation of broadleaved forests in the United States and is specifically identified in the Healthy Forest Restoration Act (HFRA) of 2003. The HFRA mandates development of a national forest threat EWS. This system is being built by the USFS and NASA is aiding integration of needed satellite data products into this system, including MODIS products. This RPC experiment enabled the MODIS follow-on, VIIRS, to be evaluated as a data source for EWS forest monitoring products. The experiment included 1) assessment of MODIS-simulated VIIRS NDVI products, and 2) evaluation of gypsy moth defoliation mapping products from MODIS-simulated VIIRS and from MODIS NDVI time series data. This experiment employed MODIS data collected over the approximately 15 million acre mid-Appalachian Highlands during the annual peak defoliation time frame (approximately June 10 through July 27) during 2000-2006. NASA Stennis Application Research Toolbox software was used to produce MODIS-simulated VIIRS data and NASA Stennis Time Series Product Tool software was employed to process MODIS and MODIS-simulated VIIRS time series data scaled to planetary reflectance. MODIS-simulated VIIRS data was assessed through comparison to Hyperion-simulated VIIRS data using data collected during gypsy moth defoliation. Hyperion-simulated MODIS data showed a high correlation with actual MODIS data (NDVI R2 of 0.877 and RMSE of 0.023). MODIS-simulated VIIRS data for the same date showed moderately high correlation with Hyperion-simulated VIIRS data (NDVI R2 of 0.62 and RMSE of 0.035), even though the datasets were collected about a half an hour apart during changing weather conditions. MODIS products (MOD02, MOD09, and MOD13) and MOD02-simulated VIIRS time series data were used to generate defoliation mapping products based on image classification and image differencing change detection techniques. Accuracy of final defoliation mapping products was assessed by image interpreting over 170 randomly sampled locations found on Landsat and ASTER data in conjunction with defoliation map data from the USFS. The MOD02-simulated VIIRS 400-meter NDVI classification produced a similar overall accuracy (87.28 percent with 0.72 Kappa) to the MOD02 250-meter NDVI classification (86.71 percent with 0.71 Kappa). In addition, the VIIRS 400-meter NDVI, MOD02 250-meter NDVI, and MOD02 500-meter NDVI showed good user and producer accuracies for the defoliated forest class (70 percent) and acceptable Kappa values (0.66). MOD02 and MOD02-simulated VIIRS data both showed promise as data sources for regional monitoring of forest disturbance due to insect defoliation.

Spruce, Joseph P.↗
DOE OSTI2014

Temperature-independent sensors based on perovskite-type oxides

The need of energy security and environment sustainability drives toward the development of energy technology in order to enhance the performance of internal combustion engines. Gas sensors play a key role for controlling the fuel oxygen ratio and monitoring the pollution emissions. The perovskite-type oxides can be synthesized for an extremely wide variety of combinations of chemical elements, allowing to design materials with suitable properties for sensing application. Lanthanum strontium ferrites, such as La{sub 0.7}Sr{sub 0.3}FeO{sub 3}, are suitable oxygen sensing materials with temperature-independence conductivity, but they have low chemical stability under reducing conditions. The addition of aluminum into the perovskite structure improves the material properties in order to develop suitable oxygen sensing probes for lean burn engine control systems. Perovskite-type oxides with formula (La{sub 0.7}Sr{sub 0.3})(Al{sub x}Fe{sub 1−x})O{sub 3} was synthesized by the citrate-nitrate combustion synthesis method. XRD analyses, show that it was synthesized a phase-pure powder belonging to the perovskite structure. Aluminum affects both the unit cell parameters, by shrinking the unit cell, and the powder morphology, by promoting the synthesis of particles with small crystallite size and large specific surface area. The partial substitution of iron with aluminum improves the chemical stability under reducing gas conditions and modulates the oxygen sensitivity by affecting the relative amount of Fe{sup 4+} and Fe{sup 3+}, as confirmed from TPR profiles. In the same time, the addition of aluminum does not affects the temperature-independent properties of lanthanum strontium ferrites. Indeed, the electrical measurements show that (La{sub 0.7}Sr{sub 0.3})(Al{sub x}Fe{sub 1−x})O{sub 3} perovskites have temperature-independence conductivity from 900 K.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2026

A two-stage optical fusion framework for wildfire severity mapping across the conterminous United States

