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At least 235 records · Page 13

Transferable Adversarial Attack on 3D Object Tracking in Point Cloud

3D point cloud object tracking has recently witnessed considerable progress relying on deep learning. Such progress, however, mainly focuses on improving tracking accuracy. The risk, especially considering that deep neural network is vulnerable to adversarial perturbations, of a tracker being attacked is often neglected and rarely explored. In order to attract attentions to this potential risk and facilitate the study of robustness in point cloud tracking, we introduce a novel transferable attack network (TAN) to deceive 3D point cloud tracking. Specifically, TAN consists of a 3D adversarial generator, which is trained with a carefully designed multi-fold drift (MFD) loss. The MFD loss considers three common grounds, including classification, intermediate feature and angle drifts, across different 3D point cloud tracking frameworks for perturbation generation, leading to high transferability of TAN for attack. In our extensive experiments, we demonstrate the proposed TAN is able to not only drastically degrade the victim 3D point cloud tracker, \ie, P2B, but also effectively deceive other unseen state-of-the-art approaches such as BAT and M^2Track, posing a new threat to 3D point cloud tracking.

97 MATHEMATICS AND COMPUTING↗

Generic Pressurized Water Reactor Model for SAPHIRE

Generic Pressurized Water Reactor Model for SAPHIRE This report contains a data dump from a SAPHIRE Generic Pressurized Water Reactor (PWR) model. The intent is to have this information reviewed for export control and classification so that the generic model can be used external to INL. The facility model is not applicable to any existing nuclear reactors. The Generic PWR model does not represent any existing power plant and was created to support research and training purposes. Three distinct types of data are used to create a SAPHIRE risk model: - Event trees representing typical PWR sequences - Fault trees representing generic system performance - Basic events (e.g., component failure information) Where possible, we have taken information from publicly available documents and referenced that information tagged to a specific item.

99 GENERAL AND MISCELLANEOUS↗

Climate-Induced Mortality of Spruce Stands in Belarus

The aim of this work is an analysis of the causes of spruce (Picea abies L.) decline and mortality in Belarus. The analysis was based on forest inventory and Landsat satellite (land cover classification, climate variables (air temperature, precipitation, evaporation, vapor pressure deficit, SPEI drought index)), and GRACE-derived soil moisture estimation (equivalent of water thickness anomalies, EWTA). We found a difference in spatial patterns between dead stands and all stands (i.e., before mortality). Dead stands were located preferentially on relief features with higher water stress risk (i.e., higher elevations, steeper slopes, south and southwestern exposure). Spruce mortality followed a series of repeated droughts between 1990 and 2010. Mortality was negatively correlated with air humidity (r = -0.52), and precipitation (r = -0.57), and positively correlated with the prior year vapor pressure deficit (r = 0.47), and drought increase (r = 0.57). Mortality increased with the increase in occurrence of spring frosts (r = 0.5), and decreased with an increase in winter cloud cover (r = -0.37). Spruce mortality was negatively correlated with snow water accumulation (r = -0.81) and previous year anomalies in water soil content (r = -0.8). Weakened by water stress, spruce stands were attacked by pests and phytopathogens. Overall, spruce mortality in Belarussian forests was caused by drought episodes and drought increase in synergy with pest and phytopathogen attacks. Vast Picea abies mortality in Belarus and adjacent areas of Russia and Eastern Europe is a result of low adaptation of that species to increased drought. This indicates the necessity of spruce replacement by drought-tolerant indigenous (e.g., Pinus sylvestris, Querqus robur) or introduced (e.g., Larix sp. or Pseudotsuga menzieslii) species to obtain sustainable forest growth management.

spruce decline↗

Regulatory Treatment of Non-Core Sources of Radioactivity for Advanced Reactor Designs

