Bayesian Modeling of Self-Exciting Marked Point Processes with Missing Histories
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This work explores the potential of utilizing temporal data from gamma-ray detectors, known as list-mode data, to enhance radioisotope identification. Traditional identification methods, which rely on full gamma-ray spectrum analysis, often require long dwell times and struggle with spectra containing similarly spaced spectral peaks. We hypothesize that by leveraging the probabilistic nature of nuclear decay and the time-encoded information from decay sequences and interactions with surrounding materials, we can improve classification accuracy over static spectral analysis. This research examines the temporal content of list-mode data through exploratory data analysis via correlation discovery and qualitative distribution analysis. Additionally, we propose a probabilistic classification model that can utilize spectral data, temporal data, or both to determine if the incorporation of temporal information improves radioisotope identification. Our findings suggest that the temporal information present in list-mode gamma-ray data has merit and should be further investigated to develop more robust and optimal methods for utilizing this temporal information in applications requiring radioisotope identification.
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N,N,N′,N′-tetraoctyldiglycolamide (TODGA) as a resin (“DGA resin”) produced by Eichrom Technologies will be used by Savannah River National Laboratory for the indiscriminate extraction of trivalent actinides and rare earth elements with the intent of recovering Cm and Am from dissolved irradiated 242 Pu Mark-18A targets in 7 to 9 M nitric acid. The extracted constituents will be recovered as an oxide by direct thermal decomposition of the loaded resin followed by calcination of the resultant residue. The characteristics of DGA resin with non-radiological feed simulant representative of the anticipated feed in the Mark-18A process, with Sm and Nd as surrogates for Cm and Am, respectively, including breakthrough point and saturation capacity were evaluated in this work. Additionally, this work examined the losses from the loaded resin by rinsing the resin bed with dilute acid to reduce the nitrate concentration in the resin bed prior to thermal decomposition operations to improve the safety posture of the process. A resin loading profile was developed, and the resin was determined to have a trivalent metal saturation capacity of 74 μmol/mL resin under the experimental conditions evaluated. Following a wash of the loaded resin bed with fresh 8 M HNO 3 , the trivalent metals retained was reduced to 68 μmol/mL resin, which represents the practical capacity of the resin for the Mark-18A process. Lighter lanthanides breakthrough the resin well before the saturation capacity is reached. Rinsing the saturated resin bed with 0.26 M HNO 3 was found to result in a rapid reduction in retention of rare earth elements by the resin. After 2.8 bed volumes of dilute acid rinse, the mean resin bed free acid concentration was reduced to 0.28 M and 3.1 bed volumes of dilute acid rinse resulted in a reduction of the cumulative rare earth element retention to 52 μmol/mL of resin.
This study presents the impact of future measurements of deeply virtual Compton scattering (DVCS) with the ePIC detector at the electron-ion collider (EIC), currently under construction at Brookhaven National Laboratory. The considered process is sensitive to generalized parton distributions (GPDs), the understanding of which is a cornerstone of the EIC physics program. Our study marks a milestone in the preparation of DVCS measurements at EIC and provides a reference point for future analyses. In addition to presenting distributions of basic kinematic variables obtained with the latest ePIC design and simulation software, we examine the impact of future measurements on the understanding of nucleon tomography and DVCS Compton form factors, which are directly linked to GPDs. We also assess the impact of radiative corrections and background contribution arising from exclusive π 0 production.
When collected over a curved path, Synthetic Aperture Radar (SAR) contains information about the three-dimensional content of a scene that can aid interpretation of this difficult imaging modality. In a point scatterer simulation with amplitudes and heights derived from a real SAR image pair, we supplement confocal processing with a monopulse-based algorithm to compute heights of certain bright points, which we find automatically. In SAR, bright points often reflect man-made infrastructure central to scene interpretation.
This report provides a deep dive into how the stability of energy dispersive spectroscopy (EDS) standards yielded insight into the shortfalls of using software to randomly select points for spectral acquisition when using heterogeneous standards. Some procedural recommendations are included which are meant to minimize the impact of anomalous reference standard spectra by detecting them before the standard is implemented into data processing.
