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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 OSTI2017

Solar Living House Final Technical Report

The Solar Living House is a high-performance solar-powered dwelling designed by a team of faculty and students from the University of Florida, in collaboration with Santa Fe College, the National University of Singapore, and Alachua Habitat for Humanity. The project was designed in accordance with the Solar Decathlon 2015, a research, design, education, and outreach program developed by the U.S. Department of Energy (DOE). The Solar Living House is fundamentally a house for living, centered on people and the activities of daily life while quietly introducing advanced design, construction, and engineering technologies. The 993 square-foot two-bedroom one-bath home was designed to embrace and frame an exterior courtyard space. This courtyard acts as an extension of the interior living spaces, maximizing the spatial potentials of a modest building footprint and introducing natural light into the primary living spaces of the house. Research Outcomes: The Solar Living House advances work on high-performance buildings through three principal technological innovations: wet/dry modular construction, a building automation system, and solar dehumidification systems. Wet / Dry Modular Construction: The house is designed as a series of five modules, including one that is designated as the “wet core.” The wet core consolidates the mechanical systems and bathroom into a single module to reduce plumbing runs, efficiency losses, and on-site construction time. The other four modules are designed to eliminate interior load bearing walls to allow for maximum flexibility in the reconfiguring of the space over time. The modules are designed to meet the structural challenges of both Florida’s hurricanes and California’s earthquakes. Building Automation System: The house is equipped with an integrated building automation system, allowing the houses environmental systems, lights, security systems, and smoke detectors to be programmed, monitored, and controlled through any mobile or computing device. These systems allow for more precise calibrations of temperature/humidity/lighting to correspond with user needs and preferences, minimizing energy losses with economical night- or day-time setbacks. Solar Dehumidification System: The most significant technological innovation in the Solar Living House is the solar thermal dehumidification system. This system generates hot water through two rooftop-mounted evacuated tube solar thermal collectors. The hot water is used to continually dry a regenerative solid desiccant material, typically white silica gel. The solid desiccant is used to adsorb moisture and humidity from the air without additional mechanical cooling. This strategy allows humidity to be modulated independently of air temperature, providing greater thermal comfort and reducing the opportunity for the growth of mold spores within the house while also reducing the overall energy consumption of the HVAC system. Economic Feasibility: The team set aggressive goals for affordability, targeting a construction cost of $138,710. An independent professional cost estimator determined the overall project costs, as designed, would be $333,799, or $336.15 per square foot of finished floor area. This is more than 2.4 times the target construction cost. By comparison, the average construction cost for a home in the United States in 2015 was $289,415, or $103.29 per square foot of finished floor area. Following work on the Solar Living House, team leaders incorporated many of its objectives into a net-zero energy home on a site in Gainesville, Florida. This site-built home avoided many of the constraints and complications of modular construction necessitated by the Solar Decathlon, allowing it to be built for a much more modest budget. This two-bedroom two bath 1,800 square foot home was constructed for $135.39 per square foot, including active photovoltaic solar systems, careful attention to continuous air barriers, increased insulation levels, and permanent site constructions. This project suggest that high-performance buildings can be realized for more modest budgets. Public Benefits: Work on the Solar Living House and Solar Decathlon 2015 offered our student team unparalleled learning opportunities. Because of the duration of the project, a number of students participated at different points in their education, from first year undergraduates all the way through to advanced graduate students. The opportunity for collaboration with students and faculty from the National University of Singapore was also extraordinary, allowing for a sharing of technical knowledge and cultural exchange. The wider public has benefited from this work as its findings have been shared through public presentations and publications. It serves as a useful stepping stone along the path towards affordable, high-performance buildings.

