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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 595 records · Page 33
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

DCTRGAN: improving the precision of generative models with reweighting

Significant advances in deep learning have led to more widely used and precise neural network-based generative models such as Generative Adversarial Networks (Gans). We introduce a post-hoc correction to deep generative models to further improve their fidelity, based on the Deep neural networks using the Classification for Tuning and Reweighting (Dctr) protocol. The correction takes the form of a reweighting function that can be applied to generated examples when making predictions from the simulation. We illustrate this approach using Gans trained on standard multimodal probability densities as well as calorimeter simulations from high energy physics. We show that the weighted Gan examples significantly improve the accuracy of the generated samples without a large loss in statistical power. This approach could be applied to any generative model and is a promising refinement method for high energy physics applications and beyond.

47 OTHER INSTRUMENTATION↗
DOE OSTI2020

Shaping attosecond pulses by controlling the minima in high-order harmonic generation through alignment of CO 2 molecules

In this paper, we report a simple method for generating shaped attosecond pulses by using a CO 2 molecule. Unlike most other molecules, owing to its unique energy and angle dependence and the presence of deep minima in the photoionization transition dipole moment, the shape of harmonic spectra, especially the position and depth of minima, can be readily controlled by tuning the degree of alignment. The sensitive alignment dependence of the minima is due to the coherent interference of a laser-induced dipole from each molecule when CO 2 molecules are moderately aligned, but not when they are well aligned or when they are isotropically distributed. Such a sensitivity offers a simple way of controlling the spectral amplitude and phase of the generated harmonics and thus shaping the generated attosecond pulses, for example, producing structured attosecond pulses by splitting a single burst into two. We illustrate how such pulses are generated and how to characterize them. This method offers a simple way to shape attosecond pulses at the generation step. It can be easily implemented experimentally to generate attosecond pulses with strong phase variations for unique applications.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2021

FL-DISCO: Federated Generative Adversarial Network for Graph-based Molecule Drug Discovery: Special Session Paper

The outbreak of the global COVID-19 pandemic emphasizes the importance of collaborative drug discovery for high effectiveness; however, due to the stringent data regulation, data privacy becomes an imminent issue needing to be addressed to enable collaborative drug discovery. In addition to the data privacy issue, the efficiency of drug discovery is another key objective since infectious diseases spread exponentially and effectively conducting drug discovery could save lives. Advanced Artificial Intelligence (AI) techniques are promising to solve these problems: (1) Federated Learning (FL) is born to keep data privacy while learning data from distributed clients; (2) graph neural network (GNN) can extract structural properties of molecules whose underlying architecture is the connected atoms; and (3) generative adversarial network (GAN) can generate novel molecules while retaining the properties learned from the training data. In this work, we make the first attempt to build a holistic collaborative and privacy-preserving FL framework, namely FL- DISCO, which integrates GAN and GNN to generate molecular graphs. Experimental results demonstrate the effectiveness of FL- DISCO on: (1) IID data for ESOL and QM9, where FL-DISCO can generate highly novel compounds with high drug-likeliness, uniqueness and LogP scores compared to the baseline; (2) non- IID data for ESOL and QM9, where FL-DISCO generates 100% novel compounds with high validity and LogP scores compared to the baseline. We also demonstrate how different fractions of clients, generator and discriminator architectures affect our evaluation scores.

Manu, Daniel↗
DOE OSTI2024

Structured Neural Network Modeling for Developing Digital Twins Models of Hydropower Generation Units

Dynamic modeling is a key part in the development of digital twin (DT) for dynamic systems. This is true for hydropower systems, where whole system modeling including penstock, turbine and generators, etc is important in realizing actuate modeling for the real systems. On the other hand, in response to the large variations of the power demand due to increased penetration of renewables such as wind and solar, hydropower systems are now required to operate in a large power generation range. This situation triggers the nonlinear characteristics of the generation unit with respect to its models. As such, it is imperative to use data driven modeling such as neural networks to learn the nonlinear dynamics of the hydropower generation unit. To achieve this objective, this study constructs a modeling and learning algorithm integrated with multiple structured neural network models for the modeling of turbine shaft speed, penstock pressure, and generator power output based on the generator power control setpoint, field current, and field voltage. In addition, the study uses the hydropower data from Tacoma Public Utilities to train and validate the proposed neural network algorithm. The results have shown that this structured neural network modeling approach can learn the system dynamics effectively by using the real-time data collected from the hydropower system with the desired modeling results.

