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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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At least 937 records · Page 52
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Ibis Networks/WattIQ (IN2 Final Report)

Ibis Networks is a full-stack cleantech company that provides plug-level energy monitoring and control to solve energy and asset management problems for the enterprise. During DATES – DATES, an NREL research team worked with the Ibis team to validate their product, the InteliSocket. The Ibis InteliSocket is a pass-through plug-load energy monitor and controller that is designed to reduce energy wasted by common 120 V plug-in devices in commercial office buildings, such as computer peripherals, conference room AV equipment, and break-room appliances. The system can shut off supply power to these end uses via remote control, manual switches, pre-set schedules, or automated control algorithms. The scope of this IN2 project was the development and refinement of “smart” learning behavior algorithms (LBAs), which could help installation processes and dramatically expand the sockets’ capabilities and energy-saving potential by suggesting suitable control schedules that are based on monitored use patterns. While Ibis has the analytical and software expertise for algorithm development, the lack of test data, both in a controlled laboratory setting and in real-life deployment scenarios, represented a key barrier toward commercialization of the product. Assistance through the IN2 program provided an opportunity to conduct the needed “trial and error” algorithm development. The project included baseline field-data collection, laboratory testing, and field validation components, all of which were conducted at the NREL campus between April 2017 and July 2019.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2022

Nuclear Forensics

Nuclear forensics is a key part of the nuclear security strategy for the United States and the international community. The NACS Division is central to the leadership role that LLNL has had in nuclear forensics over the past 25 years. Our current nuclear forensic program includes conducting R&D on provenance and attribution signatures, collaborating with international partners, training the next generation of nuclear forensic experts, developing test materials for verification and validation exercises, and providing expert advice to national and international policy makers. Key to our success in these areas has been the strong and continuing involvement in nuclear forensic casework obtained through law enforcement and intelligence channels as well as our outstanding analytical capabilities. NACS must continue to conduct forward-thinking R&D in nuclear forensics that supports operational programs and addresses intelligence gaps. To maintain leadership in nuclear forensics, we must attract, develop, and retain the best talent. The NNSA has a central leadership role in developing educational initiatives for nuclear forensics. In concert with the Glenn T. Seaborg Institute, the NACS Division will continue to participate in all nuclear forensic educational initiatives (undergraduate, graduate, postdoctoral) and incorporate LLNL’s D&I vision into its student and postdoc recruitment efforts. We will continue to build formal relationships with key academic partners and institutions with active and emerging nuclear forensic research interests. We will also strengthen relationships with NNSA DNN and SSAA funded university consortia (e.g. NSSC, ACE, CNEC, CVT, ETI, MTV), helping them conduct research of interest and relevance to nuclear forensics, while at the same time evaluating and recruiting promising talent from these programs.

07 ISOTOPE AND RADIATION SOURCES↗
DOE OSTI2024

High-Throughput Microstructural Characterization and Process Correlation Using Automated Electron Backscatter Diffraction

The need to optimize the processing conditions of additively manufactured (AM) metals and alloys has driven advances in throughput capabilities for material property measurements such as tensile strength or hardness. High-throughput (HT) characterization of AM metal microstructure has fallen significantly behind the pace of property measurements due to intrinsic bottlenecks associated with the artisan and labor-intensive preparation methods required to produce highly polished surfaces. This inequality in data throughput has led to a reliance on heuristics to connect process to structure or structure to properties for AM structural materials. In this study, we show a transformative approach to achieve laser powder bed fusion (LPBF) printing, HT preparation using dry electropolishing and HT electron backscatter diffraction (EBSD). This approach was used to construct a library of > 600 experimental EBSD sample sets spanning a diverse range of LPBF process conditions for AM Kovar. This vast library is far more expansive in parameter space than most state-of-the-art studies, yet it required only approximately 10 labor hours to acquire. Build geometries, surface preparation methods, and microscopy details, as well as the entire library of >600 EBSD data sets over the two sample design versions, have been shared with intent for the materials community to leverage the data and further advance the approach. Using this library, we investigated process–structure relationships and uncovered an unexpected, strong dependence of microstructure on location within the build, when varied, using otherwise identical laser parameters.