The recent resurgence in advance (non-light water) reactor development has been paralleled by the development of risk-informed performance-based (RIPB) licensing pathways. Specifically, the creation of the RIPB Licensing Modernization Project (LMP) approach and subsequent endorsement by the U.S. Nuclear Regulatory Commission (NRC) now provides advanced reactor vendors with a defined RIPB method to develop an affirmative safety case for licensing. In addition, the Technology Inclusive Content of Applications Project (TICAP) has published guidance on developing a license application based on the LMP approach. To support the utilization of risk information as part of advanced reactor design and licensing efforts, the American Society of Mechanical Engineers (ASME)/American Nuclear Society (ANS) Joint Committee on Nuclear Risk Management (JCNRM) has developed a probabilistic risk assessment (PRA) standard for advanced reactors. The standard, which was formerly approved by the American National Standards Institute (ANSI) in 2021 and recently endorsed by the NRC in trial use Regulatory Guide (RG) 1.247, is an integral standard, covering from initiating events to offsite consequence. A major feature of the standard is that it permits the inclusion of any source of radioactivity material at the site within the plant PRA. Therefore, non-core sources of radioactivity, such as fuel storage, fuel processing, and purification systems, can be included within a single comprehensive plant PRA. For those advanced reactor vendors utilizing a RIPB licensing approach, there is an opportunity to include the non-core sources of radioactivity within the RIPB framework for licensing decision-making, such as the categorization of events, classification of structures, systems, and components (SSCs), and evaluation of the adequacy of defense-in-depth (DID). For advanced reactor designs that contain multiple non-core sources of radioactivity, or for monolithic plant sites that include associated fuel facilities, this approach could potentially simplify licensing applications through the use of a single, uniform, and consistent decision-making framework across all radioactive sources at the site. In addition, a RIPB approach could provide additional insights regarding plant behavior, flexibility regarding licensing decision-making, and potentially allow the use of risk information as part of the plant oversight process. Risk-informing these aspects of advanced reactor licensing would also be consistent with the NRC’s risk policy statement. However, there is diverse regulation and guidance regarding the licensing of non-core sources of radioactivity and generally limited experience using RIPB approaches for the evaluation as part of licensing.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Environmental and health impacts of fine and ultrafine metallic particles: Assessment of threat scores

This study proposes global threat scores to prioritize the harmfulness of anthropogenic fine and ultrafine metallic particles (FMP) emitted into the atmosphere at the global scale. (Eco)toxicity of physicochemically characterized FMP oxides for metals currently observed in the atmosphere (CdO, CuO, PbO, PbSO{sub 4}, Sb{sub 2}O{sub 3}, and ZnO) was assessed by performing complementary in vitro tests: ecotoxicity, human bioaccessibility, cytotoxicity, and oxidative potential. Using an innovative methodology based on the combination of (eco)toxicity and physicochemical results, the following hazard classification of the particles is proposed: CdCl{sub 2}∼CdO>CuO>PbO>ZnO>PbSO{sub 4}>Sb{sub 2}O{sub 3}. Both cadmium compounds exhibited the highest threat score due to their high cytotoxicity and bioaccessible dose, whatever their solubility and speciation, suggesting that cadmium toxicity is due to its chemical form rather than its physical form. In contrast, the Sb{sub 2}O{sub 3} threat score was the lowest due to particles with low specific area and solubility, with no effects except a slight oxidative stress. As FMP physicochemical properties reveal differences in specific area, crystallization systems, dissolution process, and speciation, various mechanisms may influence their biological impact. Finally, this newly developed and global approach could be widely used in various contexts of pollution by complex metal particles and may improve risk management. - Highlights: • Seven micro- and nano- monometallic characterized particles were studied as references. • Bioaccessibility, eco and cytotoxicity, and oxidative potential assays were performed. • According to calculated threat scores: CdCl{sub 2}∼CdO>CuO>PbO>ZnO>PbSO{sub 4}>Sb{sub 2}O{sub 3}.

