Measurement of the proton dosage of the gemini astronauts with nuclear emulsions messungen der protonendosis der gemini-astronauten mit kernemulsionen.
Measurement of proton dosage of gemini astronauts with nuclear emulsions
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Measurement of proton dosage of gemini astronauts with nuclear emulsions
This report outlines a framework for selecting structural and cladding materials for the Nuclear Science User Facilities (NSUF) SAM-3 neutron irradiation campaign to support the advancement of nuclear energy technologies. The document begins with an introduction that provides background context, highlights the motivations for launching a new irradiation campaign, and defines the overall objectives. The core of the report describes the design considerations for the irradiation campaign, including capsule configurations, irradiation temperature ranges, and target dose levels (defined by displacements per atom, or dpa). The material recommendation was guided by the Specimen Identification and Prioritization (SIP) Working Group, a multidisciplinary team of experts representing national laboratories, academia, industry, federal government and agency. This group played a central role in identifying candidate materials, evaluating technical justifications, and ensuring alignment with boarder programmatic goals. A detailed set of criteria for material prioritization is then presented, taking into account reactor relevance, performance gaps, advanced manufacturing methods, and emerging material classes. Based on the input of SIP working group, specific materials were selected and justified for inclusion in the irradiation campaign by the NSUF leadership and its U.S. Department of Energy (DOE)-Office of Nuclear Energy (NE) management. The final section provides recommended capsule designs, summarizing critical parameters such as material type, fabrication method, sample geometry, irradiation conditions, and specimen quantities. This report serves as a foundation for executing a focused and high-impact neutron irradiation campaign aimed at addressing key materials challenges for both existing and advanced nuclear reactors.
The nuclear industry is increasingly considering cartridge-style experiments for irradiation testing of advanced reactor fuels and materials under flowing conditions. Cartridge loops do not require the extensive support infrastructure that are necessary for external flow loops and minimize the possibility of coolant solidification over the long distance from the reactor to the external facilities. However, there is a general lack of quality flow data for internally heated fluids in an annular configuration representative of a cartridge-type irradiation experiment, particularly one with natural circulation. To address this data need, a series of experiments was conducted to measure the natural circulation flow rates of pressurized water in a sealed, internally heated vessel with annular flow conditions that represent a molten salt or sodium cartridge loop. Temperatures and flow rates were measured under steady-state and transient conditions. Here, this paper describes the facility, methods, and results of the experiments, including the determination of nondimensional parameters. A simple 1D model of the natural convection flow rates agrees well with the experimental results. Applying this model to simulate a liquid salt cartridge experiment predicts that natural circulation flow might be able to provide liquid salt Reynolds numbers similar to those of some molten salt reactor concepts at relevant power densities.
We are currently exploring data analysis methods for their ability to strengthen the synthesis and evaluation of information generated within domestic and international safeguard regimes. Safeguard data typically includes rich heterogenous datasets amenable to advanced data analytics methods, such as machine learning. We have converted transactional data containing both numerical and categorical attributes from a domestic nuclear material control and accountability (NMC&A) system into a low-dimensional numerical structure via linear principal component analysis. This data representation allows for global structure discovery via cluster analysis, which can characterize the typical behavior of each of the primary types of transaction events. Furthermore, the structure of the top principal components captures the “typical behavior” of the data and is thus amenable to anomaly detection through statistical hypothesis testing. We explored this capability by generating erroneous permutations of the data and computing the Q-residual quantity increase associated with the information loss when these data are projected into the low-dimensional principal component analysis space representative of typical transactions.Future work will focus on identifying data transformations (e.g., graph networks) that more closely align with the inherent structure of these transactions to explain more salient information and disambiguate the underlying nuclear process—in this case, irradiation and reprocessing—from artifacts of NMC&A system transactional record keeping data.
