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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
DOE OSTI2016

Demonstration of a prototype hydrogen sensor and electronics package

This is a progress report for the demonstration of a prototype hydrogen sensor and electronics package. There are five tasks associated with this, and four have been completed as of August 2016: Station Demonstration and Site Recommendation, Order Sensor Equipment, Build Sensors, and Install Sensors. The final task to be completed is Sensor Demonstration and Data Analysis, and expected completion date is January 26, 2017. This progress report details each of the tasks and goes into detail about what is currently being worked on, along with the budget and planned work for July 27, 2016 to January 26, 2017.

36 MATERIALS SCIENCE↗
DOE OSTI2013

Recovery Act: High-Temperature Circuit Boards for use in Geothermal Well Monitoring Applications

The U.S. Department of Energy is leading the development of alternative energy sources that will ensure the long-term energy independence of our nation. One of the key renewable resources currently being advanced is geothermal energy. To tap into the large potential offered by generating power from the heat of the earth, and for geothermal energy to be more widely used, it will be necessary to drill deeper wells to reach the hot, dry rock located up to 10 km beneath the earth’s surface. In this instance, water will be introduced into the well to create a geothermal reservoir. A geothermal well produced in this manner is referred to as an enhanced geothermal system (EGS). EGS reservoirs are typically at depths of 3 to 10 km, and the temperatures at these depths have become a limiting factor in the application of existing downhole technologies. These high temperatures are especially problematic for electronic systems such as downhole data-logging tools, which are used to map and characterize the fractures and high-permeability regions in underground formations. Information provided by these tools is assessed so that underground formations capable of providing geothermal energy can be identified, and the subsequent drilling operations can be accurately directed to those locations. The mapping of geothermal resources involves the design and fabrication of sensor packages, including the electronic control modules, to quantify downhole conditions (300°C temperature, high pressure, seismic activity, etc.). Because of the extreme depths at which these measurements are performed, it is most desirable to perform the sensor signal processing downhole and then transmit the information to the surface. This approach necessitates the use of high-temperature electronics that can operate in the downhole environment. Downhole signal processing in EGS wells will require the development and demonstration of circuit boards that can withstand the elevated temperatures found at these depths. At present, the highest-temperature commercially available circuit boards are based on polyimide materials, and those have maximum use temperatures of 200 to 250°C. In addition to thermal stability, downhole electronics must also be fabricated into high-aspect-ratio packages. For example, the multilayer assemblies produced at SNL were approximately 2.5 cm wide and 50 cm long. Because of this very high form factor, glass-fiber-reinforced polymers are much more desirable than multilayer ceramic modules (MCM). MCMs have many advantages for some applications, but are susceptible to damage induced by the mechanical and vibrational loads commonly experienced by data-logging tools. Thus, as EGS technology continues to advance, there is a strong need for multilayer electronics that can provide the necessary thermal performance while also being compatible with high-form-factor circuit designs. This project involved the design and development of high-temperature circuit materials, as well as the fabrication and testing of circuit components. The material development included the evaluation of various polymer/fiberglass composites, whereas the circuit components were tested using conventional microelectronic evaluation techniques. This effort targeted development of a new class of high-temperature multilayer circuit boards for use in downhole data-logging applications where temperatures are on the order of 300°C. This is consistent with DOE’s multiyear plan for advancing technologies for use in enhanced geothermal systems. Organic and inorganic polymer systems, both with glass reinforcements, were considered to provide the following performance at elevated temperatures: • Mechanical strength and durability • High dielectric strength and electrical resistivity • Thermal stability • Strong adhesion to copper to ensure the reliability of the multilayer assemblies • Processing characteristics that are consistent with state-of-the-art multilayer circuit board manufacturing practices

15 GEOTHERMAL ENERGY↗
DOE OSTI2012

Multipurpose Acoustic Sensor for Downhole Fluid Monitoring

The projects objectives and purpose are to: (1) development a multipurpose acoustic sensor for downhole fluid monitoring in Enhanced Geothermal Systems (EGS) reservoirs over typical ranges of pressures and temperatures and demonstrate its capabilities and performance for different EGS systems; (2) determine in real-time and in a single sensor package several parameters - temperature, pressure, fluid flow and fluid properties; (3) needed in nearly every phase of an EGS project, including Testing of Injection and Production Wells, Reservoir Validation, Inter-well Connectivity, Reservoir Scale Up and Reservoir Sustainability. (4) Current sensors are limited to operating at lower temperatures, but the need is for logging at high temperatures. The present project deals with the development of a novel acoustic-based sensor that can work at temperatures up to 374 °C, in inhospitable environments.