Accurate wildfire severity mapping (WSM) is essential for post-fire recovery planning, erosion risk assessment, ecosystem monitoring, and disaster risk reduction. Although Landsat and Sentinel optical imagery have been widely used for burn severity assessment, the added value of fusing multiple optical sensors has not been sufficiently quantified across diverse fire events, particularly since the launch of Landsat-9. This study evaluates whether multisensor optical fusion improves wildfire severity mapping relative to single-sensor baselines using Sentinel-2, Landsat-8, and Landsat-9 imagery across 40 wildfire events in the conterminous United States. We tested a two-stage fusion framework that combines feature-level fusion with pixel-level dimensionality reduction. First, feature-level fused datasets were created through early fusion by combining standardized post-fire bands from each sensor into a single predictor stack. Both raw reflectance bands and pairwise spectral transforms were retained to capture within- and cross-sensor spectral interactions. Second, Linear Discriminant Analysis was applied to both single-sensor and fused datasets to produce comparable low-dimensional feature spaces. Six machine-learning classifiers were then used to benchmark model performance with repeated spatially buffered train–test splits. Results show that Landsat-9 was the strongest single-sensor baseline. Among the fusion strategies, Sentinel-2 + Landsat-9 produced the most consistent improvement and reduced performance variability. Landscape-condition analysis further showed that this fusion was most beneficial in shrubland-dominated and high-terrain fires, where it achieved the highest overall mean accuracy and the fewest failures. In contrast, its benefits were less reliable in evergreen forests, mixed vegetation, and low- to moderate-elevation terrain. In operational settings, the Sentinel-2 + Landsat-9 configuration offers a practical solution for post-fire recovery planning, erosion-risk assessment, watershed management, and ecological monitoring when field observations are available and timely satellite-based information is needed.

Landsat↗
DOE OSTI2026

The Potential and Cost of Carbon Dioxide Removal Using Direct Air Capture with Land-Based Wind and Utility-Scale Photovoltaics

The rapid deployment of direct air capture and storage (DACS) is critical for achieving emission targets, necessitating precise evaluation of the scale and cost of carbon dioxide removal. This study examines the availability of land, electricity generation, and geologic CO 2 storage within the United States, estimating a technical potential for low-temperature, adsorbent-based DACS to remove approximately 9 gigatonnes of CO 2 annually. By 2050, a substantial portion of this removal could be achieved at net-removed costs below $\$$300/tonneCO 2 , though costs are highly variable depending on factors such as facility scale, construction expenses, climate-dependent productivity and heating efficiency, and geologic storage conditions. In the short term, DACS deployment will help identify key research priorities for advancing technology and reducing removal costs. Concurrently, there is an urgent need for scientifically robust and standardized frameworks for monitoring, reporting, and verifying DACS performance across both established and emerging technologies and energy sources.

Carbon capture↗
DOE OSTI2015

Proof-of-principle demonstration of a virtual flow meter-based transducer for gaseous helium monitoring in particle accelerator cryogenics

A transducer based on a virtual flow meter is proposed for monitoring helium distribution and consumption in cryogenic systems for particle accelerators. The virtual flow meter allows technical and economical constraints, preventing installation of physical instruments in all the needed measurement points, to be overcome. Virtual flow meter performance for the alternative models of Samson [ http://www.samson.de (2015)] and Sereg-Schlumberger [ http://www.slb.com/ (2015)] is compared with the standard IEC 60534-2-1 [Industrial-process control valves—Part 2-1: Flow capacity—sizing equations for fluid flow under installed conditions (2011), https://webstore.iec.ch/publication/2461], for a large temperature range, for both gaseous and liquid helium phases, and for different pressure drops. Then, the calibration function of the transducer is derived. Finally, the experimental validation for the helium gaseous state on the test station for superconducting magnets in the laboratory SM18 [Pirotte et al., AIP Conf. Proc. 1573, 187 (2014)] at CERN is reported.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
NASA NTRS1974

Study of time-lapse processing for dynamic hydrologic conditions

The usefulness of dynamic display techniques in exploiting the repetitive nature of ERTS imagery was investigated. A specially designed Electronic Satellite Image Analysis Console (ESIAC) was developed and employed to process data for seven ERTS principal investigators studying dynamic hydrological conditions for diverse applications. These applications include measurement of snowfield extent and sediment plumes from estuary discharge, Playa Lake inventory, and monitoring of phreatophyte and other vegetation changes. The ESIAC provides facilities for storing registered image sequences in a magnetic video disc memory for subsequent recall, enhancement, and animated display in monochrome or color. The most unique feature of the system is the capability to time lapse the imagery and analytic displays of the imagery. Data products included quantitative measurements of distances and areas, binary thematic maps based on monospectral or multispectral decisions, radiance profiles, and movie loops. Applications of animation for uses other than creating time-lapse sequences are identified. Input to the ESIAC can be either digital or via photographic transparencies.