Characterization and Analytical Technique↗
DOE OSTI2011

Synthesis, crystal structure and magnetic characterization of metal(II) coordination polymers based on 2-carboxyethylphosphonic acid and 1,10-phenanthroline (metal=Cu, Co, Cd)

Three non-isostructural metal(II) coordination polymers (metal=copper, cobalt, cadmium) were synthesized under the same mild hydrothermal conditions (T=408 K) by mixture of the corresponding metal acetate with 2-carboxyethylphosphonic acid and 1,10-phenanthroline (1:1:1 M ratio) and their structures were determined by single-crystal X-ray diffraction. Cu{sub 2}(HO{sub 3}PCH{sub 2}CH{sub 2}COO){sub 2}(C{sub 12}H{sub 8}N{sub 2}){sub 2}(H{sub 2}O){sub 2} and Cd{sub 2}(HO{sub 3}PCH{sub 2}CH{sub 2}COO){sub 2}(C{sub 12}H{sub 8}N{sub 2}){sub 2} are triclinic (space group P-1) with a=7.908(5) A, b=10.373(5) A, c=11.515(5) A, {alpha}=111.683(5) Degree-Sign , {beta}=95.801(5) Degree-Sign , {gamma}=110.212(5) Degree-Sign (T=120 K), and a=8.162(5) A, b=9.500(5) A, c=11.148(5) A, {alpha}=102.623(5) Degree-Sign , {beta}=98.607(5) Degree-Sign , {gamma}=113.004(5) Degree-Sign (T=293 K), respectively. In contrast, [Co{sub 2}(HO{sub 3}PCH{sub 2}CH{sub 2}COO){sub 2}(C{sub 12}H{sub 8}N{sub 2}){sub 2}({mu}-OH{sub 2})](H{sub 2}O) is orthorhombic (space group Pbcn) with a=21.1057(2) A, b=9.8231(1) A, c=15.4251(1) A (T=120 K). For these three compounds, structural features, including H-bond network and the {pi}-{pi} stacking interactions, and thermal stability are reported and discussed. None of the materials present a long-range magnetic order in the range of temperatures investigated from 300 K down to 1.8 K. - Graphical abstract: In same synthetic conditions, both the chemical and structural features of three transition metal(II) coordination polymers based on 2-carboxyethylphosphonate and 1-10 Prime -phenanthroline are influenced by the metal cation characteristics, leading to non-homologous materials with different properties, which show the high chemical versatility of this interesting system. Highlights: Black-Right-Pointing-Pointer Non-isostructural metal coordination polymers were synthesized under mild hydrothermal conditions. Black-Right-Pointing-Pointer Ligand's flexibility provides the opportunity to design compounds with tailored properties. Black-Right-Pointing-Pointer Structural changes in the secondary building units are induced by metal features.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2016

Hydrothermal synthesis for new multifunctional materials: A few examples of phosphates and phosphonate-based hybrid materials

Novel physical or chemical properties are expected in a great variety of materials, in connection with the dimensionality of their structures and/or with their nanostructures, hierarchical superstructures etc. In the search of new advanced materials, the hydrothermal technique plays a crucial role, mimicking the nature able to produce fractal, hyperbranched, urchin-like or snow flake structures. In this short review including new results, this will be illustrated by examples selected in two types of materials, phosphates and phosphonates, prepared by this method. The importance of the synthesis parameters will be highlighted for a magnetic iron based phosphates and for hybrids containing phosphonates organic building units crystallizing in different structural types. - Graphical abstract: Phosphate dendrite like and phosphonate platelet crystals.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2018

Spark Plasma Sintering (SPS)-Assisted Synthesis and Thermoelectric Characterization of Magnéli Phase V 6 O 11