15 GEOTHERMAL ENERGY↗
DOE OSTI2023

Unified Software Architecture for Advanced Materials and Manufacturing Technologies Data Management and Processing: FY 2023 Multidimensional Data Correlation Platform

This report details the various digital manufacturing activities ongoing at ORNL as part of the Advanced Materials and Manufacturing Technologies (AMMT) program. The AMMT program is exploring a data-driven approach to demonstrate the use of AM for the fabrication of components for nuclear applications, with the goal of providing a greater understanding of manufacturing quality outcomes that would pave the way toward the development of standards for certification and qualification. The objective of this work package is to establish a digital manufacturing discipline common to all participants of the AMMT program to improve the performance, reliability, and lifetime of nuclear components. As part of this effort, we will develop a unified software architecture for AMMT data management and processing, deploy the digital platform across AMMT participants’ facilities, and generate pedigreed datasets in a common format across multiple labs and facilities. To this end, the MDDC work package has focused on three activities during FY23. First, the MDF Digital Tool was overhauled to better serve the needs of the AMMT program. Next, multiple laser powder bed fusion (L-PBF) systems at the MDF were upgraded to a common sensor package for collecting comparable in situ data across machines. Finally, various improvements relevant to the AMMT program were implemented in the ORNL-developed software tool, Peregrine. This report marks the completion of FY23 milestone M3CR-22OR0403051: Report Describing the Architecture of the Digital Platform to Support AMMT Activities.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Wireless Interrogation of High Temperature Surface Acoustic Wave Dynamic Strain Sensor

Dynamic strain sensing is necessary for high-temperature harsh-environment applications, including powerplants, oil wells, aerospace, and metal manufacturing. Monitoring dynamic strain is important for structural health monitoring and condition-based maintenance in order to guarantee safety, increase process efficiency, and reduce operation and maintenance costs. Sensing in high-temperature (HT), harsh-environments (HE) comes with challenges including mounting and packaging, sensor stability, and data acquisition and processing. Wireless sensor operation at HT is desirable because it reduces the complexity of the sensor connection, increases reliability, and reduces costs. Surface acoustic wave resonators (SAWRs) are compact, can operate wirelessly and battery-free, and have been shown to operate above 1000°C, making them a potential option for HT HE dynamic strain sensing. This paper presents wirelessly interrogated SAWR dynamic strain sensors operating around 288.8MHz at room temperature and tested up to 400°C. The SAWRs were calibrated with a high-temperature wired commercial strain gauge. The sensors were mounted onto a tapered-type Inconel constant stress beam and the assembly was tested inside a box furnace. The SAWR sensitivity to dynamic strain excitation at 25°C, 100°C, and 400°C was .439 μV/με, 0.363μV/με, and .136 μV/με, respectively. Furthermore, the experimental outcomes verified that inductive coupled wirelessly interrogated SAWRs can be successfully used for dynamic strain sensing up to 400°C.

47 OTHER INSTRUMENTATION↗
DOE OSTI2025

Casing Annulus Monitoring of CO 2 Injection Using Wireless Autonomous Distributed Sensor Networks