Coupling between electronic and nuclear energy dissipation in ion-irradiated, single crystal 4H-SiC has been investigated using Si, Ti, and Ni ions over a range of energies at 300 K, and irradiation damage accumulation is characterized using Rutherford backscattering spectroscopy in channeling geometry. The damage production rate from nuclear energy loss (S n ) is observed to decrease with increasing electronic energy loss (S e ) of the incident ions. A dynamic threshold (S e,th ) in electronic energy loss is determined for each ion species, which defines two regions: i) S e > S e,th , where electronic energy dissipation fully suppresses damage production due to nuclear energy loss along incident ion paths, and ii) S e < S e,th , where simultaneous damage recovery due to Se competes with damage production processes. Here, the electronic energy loss threshold (S e,th ) increases sublinearly with incident ion atomic number. Here, the assessment of S e,th and how it affects damage accumulation is important to advance the understanding of complex processes occurring under ion-solid interactions, as well as in the design of functional materials for opto-electronics and novel structural materials and devices tolerant to harsh thermal and radiation environments.
Metallic fuels, particularly U-10Zr and its performance in reactor irradiation conditions, have been thoroughly investigated and are a promising candidate for next-generation sodium-cooled fast spectrum nuclear reactors. Irradiation in reactors can lead to the formation of fission gas and increased pore formation which can significantly impact fuel performance. Due to the large number of pores and various phases formed in metallic fuel during irradiation, a quantitative description of fission gas pores as a function of irradiation conditions is not yet available, undermining the fidelity of fuel performance modeling to support fuel qualification. It has been difficult to clearly detect pore boundaries and distinguish matrix phases from fission gas pores using optical microscopy by using simple threshold methods working with low magnification images. The pre-trained deep learning model for fission gas pore detection was applied to ~10,260 high magnification scanning electron microscopy images. The model increased the accuracy of fission gas pore segmentation to obtain statistical features, which cannot be processed manually. A pre-trained decision tree model was used to classify pores as isolated or connected pores, providing new insight into the correlation between the movement of lanthanides, solid fission products, and the radial temperature gradient developed in fuel irradiation conditions. This paper emphasizes the potential that artificial intelligence-based machine learning models have to accelerate qualification and support nuclear fuel development.
Nuclear reactor environments are extreme in nature due to the combination of exposure to corrosive coolant, mechanical stresses, and neutron irradiation damage. This combination of environments can lead to irradiation induced/assisted precipitation, segregation, and embrittlement coupled with enhanced creep and stress corrosion cracking. While nanostructured materials are of interest in a variety of applications due to their unique properties including high mechanical strength, for nuclear applications nanostructured materials have the added benefit of irradiation resistance due to the high volume density of sinks for irradiation-induced defects. In this study, we show unique radiation-induced segregation (RIS) behavior in nanocrystalline 304 stainless steel (SS304). Typical RIS in austenitic steels includes Ni enrichment and Cr depletion within the grain boundaries. In nanostructured SS304 this RIS is reduced. Furthermore, interestingly, some grain boundaries in the nanocrystalline SS304 in this study were found to be enriched in Cr after Fe 2+ ion irradiation at 500 °C up to 50 displacements per atom (dpa). To understand this unique observation, lattice-based atomic kinetic Monte Carlo simulations were performed to investigate the effects of grain size, thermal segregation, as well as injected interstitials (introduced as Fe self-ions). The results indicate that the Cr enrichment at grain boundaries may be caused by combined effects of grain size, self-ion injection and preferential Cr diffusion via the interstitial mechanism. In conclusion, the findings also suggest a possible difference in RIS between ion and neutron irradiations.
To support the development of advanced low-enriched uranium for use in nuclear reactors, irradiation testing of U-Mo disk specimens was performed at the Oak Ridge National Laboratory (ORNL) High Flux Isotope Reactor (HFIR) to collect experimental irradiation data on this type of fuel at pressurized water reactor–relevant temperatures. U-Mo is a uranium alloy that has superior dimensional stability relative to alpha-phase uranium metal and has a substantially higher uranium density compared to UO 2 . U-Mo disks specimens were fabricated at Idaho National Laboratory and inserted into MiniFuel targets for HFIR irradiation. Three MiniFuel targets were successfully assembled, welded, tested, and delivered to HFIR, along with their quality assurance documentation. The targets were inserted into HFIR’s inner vertical experiment facility within the permanent beryllium reflector. Each target contains six disk specimens and will be irradiated in HFIR for three, four, and eight cycles, with target temperatures between 250 and 500°C. This report summarizes the experiment design, test matrix, pre-characterization of specimens, and experiment assembly.