The Magnéli phase V6O11 was synthesized in gram amounts from a powder mixture of V 6 O 11 /V 7 O 13 and vanadium metal, using the spark plasma sintering (SPS) technique. Its structure was determined with synchrotron X-ray powder diffraction data from a phase-pure sample synthesized by conventional solid-state synthesis. A special feature of Magnéli-type oxides is a combination of crystallographic shear and intrinsic disorder that leads to relatively low lattice thermal conductivities. SPS prepared V 6 O 11 has a relatively low thermal conductivity of κ = 2.72 ± 0.06 W (m K) –1 while being a n-type conductor with an electrical conductivity of σ = 0.039 ± 0.005 (μΩ m) –1 , a Seebeck coefficient of α = –(35 ± 2) μV K –1 , which leads to a power factor of PF = 4.9 ± 0.8 × 10 –5 W (m K 2 ) –1 at ~600 K. Advances in the application of Magnéli phases are mostly hindered by synthetic and processing challenges, especially when metastable and nanostructured materials such as V6O11 are involved. Here, this study gives insight into the complications of SPS-assisted synthesis of complex oxide materials, provides new information about the thermal and electrical properties of vanadium oxides at high temperatures, and supports the concept of reducing the thermal conductivity of materials with structural building blocks such as crystallographic shear (CS) planes.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Effect of Building Block Connectivity and Ion Solvation on Electrochemical Stability and Ionic Conductivity in Novel Fluoroether Electrolytes

Novel electrolytes are required for the commercialization of batteries with high energy densities such as lithium metal batteries. Recently, fluoroether solvents have become promising electrolyte candidates because they yield appreciable ionic conductivities, high oxidative stability, and enable high Coulombic efficiencies for lithium metal cycling. However, reported fluoroether electrolytes have similar molecular structures, and the influence of ion solvation in modifying electrolyte properties has not been elucidated. In this work, we synthesize a group of fluoroether compounds with reversed building block connectivity where ether moieties are sandwiched by fluorinated end groups. These compounds can support ionic conductivities as high as 1.3 mS/cm (30 °C, 1 M salt concentration). Remarkably, we report that the oxidative stability of these electrolytes increases with decreasing fluorine content, a phenomenon not observed in other fluoroethers. Using Raman and other spectroscopic techniques, we show that lithium ion solvation is controlled by fluoroether molecular structure, and the oxidative stability correlates with the “free solvent” fraction. Finally, we show that these electrolytes can be cycled repeatedly with lithium metal and other battery chemistries. Understanding the impact of building block connectivity and ionic solvation structure on electrochemical phenomena will facilitate the development of novel electrolytes for next-generation batteries.

36 MATERIALS SCIENCE↗
DOE OSTI2014

Crystal structures and optical properties of new quaternary strontium europium aluminate luminescent nanoribbons

We report the synthesis and characterizations of three series of quaternary strontium europium aluminate (Sr-Eu-Al-O; SEAO) luminescent nanoribbons that show blue, green, and yellow luminescence from localized Eu2+ luminescent centers. These three series of SEAO nanoribbons are: blue luminescent, tetragonal Sr1-xEuxAl6O10 (0 1-x Eu x Al 2 O 4 (0 1-x Eu x Al 2 O 4 (0<x<1) (y-SEAO). Among these three series of SEAO nanoribbons, the b-SEAOs and y-SEAOs are new compounds that have not been reported before. The crystal structures of the SEAO nanoribbons were comprehensively studied using various synchrotron X-ray diffraction techniques and the effects of crystal structures on materials’ luminescence properties were investigated. These one-dimensional SEAO luminescent nanoribbons can function as both light generators and waveguides, and thus have promising potential as the building blocks in miniaturized photonic circuitry.

36 MATERIALS SCIENCE↗
DOE OSTI2017

One-step volumetric additive manufacturing of complex polymer structures

Two limitations of additive manufacturing methods that arise from layer-based fabrication are slow speed and geometric constraints (which include poor surface quality). Both limitations are overcome in the work reported here, introducing a new volumetric additive fabrication paradigm that produces photopolymer structures with complex non-periodic 3D geometries on a timescale of seconds. We implement this approach using holographic patterning of light fields, demonstrate the fabrication of a variety of structures, and study the properties of the light patterns and photosensitive resins required for this fabrication approach. The results indicate that lowabsorbing resins containing ~0.1% photoinitiator, illuminated at modest powers (~10-100 mW) may be successfully used to build full structures in ~1-10 s.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Chemically recyclable polyolefin-like multiblock polymers