The SaS4D Home Team UI (python) is a software to view and interact with different layers of 3D geometries and generate usable MCNP-style input file. It is used by the remote Home Team in providing guidance and building models of environments they have never seen in order to investigate threat object discovered at the Working Point. The UI visualizes a colorized mesh, a semantic labelled mesh, and a semantic labelled probability mesh of the scanned environment as well as individual water-tight material-labeled objects. It allows for manipulation and re-processing of these objects. The UI also contains measurement tools to facilitate better MCNP input file generation in the manipulation workflow. The software is a key component in ensuring the Home Team has prompt awareness of the Working Point.
In November 2017, the Transient Reactor Test Facility returned to operation. Since that time, many transient test series have been completed, such as the Transient Heatsink Overpower Response capsule (THOR), the Transient Water Irradiation System for TREAT (TWIST), and Sirius. Each has provided valuable data for materials performance and reactor safety that can be applied in future designs. During each experimental series, detector count rates provided important information on the core behavior during transients. However, a limitation of these data is that variations in the neutron distribution during experiments can cause errors when attempting to infer reactivity evolution from detector signals. Neutron physics codes can be used to compute the flux shape variations. However, this is a poor solution when the experimental data is used for code verification, validation and uncertainty quantification. Indeed, if the output of the code is used both as a reference and to correct what the reference is compared to, the circular dependency limits the quality of the verification, validation and uncertainty quantification approach. To overcome this problem, the autocorrected reactimeter algorithm (ACRA) has been developed. This approach infers a time-dependent reactivity evolution by testing different spatial corrections and selecting the one that minimizes reactivity variations when the core is in a frozen configuration (i.e., when there is no variation in parameters affecting reactivity). However, the scope of this method was limited to transients where there were negligible thermal feedback. Indeed, the core is never in a frozen configuration when the fuel temperature varies during the whole transient. This is our motivation for developing an improved version of the ACRA that does not require frozen configurations. To develop this new algorithm, we need a precise and unbiased implementation of the inverse point kinetic equations (IPKEs) as any error in the reactivity evaluation will be propagated into the choice of the optimal spatial correction. Indeed, the previous reactimeter algorithm would use approximations, such as a negligible flux amplitude derivative, to focus on rapidity. For the numerical validation of ACRA, we aim at absolute error under for reactivity derived from signals similar to the one of this study. In this summary, we test eight different IPKE implementations. Each will process a mockup signal built for this study, similar to those that the future ACRA will process. Each reactivity output will be compared to the reference reactivity that has been used to generate the mockup signal. The implementation minimizing the difference with the reference reactivity will be used in the development of a new ACRA formulation.
Abstract Plant neutral lipids, also known as “vegetable oils”, are synthesized within the endoplasmic reticulum (ER) membrane and packaged into subcellular compartments called lipid droplets (LDs) for stable storage in the cytoplasm. The biogenesis, modulation, and degradation of cytoplasmic LDs in plant cells are orchestrated by a variety of proteins localized to the ER, LDs, and peroxisomes. Recent studies of these LD-related proteins have greatly advanced our understanding of LDs not only as steady oil depots in seeds but also as dynamic cell organelles involved in numerous physiological processes in different tissues and developmental stages of plants. In the past 2 decades, technology advances in proteomics, transcriptomics, genome sequencing, cellular imaging and protein structural modeling have markedly expanded the inventory of LD-related proteins, provided unprecedented structural and functional insights into the protein machinery modulating LDs in plant cells, and shed new light on the functions of LDs in nonseed plant tissues as well as in unicellular algae. Here, we review critical advances in revealing new LD proteins in various plant tissues, point out structural and mechanistic insights into key proteins in LD biogenesis and dynamic modulation, and discuss future perspectives on bridging our knowledge gaps in plant LD biology.
Adoption of dense and homogeneous solid electrolytes can possibly mitigate the propagation of lithium dendrites and enable lithium metal anodes. Application of external pressure helps to minimize the sintering temperature in oxide ceramics and can potentially densify softer sulfide electrolytes even under room temperature conditions. Here, a previously developed phase field-based computational scheme for predicting the high-temperature sintering-induced densification of oxide ceramic solid electrolytes is extended in the present context to capture the influence of external pressure for densifying solid electrolytes. Two different bulk deformation mechanisms, namely, "reorganization" and "creep deformation," are dominant under external pressure, which is different from the surface and grain-boundary diffusion-induced densification of solid electrolytes that occurs during high temperature sintering. External pressure also increases the points of contact between the particles, which further enhances the propensity of diffusion-induced sintering process. Results obtained from simulations indicate that densification under external pressure is independent of the solid electrolyte particle morphology. Finally, a phase map is generated between applied pressure and temperature for achieving complete densification of oxide ceramics, which can possibly guide the synthesis of thin and dense solid electrolyte separators.