Metallic fuel undergoes dramatic microstructural changes early in life due to fission gas swelling until ~2–3 at% burnup which affects the conductivity of the material, however the evolution of metallic fuel thermal conductivity during this early phase burnup has never been successfully measured in situ. The Irradiated Material Properties Accelerated Characterization Test (IMPACT) experiment will be the first in a series of experiments to irradiate advanced nuclear metallic fuel specimens with novel embedded thermal conductivity probes in ATR. In the current work the IMPACT experiment final design and supporting analysis is reported in detail. Results are evaluated for various reactor operational conditions to meet the functional requirements of the experiment. Finally, the first iteration of this IMPACT experiment will provide data regarding thermal properties evolution in uranium-zirconium (U10Zr) fuel, but this experiment vehicle is envisioned for future advanced fuels and structural materials irradiations in ATR.
Nuclear propulsion is an effective method of providing thrust in deep space, allowing for shorter mission duration for long-term surface missions to Mars. The fuel for nuclear propulsion systems must exhibit superior mechanical and thermal properties, to decrease the possibility of fuel failure and to increase reactor efficiency. Here, the objective of the Sirius project is to fabricate and irradiate cermet fuels at the Idaho National Laboratory Transient Reactor Facility to determine the properties of the fuel after irradiation at prototypical nuclear propulsion start-up conditions. The Sirius project featured 3 test capsules, Sirius-1 featured uranium nitride fuel dispersed in a matrix of tungsten and rhenium, while Sirius-2A and -2B featured uranium nitride-molybdenum-tungsten fuel (UN-Mo-W). The fuel samples from the Sirius-2A and -2B capsules were examined after irradiation using optical microscopy, scanning electron microscopy, and X-ray diffraction analyses. The mechanical properties of the fuel from Sirius-2A and -2B are discussed in a previous work. In this study, the results of the optical microscopy, scanning electron microscopy, and X-ray diffraction analyses are discussed.
Nondestructively determining the initial enrichment of irradiated uranium is a complex and laborious multivariable problem due to the presence of fission products. This work demonstrates the capabilities of machine learning to analyze gamma-ray spectral data to determine initial enrichment without knowledge of the decay time of the sample. The approach developed is agnostic to the particular scenario and is applicable to a wide variety of applications in nuclear forensics and nuclear safeguards. We irradiated 5 mg uranium standard reference materials at discrete enrichment values ranging from 0.02% to 97% 235 U (weight percent) in UT Austin’s Nuclear Engineering Teaching Laboratory TRIGA Mark II 1.1 MW research reactor, allowed each to decay for 8 hours, and then measured each sample via gamma-ray spectrometry for 50 hours post-irradiation yielding 1,400 individual gamma-ray spectra discretized into 8,192 energy bins. We then trained decision trees models to analyze individual gamma-ray spectra and estimate the associated initial enrichment without knowledge of the time since end of irradiation. We evaluated the performance of the models with a reserved test set not used for training or calibrating the model. A decision tree model constructed with this procedure achieved a mean absolute error in initial enrichment determination of 2.3% (weight percent 235 U). Next, we implemented a principal component analysis pre-processing routine of the gamma-ray spectrometry data to reduce the dimensionality of the dataset from 8,192 channels in the spectrum to 10 principal components while retaining over 99% of the inherent variance in the data. Decision tree models constructed with these data demonstrated decreased mean absolute error in enrichment determination, reduced computational time, and decreased complexity. A single decision tree model constructed with this procedure achieved a mean absolute error in initial enrichment determination of 0.05% (weight percent 235 U). Furthermore, we analyzed these models with learning curves to ensure that overfitting did not occur. The capabilities provided by these models can be naturally extended to other application-focused measurements in the fields of nuclear safeguards, nuclear forensics, and nuclear non-proliferation.