14 SOLAR ENERGY↗
DOE OSTI2016

Entropy production of doubly stochastic quantum channels

We study the entropy increase of quantum systems evolving under primitive, doubly stochastic Markovian noise and thus converging to the maximally mixed state. This entropy increase can be quantified by a logarithmic-Sobolev constant of the Liouvillian generating the noise. We prove a universal lower bound on this constant that stays invariant under taking tensor-powers. Our methods involve a new comparison method to relate logarithmic-Sobolev constants of different Liouvillians and a technique to compute logarithmic-Sobolev inequalities of Liouvillians with eigenvectors forming a projective representation of a finite abelian group. Our bounds improve upon similar results established before and as an application we prove an upper bound on continuous-time quantum capacities. In the last part of this work we study entropy production estimates of discrete-time doubly stochastic quantum channels by extending the framework of discrete-time logarithmic-Sobolev inequalities to the quantum case.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2021

Individual and Collective Strategies to Limit the Impacts of Large Power Outages of Long Duration

As modern society becomes ever more dependent on the availability of electric power, the costs that could arise from individual and social vulnerability to large outages of long duration (LLD-outages) increases. During such an outage, even a small amount of power would be very valuable. Here, this article compares individual and collective strategies for providing limited amounts of electric power to residential customers in a hypothetical New England community during a large electric power outage of long duration. We develop estimates of the emergency load required for survival and assess the cost of strategies to address outages that last 5, 10, and 20 days in either winter or summer. We find that the cost of collective solutions could be as much as 10 to 40 times less than individual solutions (less than $2 per month per home). However, collective solutions would require community-wide coordination, and if local distribution system lines are destroyed, only individual back-up systems could provide contingency power until those lines are repaired. Costs might be reduced if more robust distributed generation were employed that could be operated continuously with the ability to sell power back to the grid. Our cost-effectiveness analysis only assesses what could be done, developing estimates of preparedness cost. A decision about what should be done would require additional input from a range of stakeholders as well as some form of analytical deliberative process.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2017

Integration and assessment of component health prognostics in supervisory control systems - 291

Enhanced risk monitors (ERMs) for active components in advanced reactor concepts use predictive estimates of component failure to update, in real time, predictive safety and economic risk metrics. These metrics have been shown to be capable of use in optimizing maintenance scheduling and managing plant maintenance costs. Integrating this information with plant supervisory control systems increases the potential for making control decisions that utilize realtime information on component conditions. Such decision making would limit the possibility of plant operations that increase the likelihood of degrading the functionality of one or more components while maintaining the overall functionality of the plant. ERM uses sensor data for providing real-time information about equipment condition for deriving risk monitors. This information is used to estimate the remaining useful life and probability of failure of these components. By combining this information with plant probabilistic risk assessment models, predictive estimates of risk posed by continued plant operation in the presence of detected degradation may be estimated. In this paper, we describe this methodology in greater detail, and discuss its integration with a prototypic software-based plant supervisory control platform. In order to integrate these two technologies and evaluate the integrated system, software to simulate the sensor data was developed, prognostic models for feedwater valves were developed, and several use cases defined. The full paper will describe these use cases, and the results of the initial evaluation. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2017

Integration and Assessment of Component Health Prognostics in Supervisory Control Systems

Enhanced risk monitors (ERMs) for active components in advanced reactor concepts use predictive estimates of component failure to update, in real time, predictive safety and economic risk metrics. These metrics have been shown to be capable of use in optimizing maintenance scheduling and managing plant maintenance costs. Integrating this information with plant supervisory control systems increases the potential for making control decisions that utilize real-time information on component conditions. Such decision making would limit the possibility of plant operations that increase the likelihood of degrading the functionality of one or more components while maintaining the overall functionality of the plant. ERM uses sensor data for providing real-time information about equipment condition for deriving risk monitors. This information is used to estimate the remaining useful life and probability of failure of these components. By combining this information with plant probabilistic risk assessment models, predictive estimates of risk posed by continued plant operation in the presence of detected degradation may be estimated. In this paper, we describe this methodology in greater detail, and discuss its integration with a prototypic software-based plant supervisory control platform. In order to integrate these two technologies and evaluate the integrated system, software to simulate the sensor data was developed, prognostic models for feedwater valves were developed, and several use cases defined. The full paper will describe these use cases, and the results of the initial evaluation.

