Sensitivities of Recent Electricity Generation Water Use Findings to Data Updates and Variability
Abstract not provided
14 SOLAR ENERGY↗
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Influence of data uncertainty on cold season threshold-based climate indices
Climate indices are used to reduce the complex climate system and its changes to simple measures. The data basis – whether observational data or climate model data – to which the climate indices are applied, is usually subject to uncertainties. For threshold-based climate indices, the data uncertainty influences the threshold value, and, hence, the uncertainty can influence the values for the climate index. What the actual impacts of these uncertainties are on threshold-based climate indices is examined in this paper. The focus is not only on the climate model uncertainty, but also on the observational data uncertainty. The general sensitivity of each of the chosen climate indices to arbitrary changes in the threshold is studied. This shows a higher sensitivity of indices assessing extremes (ice days, heavy precipitation days) to changes in the threshold than indices that integrate a quantity over a given time interval (coldsum, consecutive days). For assessing an ensemble of climate model data with respect to their ability to reproduce the index values for current climate, the reference data uncertainty is applied to the chosen threshold-based climate indices by changing their threshold value by its corresponding uncertainty. It is shown that the climate model uncertainty can be within the range of the reference data uncertainty. When using threshold-based climate indices to assess changes in future climate periods, uncertainties should always be taken into account and ideally corrected in an appropriate way. This is especially important for indices that assess extremes.
54 ENVIRONMENTAL SCIENCES↗
Survey of Approaches to Generate Realistic Synthetic Graphs
A graph is a flexible data structure that can represent relationships between entities. As with other data analysis tasks, the use of realistic graphs is critical to obtaining valid research results. Unfortunately, using the actual ("real-world") graphs for research and new algorithm development is difficult due to the presence of sensitive information in the data or due to the scale of data. This results in practitioners developing algorithms and systems that employ synthetic graphs instead of real-world graphs. Generating realistic synthetic graphs that provide reliable statistical confidence to algorithmic analysis and system evaluation involves addressing technical hurdles in a broad set of areas. This report surveys the state of the art in approaches to generate realistic graphs that are derived from fitted graph models on real-world graphs.
97 MATHEMATICS AND COMPUTING↗
Testing to Evaluate Processes Expected to Occur during MSR Salt Spill Accidents
Obtaining a license for a new nuclear reactor requires the identification and assessment of the potential consequences of specified accident scenarios, which are achieved using accident progression models. Those models need to be parameterized and validated using experimental data, but existing experimental data addressing processes relevant to molten salt reactor accidents are sparse. Specifically, experimental data that quantify the sensitives of important processes to the initial conditions of the spill, the ambient environment, and the containment features are needed to parameterize individual process models. Integrated experiments that simulate accident scenarios are also needed to provide data for model validation, but these experiments will require the use of proven methods to quantify the processes under evaluation. The overarching objectives of this work are to develop the methods for simulating the targeted processes, to determine the effectiveness of the methods in producing the data required for model development, to generate data that can be used to parameterize individual process models, and to provide key insights into the behavior of spilled molten salt that should be considered in models. Experimental methods were designed to quantify aspects of individual processes expected to occur during or after a molten salt spill accident that will affect the fate of spilled molten salt and the radionuclides within. These processes include 1) molten salt spreading and heat transfer, 2) molten salt flowing and freezing in tubing, 3) stainless steel corrosion kinetics in molten salt, and 4) molten salt splashing and aerosol generation. The initial tests described in this report were conducted using eutectic FLiNaK to demonstrate the test methods, the data that are generated, and the analyses of the data to derive values needed for modeling. The primary variables that were tested include initial salt temperature and the presence of volatile surrogate fission products (e.g., cesium and iodine). The developed methods are shown to be effective in quantifying the desired processes and can be applied to study more complex salt compositions of interest to molten salt reactor developers, a wide range of environmental conditions of interest to modelers, and additional variables relevant to salt spill accidents. The developed methods and insights gained from laboratory tests can also be incorporated in future large-scale integrated tests used to simulate molten salt spill accidents.
