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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 577 records · Page 32

In-situ observation of calcium chloride hexahydrate phase separation via neutron imaging

Inorganic salt hydrate offers a low-cost thermal energy storage solution with high energy density, but phase separation during thermal cycling poses a significant challenge, leading to irreversible performance degradation. In this research, neutron radiography was used to investigate phase separation in calcium chloride hexahydrate (CaCl₂·6H₂O, CCH) during thermal cycling to track its gradual accumulation into calcium chloride tetrahydrate (CaCl₂·4H₂O, CC4). Through in-situ visualization, phase separation and CC4 sedimentation were observed to occur during the cooling phase between 301.40 K and 304.80 K. CC4 accumulated linearly to 7.99 wt% after 10 thermal cycles. Crystallization and multi-cycle conversion models were developed to validate neutron imaging results of CC4 formation. The predicted CC4 content after 10 thermal cycles closely aligned with experimental observations. Neutron imaging offers a novel approach to investigate salt hydrate phase change materials (PCMs). It enables in-situ visualization of sub-hydrate (CC4) formation from original hydrate (CCH) in metastable phase change range (between 301.40 ± 0.66 K and 304.80 ± 0.60 K). Thereby, it provides a new insight of understanding the basis of phase separation mechanism and paves the way for future research of improving PCM thermal cycling performance.

Li, Yucen [The University of Tennessee, Knoxville]↗

Combining Deep Learning With Physics Based Features in Explosion-Earthquake Discrimination

This paper combines the power of deep-learning with the generalizability of physics-based features, to present an advanced method for seismic discrimination between earthquakes and explosions. The proposed method contains two branches: a deep learning branch operating directly on seismic waveforms or spectrograms, and a second branch operating on physics-based parametric features. These features are high-frequency P/S amplitude ratios and the difference between local magnitude (ML) and coda duration magnitude (MC). The combination achieves better generalization performance when applied to new regions than models that are developed solely with deep learning. Further, we also examined which parts of the waveform data dominate deep learning decisions (i.e., via Grad-CAM). Such visualization provides a window into the black-box nature of the machine-learning models and offers new insight into how the deep learning derived models use data to make decisions.

58 GEOSCIENCES↗

Laser confocal microscope for analysis of 3013 inner container closure weld region

As part of the protocol to investigate the corrosion in the inner container closure weld region (ICCWR) a laser confocal microscope (LCM) was used to perform close visual examination of the surface and measurements of corrosion features on the surface. However, initial analysis of selected destructively evaluated (DE) containers using the LCM revealed several challenges for acquiring, processing and interpreting the data. These challenges include topography of the ICCWR sample, surface features, and the amount of surface area for collecting data at high magnification conditions. In FY17, the LCM parameters were investigated to identify the appropriate parameter values for data acquisition and identification of regions of interest. Using these parameter values, selected DE containers were analyzed to determine the extent of the ICCWR to be examined.

36 MATERIALS SCIENCE↗

Reinforcement Learning-based Traffic Control to Optimize Energy Usage and Throughput (CRADA report)

The US roadways are critical to meeting the mobility and economic needs of the nation. The United States uses 28% of its energy in moving goods and people, with approximately 60% of that utilized by cars, light trucks, and motorcycles. Thus, improved transportation efficiency is vital to America’s economic progress. The increasing congestion and energy resource requirements of transportation systems for metropolitan areas require research in methods to improve and optimize control methods. Coordinating and optimizing traffic in urban areas may introduce hundreds of thousands of vehicles and traffic management systems, which can require high performance computing (HPC) resources to model and manage. In this work, we seek to use machine learning, computer vision, and HPC to improve the energy efficiency aspects of traffic control by leveraging GRIDSMART traffic cameras as sensors for adaptive traffic control, with a sensitivity to the fuel consumption characteristics of the traffic in the camera’s visual field. Traffic control use cases using reinforcement learning have been published and achieved good results. Surveys from DOE national laboratories estimate that the fuel cost of idling is 6 billion gallons wasted annually [Argonne National Laboratory, 2019]. GRIDSMART cameras—an existing, fielded commercial product—sense the presence of vehicles at intersections and replace more conventional sensors (such as inductive loops) to issue calls to traffic control. These cameras, which have horizon-to-horizon view, offer the potential for an improved view of the traffic environment which can be used to generate better control algorithms.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Web-Based Visual Analytics for Social Media

Social media provides a rich source of data that reflects current trends and public opinion on a multitude of topics. The data can be harvested from Twitter, Facebook, Blogs, and other social applications. The high rate of adoption of social media has created a domain that has an ever expanding volume of data that make it difficult to use the raw data for analysis. Information visual analytics is key in drawing out features of interest in social media. The Scalable Reasoning System is an application that couples a back end server performing analysis algorithms and an intuitive front end visualization to allow for investigation. We provide a componentized system that can be rapidly adapted to customer needs such that the information they are most interested in is brought to their attention through the application. To this end, we have developed a social media application for use by emergency operations for the city of Seattle to show current weather and traffic trends which is important for their tasks.