54 ENVIRONMENTAL SCIENCES↗

Vacant niches help predict invasion risk by birds

Abstract Aim If communities have a ceiling determining the number of species that can coexist, then the ability of alien species to establish at any given location should be related to the quantity of vacant niches available. We developed a new approach to estimate the extent to which niches are vacant and then explored the relationship between vacant niches and alien species. Location Global with focal tests in Europe and North America. Taxon Birds. Methods Drawing on a global classification of trophic structures for birds, we calculated a ‘vacant niche ratio’ metric to quantify the expected level of saturation (i.e. number of vacant niches) for each 1° × 1° grid cell globally, based on the difference between expected and observed numbers of bird species for all trophic guilds. Next, we used random forests to examine if the presence of plant‐invertivore (whose food source represents plants, seeds, fruits and invertebrates) and granivore alien bird species was associated with the vacant niche ratio across well‐sampled regions. Results In Europe, we found a significant relationship between alien species and vacant niches, with greater numbers of alien species being found in communities that offered greater numbers of vacant niches overall, and across habitat types. In North America, we found no significant relationship between plant‐invertivores and vacant niches, while for granivores, we found that areas with fewer vacant niches had greater numbers of alien species, especially in forests. However, vacant niches alone correctly predict 69% of the presence of alien bird species when combining both regions and trophic guilds. Main Conclusions Most regions of the world have unsaturated bird communities, with the level of saturation in communities varying within regions and trophic guilds. We found that although often‐neglected, vacant niches are likely to be, at least partially, related with the successful establishment of alien bird species.

González‐del‐Pliego, Pamela↗

DOE/NNSA Efforts to Facilitate the Disposal of Risk Significant Sealed Sources - 18590

Commercial disposal of high-activity Class B and C disused sources has been particularly challenging in the U.S. For many years, a lack of disposal facility access, a shortage of certified of Type B transportation containers, and outdated regulatory guidance had effectively relegated a large number of risk-significant sources to indefinite storage. Progress has been made in all of these efforts. The DOE/NNSA Office of Radiological Security (ORS) and the Conference of Radiation Control Program Directors (CRCPD) Source Collection and Threat Reduction (SCATR) piloted the commercial disposal of a high-activity Cs- 137 source. To facilitate implementation of the NRC's revised waste classification guidance on sealed sources. Disposal of the 560 Ci blood irradiator at the U.S. Ecology facility in Richmond has helped to establish the availability of disposal access for similar sources under the 'alternative approach' provisions of the NRC's 2015 Concentration Averaging and Encapsulation Branch Technical Position (CA BTP). However, while these developments are significant for making disposal access available, the available information suggests that commercial sealed source users continue to keep disused sources in storage. This may be due to remaining uncertainty regarding disposal access, or due to the high cost of commercial disposal. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Infant burn injuries related to water heating for powdered infant formula preparation

Guidance for preparing powdered infant formula (PIF) helps to ensure it meets the nutritional needs of infants and is safe to consume. Among safety concerns is Cronobacter sakazakii contamination which can lead to serious infections and death. PIF preparation guidance varies; there is a lack of consensus on whether there is a need to boil water to inactivate potential Cronobacter and for how long to let the water cool before reconstitution. We sought to quantify the burden of burn injuries among infants related to water heating for PIF preparation. Estimating this burden may help inform preparation recommendations. Burn injuries among infants <18 months of age were identified from 2017 to 2019 National Electronic Injury Surveillance System data collected from sampled hospital emergency departments. Injuries were classified as related to PIF water heating, potentially related to PIF water heating but with undetermined causation, related to other infant feeding aspects, or unrelated to infant formula or breast milk feeding. Unweighted case counts for each injury classification were determined. Across sampled emergency departments, 7 PIF water heating injuries were seen among the 44,395 injuries reported for infants <18 months. No reported PIF water heating injuries were fatal, but 3 required hospitalization. Another 238 injuries potentially related to PIF water heating but with undetermined causation were also seen. Preparation guidance should consider both the potential risk for Cronobacter infection and the potential risk for burns.

60 APPLIED LIFE SCIENCES↗

Assessment of Extremes in Global Precipitation Products: How Reliable Are They?

Global gridded precipitation products have proven essential for many applications ranging from hydrological modeling and climate model validation to natural hazard risk assessment. They provide a global picture of how precipitation varies across time and space, specifically in regions where ground-based observations are scarce. While the application of global precipitation products has become widespread, there is limited knowledge on how well these products represent the magnitude and frequency of extreme precipitation—the key features in triggering flood hazards. Here, five global precipitation datasets (MSWEP, CFSR, CPC, PERSIANN-CDR, and WFDEI) are compared to each other and to surface observations. The spatial variability of relatively high precipitation events (tail heaviness) and the resulting discrepancy among datasets in the predicted precipitation return levels were evaluated for the time period 1979–2017. The analysis shows that 1) these products do not provide a consistent representation of the behavior of extremes as quantified by the tail heaviness, 2) there is strong spatial variability in the tail index, 3) the spatial patterns of the tail heaviness generally match the Köppen–Geiger climate classification, and 4) the predicted return levels for 100 and 1000 years differ significantly among the gridded products. More generally, our findings reveal shortcomings of global precipitation products in representing extremes and highlight that there is no single global product that performs best for all regions and climates.