Effective and secure carbon subsurface storage, involving the deep underground injection of CO 2 into geological formations where it is permanently trapped, is paramount to mitigating CO 2 emissions (Figure I). Ensuring the integrity of these storage sites and detecting potential leakage through the casing annulus necessitates robust monitoring. This work provides the first integrated demonstration of a wireless casing-annulus monitoring architecture that can operate in highly attenuating cement-brine environments relevant to CO 2 storage. This project focused on developing and validating a novel sensor system for integration with autonomous monitoring near the cement reservoir interface. The goal was a fully integrated Technology Readiness Level (TRL) 4/5 field validation of a distributed wireless intelligent sensor system providing real-time, direct subsurface formation measurements to enhance fluid movement monitoring in the cemented casing annulus. Achieving this objective required the development and integration of 1) wireless autonomous microsensor technology by California Institute of Technology (Caltech); 2) sensor packaging and emplacement technology by Research Triangle Institute (RTI); and 3) smart well completions using wireless active casing collars and NOV pipe by the Sandia National Lab (SNL). The collaboration with the Caltech team in this project aimed to develop millimeter-scale radio frequency identification (RFID) sensors capable of detecting CO 2 , pH, and/or methane levels. These sensors are engineered to be impervious to fluids, allowing them to be mixed with cement and installed within the casing annulus. They operate using RFID protocols at frequencies of 902–928 MHz for both power and communication. A Sandia National Laboratories’ team engaged their expertise in the development of a Smart Collar system designed for the wireless data collection from these RFID sensors embedded in the cement annulus and transmission of this information to the ground surface via IntelliPipe/IntelliServ NOV drill pipe. This is accomplished through inductive coupling at the collar, which facilitates data transfer through each segment of the pipe. Because the system cannot transmit a direct current signal to power the Smart Collar, both power and communication were implemented using alternating current and electromagnetic signals at varying frequencies. Furthermore, the developed microsensor technology had to be demonstrated and validated in comparison with reference transducer measurements in a field test site at The University of Texas at Austin (UT-Austin). Although the full sensor suite did not reach field-deployment readiness, the system-level integration achieved in this project establishes a validated pathway for future incorporation of advanced microsensors.

47 OTHER INSTRUMENTATION↗
DOE OSTI2020

Drone Video Platform—Collision Avoidance, Situational Awareness, and Communications

Small unmanned aerial systems are ideal for delivering sensors into areas that are inaccessible or too dangerous for human entry or manned aircraft over-flights. The systems can fly low and slow for enhanced sensitivity and in tight spaces where ordinary aircraft could never fit. We have configured and flown sensor payloads for radiation, chemical, and optical detection on small fixed-wing and rotary-wing aircraft. All the sensor packages provide telemetry, GPS coordinates, LIDAR distance ranging, and absolute time of day to microsecond accuracy. Payload weights range from less than 1 kg up to 5.5 kg. Currently, communications are over 2.4 GHz and 915 MHz radios, as well as over 4G LTE cellular data links. Real-time data feeds from the sensor payloads to web browser clients anywhere in the world are possible via a virtual EC2 server on the Amazon AWS cloud. In FY 2019, the Nevada National Security Site teamed with Virginia Tech, H3D Corp., and Unmanned Systems, Inc. to accomplish the four flight missions described in this report. A large part of this year’s mission goals were to demonstrate the ability to fly beyond visual line of sight (BVLOS).

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2023

A heat flux sensor leveraging the transverse Seebeck effect in elemental antimony

Certain configurations of anisotropic single crystal materials can generate a thermoelectric voltage orthogonal to an induced temperature gradient. This phenomenon is known as the Transverse Seebeck Effect (TSE) and can be leveraged to fabricate simple and robust heat flux sensors. Only a small number of materials have been considered as TSE-based transducers and, among these, few have been developed into sensors with ruggedization against chemical and mechanical degradation. Here, we report on the fabrication and characterization of a rugged TSE-based heat flux sensor using prismatic antimony single crystals. The heat flux sensor was tested under static and dynamic heating scenarios. The sensor has a linear responsivity of 16.8 µV/(W/cm2) to heat fluxes spanning more than two orders of magnitude and a time constant of 4.4 s. The sensor’s response to localized heating, probed with a laser scanning technique, validated that the transduction mechanism is primarily the TSE by ruling out a sizable contribution from the conventional Seebeck effect. Finite element analysis corroborated that components used in the sensor package are the primary determinants of the time constant and the decrement of the responsivity from its theoretical maximum. Design principles that may be applied to elicit a faster transient response or higher responsivity are proposed. Furthermore, the results establish single crystal antimony as a promising transducer material for heat flux measurement systems and demonstrate potential effects of ruggedization on sensor performance.