Ramuhalli, Pradeep↗
DOE OSTI2015

Adaptive Data Processing Technique for Lidar-Assisted Control to Bridge the Gap between Lidar Systems and Wind Turbines: Preprint

This paper presents first steps toward an adaptive lidar data processing technique crucial for lidar-assisted control in wind turbines. The prediction time and the quality of the wind preview from lidar measurements depend on several factors and are not constant. If the data processing is not continually adjusted, the benefit of lidar-assisted control cannot be fully exploited, or can even result in harmful control action. An online analysis of the lidar and turbine data are necessary to continually reassess the prediction time and lidar data quality. In this work, a structured process to develop an analysis tool for the prediction time and a new hardware setup for lidar-assisted control are presented. The tool consists of an online estimation of the rotor effective wind speed from lidar and turbine data and the implementation of an online cross correlation to determine the time shift between both signals. Further, initial results from an ongoing campaign in which this system was employed for providing lidar preview for feed-forward pitch control are presented.

17 WIND ENERGY↗
DOE OSTI2018

Direct Breakthrough Curve Prediction From Statistics of Heterogeneous Conductivity Fields

In this paper, we present a methodology to predict the shape of solute breakthrough curves in heterogeneous aquifers at early times and/or under high degrees of heterogeneity, both cases in which the classical macrodispersion theory may not be applicable. The methodology relies on the observation that breakthrough curves in heterogeneous media are generally well described by lognormal distributions, and mean breakthrough times can be predicted analytically. The log-variance of solute arrival is thus sufficient to completely specify the breakthrough curves, and this is calibrated as a function of aquifer heterogeneity and dimensionless distance from a source plane by means of Monte Carlo analysis and statistical regression. Using the ensemble of simulated groundwater flow and solute transport realizations employed to calibrate the predictive regression, reliability estimates for the prediction are also developed. Additional theoretical contributions include heuristics for the time until an effective macrodispersion coefficient becomes applicable, and also an expression for its magnitude that applies in highly heterogeneous systems. Finally, it is seen that the results here represent a way to derive continuous time random walk transition distributions from physical considerations rather than from empirical field calibration.

58 GEOSCIENCES↗
DOE OSTI2022

Glassy quantum nuclear pasta in neutron star crusts

We conduct a comprehensive survey of the shape parameter space of the nuclear pasta phases in neutron star crusts by conducting three-dimensional Hartree-Fock + BCS calculations. Spaghetti, waffles, lasagna, bicontinuous phases and cylindrical holes occupy local minima in the resulting constant-pressure Gibbs energy surfaces, implying multiple geometries coexist at a given depth. Notably, the bicontinuous phase, in which both the neutron gas and nuclear matter extend continuously in all dimensions appears over a large depth range. Our results support the idea that nuclear pasta is a glassy system. At a characteristic temperature, of order 10 8 – 10 9 K, different phases may become frozen into domains whose sizes we estimate to be 1–50 times the lattice spacing and over which the local density and electron fraction can vary. Above this temperature, very little long-range order exists and matter is an amorphous solid. Electron scattering off domain boundaries may contribute to the disorder resistivity of the pasta phases. Annealing of the domains may occur during cooling; repopulating of local minima during crustal heating might lead to temperature-dependent transport properties in the deep crust layers. We identify four regions distinguished by whether pasta is the true ground state, and whether the pasta structure allows delocalization of protons. The whole pasta region can occupy up to 70% of the crust by mass and 25% by thickness, and the layer in which protons are delocalized could occupy 45% of the crust mass and 15% of its thickness.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2017

FINAL REPORT - Development of High Pressure Hydrogen Storage Tank for Storage and Gaseous Truck Delivery