Risk assessment↗

Early detection and uncertainty quantification of rapid sea-level rise from Antarctica

Focal Areas: (i) classification and/or anomaly detection methods applied towards identifying critical climate system thresholds; improved emulator design for (ii) reducing computational costs relative to full-physics models and (iii) improved uncertainty quantification workflows. Rationale: The evolution of the Antarctic ice sheet in response to climate change remains the single largest uncertainty in projecting future sea-level rise (SLR), with risk-averse projections for 2100 spanning between zero and a half meter. During the past decade, DOE has made substantial investments in new ice sheet and Earth system models needed to improve both understanding and predictive capability in this area. Yet major challenges remain, including better understanding when and under what circumstances significant increases in SLR from Antarctica may be initiated and better quantifying uncertainties in model-based SLR projections. Here, we discuss the potential for transformative advances in these areas through the application of machine learning and artificial intelligence (ML and AI, respectively).

54 ENVIRONMENTAL SCIENCES↗

Revision of the Branch Technical Position on Concentration Averaging and Encapsulation - 16315

On February 25, 2015, the U.S. Nuclear Regulatory Commission (NRC) issued Revision 1 of the Branch Technical Position on Concentration Averaging and Encapsulation (CA BTP), culminating a six-year process. This revision provides updated guidance on the interpretation of paragraph 61.55(a)(8) of Title 10 of the Code of Federal Regulations, 'Determination of concentrations in wastes', as it applies to the classification of a variety of different types and forms of low-level radioactive waste (LLW) as Class A, B, or C waste. The waste class determines the minimum safety measures to be applied in order to provide reasonable assurance of safe disposal of the waste. The CA BTP is used by thousands of LLW generators, by the waste processing industry, by all operating LLW disposal sites in the U.S. and by Agreement States. The previous version of the CA BTP, published in 1995, was issued before the NRC adopted its risk-informed and performance-based regulatory policy. The revised CA BTP has been informed by that policy. The revised CA BTP also contains new guidance on acceptable methods that can be used to perform concentration averaging of LLW for the purpose of determining its waste class for disposal. This paper provides background information on why the CA BTP was issued and subsequently updated. This paper summarizes the new guidance found in the revised CA BTP. This paper also explains some of the key issues that required NRC's resolution, and the reasoning that underpins the major decisions reflected in Revision 1 of the CA BTP. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Topological Interpretability for Deep Learning

With the growing adoption of AI-based systems across everyday life, the need to understand their decision-making mechanisms is correspondingly increasing. The level at which we can trust the statistical inferences made from AI-based decision systems is an increasing concern, especially in high-risk systems such as criminal justice or medical diagnosis, where incorrect inferences may have tragic consequences. Despite their successes in providing solutions to problems involving real-world data, deep learning (DL) models cannot quantify the certainty of their predictions. These models are frequently quite confident, even when their solutions are incorrect. This work presents a method to infer prominent features in two DL classification models trained on clinical and non-clinical text by employing techniques from topological and geometric data analysis. We create a graph of a model's feature space and cluster the inputs into the graph's vertices by the similarity of features and prediction statistics. We then extract subgraphs demonstrating high-predictive accuracy for a given label. These subgraphs contain a wealth of information about features that the DL model has recognized as relevant to its decisions. We infer these features for a given label using a distance metric between probability measures, and demonstrate the stability of our method compared to the LIME and SHAP interpretability methods. This work establishes that we may gain insights into the decision mechanism of a DL model. This method allows us to ascertain if the model is making its decisions based on information germane to the problem or identifies extraneous patterns within the data.