99 GENERAL AND MISCELLANEOUS↗

A Lifeline-Based Approach for Work Requesting and Parallel Particle Advection

Particle advection, a fundamental building block for many flow visualization algorithms, is very difficult to parallelize efficiently. That said, work requesting is a promising technique to improve parallel performance for particle advection. With this work, we introduce a new work requesting-based method which uses the Lifeline scheduling method. To evaluate the impact of this new algorithm, we ran 92 experiments, running at concurrencies as high as 8192 cores, data sets as large as 17 billion cells, and as many as 16 million particles, comparing against other work requesting scheduling methods. Overall, our results show that Lifeline has significantly less idle time than other approaches, since it reduces the number of failed attempts to request work.

Pugmire, Dave↗

Migration to a fully-integrated control room - 349

The nuclear industry is faced with a pressing need to reduce operating costs in order to remain competitive with other forms of electric generation. While current industry initiatives are focused on incremental gains by streamlining work processes and reducing worker burdens, very few, if any, involve significant reductions in the base workload of a nuclear plant. Migration to a fully-integrated control room affords just such an opportunity. This report describes an NPP digital instrumentation and control (I and C) system design, along with its corresponding human systems interface (HSI) design, which achieves high plant availability, while selectively applying digital equipment redundancy and integrating traditional I and C system partitions, to minimize the digital equipment needed, and thereby minimize initial installation costs and ongoing operations and maintenance (O and M) costs. An additional key component of digital equipment minimization is optimization of the digital interface to conventional plant sensors and controlled plant devices (e.g., pumps, valves), which requires no disturbance to plant cables and results in eliminating thousands of electro-mechanical relay control components. The design is rooted in the highly integrated digital technology applied to the most recent advanced light water reactors under United States (U.S.) Nuclear Regulatory Commission (NRC) design certification review and approval. While this design employs technology from new plants, that technology has been adapted to the modernization of current operating NPPs. Hence, the highly integrated digital I and C and HSI design is referred to as the compact control room digital modernization (CDM). Along with minimal digital equipment, the corresponding HSI design employs compact operator workstations with visual display units (VDU) and soft controls for both the main control room (MCR) and remote shutdown room (RSR), to immediately improve human performance and ultimately facilitate operating staff reduction. Some advanced light water reactors have demonstrated this staff reduction through full scope simulator testing of normal and abnormal plant conditions, with U.S. licensed operating crews from currently-operating U.S. plants. Digital equipment minimization, compact operator workstations, and optimized plant component interfaces that require no disturbance to field cables, also facilitate implementation of the CDM over multiple phases, most of which can be conducted during normal refueling shutdown windows. This phased implementation method includes a novel transition of the I and C, MCR and RSR with an operations centered focus. This paper presents the CDM design, along with qualitative cost/benefit comparisons to currently operating plants with conventional analog I and C and HSI technology; this generation of I and C/HSI is referred to as a conventional control room (CCR). A CCR also includes NPPs that have been upgraded with digital systems, but retain the current partitions between plant I and C systems (i.e., no I and C integration) and retain the current plant system to control board configuration of current NPP control rooms. Even though these comparisons are qualitative, a compelling case is presented for the CDM. (authors)

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Smartphone application for visualizing building air leakage

Annually, unwanted air leakage through building envelopes accounts for 4 quads of energy consumption in the United States, which translates to about 10% of total building energy consumption. Locating and sealing leakage sites is crucial fordecreasing building energy consumption. Smartphones are ubiquitous and contain sophisticated cameras and highperformance processors that could be employed to visualize air leakage using the background-oriented schlieren imaging technique, making leak detection cheaper and easier. This technique requires a textured and high-contrast background such as a brick or concrete masonry unit wall, a building air leak that has a temperature difference compared with the ambient air, and an imaging system. This work focuses on using smartphones as the imaging system to visualize air leakages. The paper discusses application development and the results of testing to determine leakage visualization performance as a function of leak temperature. The results show that leaks with a temperature difference greater than 16°C compared with the ambient air temperature were visualized using existing smartphones.