21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
Shedding light on top partner at the LHC
We investigate the sensitivity of the 14 TeV LHC to pair-produced top partners (T) decaying into the Standard Model top quark (t) plus either a gluon (g) or a photon (γ). The decays T → tg and T → tγ can be dominant when the mixing between the top partner and top quark are negligible. In this case, the conventional decays T → bW , T → tZ, and T → th are highly suppressed and can be neglected. We take a model-independent approach using effective operators for the T-t-g and T-t-γ interactions, considering both spin-$\frac{1}{2}$ and spin-$\frac{3}{2}$ top partners. We perform a semi-realistic simulation with boosted top quark tagging and an appropriate implementation of a jet-faking-photon rate. Despite a simple dimensional analysis indicating that the branching ratios BR(T → tγ) ≪ BR(T → tg) due to the electric-magnetic coupling being much smaller than the strong force coupling, our study shows that the LHC sensitivity to $T\bar{T} → t\bar{t}γg$ is more significant than the sensitivity to $T\bar{T}→ t\bar{t}gg$. This is due to much smaller backgrounds attributed to the isolated high-p T photon. We find that with these decay channels and 3 ab -1 of data, the LHC is sensitive to top partner masses m T ≲ 1.4-1.8 TeV for spin-$\frac{1}{2}$ and spin-$\frac{3}{2}$ top partners, respectively.
71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
Can a shock-induced phonon up-pumping model relate to impact sensitivity of molecular crystals, polymorphs and cocrystals?
Impact sensitivity engineering of high-energy molecular crystals requires accurate predictive models. For this purpose, the promising multi-phonon based approach is selected, assessing a bit more its strengths and weaknesses. Presently used with high-quality phonon calculations of 22 molecular crystals, using a physics-based criterion to determine the phonon bath extent, the resulting intrinsic shock sensitivity index (SSI) is compared to the most common marker of impact sensitivity, h 50 , as determined from drop-weight impact tests. Selecting a data subset from experiments performed under very similar conditions (2.5 kg hammer with grit and 30–40 mg samples), the model can predict h 50 values for mono-molecular crystals with very good accuracy, including the ability to discriminate the polymorphs of HMX and CL20. This very good agreement validates an initial indirect up-pumping mechanism occurring under these conditions, where the doorway modes also interact with the phonon bath. However, the phonon bath criterion for mono-molecular crystals does not transfer well to cocrystals. Owing to the vibrational coupling of the co-molecules, it seems a broader phonon bath should be considered. Additionally recalling experimental uncertainty and various experimental factors affecting h 50 values for a given compounds, we recommend that the density of the sample, granularity and morphology be systematically considered and reported along with measurements, which will in turn allow for more systematic data and predictive capabilities for sensitivity models.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Precision epoch of reionization studies with next-generation CMB experiments
Future arcminute resolution polarization data from ground-based Cosmic Microwave Background (CMB) observations can be used to estimate the contribution to the temperature power spectrum from the primary anisotropies and to uncover the signature of reionization near ℓ=1500 in the small angular-scale temperature measurements. Our projections are based on combining expected small-scale E-mode polarization measurements from Advanced ACTPol in the range 300<ℓ<3000 with simulated temperature data from the full Planck mission in the low and intermediate ℓ region, 2<ℓ<2000. We show that the six basic cosmological parameters determined from this combination of data will predict the underlying primordial temperature spectrum at high multipoles to better than 1% accuracy. Assuming an efficient cleaning from multi-frequency channels of most foregrounds in the temperature data, we investigate the sensitivity to the only residual secondary component, the kinematic Sunyaev-Zel'dovich (kSZ) term. The CMB polarization is used to break degeneracies between primordial and secondary terms present in temperature and, in effect, to remove from the temperature data all but the residual kSZ term. We estimate a 15σ detection of the diffuse homogeneous kSZ signal from expected AdvACT temperature data at ℓ>1500, leading to a measurement of the amplitude of matter density fluctuations, σ{sub 8}, at 1% precision. Alternatively, by exploring the reionization signal encoded in the patchy kSZ measurements, we bound the time and duration of the reionization with σ(z{sub re})=1.1 and σ(Δz{sub re})=0.2. We find that these constraints degrade rapidly with large beam sizes, which highlights the importance of arcminute-scale resolution for future CMB surveys.
