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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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A study on computational fluid dynamics modeling of a refrigerated container for COVID-19 vaccine distribution with experimental validation
A key issue with the distribution of vaccines to prevent COVID-19 is the temperature level required during transport, storage, and distribution. Typical refrigerated transport containers can provide a temperature-controlled environment down to -30 °C. However, the Pfizer vaccine must be carefully transported and stored under a lower temperature between -80 °C and -60 °C. One way to provide the required temperature is to pack the vaccine vials into small packages containing dry ice. Dry ice sublimates from a solid to a gas, which limits the allowable transport duration. This can be mitigated by transporting in a -30 °C refrigerated container. Moreover, because the dry ice will sublimate and thereby release CO 2 gas into the transport container, monitoring the CO 2 concentration within the refrigerated container is also essential. In the present work, a 3D computational fluid dynamics model was developed based on a commercially available refrigerated container and validated with experimental data. The airflow, temperature distribution, and CO 2 concentration within the container were obtained from the simulations. The modeling results can provide guidance on preparing experimental setups, thus saving time and lowering cost, and also provide insight into safety precautions needed to avoid hazardous conditions associated with the release of CO 2 during vaccine distribution.
High-Efficiency Recycled Silicon Solar Cell
The project, High-Efficiency Recycled Silicon Solar Cell, addresses the critical challenge of end-of-life (EoL) photovoltaic (PV) waste, which is expected to reach 78 million tons by 2050. Traditional recycling methods for recovering valuable materials like silver from silicon solar cells are inefficient, environmentally harmful, and economically unfeasible. Therefore, presently waste solar cells end up as landfills. This project aimed to develop a green, scalable, laser-based method for silver recovery, avoiding hazardous chemicals and minimizing operational costs. This research contributes to the circular economy in the renewable energy sector by enhancing material recovery from PV waste.
Investigating a Renewable-Resource-Targeting Mobile Aquaculture System Using Route Optimization Based on Optimal Foraging Theory
Aquaculture systems require careful consideration of location, which determines water conditions, pollution impacts, and hazardous conditions. Mobility may be able to address these factors while also supporting the targeting of renewable energy sources such as wind, wave, and solar power throughout the year. In this paper, a purpose-built mobile aquaculture ship is identified and modeled with a combination of renewable energy harvesting capabilities as a case study with the objective of assessing the potential benefits of targeting high renewable energy potentials to power aquaculture operations. A route optimization algorithm is created and tuned to simulate the mobility of the aquaculture platform and cost-basis comparisons are made to a stationary system. The small spatial variability in renewable energy potential when combining multiple resources significantly limits the benefits of a mobile, renewable-targeting aquaculture system. On the other hand, the consistent energy harvest from a blend of renewable energy types (13 kW installed wind capacity, 661 m 2 installed solar, and 1 m characteristic width wave-energy converter) suggests that the potential benefits of a mobile platform for offshore aquaculture (mitigation of environmental and social concerns, any potential positive impact on yields, hazard avoidance, etc.) can likely be pursued without significant increases in energy harvester costs.