Wang, Hong↗
DOE OSTI2023

Understanding SYCL Portability for Pseudorandom Number Generation: a Case Study with Gene-Expression Connectivity Mapping

Towards the goal of improving functional and performance portability of SYCL, we study a bioinformatics application that has been accelerated with CUDA and fast pseudorandom number generation on a GPU. We describe the experience of migrating pseudorandom number generation from CUDA to SYCL, evaluate the performance of pseudorandom number generators using the CUDA random number generation library, suggest the support of the XORWOW pseudorandom number generator in the oneAPI math kernel library (oneMKL) interface for performance portability, and identify the performance gap using the MKL interface in SYCL that supports pseudorandom number generation with third-party libraries. We hope that the results are valuable for the development of the SYCL ecosystem.

Jin, Zheming↗
DOE OSTI2017

Model-free Load Control for High Penetration of Solar Photovoltaic Generation

This paper presents a new model-free control (MFC) mechanism that enables the local distribution level circuit consumption of the photovoltaic (PV) generation by local building loads, in particular, distributed heating, ventilation and air conditioning (HVAC) units. The local consumption of PV generation will help minimize the impact of PV generation on the distribution grid, reduce the required battery storage capacity for PV penetration, and increase solar PV generation penetration levels. The proposed MFC approach with its corresponding intelligent controllers does not require any precise modeling for buildings, where their reliable modeling is a demanding task. Even when assuming the availability of a good model, the various building architectures would compromise the performance objectives of any model-based control strategy. The objective is to consume most of the PV generation locally while maintaining occupants comfort and physical constraints of HVAC units. That is, by enabling proper scheduling of responsive loads temporally and spatially to minimize the difference between demand and PV production, it would be possible to reduce voltage variations and two-way power flow. Computer simulations show promising results where a significant proportion of the PV generation can be consumed by building HVAC units with the help of intelligent control.

Bara, Ouassim↗
DOE OSTI2018

Photocarrier generation from interlayer charge-transfer transitions in WS 2 -graphene heterostructures

Efficient interfacial carrier generation in van der Waals heterostructures is critical for their electronic and optoelectronic applications. We demonstrate broadband photocarrier generation in WS 2 -graphene heterostructures by imaging interlayer coupling–dependent charge generation using ultrafast transient absorption microscopy. Interlayer charge-transfer (CT) transitions and hot carrier injection from graphene allow carrier generation by excitation as low as 0.8 eV below the WS 2 bandgap. The experimentally determined interlayer CT transition energies are consistent with those predicted from the first-principles band structure calculation. CT interactions also lead to additional carrier generation in the visible spectral range in the heterostructures compared to that in the single-layer WS 2 alone. The lifetime of the charge-separated states is measured to be ~1 ps. These results suggest that interlayer interactions make graphene–two-dimensional semiconductor heterostructures very attractive for photovoltaic and photodetector applications because of the combined benefits of high carrier mobility and enhanced broadband photocarrier generation.

36 MATERIALS SCIENCE↗
DOE OSTI2018

Dual-Frequency Generation in Quantum Cascade Lasers of the 8-μm Spectral Range

Results of an investigation of quantum cascade lasers of the 8-μm spectral range generating dual-frequency radiation at room temperature are presented. The dependences of radiation intensity for two lines of laser generation obtained as a result of investigation of the generation spectra revealed the presence of saturation and decay of the long-wavelength line of generation and linear growth of the intensity of the short-wavelength one. Based on analysis of the obtained data, a mechanism of the dual-frequency generation in the studied QCL samples is proposed Generation.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2019

CosmoGAN: creating high-fidelity weak lensing convergence maps using Generative Adversarial Networks

Abstract Inferring model parameters from experimental data is a grand challenge in many sciences, including cosmology. This often relies critically on high fidelity numerical simulations, which are prohibitively computationally expensive. The application of deep learning techniques to generative modeling is renewing interest in using high dimensional density estimators as computationally inexpensive emulators of fully-fledged simulations. These generative models have the potential to make a dramatic shift in the field of scientific simulations, but for that shift to happen we need to study the performance of such generators in the precision regime needed for science applications. To this end, in this work we apply Generative Adversarial Networks to the problem of generating weak lensing convergence maps. We show that our generator network produces maps that are described by, with high statistical confidence, the same summary statistics as the fully simulated maps.