79 ASTRONOMY AND ASTROPHYSICS↗
Observation of Fermi arcs and Weyl nodes in a noncentrosymmetric magnetic Weyl semimetal
Weyl semimetal (WSM), a novel state of quantum matter, hosts Weyl fermions as emergent quasiparticles resulting from the breaking of either inversion or time-reversal symmetry. Magnetic WSMs that arise from broken time-reversal symmetry provide an exceptional platform to understand the interplay between magnetic order and Weyl physics, but only a few WSMs have been realized. Here, in this study, we identify CeAlSi as a new noncentrosymmetric magnetic WSM via angle-resolved photoemission spectroscopy (ARPES) and first-principles, density-functional theory based calculations. Our surface-sensitive vacuum ultraviolet ARPES data confirm the presence of surface Fermi arcs as the conclusive evidence for the existence of the Weyl semimetallic state in CeAlSi. We also observe bulk Weyl cones at the Fermi arc terminations in CeAlSi using bulk-sensitive soft-x-ray ARPES measurements. These results implicate CeAlSi as a unique platform for investigating exotic quantum phenomena resulting from the interaction of topology and magnetism.
36 MATERIALS SCIENCE↗
Investigating Similarity Differences for Light-Water-Moderated and Polyethylene-Moderated Systems [Slides]
Validation efforts revealed noticeable differences in c k for light-water and polyethylene moderated systems when compared to experimental systems. Although 1 H-H 2 O and 1 H-poly use some of the same cross section and identical covariance data, the treatment of TSLs in SCALE lead to no contribution to c k between polyethylene application and benchmark experiment. When H 2 O contribution is removed the difference in c k appears to come from 239 Pu chi. Sensitivity profiles and data-induced uncertainty confirm that the polyethylene application more closely resembles the benchmark experiment. Interrogation techniques were used to observe how TSLs and nuclide IDs affect c k . Specific differences between similar systems can be accounted for and examined to help understand differences in similarity (c k ) between systems
73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
Second-order adjoint sensitivity analysis methodology (2ND-ASAM) for computing exactly and efficiently first- and second-order sensitivities in large-scale systems - 14356
This work presents the second-order adjoint sensitivity analysis methodology (2.-ASAM) for computing exactly and efficiently the second-order functional derivatives ('sensitivities') of system responses to the system's model parameters. For a physical system comprising N{sub α} parameters and N{sub r} responses, forward methods require a total of at least (N{sup 2}{sub α}/2+3N{sub α}/2) large-scale computations for obtaining all of the first- and second-order sensitivities, for all N{sub r} system responses. On the other hand, for one functional-type system response, the 2.-ASAM requires one large-scale computation using the first-level adjoint sensitivity system (1.-LASS) for obtaining all of the first-order sensitivities, followed by at most (2N{sub α}+1) large-scale computations using the second-level adjoint sensitivity systems (2.-LASS) for obtaining all of the second-order sensitivities. The second-order sensitivities contribute decisively to causing asymmetries in the response distribution, since they are the leading contributors to the third-order response correlations (skewness). They also cause the 'expected value of the response' to differ from the 'computed nominal value of the response'. The implementation of the 2.-ASAM requires very little additional effort beyond the construction of the adjoint sensitivity system needed for computing the first-order sensitivities. Only the sources on the right-sides of the diffusion (differential) operator needed to be modified; the left-side of the differential equations (and hence the 'solver' in large-scale practical applications) remain unchanged. The application of the 2.-ASAM is illustrated on a benchmark heat conduction/convection problem, which makes transparent the underlying mathematical derivations. For this illustrative problem, 4 'large-scale' adjoint computations suffice for computing exactly all of the 6 first- and 21 distinct second-order derivatives. The 2.-ASAM presented in this work should enable the hitherto very difficult, if not intractable, exact computation of all of the second-order response sensitivities for large-systems involving many parameters, which is expected to affect significantly other fields that need efficiently computed second-order response sensitivities, such as optimization, data assimilation/adjustment, model calibration, and predictive modeling. (author)
42 ENGINEERING↗
A system to detect cerebral aneurysms in multimodality angiographic data sets
Purpose: The early detection of cerebral aneurysms plays a major role in preventing subarachnoid hemorrhage. The authors present a system to automatically detect cerebral aneurysms in multimodal 3D angiographic data sets. The authors’ system is parametrizable for contrast-enhanced magnetic resonance angiography (CE-MRA), time-of-flight magnetic resonance angiography (TOF-MRA), and computed tomography angiography (CTA). Methods: Initial volumes of interest are found by applying a multiscale sphere-enhancing filter. Several features are combined in a linear discriminant function (LDF) to distinguish between true aneurysms and false positives. The features include shape information, spatial information, and probability information. The LDF can either be parametrized by domain experts or automatically by training. Vessel segmentation is avoided as it could heavily influence the detection algorithm. Results: The authors tested their method with 151 clinical angiographic data sets containing 112 aneurysms. The authors reach a sensitivity of 95% with CE-MRA data sets at an average false positive rate per data set (FP{sub DS}) of 8.2. For TOF-MRA, we achieve 95% sensitivity at 11.3 FP{sub DS}. For CTA, we reach a sensitivity of 95% at 22.8 FP{sub DS}. For all modalities, the expert parametrization led to similar or better results than the trained parametrization eliminating the need for training. 93% of aneurysms that were smaller than 5 mm were found. The authors also showed that their algorithm is capable of detecting aneurysms that were previously overlooked by radiologists. Conclusions: The authors present an automatic system to detect cerebral aneurysms in multimodal angiographic data sets. The system proved as a suitable computer-aided detection tool to help radiologists find cerebral aneurysms.