This report contains the Engineering Calculations and Analysis Report (ECAR)-5510 documenting the thermal as-run analysis of the 1 and 3 DPA capsules that comprised the BSU-8242 Nuclear Science User Facilities Experiment.
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The Nuclear Science User Facilities (NSUF) is the United States Department of Energy Office of Nuclear Energy's only designated nuclear energy user facility. Its mission is to provide nuclear energy researchers access to world-class capabilities and to facilitate the advancement of nuclear science and technology. This mission is supported by providing access to state-of-the-art experimental irradiation testing, post-irradiation examination facilities, and high-performance computing capabilities as well as technical and scientific assistance for the design and execution of projects. Two NSUF irradiation experiments, Boise State University-8242 and General Electric Hitachi, used melt wire packs to determine peak temperatures reached during irradiation testing. This report will discuss the temperature evaluation process and present the associated data.
Irradiation-induced property change in nuclear graphite is particularly important when considering the in-service lifetimes of graphite components. In other works, it has been shown that annealing of irradiated graphite above the irradiation temperature may heal atomic-level defects and thus reverse some amount of physical property change. In this work, virgin nuclear graphite IG-110 was annealed at 2500°C to observe any microstructural changes due solely to high-temperature thermal annealing. We report the results shown in this study suggest that fullerene-like defects will arise due to thermal annealing near graphitization temperature. Consequently, such defects may directly contribute to non-recoverable physical property change which has previously been observed in irradiated nuclear graphites.
The Graphite Technology Development Program ran a series of six experiments to quantify the effects of irradiation on nuclear grade graphite. This report focuses on the fourth experiment, Advanced Graphite Creep 4 (AGC 4). The Advanced Reactor Development (ARD) Technology Development Office (TDO) Program for research and development activities require documentation of qualified monitoring data to design and license the first high-temperature reactor nuclear plant. Qualified data meets the requirements for use as described in the experiment planning and quality assurance documents. Failed data do not meet the requirements and provide no useable information. Trend data may not meet all requirements but still provide some useable information. Use of Trend data requires assessment of how any deficiencies affect a particular use of the data. AGC-4 began with Advanced Test Reactor (ATR) Cycle 157D on May 30, 2015. After irradiating the graphite for two cycles, the capsule was removed from the reactor after ATR Cycle 158A, which ended on January 2, 2016, due to interference with another experiment. Irradiation was resumed with Cycle 162A on October 7, 2017 after the interfering experiment was removed from the reactor. AGC-4 irradiation completed by the end of Cycle 166B on January 10, 2020. Between Cycles 162A and 166B, AGC-4 capsule was removed from the reactor core during two Powered Axial Locator Mechanism (PALM) Cycles 163A and 165A to avoid overheating. All thermocouples (TCs) have functioned throughout the AGC-4 experiment. A total of 9,256,184 out of all 11,167,213 temperature records (or 82.9%) are Qualified for use by the ARD Program and 1,911,029 missing values are Failed. Argon, helium, and total gas flow data were within expected ranges, except only eight out-of-range values occurred during outages. A total of 21,240,627 out of all 22,288,5103 gas flow rates (or 92.8%) are Qualified for use by the ARD Program and 1,644,476 are Failed records mostly due to missing values. Discharge gas line moisture values were consistently low during full ATR power, except for 162B, when moisture content was increasing to more than 200 ppmv by the end of this cycle. During outages, moisture content reached as high as 700 ppmv. 1,089,941 out of a total of 1,107,331 moisture values (or 98.4%) are within the measurement range of the instrument and are Qualified for use by the ARD Program and 17,390 missing moisture values are Failed. Graphite creep specimens were subjected to one of three loads: 393, 491, or 589 lbf. For a brief period during Cycle 157D between 12:19 on June 2, 2015, and 08:23 on June 11, 2015, the load cells were wired incorrectly, resulting in missing stack load data. Missing stack loads were estimated from measured ram pressures using regression equations developed from the existing data from Cycle 157D. Estimated stack loads during this period are considered to be an accurate representation of actual load applied to the stacks. These loads deviate slightly from the planned loads. This deviation does not prevent the data from being Qualified for use but must be taken into account when analyzing the effect of load on creep. 