CLEAP Project: OR-SAGE Analysis for MT, UT, and CO States
The OR-SAGE tool is designed to use industry-accepted practices in screening sites and then employ the proper array of data sources through the considerable computational capabilities of GIS technology available at ORNL. The tool was developed to screen the potential for NPP siting on a national and regional basis. However, because of the tool granularity, it is often focused specifically on the immediate area around user sites of interest. If data center siting parameters can be added to OR-SAGE, the ability to evaluate data center siting on a localized scale will be beneficial.1 More than 60 data sets have been collected and processed by ORNL to develop exclusionary, avoidance, and suitability criteria for screening sites for a variety of power generation types, including nuclear power plants. Available site evaluation parameters include population density, slope, seismic activity, proximity to cooling-water sources, proximity to hazard facilities, avoidance of protected lands and floodplains, susceptibility to landslide hazards, and many others. All siting parameters should be considered as flags to inform siting decisions and should not be used to rule in or rule out any NPP site. Once data center siting parameters are identified, appropriate data sets will be collected and processed. The OR-SAGE process is very versatile. Essentially, OR-SAGE is a visual, relational database. The database partitions the contiguous United States, a total of 720 million hectares (~1.8 billion acres), into 100-m by 100-m (1 hectare or ~2.5 acre) cells. The database is tracking just under 700 million individual land cells. Successive suitability criterion is applied to each cell in the database. User-specified thresholds can be applied to each siting parameter data layer. In this manner, a variety of scenarios can be quickly and thoroughly evaluated. Data can be added and/or revised within OR-SAGE to address user interests. Siting security assessment capability is currently being added to OR-SAGE. Security is expected to be of concern at data centers whether it is collocated with a nuclear power generating technology or not. If data center is collocated with a nuclear power generating source, the security threat attractiveness level of both will likely increase. It will be of additional benefit if a potential data center site is also assessed for security vulnerability.
Nanostructured gadolinium-doped ceria microsphere synthesis from ion exchange resin: Multi-scale in-situ studies of solid solution formation
In the current nano-sized material revolution, the main limitations to a large-scale deployment of nanomaterials involve health concerns related to nano-dissemination via air. Developing new chemical routes benefiting from nano-size advantages while avoiding their hazards could overcome these limitations. Addressing this need, a chemical route leading to soft nano-particle agglomerates, i.e., macroscopic precursors presenting the ability to be decomposed into nano-sized materials, was developed and applied to Ce{sub 0.8}Gd{sub 0.2}O{sub 2−δ}. Using cerium/gadolinium-loaded ion exchange resin, the Ce{sub 0.8}Gd{sub 0.2}O{sub 2−δ} solid solution formation as a function of temperature was studied in-situ through X-ray diffraction, X-ray absorption spectroscopy and Raman spectroscopy. Temperatures corresponding to the organic skeleton decomposition and to the mixed oxide crystallization were identified. An optimal heat treatment, leading to nanostructured soft agglomerates, was established. Microsphere processing capabilities were evaluated and particle size distribution measurements were recorded. A very low fracture strength was calculated, and a nanometric particle size distribution (170 nm) was determined. - Graphical abstract: The elaboration of micro-spherical precursors leading to the formation of nano-oxide soft agglomerates was studied and approved through the use of ion exchange resin loaded with cerium and gadolinium. The formation of the solid solution was followed through in-situ measurements such as XAS, XRD, Raman, TGA and DSC. Key temperatures were identified for the formation of the mixed-oxide. Following this study, the microstructure and particle size of oxide microspheres formed highlight the formation of soft nano-arrangments. - Highlights: • Soft microspherical agglomerates able to be decomposed into nano-sized materials. • In situ study of cerium/gadolinium-loaded ion exchange resin conversion in oxide. • In situ multi-scale study through Raman spectroscopy, XAS and HT-XRD. • Monodisperse nanometric particle synthesis suitable for ceramic processing.
Onboard early detection and mitigation of lithium plating in fast-charging batteries
Fast-charging is considered as one of the most desired features needed for lithium-ion batteries to accelerate the mainstream adoption of electric vehicles. However, current battery charging protocols mainly consist of conservative rate steps to avoid potential hazardous lithium plating and its associated parasitic reactions. A highly sensitive onboard detection method could enable battery fast-charging without reaching the lithium plating regime. Here, we demonstrate a novel differential pressure sensing method to precisely detect the lithium plating event. By measuring the real-time change of cell pressure per unit of charge (dP/dQ) and comparing it with the threshold defined by the maximum of dP/dQ during lithium-ion intercalation into the negative electrode, the onset of lithium plating before its extensive growth can be detected with high precision. In addition, we show that by integrating this differential pressure sensing into the battery management system (BMS), a dynamic self-regulated charging protocol can be realized to effectively extinguish the lithium plating triggered by low temperature (0 °C) while the conventional static charging protocol leads to catastrophic lithium plating at the same condition. We propose that differential pressure sensing could serve as an early nondestructive diagnosis method to guide the development of fast-charging battery technologies.