Mustafa, Mustafa (ORCID:0000000291770283)↗
DOE OSTI2023

EPiC-GAN: Equivariant point cloud generation for particle jets

With the vast data-collecting capabilities of current and future high-energy collider experiments, there is an increasing demand for computationally efficient simulations. Generative machine learning models enable fast event generation, yet so far these approaches are largely constrained to fixed data structures and rigid detector geometries. In this paper, we introduce EPiC-GAN - equivariant point cloud generative adversarial network - which can produce point clouds of variable multiplicity. This flexible framework is based on deep sets and is well suited for simulating sprays of particles called jets. The generator and discriminator utilize multiple EPiC layers with an interpretable global latent vector. Crucially, the EPiC layers do not rely on pairwise information sharing between particles, which leads to a significant speed-up over graph- and transformer-based approaches with more complex relation diagrams. We demonstrate that EPiC-GAN scales well to large particle multiplicities and achieves high generation fidelity on benchmark jet generation tasks.

Buhmann, Erik↗
DOE OSTI2018

Coal-Powered Electric Generating Unit Efficiency and Reliability Dialogue: Summary Report

Coal continues to play a critical role in powering the Nation’s electricity generation, especially for baseload power plants. With aging coal generation assets facing decreased performance due to the state of the equipment, and with challenges exacerbated by the current market pressures on the coal sector, there are opportunities to advance early-stage technologies that can retrofit or replace equipment components. These changes will eventually result in significant improvements in plant performance once further developed and deployed by industry. Research and development in areas such as materials, fluid dynamics, fuel properties and preparation characteristics, and a new generation of plant controls can lead to new components and systems that can help improve the efficiency and reliability of coal-fired power plants significantly, allowing these assets to continue to provide baseload power. Coal stockpiles at electricity generation plants are typically large enough to provide 30 to 60 days of power prior to resupply—significantly enhancing the stability and reliability of the U.S. electricity sector. Falling prices for non-dispatchable renewable energy and mounting environmental regulations, among other factors, have stimulated efforts to improve the efficiency of these coal-fired electric generating units (EGUs). In addition, increased reliance on natural gas and non-dispatchable energy sources has spurred efforts to further increase the reliability of coal EGUs. The Coal Powered EGU Efficiency and Reliability Dialogue brought together stakeholders from across the coal EGU industry to discuss methods for improvement. Participants at the event reviewed performance-enhancing innovations in coal EGUs, discussed the potential for data-driven management practices to increase efficiency and reliability, investigated the impacts of regulatory compliance on coal EGU performance, and discussed upcoming challenges for the coal industry. This report documents the key findings and research suggestions discussed at the event. Discussions at the workshop will aid DOE in developing a set of distinct initiatives that can be pursued by government and industry to realize promising technological pursuits. DOE plans to use the results of the Dialogue coupled with ongoing technical analysis of efficiency opportunities within the coal-fired fleet, and additional studies to develop a comprehensive strategy for capitalizing on thermal efficiency improvements. Expected Power Plant Efficiency Improvements include developing cost-effective, efficient, and reliable technologies for boilers, turbines, and sensors and controls to improve the reliability and efficiency of existing coal-based power plants. The Office of Fossil Energy at DOE plans to work with industry to develop knowledge pertaining to advanced technologies and systems that industry can subsequently develop. These technologies and systems will increase reliability, add operational flexibility and improve efficiency, thereby providing more robust power generation infrastructure. The following table lists the research suggestions and questions for further investigation that were identified by participants in each session of the dialogue.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2018