6,095,728 out of a total of 6,403,985 moisture values (or 95.2%) are within the measurement range of the instrument and are Qualified for use by the ARD Program and 308,257 missing load values are Failed. Stack displacement increased consistently throughout the eight cycles, with total displacement reached highest value of 2.4 in by the end of irradiation. During ATR outages, a set of pneumatic rams raised the stacks of graphite creep specimens to ensure the specimens were not stuck within the test train. This stack raising was performed seven times throughout irradiation. All stacks were raised successfully each time. 4,744,974 out of a total of 6,094,513 displacement values (or 77.9%) are within the measurement range of the instrument and are Qualified for use by the ARD Program and 1,349,539 displacement values are Failed mostly due to missing values. Analyses were conducted on correlations between TCs to look for trends and step changes that might indicate instrument degradation or failure. Correlation analysis was used to identify instances when TCs form short circuits, referred to as virtual junctions, which result in TCs reporting temperatures from some location in the capsule other than the location where they were intended to read. No evidence of virtual junctions was found. Analyses were also conducted on control charts of temperature differences of between two TCs, which are expected to behave consistently throughout the entire irradiation period. Upward or downward trend over time indicates at least one TC in the pair was drifted. Examining control charts for all 66 possible pairs out of twelve TCs installed in the AGC-4 capsules reveal no clear drift failures occurred, except unstable behavior of two TCs in Zone 3, TC-7 and TC-8, over irradiation time. In conclus
Transmission electron microscopic (TEM) in situ mechanical testing has become a widely utilized tool for simultaneously measuring mechanical properties and understanding fundamental deformation mechanisms in irradiated and nuclear materials. Although tensile and compression specimen geometries are amongst the most common, opportunities remain for investigating alternative geometries that could provide unique insights into the plasticity of irradiated materials. This research demonstrates a new TEM in situ cantilever beam configuration. Cantilevers are produced from as-received and proton irradiated (1 dpa, 500°C) Fe-9%Cr oxide dispersion strengthened (ODS) steel. Flow stress is measured using a TEM in situ depth-sensing mechanical testing holder. A 200 MPa increase in flow stress is measured due to irradiation. Size effects arise when the intrinsic (i.e. microstructural) size approaches the extrinsic (i.e. external dimensions) size and can be described using a power law relationship as a function of the material microstructure and cantilever dimensions.
The lifetime, thermodynamic efficiency, safety and economic viability of new generation fission and fusion reactor concepts can largely be tied to the mechanical performance and stability of structural alloys under extreme environments. In this context, engineered nano materials could have broad-reaching impact on the future of advanced nuclear fuel-cycle and reactors. These systems are characterized by a large number density of interfaces which are efficient sinks for point defects and moderately biased; therefore limiting the deleterious effects of irradiation. Broadly, nuclear nano-technology deals with the use of the latest engineered-nanomaterials for improving the nuclear power performances and safety in all areas of nuclear energy production to bring new generations of nuclear power units. New advanced fuel assembly designs also have implications for securities and safeguards. To support the readiness for potential future license applications, an understanding of the technologies that would enable new reactor designs in the areas of component performance and domestic safeguards is necessary. This technical report letter work explores the technical issues and potential regulatory considerations associated with developing and adopting fuel claddings made of advanced nano- materials. Specifically three classes of nanomaterials are considered: (i) reduced activation ferritic/martensitic (RAFM) steels, (ii)oxide dispersed steels (ODS) and (iii) multi-metallic layered composites (MMLC).