Helium as a Surrogate for Deuterium in LPI Studies
Helium or neopentane can be used as surrogate gas fill for deuterium (D2) or deuterium-tritium (DT) in laser-plasma interaction studies. Surrogates are convenient to avoid flammability hazards or the integration of cryogenics in an experiment. To test the degree of equivalency between deuterium and helium, experiments were conducted in the Pecos target chamber at Sandia National Laboratories. Observables such as laser propagation and signatures of laser-plasma instabilities (LPI) were recorded for multiple laser and target configurations. It was found that some observables can differ significantly despite the apparent similarity of the gases with respect to molecular charge and weight. While a qualitative behaviour of the interaction may very well be studied by finding a suitable compromise of laser absorption, electron density, and LPI cross sections, a quantitative investigation of expected values for deuterium fills at high laser intensities is not likely to succeed with surrogate gases.
Data Interfaces for Automated Vehicle Services - A Municipality Perspective
As Automated Vehicle (AV) services proliferate, data sharing between AV operators and municipal agents is assuming greater importance. Information on the dynamic nature of the road system such as incidents to avoid, weather hazards (such as flooding), construction and detours, as well as active safety concerns (e.g. - riots) is important for AV operators. Such information cannot be directly sensed from a vehicle's sensor array, but instead must be communicated in a timely and trustworthy channel. Municipalities are interested in pushing this information to AV operators to support emergency response efforts, reduce traffic in construction zones, and generally improve operation of the system. Similarly, information on vehicle safety such as disengagements, as well as critical information on the use of roadway system (trips, origin and destination patterns) are important performance factors for municipalities to understand utilization and plan for appropriate infrastructure. As mobility shifts to on-demand options, the need for safe and coordinated pick-up and drop-off zones will increase (potentially reducing parking needs). For all of these reasons, communication flows between AV operators and municipalities are becoming increasingly important. This paper investigates the functions, emerging practices and protocols for sharing of such critical data, and identifies gaps in and challenges in existing practices. Additionally, case studies are used to highlight the impacts of data sharing between AV operators and municipalities.
Toward a Fieldable Atomic Mass Spectrometer for Safeguards Applications: Sample Preparation and Ionization
The International Atomic Energy Agency’s (IAEA’s) long-term research and development plan calls for the development of new methods to detect misuse at nuclear fuel cycle facilities such as reprocessing and enrichment plants. At enrichment plants, for example, the IAEA’s contemporary safeguards approaches are based on a combination of routine and random inspections that include collection of UF6 samples from in-process material and selected cylinders for subsequent analyses. These analyses include destructive analysis (DA) in a laboratory (typically by mass spectrometry [MS]) for isotopic characterization, and environmental sampling (ES) for subsequent laboratory elemental and isotopic analysis (also both typically by MS). One area of new method development includes moving this kind of isotope ratio analytical capability for DA and ES activities into the field. Some of the reasons for these developments include timeliness of results, avoidance of hazardous material shipments, and guidance for additional sample collecting. However, this capability does not already exist for several reasons, such as that most lab-based chemical and instrumental methods rely on laboratory infrastructure (highly trained staff, power, space, hazardous material handling, etc.) and require significant amounts of consumables (power, compressed gases, etc.). In addition, there are no currently available, fieldable instruments for atomic or isotope ratio analysis. To address these issues, Pacific Northwest National Laboratory (PNNL) and collaborator, Clemson University, are studying key areas that limit the fieldability of isotope ratio mass spectrometry for atomic ions: sample preparation and ionization, and reducing the physical size of a fieldable mass spectrometer. PNNL is seeking simple and robust techniques that could be effectively used by inspectors who may have no expertise in analytical MS. In this report, we present and describe the preliminary findings for three candidate techniques: matrix-assisted laser desorption/ionization (MALDI) MS, liquid sampling-atmospheric pressure glow discharge (LS-APGD), and laser ablation/ionization (LAI) MS at atmospheric pressure. Potential performance metrics for these techniques will be presented, including detectability, response, isotope ratio accuracy and precision, and ease of use.