Serebreny, S. M.↗
NASA NTRS1993

Operational radiological support for the US manned space program

Radiological support for the manned space program is provided by the Space Radiation Analysis Group at NASA/JSC. This support ensures crew safety through mission design analysis, real-time space environment monitoring, and crew exposure measurements. Preflight crew exposure calculations using mission design information are used to ensure that crew exposures will remain within established limits. During missions, space environment conditions are continuously monitored from within the Mission Control Center. In the event of a radiation environment enhancement, the impact to crew exposure is assessed and recommendations are provided to flight management. Radiation dosimeters are placed throughout the spacecraft and provided to each crewmember. During a radiation contingency, the crew could be requested to provide dosimeter readings. This information would be used for projecting crew dose enhancements. New instrumentation and computer technology are being developed to improve the support. Improved instruments include tissue equivalent proportional counter (TEPC)-based dosimeters and charged particle telescopes. Data from these instruments will be telemetered and will provide flight controllers with unprecedented information regarding the radiation environment in and around the spacecraft. New software is being acquired and developed to provide 'smart' space environmental data displays for use by flight controllers.

Golightly, Michael J.↗
NASA NTRS1994

Optical storage media data integrity studies

Optical disk-based information systems are being used in private industry and many Federal Government agencies for on-line and long-term storage of large quantities of data. The storage devices that are part of these systems are designed with powerful, but not unlimited, media error correction capacities. The integrity of data stored on optical disks does not only depend on the life expectancy specifications for the medium. Different factors, including handling and storage conditions, may result in an increase of medium errors in size and frequency. Monitoring the potential data degradation is crucial, especially for long term applications. Efforts are being made by the Association for Information and Image Management Technical Committee C21, Storage Devices and Applications, to specify methods for monitoring and reporting to the user medium errors detected by the storage device while writing, reading or verifying the data stored in that medium. The Computer Systems Laboratory (CSL) of the National Institute of Standard and Technology (NIST) has a leadership role in the development of these standard techniques. In addition, CSL is researching other data integrity issues, including the investigation of error-resilient compression algorithms. NIST has conducted care and handling experiments on optical disk media with the objective of identifying possible causes of degradation. NIST work in data integrity and related standards activities is described.

Podio, Fernando L.↗
NASA NTRS2006

Intelligent Chemical Sensor Systems for In-space Safety Applications

Future in-space and lunar operations will require significantly improved monitoring and Integrated System Health Management (ISHM) throughout the mission. In particular, the monitoring of chemical species is an important component of an overall monitoring system for space vehicles and operations. For example, in leak monitoring of propulsion systems during launch, inspace, and on lunar surfaces, detection of low concentrations of hydrogen and other fuels is important to avoid explosive conditions that could harm personnel and damage the vehicle. Dependable vehicle operation also depends on the timely and accurate measurement of these leaks. Thus, the development of a sensor array to determine the concentration of fuels such as hydrogen, hydrocarbons, or hydrazine as well as oxygen is necessary. Work has been on-going to develop an integrated smart leak detection system based on miniaturized sensors to detect hydrogen, hydrocarbons, or hydrazine, and oxygen. The approach is to implement Microelectromechanical Systems (MEMS) based sensors incorporated with signal conditioning electronics, power, data storage, and telemetry enabling intelligent systems. The final sensor system will be self-contained with a surface area comparable to a postage stamp. This paper discusses the development of this "Lick and Stick" leak detection system and it s application to In-Space Transportation and other Exploration applications.