36 MATERIALS SCIENCE↗
DOE OSTI2011

Integrated Sensing and Controls for Coal Gasification - Development of Model-Based Controls for GE's Gasifier and Syngas Cooler (Final Technical Report)

This report summarizes the achievements and final results of this program. The objective of this program is to develop a comprehensive systems approach to integrated design of sensing and control systems for an Integrated Gasification Combined Cycle (IGCC) plant, using advanced model-based techniques. In particular, this program is focused on the model-based sensing and control system design for the core gasification section of an IGCC plant. The overall approach consists of (i) developing a first-principles physics-based dynamic model of the gasification section, (ii) performing model-reduction where needed to derive low-order models suitable for controls analysis and design, (iii) developing a sensing system solution combining online sensors with model-based estimation for important process variables not measured directly, and (iv) optimizing the steady-state and transient operation of the plant for normal operation as well as for startup using model predictive controls (MPC). Initially, available process unit models were implemented in a common platform using Matlab/Simulink{reg_sign}, and appropriate model reduction and model updates were performed to obtain the overall gasification section dynamic model. Also, a set of sensor packages were developed through extensive lab testing and implemented in the Tampa Electric Company IGCC plant at Polk power station in 2009, to measure temperature and strain in the radiant syngas cooler (RSC). Plant operation data was also used to validate the overall gasification section model. The overall dynamic model was then used to develop a sensing solution including a set of online sensors coupled with model-based estimation using nonlinear extended Kalman filter (EKF). Its performance in terms of estimating key unmeasured variables like gasifier temperature, carbon conversion, etc., was studied through extensive simulations in the presence sensing errors (noise and bias) and modeling errors (e.g. unknown gasifier kinetics, RSC fouling). In parallel, an MPC solution was initially developed using ideal sensing to optimize the plant operation during startup pre-heating as well as steady state and transient operation under normal high-pressure conditions, e.g. part-load, base-load, load transition and fuel changes. The MPC simulation studies showed significant improvements both for startup pre-heating and for normal operation. Finally, the EKF and MPC solutions were coupled to achieve the integrated sensing and control solution and its performance was studied through extensive steady state and transient simulations in the presence of sensor and modeling errors. The results of each task in the program and overall conclusions are summarized in this final report.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2016

Thermoelectric-Driven Sustainable Sensing and Actuation Systems for Fault-Tolerant Nuclear Incidents

The Fukushima Daiichi nuclear incident in March 2011 represented an unprecedented stress test on the safety and backup systems of a nuclear power plant. The lack of reliable information from key components due to station blackout was a serious setback, leaving sensing, actuation, and reporting systems unable to communicate, and safety was compromised. Although there were several independent backup power sources for required safety function on site, ultimately the batteries were drained and the systems stopped working. If, however, key system components were instrumented with self-powered sensing and actuation packages that could report indefinitely on the status of the system, then critical system information could be obtained while providing core actuation and control during off-normal status for as long as needed. This research project focused on the development of such a self-powered sensing and actuation system. The electrical power is derived from intrinsic heat in the reactor components, which is both reliable and plentiful. The key concept was based around using thermoelectric generators that can be integrated directly onto key nuclear components, including pipes, pump housings, heat exchangers, reactor vessels, and shielding structures, as well as secondary-side components. Thermoelectric generators are solid-state devices capable of converting heat directly into electricity. They are commercially available technology. They are compact, have no moving parts, are silent, and have excellent reliability. The key components to the sensor package include a thermoelectric generator (TEG), microcontroller, signal processing, and a wireless radio package, environmental hardening to survive radiation, flooding, vibration, mechanical shock (explosions), corrosion, and excessive temperature. The energy harvested from the intrinsic heat of reactor components can be then made available to power sensors, provide bi-directional communication, recharge batteries for other safety systems, etc. Such an approach is intrinsically fault tolerant: in the event that system temperatures increase, the amount of available energy will increase, which will make more power available for applications. The system can also be used during normal conditions to provide enhanced monitoring of key system components.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2012

Ultra Fast X-ray Streak Camera for TIM Based Platforms

Ultra fast x-ray streak cameras are a staple for time resolved x-ray measurements. There is a need for a ten inch manipulator (TIM) based streak camera that can be fielded in a newer large scale laser facility. The LLNL ultra fast streak camera's drive electronics have been upgraded and redesigned to fit inside a TIM tube. The camera also has a new user interface that allows for remote control and data acquisition. The system has been outfitted with a new sensor package that gives the user more operational awareness and control.