The “Development of High Pressure Hydrogen Storage Tanks for Storage and Gaseous Truck Delivery” project [DE-FG36-08GO18062] was initiated on 01 July 2008. Hexagon Lincoln (then Lincoln Composites) received grant funding from the U.S. Department of Energy to support the design and development of an improved bulk hauling and storage solution for hydrogen in terms of cost, safety, weight and volumetric efficiency. The development of this capability required parallel development and qualification of large all-composites pressure vessels, a custom ISO container to transport and store said tanks, and performance of trade studies to identify optimal operating pressure for the system. Qualification of the 250 bar TITAN® module was completed in 2009 with supervision from the American Bureau of Shipping [ABS], and the equipment has been used internationally for bulk transportation of fuel gases since 2010. Phase 1 of the project was successfully completed in 2012 with the issuance of USDOT SP 14951, the special permit authorizing the manufacture, marking, sale and use of TITAN® Mobile Pipeline® equipment in the United States. The introduction of tube trailers with light weight composite tankage has meant that 2 to 3 times as much gaseous fuel can be transported with each trip. This increased hauling efficiency offers dramatically reduced operating costs and has enabled a profitable business model for over-the-road compressed natural gas delivery. The economic drivers of this business opportunity vary from country to country and region to region, but in many places gas distribution companies have realized profitable operations. Additional testing was performed in 2015 to characterize hydrogen-specific operating protocols for use of TITAN® systems in CHG service at 250 bar. This program demonstrated that existing compression and decompression methodologies can efficiently and safely fill and unload lightweight bulk hauling systems. Hexagon Lincoln and U.S. DOE agreed to continue into Phase 2 of the project without pursuing the development of higher pressure capabilities as originally planned. At 250 bar, development of equipment for hydrogen transport is supported by strong activity in the adjacent natural gas transportation sector. Trade studies performed since 2011 indicate optimization of hauling efficiency and system cost for hydrogen transport at about 350 bar (5076 psi). However, due to reduced efficiency of compression of natural gas above 250 bar, 350 bar operation is not an attractive option for natural gas transportation. The CHG market is not developed at this time, and it is difficult to forecast the arrival of significant revenues. On the investment side, the cost to fully qualify a large tank module at 350 bar is estimated at $3MM to $5MM. There is insufficient CHG market definition to support a stand-alone business case for this investment without near term revenue in the adjacent CNG transportation market. Therefore development of a 350 bar TITAN® system was deferred and not pursued under this project. Hexagon Lincoln continues to support the development of tankage and equipment for operation at 350 bar and above; with 700 bar vehicle tanks and 950 bar tanks for ground storage applications. Phase 2 activities were focused on reducing system cost, increasing system capacity, increasing system safety and characterization of polymer material performance specific to hydrogen pressure vessel usage. With the successful launch of TITAN® modules and trailers in natural gas transportation, over 600 units have been produced through the end of 2016, resulting in improved purchasing power for raw materials and manufactured components. This has allowed Hexagon Lincoln to approach the current project goals for system cost. At $590/kg of compressed hydrogen delivered, the system cost of the baseline TITAN® module is below the project’s 2015 target of $730/kg H2 delivered, and very close to the project’s 2020 target of $575/kg H2 delivered. [Based on product pricing in 1Q2017.] Emphasis was placed on configuration of larger capacity systems within the vehicle weights and dimensions allowed on federal and state highways in the United States and other countries. These activities resulted in the design and development of integrated tube trailer systems that have increased delivery capacities by 45%. The hydrogen delivery capacity of our largest system is 845 kg, exceeding the project’s 2015 target of 700 kg H2 delivered. Emerging technologies offering improvement of the safety systems used on the equipment were investigated, with particular focus on improving the reliability and cost of the emergency venting system for fire protection. Finally, investment in our materials laboratory improved detection and characterization of hydrogen-induced damage in polymer materials, supporting the development of operational protocols to avoid damage to pressure vessel liners and valve components.