Synthesis of quantum dots
Common approaches to synthesizing alloyed quantum dots employ high-cost, air-sensitive phosphine complexes as the selenium precursor. Disclosed quantum dot synthesis embodiments avoid these hazardous and air-sensitive selenium precursors. Certain embodiments utilize a combination comprising a thiol and an amine that together reduce and complex the elemental selenium to form a highly reactive selenium precursor at room temperature. The same combination of thiol and amine acts as the reaction solvent, stabilizing ligand, and sulfur source in the synthesis of quantum dot cores. A non-injection approach may also be used. The optical properties of the quantum dots synthesized by this new approach can be finely tuned for a variety of applications by controlling size and/or composition of size and composition. Further, using the same approach, a shell can be grown around a quantum dot core that improves stability, luminescence efficiency, and may reduce toxicity.
Evaluation of Computed Tomography Techniques for Material Identification in Low Level and Intermediate Level Waste - 16648
Measures required to assure long term safe storage of Low-level and intermediate-level short-lived (LIL/SL) waste generated by the nuclear-power industry in France include the characterization of the waste and identification of materials within the waste. Digital Radiography (DR) techniques using x-ray at energies in the 6 MeV range have been shown to be effective for validation of the integrity of the concrete containers, and it was considered that the use of this technique together with the addition of Computed Tomography (CT) techniques could effectively identify materials within the waste. This paper describes the initial evaluation of two DR imaging techniques and two CT techniques using x-ray energy spectra up to 9 MeV to inspect a surrogate waste package, which comprised an outer concrete cylindrical container of 1400 mm diameter with 148 mm wall thickness, and an overall volume of 2 meters cubed, within which a 200 liter drum containing representative heterogeneous inactive waste, was placed in the center and the annulus between the 200 liter drum and the outer cylindrical package was filled with cement grout. The surrogate waste within the 200 liter drum comprised three separate layers of high density, medium density and low density mixed materials. The equipment used was a linear accelerator producing high energy spectra at either 6 MeV or 9 MeV and a high-precision CT manipulator with X, Y, Z and rotation motions, which were common to all techniques investigated. Two different digital detectors were used in the DR and CT performance evaluations, a Digital Detector Array (DDA) comprising a columnar Thallium-doped Cesium-Iodide scintillator screen in intimate contact with a 2 k by 2 k array of amorphous silicon detectors, 200 μm x 200 μm in area, and a Linear Diode Array (LDA) comprising a line of Cadmium-Tungstate columns, 1 cm thick and 400 μm x 400 μm in area. The work comprised evaluations of linear accelerator spectra and the attenuation effects of the waste container and contents, image acquisition performance of each detector, and CT techniques using area detector and linear detector. The results presented in this paper include mathematical evaluation of the two CT techniques, and analysis of measurement data, digital images, CT reconstruction images, and estimated material densities. The data was compared with recorded details and photographs of the actual configuration of materials within the surrogate waste. The Digital Detector Array can generate CT inspection volumes with considerable resolution and detail for the low-density and medium-density sections of the surrogate waste, however, the high-density sections were not imaged with sufficient detail and the images contained a large number of artifacts mainly due to the detectors lack of high energy photon stopping power. Materials identification with the Digital Detector Array, while possible for certain materials, for materials in the steel to plastic density range the attenuation values of the voxels in the reconstruction are too similar and difficult to resolve from the artifacts present. The Linear Diode Array can generate CT inspection volumes of regions of interest of the low-density and medium-density sections with considerable resolution and contrast, and potentially acceptable levels of resolution and contrast of the high-density section of the waste. While a few artifacts were present in the reconstructions, the majority are not due to the fundamental properties of the detector and are considered to be correctable. Materials identification with the LDA inspection data appear to be viable, with steel, copper, and higher-density metals being readily be distinguished from other materials on the basis of voxel