Boudreaux, Philip [ORNL] (ORCID:0000000229564665)↗

Multi-scale visual analysis of time-varying electrocorticography data via clustering of brain regions

There exists a need for effective and easy-to-use software tools supporting the analysis of complex Electrocorticography (ECoG) data. Understanding how epileptic seizures develop or identifying diagnostic indicators for neurological diseases require the in-depth analysis of neural activity data from ECoG. Such data is multi-scale and is of high spatio-temporal resolution. Comprehensive analysis of this data should be supported by interactive visual analysis methods that allow a scientist to understand functional patterns at varying levels of granularity and comprehend its time-varying behavior. We introduce a novel multi-scale visual analysis system, ECoG ClusterFlow, for the detailed exploration of ECoG data. Our system detects and visualizes dynamic high-level structures, such as communities, derived from the time-varying connectivity network. The system supports two major views: 1) an overview summarizing the evolution of clusters over time and 2) an electrode view using hierarchical glyph-based design to visualize the propagation of clusters in their spatial, anatomical context. We present case studies that were performed in collaboration with neuroscientists and neurosurgeons using simulated and recorded epileptic seizure data to demonstrate our system's effectiveness. ECoG ClusterFlow supports the comparison of spatio-temporal patterns for specific time intervals and allows a user to utilize various clustering algorithms. Neuroscientists can identify the site of seizure genesis and its spatial progression during various the stages of a seizure. Our system serves as a fast and powerful means for the generation of preliminary hypotheses that can be used as a basis for subsequent application of rigorous statistical methods, with the ultimate goal being the clinical treatment of epileptogenic zones.

60 APPLIED LIFE SCIENCES↗

General Mode Scanning Probe Microscopy

A critical part of SPM measurements is the information transfer from the probe-sample junction to the measurement system. Current information transfer methods heavily compress the information-rich data stream by averaging the data over a time interval, or via heterodyne detection approaches such as lock-in amplifiers and phase-locked loops. As a consequence, highly valuable information at the sub-microsecond time scales or information from frequencies outside the measurement band is lost. We have developed a fundamentally new approach called General Mode (G-mode), where we can capture the complete information stream from the detectors in the microscope. The availability of the complete information allows the microscope operator to analyze the data via information-theory analysis or comprehensive physical models. Furthermore, the complete data stream enables advanced data-driven filtering algorithms, multi-resolution imaging, ultrafast spectroscropic imaging, spatial mapping of multidimensional variability in material properties, etc. Though we applied this approach to scanning probe microscopy, the general philosophy of G-mode can be applied to many other modes of microscopy. G-mode data is captured by completely custom software written in LabVIEW and Matlab. The software generates the waveforms to electrically, thermally, or mechanically excite the SPM probe. It handles real-time communications with the microscope software for operations such as moving the SPM probe position and also controls other instrumentation hardware. The software also controls multiple variants of high-speed data acquisition cards to excite the SPM probe with the excitation waveform and simultaneously measure multiple channels of information from the microscope detectors at sampling rates of 1-100 MHz. The software also saves the raw data to the computer and allows the microscope operator to visualize processed or filtered data during the experiment. The software performs all these features while offering a user-friendly interface.

Somnath, Suhas↗

Non-destructive Post-Transient Examination Results of the MOXTOP-1 Experiment

The MOXTOP-1 experiment has been assembled and irradiated in INL’s HFEF and TREAT facilities followed by disassembly of the experiment to enable initial post-transient examination. Results of neutron radiography of the fuel pin still in the THOR capsule were somewhat inconclusive due to the additional scatter and attenuation from the iron heat sink included in the design. Nonetheless, no obvious failure or fuel relocation could be identified in the radiography. Following disassembly of the fuel pin from the capsule, initial visual inspections were performed, and documented via images obtained through the hot cell window. No obvious signs of fuel failure were identified, indicating that the fuel pin remained intact during the transient. Some discoloration was observed near the middle of the fuel pin, likely corresponding to the fueled zone indicating that that region may have reached a relatively high temperature. Pre-transient, and post-transient profilometry of the fuel pin were performed and compared. Some additional strain displacement in the bottom portion of the fuel zone is identified, but remains well below 1%.