08 HYDROGEN↗
DOE OSTI2015

Convergence of Vehicle and Infrastructure Data for Traffic and Demand Management

The increasing availability of highly granular, vehicle trajectory data combined with ever increasing stores of roadway sensor data has provided unparalleled observability into the operation of our urban roadway networks. These data sources are quickly moving from research and prototype environments into full-scale commercial deployment and data offerings. The observability gained allows for increased control opportunities to enhance transportation mobility, safety and energy efficiency. The National Renewable Energy Laboratory (NREL) is involved in three initiatives to leverage these data for positive outcomes: 1) In 2015 NREL, in cooperation with industry and university partners, was awarded an ARPA-E research grant to research a control architecture to incentivize individual travelers toward more sustainable travel behavior. Based on real-time data on the traveler's destination and state of the system, the traveler is presented with route and/or mode choices and offered incentives to accept sustainable alternatives over less-sustainable ones. The project tests the extent to which small incentives can influence, or tip the balance toward more sustainable travel behavior. 2) Although commercial sources of travel time and speed have emerged in recent years based on vehicle probe data, volume estimates continue to rely primarily on historical count data factored for the time of day, day of week, and season of year. Real-time volume flows would enable better tools, simulation in the loop, and ultimately more effective control outcomes. NREL in cooperation with the University of Maryland and industry traffic data providers (INRIX, HERE and TomTom), are attempting to accelerate the timeframe to a viable real-time vehicle volume data feed based on probe data. 3) Signal control on urban arterials for years has had to rely on models rather than measured data to assess performance. High-resolution controller data and low-cost re-identification data now allows for direct measurement of the quality of progression along a corridor. Though still requiring an investment in equipment and communications, these data sources are transforming traffic signal management to a data driven, performance management basis. Ever increasing availability of granular GPS trace data from automobiles may allow for assessment of traffic signal performance, allowing for signal optimization while minimizing the investment in additional sensors and communication infrastructure.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2017

Determination of a Generic Human Error Probability Distribution, Part 1: A Dynamic Formulation of SPAR-H

In almost all major nuclear power plants (NPP) events include a significant human error component. As an example, in Fukushima Daiichi (2011) nuclear meltdown, the human actions related to the high-pressure injection cooling strongly affected accident evolution. Furthermore, in the Three Mile Island accident (1979) (which was initiated by a stuck open valve and thus was triggered a loss of coolant accident) the unit operators made decisions based upon false assumptions that contributed negatively to the accident. Given these premises, the ability to accurately model human interactions with plant evolution and, in particular, dynamically calculate human error probability (HEP) plays a major role in a probabilistic risk analysis (PRA). Human reliability analysis (HRA) identifies and models the causes of human errors, and quantifies HEP by applying different methodologies. HRA methods identify errors and reflect on the understanding of error-prone people and systems. There are a number of HRA methods available that assist in identifying the vulnerabilities in the system and provide guidance in determining the HEP. HEP is the probability of a human failure event (HFE), and quantification of HEPs under various situations is utilized in PRA of large complex systems. One of the more prominent HRA methods is the Standardized Plant Analysis Risk-Human Reliability Analysis (SPAR-H) method that was developed to estimate HEPs for the use in the Standardized Plant Analysis Risk (SPAR) PRA models employed in U.S. NPPs. SPAR-H is implemented in U.S. NPPs by regulators at the U.S. Nuclear Regulatory Commission (NRC) to determine the HEP based on expert estimation through the use of calculation worksheets. In SPAR-H, the nominal HEPs (NHEPs) are multiplied by performance shaping factors (PSF) multiplier values to obtain the overall error probability. PSFs encompass the human components, individual characteristics, their environment, and aspects of the task. With PSFs, the goal is to capture all factors that can affect human performance. In SPAR-H there are eight PSFs used, each having respective levels corresponding to multipliers: Available Time, Stress/Stressors, Complexity, Experience/Training, Procedures, Ergonomics/Human Machine Interface, Fitness for Duty, and Work Processes. The PSF multipliers indicate enhanced, nominal, or degraded human performance. The SPAR-H method estimates the HEP through multiplying a NHEP with PSFs. Hence, SPAR-H is a traditional HRA method that assesses human performance at a fixed, or static, point in time. In a dynamic HRA framework, human performance is assessed on a continuous time basis. SPAR-H can be used within a dynamic PRA framework through the use of simulation and stochastic models. The goal of dynamic HRA is to build a more realistic model of the human-system interaction to enhance calculation of reliability, risk and safety analysis. The progression of events in dynamic SPAR-H considers that some PSFs may experience gradual change, while other change can be sudden due to individualistic differences or rapid plant status changes. The PSF changes are caused by contextual changes in the scenario. For example, as more time passes, the realization that a task should be completed sooner may cause the operator more stress. In another example, a sudden relay of information about sickness of a family member may alter the operator's general stress level and fitness for duty. Each PSF has a different dynamic nature; PSFs like stress and complexity change more quickly over the course of a task than experience and training. While the experience of an operator changes over the course of attaining the objective, the amount that this added experience changes the HEP is very minimal. In contrast, the stress, complexity, and procedures PSFs may change quite a bit over the course of task completion.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2020