value. Future work is needed to obtain a better definition of optimum spatial resolution and inspection speed, and to develop a system of 'calibration rods' which would consist of a series of 50 mm diameter cylinders of 7 materials; Plastic, Teflon, Concrete, Aluminum, Copper, Tungsten and Lead. The cylinders will be distributed at a certain radius in the surrogate waste and will be used as reference points in the evaluation and demonstration of the contrastive performance for the low, medium and high-density cases. The ability to identify the materials within a sealed waste container, by nondestructive examination, enables the verification of waste acceptance criteria without the need to open the waste containers. This eliminates the need for complex and expensive equipment to open and remotely handle the intermediate level waste, avoids potential hazards and risk of personnel dose uptake, and does not increase the volume of waste caused by repackaging of materials after examination and the decontamination or disposal of equipment used.
Remote methane sensor for emissions from pipelines and compressor stations using chirped-laser dispersion spectroscopy
Leak rates of methane (CH 4 ) from the natural gas supply chain result in lost profit from unsold product, public safety and property concerns due to potential explosion hazards, and a potentially large source of economic damages from legal liabilities. Yet large measurement challenges exist in identifying and quantifying CH 4 leak rates along the vast number and type of components in the natural gas supply chain. This is particularly true of the “midstream” components involved in the gathering, processing, compression, transmission, and storage of natural gas. This project developed and deployed new advances in chirped laser dispersion spectroscopy (CLaDS) to detect methane leaks from pipelines, compressor stations, and other midstream infrastructure from a remote position (standoff detection). The system was deployed from a van to measure fugitive methane leaks from a local compressor station as a proof-of-concept. The technique was validated through mobile laboratory measurements with in-situ sensors as well as controlled releases of methane. The system also mapped a plume from a controlled release of methane by tracking a small unmanned aerial system (sUAS) that carried a corner cube retroreflector which reflected the beam back to the instrument. The drone-based system quantified a leak rate to within 30% of the actual rate and localized the emission location within 5 m of the actual release location at standoff distances of 25-45 m. This sUAS-reflector tracking approach has benefits for mapping leak locations remotely using small drones flying around a facility. Benefits of a commercial sensor with these capabilities include reductions of leaks for pipeline operators (more profit), earlier detection of leaks to avoid catastrophic explosion hazards for public health and to mitigate property damage, and reduced methane emissions to the atmosphere (improving air quality).
Conductive two-dimensional titanium carbide ‘clay’ with high volumetric capacitance
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Reevaluating linear accelerator shielding for 320 µA of proton beam
The collider-accelerator facilities at Brookhaven National Laboratory (BNL) have been developing since the completion of the experiments they were originally built for, and their uses for research have evolved over the years with a variety of users. With these changes, we must be careful to avoid potential radiation hazards of worst-case scenarios, although these faults are unlikely. One of these changes in the Collider-Accelerator Department (C-AD) is the replacement of power supplies and upgrading the linear accelerator (Linac) radiofrequency system to allow the Brookhaven Linac Isotope Producer (BLIP) to use a 320 μA average current. This current of 320 μA is greater than any current that the Linac shielding has withstood before, and thus this project in reevaluating the Linac shielding is necessary to ensure all future Linac research is conducted safely. Particularly, this project aims to estimate the radiation doses in the Alternating Gradient Synchrotron (AGS) tunnel near the Linac tunnel and in the equipment bay room near the gate valve of the last tank (tank 9) of Linac. To do this, we used the particle transport code, Monte Carlo N-Particle 6.2 (MCNP6.2), to perform the simulation and model the facilities of Linac and AGS at BNL. This simulation allowed us to investigate the extent of radiation dose rates in various areas of the facilities by placing detectors in specific locations. We could therefore determine whether the dose rates due to these faults is acceptable for limits set by the Department of Energy (DOE) and BNL, and if the shielding is sufficient.