60 APPLIED LIFE SCIENCES↗
A MULTI-WAVELENGTH STUDY OF THE SUNYAEV-ZEL'DOVICH EFFECT IN THE TRIPLE-MERGER CLUSTER MACS J0717.5+3745 WITH MUSTANG AND BOLOCAM
We present 90, 140, and 268 GHz subarcminute resolution imaging of the Sunyaev-Zel'dovich effect (SZE) in the disturbed, intermediate-redshift (z 0.5458) galaxy cluster MACS J0717.5+3745, a triple-merger system comprising four distinct, optically detected subclusters. Our 90 GHz SZE data result in a sensitive, 34 {mu}Jy beam{sup -1} map of the SZE at 13'' effective resolution using the MUSTANG bolometer array on the Green Bank Telescope (GBT). Our 140 and 268 GHz SZE imaging, with resolutions of 58'' and 31'' and sensitivities of 1.8 and 3.3 mJy beam{sup -1}, respectively, was obtained through observations from the Caltech Submillimeter Observatory using Bolocam. We compare these maps to a two-dimensional pressure map derived from Chandra X-ray observations. Our MUSTANG SZE data confirm previous indications from Chandra of a pressure enhancement due to shock-heated, {approx}> 20 keV gas immediately adjacent to extended radio emission seen in low-frequency radio maps of this cluster. MUSTANG also detects pressure substructure that is not well constrained by the Chandra X-ray data in the remnant core of a merging subcluster. We find that the small-scale pressure enhancements in the MUSTANG data amount to {approx}2% of the total pressure measured in the 140 GHz Bolocam observations. The X-ray inferred pseudo-pressure template also fails on larger scales to accurately describe the Bolocam data, particularly at the location of the subcluster with a remnant core known to have a high line-of-sight optical velocity of {approx}3200 km s{sup -1}. Our Bolocam data are adequately described when we add an additional component-not described by a thermal SZE spectrum-to the X-ray template coincident with this subcluster. Using flux densities extracted from our model fits, and marginalizing over the X-ray spectroscopic temperature constraints for the region, we fit a thermal + kinetic SZE spectrum to our Bolocam data and find that the subcluster has a best-fit line-of-sight proper velocity v{sub z} 3600{sup +3440}{sub -{sub 2160}} km s{sup -1}, in agreement with the optical velocity estimates for the subcluster. The probability v{sub z} {<=} 0 given our measurements is 2.1%. Repeating this analysis using flux densities measured directly from our maps results in a 3.4% probability v{sub z} {<=} 0. We note that this tantalizing result for the kinetic SZE is on resolved, subcluster scales.