Continuous and discrete modeling of HIV-1 decline on therapy

Mathematical models have shed light on the dynamics of HIV- 1 infection in vivo. In this paper, we generalize continuous mathematical models of drug therapy for HIV-1 by Perelson et al. (Science 271:1582–1586, 1996) and Perelson and Nelson (SIAM Rev 41:3–44, 1999) on time scales, i.e., a nonempty closed subset of real numbers in order to derive new discrete models that predict the total concentration of plasma virus as a function of time. Here, one of our main goals is to compare discrete mathematical models with the continuous model in Perelson et al. (1996) where HIV infected patients were given protease inhibitors and sampled frequently thereafter. For the comparison, we use experimental data collected in Perelson et al. (1996) and estimate the parameters such as the virion clearance rate and the rate of loss of infected cells by fitting the total concentration of plasma virus to this data set. Our results show that discrete systems describe the best fit. In the previous models of this study, the efficacy of protease inhibitor is assumed to be perfect. Motivated by Perelson and Nelson (1999), we end the paper with a mathematical model of imperfect protease inhibitor and reverse transcriptase (RT) inhibitor combination therapy of HIV-1 infection on time scales with its stability analysis.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2012

SPECKLE INTERFEROMETRY AND ORBITS OF 'FAST' VISUAL BINARIES

Results of speckle observations at the 4.1 m SOAR telescope in 2012 (158 measures of 121 systems, 27 non-resolutions) are reported. The aim is to follow fast orbital motion of recently discovered or neglected close binaries and sub-systems. Here, eight previously known orbits are defined better, two more are completely revised, and five orbits are computed for the first time. Using differential photometry from Hipparcos or speckle and the standard relation between mass and absolute magnitude, the component's masses and dynamical parallaxes are estimated for all 15 systems with new or updated orbits. Two astrometric binaries HIP 54214 and 56245 are resolved here for the first time, another eight are measured. We highlight several unresolved pairs that may actually be single despite multiple historic measures, such as 104 Tau and f Pup AB. Continued monitoring is needed to understand those enigmatic cases.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2018

Hydrogen Generation Rates for Tank 50 and Saltstone Related Samples using a Sealed Reactor System

This report documents the results of sealed reactor tests to measure the hydrogen generation rate (HGR) from Tank 50 waste, which may be on the order of 10 -10 (ft 3 /h)/gal. Because the estimated HGR limit of detection (LOD) for an open, continuous flow system is approximately 10 -7 (ft 3 /h)/gal a more sensitive method was needed. By accumulating generated gasses in a sealed system without a continuous purge gas, the resulting concentrations can increase the sensitivity of measurement, which is based on time of heating.