47 OTHER INSTRUMENTATION↗
DOE OSTI2020

Multicube retroreflector and retroreflector-based communication system

A “multicube” retroreflector may include “nested” corner cubes. Such a design combines the ease of fabrication of conventional corner cubes (e.g., stamping from a sheet) and the ability to easily and densely package them with a greater range of angles over which light will be reflected back towards the source. Such multicube retroreflectors may reflect 50% more light than corner cube retroreflectors. A retroreflector, or an array of retroreflectors, may be used as part of a communication system. A modulated retroreflector or an array thereof can form the basis of a unique communication system. For instance, by using a modulated retroreflector, or an array of such retroreflectors, a host system (e.g., an aircraft) can receive data from a remote system (e.g., a drone, an air-dropped sensor package, etc.) in a way that is difficult to intercept, and minimizes the power, computation, and antenna pointing requirements for the remote system.

42 ENGINEERING↗
DOE OSTI2024

COMPASS-FME Synoptic Sites Level 1 Sensor Data v1-2

This is the version 1-2 Level 1 (L1) data release for COMPASS-FME environmental sensors located at our synoptic field sites. COMPASS-FME is studying sites in two distinct regions, the Chesapeake Bay and the Western Lake Erie Basin. We established the network at seven "synoptic" (observational) sites along the Chesapeake Bay and Lake Erie coastlines, collectively generating over three million observations per month, to track and comprehend environmental changes where land and water intersect. Additionally, the two regions provide an interesting contrast of saltwater and freshwater coasts that allow us to differentiate the impacts of inundation and coastal water chemistries in two nationally important coastal systems.L1 data are close to raw, but are units-transformed and have out-of-instrument-bounds and out-of-service flags added. Duplicates and missing data are removed but otherwise these data are not filtered, and have not been subject to any additional algorithmic or human QA/QC. Any scientific analyses of L1 data should be performed with care. **This dataset will be updated quarterly with new data for the duration of the project**This dataset includes:- An overall dataset README file that describes the current version, gives citation and contact information, etc.- Site- and year-specific folders, each holding up to 12 CSV (comma separated value) data files for each site and plot in that year.- Metadata files within each site-year folder provide full information on data units, expected ranges, contact information, as well as a general description of the site.- Environmental sensor types that appear in the data files include weather (ClimaVUE50, CS, RM Young, and LI instruments in the graphs below); soil conditions (TEROS12); soil redox state (Redox); groundwater variables (AquaTROLL200 and AquaTROLL600); open water sondes (Exo); tree sap velocity (Sapflow); and system voltage and state (Datalogger). Data are normally logged every 15 minutes. Please see v1-2 Synoptic L1 Sensor Package Quick Start.pdf for detailed information on data package structure, temporal coverage, and versioning.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Comparison of Machine Learning Algorithms for Natural Gas Identification with Mixed Potential Electrochemical Sensor Arrays

Mixed-potential electrochemical sensor arrays consisting of indium tin oxide (ITO), La 0.87 Sr 0.13 CrO 3 , Au, and Pt electrodes can detect the leaks from natural gas infrastructure. Algorithms are needed to correctly identify natural gas sources from background natural and anthropogenic sources such as wetlands or agriculture. We report for the first time a comparison of several machine learning methods for mixture identification in the context of natural gas emissions monitoring by mixed potential sensor arrays. Random Forest, Artificial Neural Network, and Nearest Neighbor methods successfully classified air mixtures containing only CH 4 , two types of natural gas simulants, and CH 4 +NH 3 with >98% identification accuracy. The model complexity of these methods were optimized and the degree of robustness against overfitting was determined. Finally, these methods are benchmarked on both desktop PC and single-board computer hardware to simulate their application in a portable internet-of-things sensor package. The combined results show that the random forest method is the preferred method for mixture identification with its high accuracy (>98%), robustness against overfitting with increasing model complexity, and had less than 10 ms training time and less than 0.1 ms inference time on single-board computer hardware.