Hunter, G. W.↗
NASA NTRS2015

4.4 Development of a 30-Year Soil Moisture Climatology for Situational Awareness and Public Health Applications

This paper provided a brief background on the work being done at NASA SPoRT and the CDC to create a soil moisture climatology over the CONUS at high spatial resolution, and to provide a valuable source of soil moisture information to the CDC for monitoring conditions that could favor the development of Valley Fever. The soil moisture climatology has multi-faceted applications for both the NOAA/NWS situational awareness in the areas of drought and flooding, and for the Public Health community. SPoRT plans to increase its interaction with the drought monitoring and Public Health communities by enhancing this testbed soil moisture anomaly product. This soil moisture climatology run will also serve as a foundation for upgrading the real-time (currently southeastern CONUS) SPoRT-LIS to a full CONUS domain based on LIS version 7 and incorporating real-time GVF data from the Suomi-NPP Visible Infrared Imaging Radiometer Suite (Vargas et al. 2013) into LIS-Noah. The upgraded SPoRT-LIS run will serve as a testbed proof-of-concept of a higher-resolution NLDAS-2 modeling member. The climatology run will be extended to near real-time using the NLDAS-2 meteorological forcing from 2011 to present. The fixed 1981-2010 climatology shall provide the soil moisture "normals" for the production of real-time soil moisture anomalies. SPoRT also envisions a web-mapping type of service in which an end-user could put in a request for either an historical or real-time soil moisture anomaly graph for a specified county (as exemplified by Figure 2) and/or for local and regional maps of soil moisture proxy percentiles. Finally, SPoRT seeks to assimilate satellite soil moisture data from the current Soil Moisture Ocean Salinity (SMOS; Blankenship et al. 2014) and the recently-launched NASA Soil Moisture Active Passive (SMAP; Entekhabi et al. 2010) missions, using the EnKF capability within LIS. The 9-km combined active radar and passive microwave retrieval product from SMAP (Das et al. 2011) has the potential to provide valuable information about the near-surface soil moisture state for improving land surface modeling output.

land surface modeling↗
DOE OSTI2016

Robust Ceramic Coaxial Cable Down-Hole Sensors for Long-Term In Situ Monitoring of Geologic CO 2 Injection and Storage

Energy generation by use of fossil fuels produces large volumes of CO 2 and other greenhouse gases, whose accumulation in the atmosphere is widely seen as undesirable. CO 2 Capture followed by sequestration has been identified as the solution. Subsurface geologic formations offer a potential location for long-term storage of CO 2 because of their requisite size. Unfortunately, the inaccessibility and complexity of the subsurface, the wide range of scales of variability, and the coupled nonlinear processes, impose tremendous challenges to determine the transport and predict the fate of the stored CO 2 . Among the various monitoring approaches, in situ down-hole monitoring of the various state parameters provides critical and direct data points that can be used to validate the models, optimize the injection, detect leakage and track the CO 2 plume. However, down-hole sensors that can withstand the harsh conditions and operate over decades of the project lifecycle remain unavailable. Given that the widespread of carbon capture and storage will be the necessity and reality in the future, fundamental and applied research is required to address the significant challenges and technological gaps in lack of long-term reliable down-hole sensors This project focused on the development and demonstration of a novel, low-cost, distributed, robust ceramic coaxial cable sensor platform for in situ down-hole monitoring of geologic CO 2 injection and storage with high spatial and temporal resolutions. The coaxial cable Fabry-Perot interferometer (CCFPI) has been studied as a general sensor platform for in situ, long-term, measurement of temperature, pressure and strain, which are critical to CO 2 injection and storage. A novel signal processing scheme has been developed and demonstrated for dense multiplexing of the sensors for low-cost distributed sensing with high spatial resolution. The developed temperature, pressure and strain sensors have been extensively tested under laboratory conditions that are similar to the downhole CO 2 storage environment, showing excellent capability for in situ monitoring the various parameters that are important to model, optimize the injection, detect leakage and track the CO 2 plume. In addition, the interactions between the sensor datum and the geological models have been investigated in details for the purposes of model validation, guiding sensor installation/placement, enhancement of model prediction capability and optimization of the injection processes. This project has resulted in the successful development of new ceramic coaxial cable based sensor systems that can monitor directly the changes in pressure, temperature, and strain caused by increased reservoir pressure and reduced reservoir temperature due to the supercritical CO 2 injection. Integrated with geological models, the sensors and measurement data can improve the possibility to identify plume movement and leakage in the cap rock and wells with higher precision and more accuracy. The low cost, ease of deployment, small size and dense multiplexing features of the new sensing technology will allow a large number of sensors to be deployed to address the objective to demonstrate that 99% of the CO 2 remains in the injection zone.

01 COAL, LIGNITE, AND PEAT↗