Spannaus, Adam↗

Integrated characterization of CO 2 storage reservoirs on the Rock Springs Uplift combining geomechanics, geochemistry, and flow modeling

This project improves understanding of the effects CO 2 injection and storage on geomechanical, petrophysical, and other properties on two potential reservoirs, the Madison Limestone and Weber Sandstone, at the Rock Springs Uplift, southwest Wyoming. Rock physics studies, laboratory experiments, and computer simulations were employed. Two groups of rock samples were prepared, one aged with formation brine and the second aged with CO 2 -saturated formation brine and subsequently used for geomechanical, geochemical, and petrophysical testing. Rock physics studies provided a facies classification to discriminate among different lithologies and to investigate the feasibility of predicting petrophysical properties using seismic inversion. By applying a zone-wise regression relation established in this facies analysis, a 3D reservoir model was developed. It was determined that time-lapse seismic data are not feasible for monitoring CO 2 displacement at the Rock Springs Uplift or to mitigate leakage-risks situations because pressure and fluid saturation have small effects on elastic velocities and synthetic seismograms. The small variations that do occur are due to the low porosity of the sandstone and the high stiffness of the dolomite. In the Madison Limestone, mineral dissolution due to reaction with CO 2 -saturated brine was observed in highly permeable pathways while mineral precipitation happened in intergranular or micropores. Changes in pore size were quantified via Time-Domain Nuclear Magnetic Resonance transverse relaxation time (T 2 ) and diffusion coefficient distributions. As opposed to continuous injection of CO 2 -saturated brine, a subtle increase in porosity after static ‘soaking’ with CO 2 -saturated brine increases permeability due to the heterogeneity of changes in pore and pore throat sizes. Porosity-permeability relationships are fitted using a power-law function that can be adopted to model time-evolved porosity and permeability in a transport-limited CO 2 injection process. The effect of CO 2 -saturated brine on the linear elastic properties of Weber Sandstone and Madison Limestone cannot be generally concluded. Considering horizontal and vertical orientations and different confining pressures, no consistent relationship between stress (or strain) data and reaction with CO 2 -saturated brine was observed in the nonlinear plastic and post-failure regime. The change of elastic constants due to reaction with CO 2 -saturated brine is more significant in Madison Limestone than in Weber Sandstone; however, no consistent trend was observed. Reservoir simulations suggest that injectivity for Weber Sandstone is adversely impacted by low permeability. Changes in confining pressure do not impact injection rate and can be ignored while the effect of changes to pore pressure cannot. The effect of confining pressure and pore pressure on the size of the CO 2 plume in the Madison Limestone is negligible because of higher permeability. Geomechanical and petrophysical properties induced by CO 2 -brine-rock reactions were time-dependent. Simulations considered these time-dependent properties and indicate that injectivity, porosity distribution, pressure distribution and CO 2 saturation were affected.

58 GEOSCIENCES↗

Integrating Machine Learning into a Methodology for Early Detection of Wellbore Failure [Slides]

Approximately 93% of US total energy supply is dependent on wellbores in some form. The industry will drill more wells in next ten years than in the last 100 years (King, 2014). Global well population is around 1.8 million of which approximately 35% has some signs of leakage (i.e. sustained casing pressure). Around 5% of offshore oil and gas wells “fail” early, more with age and most with maturity. 8.9% of “shale gas” wells in the Marcellus play have experienced failure (120 out of 1,346 wells drilled in 2012) (Ingraffea et al., 2014). Current methods for identifying wells that are at highest priority for increased monitoring and/or at highest risk for failure consists of “hand” analysis of multi-arm caliper (MAC) well logging data and geomechanical models. Machine learning (ML) methods are of interest to explore feasibility for increasing analysis efficiency and/or enhanced detection of precursors to failure (e.g. deformations). MAC datasets used to train ML algorithms and preliminary tests were run for “predicting” casing collar locations and performed above 90% in classification and identifying of casing collar locations.