Mixed Oxide↗

Improvement of field emission performance on nitrogen ion implanted ultrananocrystalline diamond films through visualization of structure modificaitons.

The relationship between the electron field emission properties and structure of ultra-nanocrystalline diamond (UNCD) films implanted by nitrogen ions or carbon ions was investigated. The electron field emission properties of nitrogen-implanted UNCD films and carbon-implanted UNCD films were pronouncedly improved with respect to those of as-grown UNCD films, that is, the turn-on field decreased from 23.2 V/{micro}m to 12.5 V/{micro}m and the electron field emission current density increased from 10E-5 mA/cm{sup 2} to 1 x 10E-2 mA/cm{sup 2}. The formation of a graphitic phase in the nitrogen-implanted UNCD films was demonstrated by Raman microscopy and cross-sectional high-resolution transmission electron microscopy. The possible mechanism is presumed to be that the nitrogen ion irradiation induces the structure modification (converting sp{sup 3}-bonded carbons into sp{sup 2}-bonded ones) in UNCD films.

74 ATOMIC AND MOLECULAR PHYSICS↗

Systematic network assessment of the carcinogenic activities of cadmium

Cadmium has been defined as type I carcinogen for humans, but the underlying mechanisms of its carcinogenic activity and its influence on protein-protein interactions in cells are not fully elucidated. The aim of the current study was to evaluate, systematically, the carcinogenic activity of cadmium with systems biology approaches. From a literature search of 209 studies that performed with cellular models, 208 proteins influenced by cadmium exposure were identified. All of these were assessed by Western blotting and were recognized as key nodes in network analyses. The protein-protein functional interaction networks were constructed with NetBox software and visualized with Cytoscape software. These cadmium-rewired genes were used to construct a scale-free, highly connected biological protein interaction network with 850 nodes and 8770 edges. Of the network, nine key modules were identified and 60 key signaling pathways, including the estrogen, RAS, PI3K-Akt, NF-κB, HIF-1α, Jak-STAT, and TGF-β signaling pathways, were significantly enriched. With breast cancer, colorectal and prostate cancer cellular models, we validated the key node genes in the network that had been previously reported or inferred form the network by Western blotting methods, including STAT3, JNK, p38, SMAD2/3, P65, AKT1, and HIF-1α. These results suggested the established network was robust and provided a systematic view of the carcinogenic activities of cadmium in human. - Highlights: • A cadmium-influenced network with 850 nodes and 8770 edges was established. • The cadmium-rewired gene network was scale-free and highly connected. • Nine modules were identified, and 60 key signaling pathways related to cadmium-induced carcinogenesis were found. • Key mediators in the network were validated in multiple cellular models.

60 APPLIED LIFE SCIENCES↗

Energetic particle transport and loss induced by helically-trapped energetic-ion-driven resistive interchange modes in the Large Helical Device

Here, energetic-ion confinement and loss due to energetic-ion driven magnetohydrodynamic modes are studied using comprehensive neutron diagnostics and orbit-following numerical simulations for the Large Helical Device (LHD). The neutron flux monitor is employed in order to obtain global confinement of energetic ions and two installed vertical neutron cameras (VNCs) viewing different poloidal cross-sections are utilized in order to measure the radial profile of energetic ions. A strong helically-trapped energetic-ion-driven resistive interchange mode (EIC) excited in relatively low-density plasma terminated high-temperature state in LHD. Changes in the neutron emission profile due to the EIC excitation are clearly visualized by the VNCs. The reduction in the neutron signal for the helical ripple valley increases with EIC amplitude, which reaches approximately 50%. In addition to the EIC experiment, orbit-following simulations using the DELTA5D code with EIC fluctuations were performed to assess the energetic-ion transport and loss. Two-dimensional temporal evolution results show that the neutron emissivity at the helical ripple decreases significantly due to the EIC. The rapid reduction in neutron emissivity shows that the helically-trapped beam ions immediately escape from the plasma. The reduction in the VNC signals for the helical ripple valley and the total neutron emission rate increase with increasing EIC amplitude, as observed in the experiment. Calculated line-integrated neutron emission results show that the profile measured by VNC1 has one peak, whereas the profile measured by VNC2 has two peaks, as observed in the experiment. Although the neutron emission profile for VNC2 has a relatively wide peak compared with the experimental results, the significant decrease in neutron signal corresponding to the helical ripple valley was successfully reproduced.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Open Source Platform for Live Processing of High Data Rate Electron Microscopy (SBIR Phase I Award Topic 15, Subtopic B, Final Scientific / Technical Report)