03 NATURAL GAS↗
DOE OSTI2019

A novel occupancy detection solution using low-power IR-FPA based wireless occupancy sensor

Significant energy savings can be achieved by operating heating, ventilation, and air conditioning control systems with indoor occupancy measurement information. This paper presents a novel plug-and-play occupancy sensing method which will enable temporal minimization of building energy consumption to meet building usage behavior without privacy concerns. The proposed wireless occupancy sensing platform is based on long-wave infra-red (LWIR) focal-plane arrays (FPAs), or thermal imagers, that detect thermal energy rather than visible light. We developed an advanced sensor package consisting of multiple thermal imagers with low-cost optical enhancements to increase field of view and increase sensitivity to occupant detection (filtering building clutter). These imagers can be coupled with radio frequency and ultrasonic-based radar to enhance data collection at key occupant zone boundaries to improve accuracy. Standard filtering and estimation techniques from the image processing and computer vision communities are introduced to overcome the accuracy issues suffered by traditional PIR based sensing, especially when occupants remain relatively still. Accurate low-level counting of individuals can be achieved with minimal impact on privacy. As a result, the proposed occupancy detection method can work as a retrofit to enable real-time understanding of the building operational state and usage behavior. Sensor data obtained from real test building zones was used to test the efficacy of the method.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2024

COMPASS-FME Terrestrial Ecosystem Manipulation to Probe the Effects of Storm Treatments (TEMPEST) Experiment Level 1 Sensor Data v1-2

This is the version 1-2 Level 1 (L1) data release for COMPASS-FME environmental sensors located at our Terrestrial Ecosystem Manipulation to Probe the Effects of Storm Treatments (TEMPEST) experimental site. This manipulative, ecosystem-scale TEMPEST experiment addresses the potential for freshwater and estuarine-water disturbance events to alter tree function, species composition, and ecosystem processes in a deciduous coastal forest in MD, USA. The experiment uses a large-unit (2000 m2), un-replicated experimental design, with three 50 m × 40 m plots serving as control, freshwater, and estuarine-water treatments.L1 data are close to raw, but are units-transformed and have out-of-instrument-bounds and out-of-service flags added. Duplicates and missing data are removed but otherwise these data are not filtered, and have not been subject to any additional algorithmic or human QA/QC. Any scientific analyses of L1 data should be performed with care. **This dataset will be updated quarterly with new data for the duration of the project**This dataset includes:- An overall dataset README file that describes the current version, gives citation and contact information, etc.- Site- and year-specific folders, each holding up to 12 CSV (comma separated value) data files for each site and plot in that year.- Metadata files within each site-year folder provide full information on data units, expected ranges, contact information, detailed flood times, as well as a general description of the site.- Environmental sensor types that appear in the data files include weather (ClimaVUE50, CS, RM Young, and LI instruments in the graphs below); soil conditions (TEROS12); soil redox state (Redox); groundwater variables (AquaTROLL200 and AquaTROLL600); open water sondes (Exo); tree sap velocity (Sapflow); and system voltage and state (Datalogger). Data are normally logged every 15 minutes.Please see v1-2 TEMPEST L1 Sensor Package Quick Start.pdf for detailed information on data package structure, temporal coverage, and versioning.The TEMPEST flood events occurred on the following dates. They lasted for ~10 hours each day and delivered ~80,000 gallons to each plot; many data streams are available at 1 or 5 minute frequency during these periods.* Tests: Aug 25 (fresh plot) and Sep 9 (salt plot), 2021* TEMPEST 1: June 22, 2022* TEMPEST 2: June 6-7, 2023* TEMPEST 3: June 11-13, 2024

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Identifying Controlling Variables Related to Mercury Vapor Concentrations in Legacy Facilities: SRNL Technology Development For D&D

A suite of sensor packages has been installed in the Alpha-4 facility at Y-12 and preliminary data analysis to isolate the controlling variables has been performed after two months of data collection. In line with the conceptual model presented in Section 2.0, the preliminary analysis has demonstrated that temperature, barometric pressure, and relative humidity are the key controlling variables for mercury vapor releases within the building. The data analysis will continue to explore these controlling variables across the next several months to capture a more complete picture of the annual change in meteorological conditions at Y-12.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2016

Demonstration of a Prototype Hydrogen Sensor and Electronics Package - Progress Report 2

This is the second progress report on the demonstration of a prototype hydrogen sensor and electronics package. It goes into detail about the five tasks, four of which are already completed as of August 2016, with the final to be completed by January 26, 2017. Then the budget is detailed along with the planned work for May 27, 2016 to July 27, 2016.

36 MATERIALS SCIENCE↗