54 ENVIRONMENTAL SCIENCES↗

Integrating Machine Learning into a Methodology for Early Detection of Wellbore Failure [Slides]

Approximately 93% of US total energy supply is dependent on wellbores in some form. The industry will drill more wells in next ten years than in the last 100 years (King, 2014). Global well population is around 1.8 million of which approximately 35% has some signs of leakage (i.e. sustained casing pressure). Around 5% of offshore oil and gas wells “fail” early, more with age and most with maturity. 8.9% of “shale gas” wells in the Marcellus play have experienced failure (120 out of 1,346 wells drilled in 2012) (Ingraffea et al., 2014). Current methods for identifying wells that are at highest priority for increased monitoring and/or at highest risk for failure consists of “hand” analysis of multi-arm caliper (MAC) well logging data and geomechanical models. Machine learning (ML) methods are of interest to explore feasibility for increasing analysis efficiency and/or enhanced detection of precursors to failure (e.g. deformations). MAC datasets used to train ML algorithms and preliminary tests were run for “predicting” casing collar locations and performed above 90% in classification and identifying of casing collar locations.

54 ENVIRONMENTAL SCIENCES↗

Reassessing Hybrid Vigor or Hybrid Dysfunction Using Physiological Trade-Offs in an Endangered Salamander System

Fitness of interspecific hybrids can be higher or lower than that of their parental genotypes, with major ramifications for evolution and conservation. A recent study found that hybrid tiger salamanders had higher metabolic rates than their parental forms. Specifically, the ratio of resting metabolic rate to water loss, which was used as a measure of performance, was greater in hybrids. Recent genetic research showed that over half of the experimental subjects in that study were genetically pure California tiger salamanders (Ambystoma californiense) misclassified as hybrids. We reanalyzed the data using the corrected identification of hybrids and parentals. As expected, updating the classification revealed even stronger evidence for differences between hybrids and parentals. Hybrids had higher resting metabolic rates and greater water loss than parentals. The ratio of resting metabolic rate to water loss was also higher in hybrids. However, we suggest that this ratio might not be a positive measure of salamander performance. Higher metabolic rate means higher energy expenditure, and higher water loss suggests increased risk of desiccation. Both are major challenges for terrestrial amphibians, especially salamanders, which are hypothesized to be low-energy, low-water-loss specialists. Under this hypothesis, the ratio of energy expenditure to water loss is a ratio of two costs rather than a ratio of benefit to cost. While our analyses corroborate and strengthen the previous statistical results, we suggest that high resting metabolic rate is better interpreted as hybrid dysfunction, not vigor. Here, both hypotheses are speculative, and specific research on the fitness effects of these physiological differences is needed to resolve this important ecological question.

Ambystoma californiense↗

Towards Anomaly Detection at the CMS High-Level Trigger System

Traditional trigger strategies in CMS typically rely on model-dependent selections or rigid kinematic cuts, risking the omission of unexpected exotic signatures. To address this, we propose a novel anomaly detection (AD) algorithm for the High-Level Trigger (HLT), designed to serve as a complementary second layer of filtering to the Level-1 AXOL1TL AD algorithm. We employ a transformer-based foundation model trained on a diverse ensemble of Standard Model processes. By combining a joint contrastive and classification objective, and using particle kinematics as inputs, the model learns to map events to a physics-informed latent space where anomalous events are isolated from dominant backgrounds. Preliminary results show that this strategy enhances the signal-to-background ratio across a range of rare SM and BSM scenarios. Furthermore, this work constitutes foundational R&D for the potential implementation of an analogous AD algorithm in the Level-1 trigger system for Phase-2.

Cruz, Roy [U. Wisconsin, Madison (main)] (ORCID:00↗

Assessing Hurricane Katrina Vegetation Damage at Stennis Space Center using IKONOS Image Classification Techniques

Hurricane Katrina hit southwestern Mississippi on August 29, 2005, at 9:45 a.m. CDT as a category 3 storm with surges up to approx. 9 m and sustained winds of approx. 120 mph. The hurricane's wind, rain, and flooding devastated several coastal towns, from New Orleans through Mobile. The storm also caused significant damage to infrastructure and vegetation of NASA's SSC (Stennis Space Center). Storm recovery at SSC involved not only repairs of critical infrastructure but also forest damage mitigation (via timber harvests and control burns to reduce fire risk). This presentation discusses an effort to use commercially available high spatial resolution multispectral IKONOS data for vegetation damage assessment, based on data collected over SSC on September 2, 2005.

Spruce, Joseph P.↗