Polyolefins are the most important and largest volume plastics produced. Unfortunately, the enormous use of plastics and lack of effective disposal or recycling options have created a plastic waste catastrophe. Here in this work, we report an approach to create chemically recyclable polyolefin-like materials with diverse mechanical properties through the construction of multiblock polymers from hard and soft oligomeric building blocks synthesized with ruthenium-mediated ring-opening metathesis polymerization of cyclooctenes. The multiblock polymers exhibit broad mechanical properties, spanning elastomers to plastomers to thermoplastics, while integrating a high melting transition temperature (T m ) and low glass transition temperature (T g ), making them suitable for use across diverse applications (T m as high as 128°C and T g as low as –60°C). After use, the different plastics can be combined and efficiently deconstructed back to the fundamental hard and soft building blocks for separation and repolymerization to realize a closed-loop recycling process.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Results and Responses for the 2022 User Forum Survey [Slides]

This presentation discusses the results of a MCNP user survey. Example of questions asked include: "Which MCNP particle types do you typically use?," "What sort of simulations do you run most often?," "Do you build the code?," "Which variance reduction methods do you use?," "Opinions on HDF5," with frequent discussions regarding each question.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗
DOE OSTI2025

MOOSE-based Tritium Migration Analysis Program, Version 8 (TMAP8) for advanced open-source tritium transport and fuel cycle modeling

Tritium management is critical for the safety, sustainability, and economics of fusion energy systems, and advanced and reliable modeling tools help accelerate the development of tritium technologies. This paper presents the Tritium Migration Analysis Program, Version 8 (TMAP8), an open-source, MOOSE-based application developed to provide state-of-the-art tritium transport and fuel cycle modeling capabilities. TMAP8 aims to expand the capabilities of previous versions (i.e., TMAP4 and TMAP7) by leveraging modern computational techniques, ensuring high software quality assurance standards (key to building trust), and enabling multispecies, multiscale, and multiphysics simulations for integrated tritium transport modeling in complex geometries. This paper outlines TMAP8’s scope and rigorous development practices, emphasizing its transparency, accessibility, modularity, and reliability. We present the current suite of verification and validation cases based on those from TMAP4, demonstrating TMAP8’s accuracy and reliability against analytical solutions and experimental data. Additionally, the paper showcases TMAP8’s integrated fuel cycle modeling capabilities, highlighting its applicability at various scales and levels. The TMAP8 code and documentation are openly available, promoting collaborative development and widespread adoption within the fusion community. Future work will soon expand TMAP8’s verification and validation suite to include those from TMAP7 and other recent experimental studies for validation.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2025

The scoping, design, and plasma physics optimization of the Eos neutron source stellarator

On the path to a fusion pilot plant, Thea Energy plans to build Eos, a sub-breakeven, deuterium-deuterium, beam-target fusion, stellarator neutron source facility for producing tritium and other valuable radioisotopes. In this paper, a set of 1D plasma physics models are coupled and used to design the operating point of the facility and predict performance. At this foundational stage of the design, analytic and approximate models are sufficient to capture the leading-order effects, and fast enough to run in the inner loop of an optimizer. Higher-fidelity analyses will follow. Models of 1D profile-dependent neutral beam stopping, ion beam slowing down, beam-target fusion, electron-ion classical heat transfer, energy confinement (ISS04), beam pressure, beam heating of ions and electrons, beam-beam fusion fraction, and neutral beam injection and gyrotron heating electrical efficiencies are included. A numerical optimizer is used to determine the minimum required facility electric power to generate tritium at a given rate. A potentially advantageous regime is described in which modern precisely-quasisymmetric stellarators, new high-temperature superconductors, ITER-derived neutral beam injection, and new high-frequency gyrotrons enable a suitible target plasma with hot electrons, cold ions, peaked density and temperature profiles, and high beam-injected ion density. It appears possible at this time for a facility with a medium-scale and medium-strength stellarator whose required facility electric power is less than 40 MW to produce $2.5\times 10^{17}$ neutrons s -1 for the production of radioisotopes. With the addition of a tritium breeding blanket, such a facility could produce 0.2 grams d -1 or 70 grams yr -1 of tritium.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2022