This project was motivated by State-of-the-Art (SOTA) technology that incorporates Network on Chips (NOC) for efficient data communication across the various computer kernels. For example, on the AMD Versal Field Programmable Gate Arrays (FPGA), an NoC has been incorporated for fast data communication from the programmable logic and other computer kernels (processing system, adaptable intelligence engines, etc.). The radiation effects on the legacy technology of this FPGA, such as the programmable logic, are well understood, and established methods exist to measure cross-sections when new families/generations are released; however, newly incorporated technologies, such as the NoC, are not fully understood and could introduce new failure points into the mission space.
Over recent years, several hypotheses have been put forward to elucidate supercritical transition states. Despite significant progress on the fundamental understanding of fluids at these supercritical conditions, important questions concerning the microstructure and dynamical processes remain. A particular research issue is hereby the fundamental understanding of the morphology of the molecular microstructure and its effect on the macroscopic behaviour and thermodynamic response functions. It is widely believed that the supercritical state is homogeneous without structural and dynamic observables to distinguish between a liquid and a vapor. However, recent investigations have identified regions of distinct liquid-like or vapor-like properties even under supercritical conditions. Specifically, it was shown that the transition between liquid-like and vapor-like states occurs across an extension to the coexistence line, marked by almost discontinuous changes in fluid properties. This transition was first identified experimentally by Nishikawa and Tanaka and stands in contrast to the classical presentation of the supercritical state space as a featureless, homogeneous domain. Structurally, the most important properties of supercritical fluids are the dynamic heterogeneities and local density fluctuations that are present within the fluid state at the microscopic level. These inhomogeneities are associated with the formation of molecular clusters of various sizes with liquid-like properties separated by voids of unbound gas-phase molecules which continuously restructure itself at picosecond timescales. By utilizing ultrafast X-ray Photon Correlation Spectroscopy (XPCS) at the Linac Coherent Light Source (LCLS) and X-ray synchrotron measurements as an experimental probe of these structural changes at the molecular level we seek to elucidate the higher-order phase transition from a liquid-like to a vapor-like state in the region extending the critical point. Open questions we seek to address particularly with XPCS are: (i) the underlying mechanisms responsible for the density fluctuations at supercritical conditions and how these dynamical processes at the molecular level affect the thermodynamic response functions and (ii) on what timescales do dynamical processes evolve that are associated with thermalization, molecular diffusion, and intermolecular cluster transfer.
This paper presents a techno-economic assessment of adding state-of-the-art solvent-based CO 2 capture technologies to greenfield steam methane reforming (SMR)-based H 2 production plants and quantifies the impacts of improvements in CO 2 capture technology. Current conventional capture technologies are reviewed, and future technologies in intermediate and long-term scenarios are analyzed. The results show that adding significantly more efficient solvent-based capture technologies leads to an equivalent rate of natural gas consumption as that of a conventional SMR plant without capture, despite capturing most of the CO 2 and producing the same amount of H 2 . Overall, improvements in reboiler duty and reductions in capital costs can significantly reduce the cost of H 2 production and cost of capture. Particularly, the reboiler duty of pre-combustion capture and the capital cost of post-combustion capture have the greatest impact. Based on the results, research goals are suggested. Solvent development is recommended—particularly pre-combustion solvents—for reducing the reboiler duties, and process schemes to reduce the capital costs. Costlier but more efficient solvents can be considered. A sensitivity analysis using natural gas price shows that technological improvements can reduce the impacts of high natural gas prices. The degree of economic feasibility of CO 2 capture increases with improvements to the capture technology.