Method to control the etching rate of materials
A method for etching materials in which organic solvents are added to the etching mixture and combined in a mixing arrangement. When agitated organic materials mix with the etching agent and interact with the underlying material to form a shield around the etched areas that prevents the additional interaction of water with the newly etched areas and enables the etching of silicon oxides (SiOx) but does not oxidize Si. This method leads to milder reactions with less heat generation and avoids the safety hazards associated with conventional etching methods.
Sidewall Breach During Lithium-Ion Battery Thermal Runaway Triggered by Cell-to-Cell Propagation Visualized Using High-Speed X-Ray Imaging
With the rapid deployment of Li-ion batteries (LiBs) in a range of applications, it is crucial to ensure their safe operation. Therefore, it is necessary to investigate the rapid thermal runaway failure that LiBs can undergo if improperly operated or subjected to abuse scenarios so that hazardous events can be avoided or mitigated. Sidewall breaches or ruptures of LiBs during thermal runaway are considered the most hazardous failure scenario, resulting in hot abrasive flare from the casing of the cell that can impinge on neighbouring cells and lead to the propagation of thermal runaway throughout a battery pack. Yet, the process leading up to the sidewall breach is not well understood due to the extreme difficulty in visualizing such a failure in commercially relevant cells. With the application of a newly developed chamber for remote-controlled abuse testing of batteries coupled with simultaneous X-ray imaging, we demonstrate here for the first time an in-situ visualization of a sidewall breach. By further applying spatiotemporal mapping techniques, the internal thermal runaway events leading up to the sidewall breach can be analyzed in detail. Subsequently, the speed of the electrode layer delamination could be calculated to a speed of 0.6 m/s. These new insights bring more clarity regarding this phenomenon, that in turn can help battery designers improve battery safety.
SU-D-201-05: On the Automatic Recognition of Patient Safety Hazards in a Radiotherapy Setup Using a Novel 3D Camera System and a Deep Learning Framework
Purpose: Patient safety hazards such as a wrong patient/site getting treated can lead to catastrophic results. The purpose of this project is to automatically detect potential patient safety hazards during the radiotherapy setup and alert the therapist before the treatment is initiated. Methods: We employed a set of co-located and co-registered 3D cameras placed inside the treatment room. Each camera provided a point-cloud of fraxels (fragment pixels with 3D depth information). Each of the cameras were calibrated using a custom-built calibration target to provide 3D information with less than 2 mm error in the 500 mm neighborhood around the isocenter. To identify potential patient safety hazards, the treatment room components and the patient’s body needed to be identified and tracked in real-time. For feature recognition purposes, we used a graph-cut based feature recognition with principal component analysis (PCA) based feature-to-object correlation to segment the objects in real-time. Changes in the object’s position were tracked using the CamShift algorithm. The 3D object information was then stored for each classified object (e.g. gantry, couch). A deep learning framework was then used to analyze all the classified objects in both 2D and 3D and was then used to fine-tune a convolutional network for object recognition. The number of network layers were optimized to identify the tracked objects with >95% accuracy. Results: Our systematic analyses showed that, the system was effectively able to recognize wrong patient setups and wrong patient accessories. The combined usage of 2D camera information (color + depth) enabled a topology-preserving approach to verify patient safety hazards in an automatic manner and even in scenarios where the depth information is partially available. Conclusion: By utilizing the 3D cameras inside the treatment room and a deep learning based image classification, potential patient safety hazards can be effectively avoided.