4D scanning transmission electron microscopy (STEM) is experiencing a revolution both in terms of data size, and data veracity, as are many other areas of experimental data acquisition. This presents enormous opportunities to make new scientific discoveries, but is also hamstrung by aging software that is no longer fit for purpose. Experimental data acquisition platforms must make the same investments in software infrastructure that the simulation community made decades ago to take advantage of high-performance computing (HPC) if they hope to realize the full potential of the latest advances made in detector technology. This requires rethinking the design and deployment of hardware, moving away from small, fixed commodity computing capabilities with closed interfaces to open, modular, scalable systems designed for parallelism and throughput. The technical approach will leverage best-in-class open source technologies, and develop new approaches strategically to build an open source platform for experimental data acquisition targeting high data rate electron microscopy. The project will develop a software platform that uses the power and performance of modern HPC resources to ingest the large volume of data produced by electron microscopes using direct electron detectors. A set of configurable pipelines will be used to enable the processing to be tailored to the problem being investigated with builtin visualization of data at interactive rates. This project will leverage investments made by the DOE and other agencies to provide a powerful software platform for the experimental data community working with most powerful electron microscopes, such as 4D STEM detectors. It will create a platform that serves as a reference for the community. Permissive open source licensing will make the platform available to all, with a simple deployment strategy offering the ability to keep data close to where it is generated. This advanced software platform will require customization for each deployment, creating opportunities for software services that are typically offered to extend open source software platforms.

97 MATHEMATICS AND COMPUTING↗

Validation of Pronghorn for Natural-Circulation Molten Salt Loops

This paper presents the development and validation of a high-fidelity thermal-hydraulic model of a molten salt natural circulation flow loop, designed for integration within a digital twin framework. The study evaluates the performance of Idaho National Laboratory’s Pronghorn against experimental data from Texas A&M University Molten Salt Flow Loop (MSFL) four Hitec-salt test benchmark data. Natural circulation of high-Prandtl-number fluids exhibits complex, counter-intuitive flow patterns that make pointwise thermocouple readings unreliable. Experimental work at TAMU’s MSFL provides benchmark data, including flow visualization at a test-section and centerline steady-state temperature measurements along the loop. Validation includes four single-phase natural circulation test cases with Hitec salt. Key metrics include flow profile agreement and steady-state temperature accuracy. Pronghorn results for two-dimensional single-phase agree qualitatively with the experimental flow profile. This paper illustrates the importance of Computational Fluid Dynamics (CFD) in elucidating the behavior of high-Prandtl-number thermal-hydraulics, along with how misleading centerline temperature measurements can be. Pronghorn reproduces the axial and radial stratification that makes single thermocouple readings unreliable. Future research will focus on reduced-order modeling techniques to enable rapid simulation suitable for real-time digital twin applications. The validated cases provide a basis for developing reduced-order surrogates aimed at real-time digital-twin applications.

22 - GENERAL STUDIES OF NUCLEAR REACTORS↗

Vacancy-Induced Formation and Growth of Inversion Domains in Transition-Metal Dichalcogenide Monolayer

Sixty degree grain boundaries in semiconducting transition-metal dichalcogenide (TMDC) monolayers have been shown to act as conductive channels that have profound influence on both the transport properties and exciton behavior of the monolayers. We show that annealing TMDC monolayers at high temperature induces the formation of large-scale inversion domains surrounded by such 60° grain boundaries. To study the formation mechanism of such inversion domains, we use the electron beam in a scanning transmission electron microscope to activate the dynamic process within pristine TMDC monolayers. Moreover, the electron beam acts to generate chalcogen vacancies in TMDC monolayers and provide energy for them to undergo structural evolution. We directly visualize the nucleation and growth of such inversion domains and their 60° grain boundaries atom-by-atom within a MoSe 2 monolayer and explore their formation mechanism. Combined with density functional theory, we conclude that the nucleation of the inversion domains and migration of their 60° grain boundaries are driven by the collective evolution of Se vacancies and subsequent displacement of Mo atoms, where such a dynamical process reduces the vacancy-induced lattice shrinkage and stabilizes the system. Our results can help to understand the performance of such materials under severe conditions (e.g., high temperature).

36 MATERIALS SCIENCE↗