Study of Multiple Exciton Generation with New Multi-dimensional Spectroscopies

Multiple exciton generation is a process that can occur in semiconductor nanocrystals small enough that their electronic properties deviate from that of the bulk semiconductor. Such small nanocrystals are known as quantum dots. At the time this project began, there were reports that multiple exciton generation in quantum dots was far more efficient than the analogous process of charge carrier multiplication in bulk semiconductors. In bulk semiconductors, this effect requires ultraviolet light, but is used for high energy photo-detectors. By exploiting enhanced photocurrent from photons with more than twice the bandgap energy, carrier multiplication is a potential route to more efficient photovoltaics using quantum dots with infrared bandgaps. The reports of enhanced multiple exciton generation in such materials motivated the fundamental investigations of the multiple exciton generation mechanism in this project. These experimental investigations showed that the initial charge carrier dynamics after exciting low bandgap quantum dots with photons far above bandgap are not those of the bound electron-hole pairs known as excitons, but rather those of the rapidly separating charge carriers found in the bulk semiconductor at similar excitation energies. This result was theoretically explained in terms of new fundamental criteria for size dependent changes in the optical properties of semiconductors. This result indicates that any new mechanism for multiple exciton generation must arise from the larger surface area to volume ratio of quantum dots. Several artifacts arising from repetitive excitation, poorly passivated quantum dot surfaces, and oxygen exposure were found. After eliminating these artifacts, investigations of the backward reaction have confirmed that its rate does increase as size decreases, in accord with theory, but were not able to isolate surface effects. Using two-dimensional electronic spectroscopy to investigate the influence of the surface upon excitation at the bandgap found no measurable effect. These studies indicate that better control of the quantum dot surface would be required to optimize multiple exciton generation for photovoltaics.

14 SOLAR ENERGY↗
DOE OSTI2019

Investigation of thermolytic hydrogen generation rate of tank farm simulated and actual waste

To support resolution of Potential Inadequacies in the Safety Analysis for the Savannah River Site (SRS) Tank Farm, Savannah River National Laboratory conducted research to determine the thermolytic hydrogen generation rate (HGR) with simulated and actual waste. Gas chromatography methods were developed and used with air-purged flow systems to quantify hydrogen generation from heated simulated and actual waste at rates applicable to the Tank Farm Documented Safety Analysis (DSA). Initial simulant tests with a simple salt solution plus sodium glycolate demonstrated the behavior of the test apparatus by replicating known HGR kinetics. Additional simulant tests with the simple salt solution excluding organics apart from contaminants provided measurement of the detection and quantification limits for the apparatus with respect to hydrogen generation. Testing included a measurement of HGR on actual SRS tank waste from Tank 38. A final series of measurements examined HGR for a simulant with the most common SRS Tank Farm organics at temperatures up to 140 °C. The following conclusions result from this testing. HGR was measured for an actual-waste Tank 38 sample. The HGR measurements at 80, 90, 100, and 110 °C were 1.7×10 -7 , 4.7×10 -7 , 5.9×10 -7 , and 2.6×10 -6 ft 3 hr -1 gal -1 , respectively. The Limit of Detection and Limit of Quantification for the HGR measurements were 2.6×10-8 ft3 hr-1 gal-1 and 5.1×10 -8 ft 3 hr -1 gal -1 , respectively. HGR was measured in a high boiling point (HBP) simulant with major known SRS Tank Farm organic compounds. Testing used fresh organics and did not simulate the long-term exposure of these organics already experienced in the waste. Hence, testing is expected to provide high bias to the hydrogen generation rates. The final HGR measurements at 75, 100, and 140 °C were 6.2×10 -7 , 3.0×10 -6 , and 8.1×10 -5 ft 3 hr -1 gal -1 , respectively. Decreases in the HGR were noted at isothermal conditions with steady gas tracer concentration, which clouds development of a temperature dependent correlation for generation rate. While the simulant contains high concentrations of major SRS organics tested at high temperatures found in the 3H Evaporator, this limited data set may not fully bound values under all possible operating conditions. The HGR measurement apparatus was successfully employed to replicate hydrogen production rate experiments. Simulant without deliberately added organic carbon was found to contain approximately 200 mg/L of organic carbon from tramp organics in the reagents used to prepare the solution. The tests using such simulant generated hydrogen at rates consistent with, but somewhat lower than, those predicted at equivalent carbon and aluminum loadings by methods used at the Hanford Site. Prior to identifying the organic contaminants, potential sources of hydrogen in simulants without deliberately added organic carbon were examined. Testing determined that this hydrogen is not due to caustic reaction of organic materials of construction within the reaction vessel, electrolysis due to current leak, anode/cathode reactions, corrosion, or the method of heating employed in the experiment. During the HBP and Tank 38 testing, a peak was identified at a retention time greater than the retention time of the inert tracer of krypton. This peak has been identified as methane, and the data have been reexamined to obtain methane concentrations. For the HBP testing, methane concentration was constant at the highest temperature studied (140 °C) and higher than hydrogen. At the lower temperatures (100 and 75 °C), methane and hydrogen tracked closely, with methane concentration generally lower than hydrogen. For Tank 38, methane concentration was approximately 1/3 of the hydrogen concentration during testing (100 and 110 °C). At lower temperatures for Tank 38 testing (90, 80, and 27 °C), methane fell below the quantification range.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2018