79 ASTRONOMY AND ASTROPHYSICS↗
A minimal set of physiomarkers in continuous high frequency data streams predict adult sepsis onset earlier
Purpose: We report that sepsis is a life-threatening condition with high mortality rates and expensive treatment costs. To improve short- and long-term outcomes, it is critical to detect at-risk sepsis patients at an early stage. Methods: A data-set consisting of high-frequency physiological data from 1161 critically ill patients was analyzed. 377 patients had developed sepsis, and had data at least 3 h prior to the onset of sepsis. A random forest classifier was trained to discriminate between sepsis and non-sepsis patients in real-time using a total of 132 features extracted from a moving time-window. The model was trained on 80% of the patients and was tested on the remaining 20% of the patients, for two observational periods of lengths 3 and 6 h prior to onset.Results: The model that used continuous physiological data alone resulted in sensitivity and F1 score of up to 80% and 67% one hour before sepsis onset. On average, these models were able to predict sepsis 294.19 ± 6.50 min (5 h) before the onset. Conclusions: Lastly, the use of machine learning algorithms on continuous streams of physiological data can allow for early identification of at-risk patients in real-time with high accuracy.
59 BASIC BIOLOGICAL SCIENCES↗
Probabilistic Voltage Sensitivity based Preemptive Voltage Monitoring in Unbalanced Distribution Networks
With increasing penetration of renewable energy and active consumers, control and management of power distribution networks has become challenging. Renewable energy sources can cause random voltage fluctuations as their output power depends on weather conditions. Conventional voltage control schemes such as tap changers and capacitor banks lack the foresight required to quickly alleviate voltage violations. Thus, there is an urgent need for effective approaches for predicting and mitigating voltage violations as a result of random fluctuations in power injections. This work proposes a novel voltage monitoring approach based on low-complexity, data-driven probabilistic voltage sensitivity analysis. The usefulness of this work is not only in predicting voltage violations in unbalanced distribution grids, but also in opening up the door for optimal voltage control. Using system data and forecasts, the proposed approach predicts the distribution of system node voltages which is then used to to identify nodes that may violate the nominal operational limits with high probability. The method is tested on the IEEE 37 node distribution system considering integrated distributed solar energy sources. The method is validated against the classic load flow based method and offers over 95% accuracy in predicting voltage violations.
Abujubbeh, Mohammad↗
FL‐ADS: Federated learning anomaly detection system for distributed energy resource networks
Abstract With the ongoing development of Distributed Energy Resources (DER) communication networks, the imperative for strong cybersecurity and data privacy safeguards is increasingly evident. DER networks, which rely on protocols such as Distributed Network Protocol 3 and Modbus, are susceptible to cyberattacks such as data integrity breaches and denial of service due to their inherent security vulnerabilities. This paper introduces an innovative Federated Learning (FL)‐based anomaly detection system designed to enhance the security of DER networks while preserving data privacy. Our models leverage Vertical and Horizontal Federated Learning to enable collaborative learning while preserving data privacy, exchanging only non‐sensitive information, such as model parameters, and maintaining the privacy of DER clients' raw data. The effectiveness of the models is demonstrated through its evaluation on datasets representative of real‐world DER scenarios, showcasing significant improvements in accuracy and F1‐score across all clients compared to the traditional baseline model. Additionally, this work demonstrates a consistent reduction in loss function over multiple FL rounds, further validating its efficacy and offering a robust solution that balances effective anomaly detection with stringent data privacy needs.
Purohit, Shaurya [Iowa State University Ames Iowa ↗
Constraining low redshift [C II ] emission by cross-correlating FIRAS and BOSS data
ABSTRACT We perform a tomographic cross-correlation analysis of archival FIRAS data and the BOSS galaxy redshift survey to constrain the amplitude of [C II] 2P3/2 → 2P1/2 fine structure emission. Our analysis employs spherical harmonic tomography (SHT), which is based on the angular cross-power spectrum between FIRAS maps and BOSS galaxy over-densities at each pair of redshift bins, over a redshift range of 0.24 < z < 0.69. We develop the SHT approach for intensity mapping, where it has several advantages over existing power spectral estimators. Our analysis constrains the product of the [C II] bias and [C II] specific intensity, $b_{\rm [C \small{\rm II}]}I_{\rm [C \small{\rm II}]}$, to be <0.31 MJy/sr at z ≈ 0.35 and <0.28 MJy/sr at z ≈ 0.57 at $95{{\ \rm per\ cent}}$ confidence. These limits are consistent with most current models of the [C II] signal, as well as with higher-redshift [C II] cross-power spectrum measurements from the Planck satellite and BOSS quasars. We also show that our analysis, if applied to data from a more sensitive instrument such as the proposed PIXIE satellite, can detect pessimistic [C II] models at high significance.