Efficient Loads Surrogates for Waked Turbines in an Array

Accurately and efficiently predicting wind turbine structural loading is a crucial step in wind farm design. Without considering structural loading, wind farm optimization could negatively impact turbine fatigue and ultimate loads, especially for waked and partially waked turbines, which could result in higher maintenance costs and reduced turbine lifetime. However, predicting turbine loads throughout an array is a costly step, as these quantities require time-accurate results across long time histories, which is often intractable for large array optimization. Therefore, surrogate models that link array spacing to load outputs are often used, but the surrogates are then unique to the inflow conditions and array configurations in the training library. This work develops surrogate models for many wind turbine load outputs based solely on rotor plane velocity measurements, with no required input about array configuration or freestream inflow parameters. Surrogate models were constructed for many turbine quantities of interest (QoI), considering mean, standard deviation, ultimate, and fatigue loads. In general, most QoI statistics were accurately captured, as measured by predicted vs. actual correlation coefficient, confirming the suitability of the approach. Temporal mean values of the QoI required only temporal mean measurements of the rotor plane inflow velocity. However, accurate prediction of temporal standard deviation, ultimate, and fatigue values of QoI also required temporal standard deviations of the rotor plane velocity field. Poor surrogate performance was observed when too many correlated inputs were used, such as multiple velocity components. If the fewest inflow parameters are used to construct the surrogates, the average correlation coefficient value for all output QoI statistics is 0.89. Surrogates for standard deviations and damage equivalent loads (DELs) of turbine QoIs generally had lower accuracy and tower-base and shaft load channels posed the most difficult to capture accurately. The results suggest that these surrogates could be easily paired with analytic wake models, which are frequently used for pre-construction wind farm array optimization, to account for turbine loading in addition to power production. By including the optimal inflow conditions, the surrogate accuracy can improve to an average correlation coefficient value for all output QoI statistics of 0.92. This work has established the ability to build accurate surrogates for mean, standard deviation, ultimate load, and DEL turbine QoI values based on the rotor plane inflow velocity, and identified which inflow conditions lead to greater surrogate accuracy.

17 WIND ENERGY↗
DOE OSTI2015

ORBiT: Oak Ridge biosurveillance toolkit for public health dynamics

Background: The digitization of health-related information through electronic health records (EHR) and electronic healthcare reimbursement claims and the continued growth of self-reported health information through social media provides both tremendous opportunities and challenges in developing effective biosurveillance tools. With novel emerging infectious diseases being reported across different parts of the world, there is a need to build systems that can track, monitor and report such events in a timely manner. Further, it is also important to identify susceptible geographic regions and populations where emerging diseases may have a significant impact. Methods: In this paper, we present an overview of Oak Ridge Biosurveillance Toolkit (ORBiT), which we have developed specifically to address data analytic challenges in the realm of public health surveillance. In particular, ORBiT provides an extensible environment to pull together diverse, large-scale datasets and analyze them to identify spatial and temporal patterns for various biosurveillance-related tasks. Results: We demonstrate the utility of ORBiT in automatically extracting a small number of spatial and temporal patterns during the 2009-2010 pandemic H1N1 flu season using claims data. These patterns provide quantitative insights into the dynamics of how the pandemic flu spread across different parts of the country. We discovered that the claims data exhibits multi-scale patterns from which we could identify a small number of states in the United States (US) that act as “bridge regions” contributing to one or more specific influenza spread patterns. Similar to previous studies, the patterns show that the south-eastern regions of the US were widely affected by the H1N1 flu pandemic. Several of these south-eastern states act as bridge regions, which connect the north-east and central US in terms of flu occurrences. Conclusions: These quantitative insights show how the claims data combined with novel analytical techniques can provide important information to decision makers when an epidemic spreads throughout the country. Taken together ORBiT provides a scalable and extensible platform for public health surveillance.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Framework for an adaptive integrated observation system using a hierarchy of machine learning approaches