Demonstration of Fully Coupled Calculations in Helical Steam Generator: Toward Predictions of Fluid Elastic Instability

The NEAMS program aims to develop an integrated multi-physics simulation capability “pellet-to-plant” for the design and analysis of future generations of nuclear power plants. In particular, the Reactor Product Line code suite's multi-resolution hierarchy is being designed to ultimately span the full range of length and time scales present in relevant reactor design and safety analyses, as well as scale from desktop to petaflop computing platforms. Flow-induced vibration (FIV) is widespread problem in energy systems because they rely on fluid movement for energy conversion. Vibrating structures may be damaged as fatigue or wear occurs. Given the importance of reliable components in the nuclear industry, flow-induced vibration has long been a major concern in safety and operation of nuclear reactors. In particular, nuclear fuel rods and steam generators have been known to suffer from flow-induced vibration and related failures. Advanced reactors, such as integral Pressurized Water Reactors (PWRs) considered for Small Modular Reactors (SMR), often rely on innovative component designs to meet cost and safety targets. One component that is the subject of advanced designs is the steam generator, some designs of which forego the usual shell-and-tube architecture in order to fit within the primary vessel. In addition to being more cost- and space-efficient, such steam generators need to be more reliable, since failure of the primary vessel represents a potential loss of coolant and a safety concern. A significant amount of data exists on flow-induced vibration in shell-and-tube heat exchangers, and heuristic methods are available to predict their occurrence based on a set of given assumptions. In contrast, advanced designs have far less data available. Advanced modeling and simulation based on coupled structural and fluid simulations have the potential to predict flow-induced vibration in a variety of designs, reducing the need for expensive experimental programs, especially at the design stage. Over the past seven years, the Reactor Product Line has developed the integrated multi-physics code suite SHARP. The goal of developing such a tool is to perform multi-physics neutronics, thermal/fluid, and structural mechanics modeling of the components inside the full reactor core or portions of it with a user-specified fidelity. In particular SHARP contains high-fidelity single-physics codes Diablo for structural mechanics and Nek5000 for fluid mechanics calculations. Both codes are state-of-the-art, highly scalable tools that have been extensively validated. These tools form a strong basis on which to build a flow-induced vibration modeling capability. In the last two years a significant effort was devoted to 1) develop and validate a fully coupled capability in SHARP for Fluid-Structure calculations (FSI) and 2) validate the use of SHARP for one-way coupled calculations in helical steam generators on legacy data available as well as novel experiments. In this report we discuss an extension of previous one-way coupled calculations performed with Nek5000 and Diablo aimed at simulating available FIV experiments in helical steam generators in the turbulent buffeting regime. It was demonstrated that in the buffeting regime one-way coupling was judged sufficient because the pressure loads do not cause substantial displacements. However, higher speeds led to a reduction in accuracy and the need for a fully coupled capability for velocity or approaching the critical velocity and fluid elastic instability. In this report we demonstrate such fully coupled capability on the Argonne test case discussed in previous reports.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2018

Illinois Distributed Generation Rebate - Preliminary Stakeholder Input and Calculation Considerations