79 ASTRONOMY AND ASTROPHYSICS↗
ORBITAL PHASE VARIATIONS OF THE ECCENTRIC GIANT PLANET HAT-P-2b
We present the first secondary eclipse and phase curve observations for the highly eccentric hot Jupiter HAT-P-2b in the 3.6, 4.5, 5.8, and 8.0 {mu}m bands of the Spitzer Space Telescope. The 3.6 and 4.5 {mu}m data sets span an entire orbital period of HAT-P-2b (P = 5.6334729 d), making them the longest continuous phase curve observations obtained to date and the first full-orbit observations of a planet with an eccentricity exceeding 0.2. We present an improved non-parametric method for removing the intrapixel sensitivity variations in Spitzer data at 3.6 and 4.5 {mu}m that robustly maps position-dependent flux variations. We find that the peak in planetary flux occurs at 4.39 {+-} 0.28, 5.84 {+-} 0.39, and 4.68 {+-} 0.37 hr after periapse passage with corresponding maxima in the planet/star flux ratio of 0.1138% {+-} 0.0089%, 0.1162% {+-} 0.0080%, and 0.1888% {+-} 0.0072% in the 3.6, 4.5, and 8.0 {mu}m bands, respectively. Our measured secondary eclipse depths of 0.0996% {+-} 0.0072%, 0.1031% {+-} 0.0061%, 0.071%{sub -0.013%}{sup +0.029,} and 0.1392% {+-} 0.0095% in the 3.6, 4.5, 5.8, and 8.0 {mu}m bands, respectively, indicate that the planet cools significantly from its peak temperature before we measure the dayside flux during secondary eclipse. We compare our measured secondary eclipse depths to the predictions from a one-dimensional radiative transfer model, which suggests the possible presence of a transient day side inversion in HAT-P-2b's atmosphere near periapse. We also derive improved estimates for the system parameters, including its mass, radius, and orbital ephemeris. Our simultaneous fit to the transit, secondary eclipse, and radial velocity data allows us to determine the eccentricity (e = 0.50910 {+-} 0.00048) and argument of periapse ({omega} = 188. Degree-Sign 09 {+-} 0. Degree-Sign 39) of HAT-P-2b's orbit with a greater precision than has been achieved for any other eccentric extrasolar planet. We also find evidence for a long-term linear trend in the radial velocity data. This trend suggests the presence of another substellar companion in the HAT-P-2 system, which could have caused HAT-P-2b to migrate inward to its present-day orbit via the Kozai mechanism.
79 ASTRONOMY AND ASTROPHYSICS↗
Using excitation-energy dependent fission yields to identify key fissioning nuclei in r -process nucleosynthesis
The possibility that nucleosynthesis in neutron star mergers may reach fissioning nuclei introduces significant uncertainties in predicting the relative abundances of $r$-process material from such events. We evaluate the impact of using sets of fission yields given by the 2016 GEF code for spontaneous (sf), neutron-induced $((n, f))$, and $β$-delayed (βdf) fission processes which take into account the approximate initial excitation energy of the fissioning compound nucleus. We further explore energy-dependent fission dynamics in the $r$ process by considering the sensitivity of our results to the treatment of the energy sharing and de-excitation of the fission fragments using the FREYA code. We show that the asymmetric-to-symmetric yield trends predicted by GEF 2016 can reproduce the high-mass edge of the second $r$-process peak seen in solar data and examine the sensitivity of this result to the mass model and astrophysical conditions applied. We consider the effect of fission yields and barrier heights on the nuclear heating rates used to predict kilonova light curves. We find that fission barriers influence the contribution of 254 Cf spontaneous fission to the heating at ~100 d, such that a light curve observation consistent with such late-time heating would both confirm that actinides were produced in the event and imply the fission barriers are relatively high along the 254 Cf β-feeding path. We lastly determine the key nuclei responsible for setting the r-process abundance pattern by averaging over thirty trajectories from a 1.2–1.4 M ⊙ neutron star merger simulation. Finally, we show it is largely the odd-N nuclei undergoing $(Z, N)(n, f)$ and $(Z, N)β$df that control the relative abundances near the second peak. We find the 'hot spots' for β-delayed and neutron-induced fission given all mass models considered and show most of these nuclei lie between the predicted $N$ = 184 shell closure and the location of currently available experimental decay data.
73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