The results of heat transfer experiments with supercritical CO2 (sCO2) to capture the performance of ribbed, serpentine cooling passages for Reynolds numbers in the range of 100,000 - 400,000 are presented. The oxy-combustion turbine operating in an Allam-Fetvedt cycle has a turbine inlet temperature exceeding 1100°C, necessitating internally cooled turbine blades due to material creep strength limits. Reynolds numbers for sCO2, with its combination of high fluid density and low viscosity, can be up to an order of magnitude higher than comparable internal cooling conditions for an air-breathing engine where the majority of experimental data exists. To improve the prediction of cooling performance through turbulated passages, a test rig was designed and constructed with interchangeable insert capability for operation in sCO2 with heat transfer from a heater outlet flow stream to a lower temperature recuperator outlet flow stream. The inserts included serpentine passage geometry with five passes, one of the inserts including chevron ribs and the other a plain wall. The multi-pass serpentine geometry allowed for the evaluation of the effects 180 deg. tip turns have on the return passage flow characteristics, as they can depart significantly from fully-developed flow characteristics. The test procedure included the use of a modified Wilson plot method, with hot flow stream conditions kept effectively constant so that monitored changes in the overall thermal resistance could be attributed to manipulations in cooling flow stream conditions. Conditions during testing consisted of test section pressures of approximately 180 bar, cooling flow stream temperature of 175°C and hot flow stream temperature of 410°C. Test points at discrete cool flow Reynolds numbers up to 400,000 demonstrated an expected trend of decreased fluid thermal resistance with increasing Reynolds number, while at comparable Reynolds number there was an exhibited lower thermal resistance and higher passage pressure drop for the ribbed insert compared to the plain-walled insert. Processing of test data included establishment of Nusselt number enhancement ratios, so that for different internal cooling passage dimensions in the actual turbine blade at comparable Reynolds number the ratio could be applied to predict cooling performance.
The proposed research is a collaborative effort between NASA/Goddard Space Flight Center and the Hebrew University of Jerusalem. While the NASA team focused on analyzing ground-based hyper-spectral radiance observations to understand cloud edge properties and their connection to mixing processes, the Hebrew University team tackled the problem through cloud modeling activities. By approximating the shortwave spectra in the cloud-clear transition zone as a linear combination of purely clear and purely cloudy spectra we can characterize the variations of cloud optical thickness and cloud droplet effective radius in the transition zone. When applying this method to the measurements of a ground-based shortwave spectroradiometer at the ARM’s SGP site, representing continental conditions, and MAGIC field campaign between Log Angeles, California and Honolulu, Hawaii, representing maritime scenarios, we found that cloud optical depth consistently decreases in both cases, but droplet size decreases much more substantially for the continental regime, suggesting different mixing processes for the continental and maritime conditions. The investigation and measurements of radiation clouds were coupled with a unique cloud modeling. A novel spectral bin microphysics was developed and implemented to the System of Atmospheric Modeling (SAM). In order to resolve cloud transition zones with high spatial gradients of microphysical variables a unique high resolution (10 m) was used in simulations. The model calculates droplet size distributions in each grid point. The model output was transferred to the NASA/GSFC team for utilization in radiative calculations and testing of both radiative algorithm and model representation.
MGARD is a software providing error-controlled lossy compression and data refactoring based on multi-grid theories. It transforms floating-point scientific data into a multilevel representation, followed by quantization and lossless encoding processes, resulting in a self-describing compressed buffer. It supports diverse data topologies, error control norms, and computing architectures.
Coulomb explosion imaging (CEI) provides a direct means of imaging molecular geometry by correlating fragment ion momenta following the fragmentation of a molecular polycation. Here, we demonstrate the use of three-body covariance and four-body cumulant analysis to extract three-dimensional (3D) structural information from the X-ray-induced Coulomb explosion of tert-butyl iodide (C4H9I). Site-selective ionization at the iodine 4d edge with intense femtosecond soft X-ray pulses from an X-ray free-electron laser (XFEL) enables rapid charge buildup and molecular breakup. By correlating ionic fragments in the molecular frame, we isolate complete dissociation channels and reveal subtle structural changes, such as umbrella-type motion of the branched alkyl chain, during the ionization process. Comparison with point-charge simulations of the Coulomb explosion shows close agreement, validating the approach. Furthermore, these results establish covariance/cumulant mapping as a powerful strategy for imaging complex three-dimensional molecular structures and point the way toward time-resolved CEI using both XFEL and tabletop sources for capturing ultrafast structural dynamics.