What is the value of distributed generation to the distribution system and how do we assign that value to a rebate? This white paper is an update to Illinois Distributed Generation Rebate Calculation Considerations (PNNL-27569) and provides a preliminary look at potential distributed generation valuation methodologies and compensation options for Illinois by taking into consideration data needs and availability, stakeholder comments, and Illinois Public Utilities Act language. Pacific Northwest National Laboratory (PNNL) is supporting the Illinois Commerce Commission (ICC) with initial stakeholder engagement to advance the conversation around distributed generation valuation in Illinois. PNNL’s educational support will help set the stage for a productive formal process as the ICC will be called upon, in relatively short order, to start formal distributed generation valuation proceedings in response to Illinois Public Act 99-0906, also known as the Future Energy Jobs Act (FEJA), and codified in Illinois Public Utilities Act Section 16-107.6. This white paper does not represent the ICC’s formal investigation of distributed generation rebate valuation and is not intended to characterize or prejudge any decisions on behalf of the ICC.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2023

Relative humidity threshold for oxygen generation by high-purity plutonium dioxides in 3013 containers

High-purity plutonium dioxide with adsorbed water in a sealed container can generate oxygen, but oxygen will not be generated in low water loading conditions. A threshold for oxygen generation has been observed in the hydrogen generation rate normalized by the specific power for high-purity plutonium dioxide. Normalized hydrogen generation rates above this threshold generate oxygen and below the threshold consume oxygen. The threshold rate is determined by the amount of water adsorbed onto the surface of the oxide. The relative humidity of the atmosphere that the oxide is in equilibrium with determines the amount of physisorbed water adsorbed on the surface. We calculate the relative humidity corresponding to the threshold rate as a function of mass and specific surface area of material stored in 3013 containers. Exceeding the calculated relative humidity may result in flammable gas mixtures of hydrogen and oxygen at some time during storage.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2024

Wholesale Electricity Markets and Resource Adequacy with High Clean Energy Generation Targets

Wholesale electricity markets are intended to incentivize system generation investments and operations outcomes that meet evolving system needs. In this work, we evaluate the effectiveness of wholesale market structures, rules and policies in achieving system resource adequacy (RA) and clean energy targets in the presence of self-interested generation investors using the Electricity Markets and Investment Suite Agent-based Simulation (EMIS-AS) model. Results highlight that both capacity markets and operating reserve demand curves (ORDCs) can help achieve a reliable system but with different RA compliance timelines and distribution of generation technologies. Structures with capacity markets tend to favor more capital-intensive peaking technologies while reducing wind and solar build-outs due to suppressed energy and clean energy market prices, particularly in the absence of strong clean energy targets. Conversely, ORDCs improve the commitment of available generation units, but this comes at the expense of higher system costs and renewable generation curtailment. We also find that well-calibrated static capacity demand curves can yield similar reliability and total cost compared to capacity market demand curves informed dynamically by resource adequacy while also yielding stable annual capacity prices. Different approaches to formulating ORDC curves can also yield key trade-offs, namely that a more efficient treatment of storage chronology results in lower ORDC curves and prices, yielding less investment and cost but at the expense of reliability. Finally, the effectiveness of wholesale electricity markets in practically achieving very high clean energy generation targets highly depends on the cost-competitiveness of clean energy technologies that can support critical balancing needs across multiple timescales.

capacity expansion↗
DOE OSTI2025

Testing a Hazmatpac Can with Locking Ring as a Secondary Shipping Container for Radium-224/Lead-212 Generators

A Hazmatpac can, paint can style shipping container with locking ring, was tested for use as an alternative shipping configuration for shipment of radium- 224 /lead- 212 generators. 224 Ra ( t 1/2 = 3.63 d) decays by alpha emission to radon-220 ( t 1/2 = 55.6 s). The potential for the radioactive radon gas to escape the generator column and the shipping container is of particular concern for the safe delivery of 224 Ra/ 212 Pb generators to customers. The purpose of this study was to evaluate whether the Hazmatpac can is a suitable shipping configuration, capable of containing the radon gas that may escape the generator column during transit. A 17.3 mCi 224 Ra/ 212 Pb generator was built and packaged into a Hazmatpac can. The can was smeared by a Radiological Control Technician (RCT) every day for seven days to analyze for radioactive contamination on the outside of the can. Over the course of the study, no radioactive contamination was found on the outside of the can. Therefore, the Hazmatpac can was approved as an alternative shipping configuration for shipment of 224 Ra/ 212 Pb generators.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