08 HYDROGEN↗
DOE OSTI2025

Design Report on the MiniFuel Instrumented Test Apparatus for Understanding Radiation Effects

Most nuclear fuels irradiations at Oak Ridge National Laboratory (ORNL) over the past decade have been conducted using MiniFuel—a static capsule design employing subscale fuel specimens to collect separate-effects irradiated fuel performance data. Irradiation conditions for MiniFuel experiments are predicted pre-test using reactor physics, and thermal models are verified post-irradiation via SiC dilatometry and various spectrometry methods. Relevant fuel performance parameters are also observed post-irradiation in a hot cell, thereby providing a single data point for each parameter representing the cumulative effects of the irradiation conditions. Substantially more data can be harvested from a single test and within a shorter duration by instrumenting irradiation vehicles and measuring desired quantities in situ. This report presents the design and analysis of the MiniFuel INstrumented Irradiation Test Apparatus for Understanding Radiation Effects (MINITAURE)—an instrumented test rig based on the separate-effects MiniFuel concept that aims to capture fission gas release (FGR) and thermal conductivity degradation of fuel specimens during irradiation in the High Flux Isotope Reactor (HFIR). MINITAURE will be integrated with the Materials Irradiation Facility (MIF) located in the HFIR building outside the reactor containment. The MIF will act as the instrumentation and control center for the experiment, enabling real-time feedback from in situ sensors and control of irradiation temperatures via a gas delivery system. Two unique capsule designs were developed to capture each phenomenon: the thermal conductivity capsule, which uses a thermopile method to estimate fuel specimen thermal conductivity, and the fission gas release capsule, which will have continuous flowing gas communication to high-purity germanium detectors that are housed in the MIF for monitoring FGR. This report details the reactor physics and heat transfer modeling activities that were used to inform the experiment design and predict capsule performance. It also describes out-of-pile activities conducted to stand up this new capability and verify the measurement techniques. Modeling efforts to date have demonstrated the feasibility of the in situ measurement techniques and supported the development of the MINITAURE assembly configuration. Out-of-pile testing of the thermal conductivity measurement shows promise in capturing relative changes in thermal conductivity. However, significant errors exist in the measured absolute value, posing a need for further refinement.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2019

Automatic high-frequency measurements of full soil greenhouse gas fluxes in a tropical forest

Measuring in situ soil fluxes of carbon dioxide (CO 2 ), methane(CH 4 ), and nitrous oxide (N 2 O) continuously at highfrequency requires appropriate technology. We tested the combination of acommercial automated soil CO 2 flux chamber system (LI-8100A) with a CH 4 and N 2 O analyzer (Picarro G2308) in a tropicalrainforest for 4 months. A chamber closure time of 2 min was sufficient fora reliable estimation of CO 2 and CH 4 fluxes (100 %and 98.5 % of fluxes were above minimum detectable flux – MDF,respectively). This closure time was generally not suitable for a reliableestimation of the low N 2 O fluxes in this ecosystem but wassufficient for detecting rare major peak events. A closure time of 25 minwas more appropriate for reliable estimation of most N 2 O fluxes(85.6 % of measured fluxes are above MDF ± 0.002 nmol m -2 s -1 ). Our study highlights the importance ofadjusted closure time for each gas.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Adaptive, self-tuning virtual sensing system for cyber-attack neutralization

An industrial asset may have a plurality of monitoring nodes, each monitoring node generating a series of monitoring node values over time representing current operation of the industrial asset. An abnormality detection computer may determine that an abnormal monitoring node is currently being attacked or experiencing a fault. An autonomous, resilient estimator may continuously execute an adaptive learning process to create or update virtual sensor models for that monitoring node. Responsive to an indication that a monitoring node is currently being attacked or experiencing a fault, a level of neutralization may be automatically determined. The autonomous, resilient estimator may then be dynamically reconfigured to estimate a series of virtual node values based on information from normal monitoring nodes, appropriate virtual sensor models, and the determined level of neutralization. The series of monitoring node values from the abnormal monitoring node or nodes may then be replaced with the virtual node values.

Abbaszadeh, Masoud↗