Focal Area(s): 1. Data acquisition enabled by machine learning, AI, and advanced methods including experimental/network design/optimization, and hardware-related efforts involving AI. 2. Insight gleaned from complex measurements using AI, big data analytics, and other advanced methods, including explainable AI and physics- or knowledge-guided AI Science Challenge and Rationale: Atmospheric processes are stochastic, occur at scales from the micrometer to many kilometers, and are constantly changing over time. Characterizing these interactions and associated environmental conditions using traditional measurement techniques is difficult and can take years to build statistics on atmospheric phenomena that occurs episodically. Developing new innovative approaches to modify sampling strategies in real-time would enable the routine collection of targeted measurements focused on a specific set of science questions.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2017

Autonomous Energy Grids: Preprint

With much higher levels of distributed energy resources - variable generation, energy storage, and controllable loads just to mention a few - being deployed into power systems, the data deluge from pervasive metering of energy grids, and the shaping of multi-level ancillary-service markets, current frameworks to monitoring, controlling, and optimizing large-scale energy systems are becoming increasingly inadequate. This position paper outlines the concept of 'Autonomous Energy Grids' (AEGs) - systems that are supported by a scalable, reconfigurable, and self-organizing information and control infrastructure, can be extremely secure and resilient (self-healing), and self-optimize themselves in real-time for economic and reliable performance while systematically integrating energy in all forms. AEGs rely on scalable, self-configuring cellular building blocks that ensure that each 'cell' can self-optimize when isolated from a larger grid as well as partaking in the optimal operation of a larger grid when interconnected. To realize this vision, this paper describes the concepts and key research directions in the broad domains of optimization theory, control theory, big-data analytics, and complex system modeling that will be necessary to realize the AEG vision.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2017

Integrated Modeling and Monitoring Technologies for Environmental Resiliency in Nuclear Energy

Environmental concerns pose the biggest challenge for the development of the nuclear energy industry, often preventing or limiting the construction of new plants and radioactive waste disposal facilities. There are currently numerous sites in the world at which surface and groundwater are contaminated by nuclear weapon production and testing, as well as due to nuclear power plant accidents. Many of those sites remain unused or inhabited primarily due to public concern. Improving scientific and technical capabilities to develop environmental resiliency is critical not only to address existing contamination, but also to build public confidence and support for nuclear energy. One of the obstacles in remediation is to tackle a large volume of contaminated soil and groundwater with relatively low concentrations. Although many contaminant removal technologies have developed (e.g., pump-and-treat systems), they are often expensive and not cost-effective for low-concentration radionuclide contamination. Although soil removal is often the most effective, it produces a large amount of waste that has to be stored securely for a long period of time or treated at the special treatment facilities. Transporting a large amount of waste may also produce greenhouse gases and disrupt local communities. Recently, the concept of 'sustainable remediation' has been proposed to improve a remediation system as a whole, including the consideration of cost effectiveness, reduction of greenhouse emission, waste production and energy usage. Rather than just focusing on removing contaminants, the sustainable remediation highlights the use of passive remediation technologies to immobilize radionuclides along with the application of monitored natural attenuation and longer institutional control. However, such passive technologies and monitored natural attenuation require the increased burden of proof to ensure that those immobilized contaminants would not compromise the long-term public health. Although contaminant transport modeling and risk assessments are always performed, they sometimes fail due to the lack of understanding the contaminant transport proposes at the time of the risk assessment or due to some unexpected processes. Monitoring technologies are critical to ensure the long-term stability of such remediated sites, and also to address the public concerns. Recent advances in in situ sensor technologies and spatially-extensive mapping technologies (such as unmanned aerial vehicles, airborne mapping, geophysics) have improved monitoring of contamination over space and time. In addition to new sensing devices, data management and data analytics technologies have been expanded to manage and process large spatial and temporal datasets. Such technologies can be used to reduce monitoring cost significantly, and to facilitate long-term monitoring. In this study, we demonstrate our data analytics technologies for two nuclear-related contaminated sites: (1) air dose rate monitoring in Fukushima prefecture, and (2) groundwater monitoring at the Savannah River Site F-Area. We are developing the spatial and temporal data integration methodologies to integrate various spatially extensive data and time-series data for improving long-term monitoring. Such monitoring technologies and experiences at the existing contaminated sites can be transferred to build a better monitoring system for nuclear facilities, such as nuclear power plants or nuclear waste storages.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