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At least 793 records · Page 44

Industrial Control Systems: Cyber Security Risk Candidate Methods Analysis

In recognition of their mission and in response to continuously evolving cyber threats against nuclear facilities, Department of Energy - Nuclear Energy (DOE-NE) is building the Nuclear Energy Cyber security Research, Development, and Demonstration (RD&D) Program, which includes a cyber risk management thrust. This report supports the cyber risk management thrust objective which is to deliver "Standardized methodologies for credible risk-based identification, evaluation and prioritization of digital components." In a previous task, the Sandia National Laboratories (SNL) team presented evaluation criteria and a survey to review methods to determine the most suitable techniques. In this task we will identify and evaluate a series of candidate methodologies. In this report, 10 distinct methodologies are evaluated. The overall goal of this effort was to identify the current range of risk analysis techniques that were currently available, and how they could be applied, with an focus on industrial control systems (ICS). Overall, most of the techniques identified did fall into accepted risk analysis practices, though they generally addressed only one step of the multi-step risk management process. A few addressed multiple steps, but generally their treatment was superficial. This study revealed that the current state of security risk analysis in digital control systems was not comprehensive and did not support a science-based evaluation. The papers surveyed did use mathematical formulation to describe the addressed problems, and tied the models to some kind of experimental or experiential evidence as support. Most of the papers, however, did not use a rigorous approach to experimentally support the proposed models, nor did they have enough evidence supporting the efficacy of the models to statistically analyze model impact. Both of these issues stem from the difficulty and expense associated with collecting experimental data in this domain.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗

Visualizing Clustering and Uncertainty Analysis with Multivariate Longitudinal Data

Multivariate time-series datasets are intrinsic to the study of dynamic, naturalistic behavior, such as in the applications of finance and motion video analysis. Statistical models provide the ability to identify event patterns in these data under conditions of uncertainty, but researchers must be able to evaluate how well a model uses available information in a dataset for clustering decisions and for uncertainty information. The Hidden Markov Model (HMM) is an established method for clustering time-series data, where the hidden states of the HMM are the clusters. We develop novel methods for quantifying the uncertainty of the performance of and for visualizing the clustering performance and uncertainty of fitting a HMM to multivariate time-series data. We explain the usefulness of uncertainty quantification and visualization with evaluating the performance of clustering models, as well as how information exploitation of time-series datasets can be enhanced. We implement our methods to cluster patterns of scanpaths from raw eye tracking data.

97 MATHEMATICS AND COMPUTING↗

Data Evaluation of Actinide Cross Sections: 237 Np and 239 Np

A new evaluation of the ENDL cross section set for Neptunium (Z=93) is developed using the TALYS statistical model cross section code. The primary goal of this effort is to produce an evaluation that attempts to match as closely as possible fission cross sections developed through surrogate reaction techniques on actinide targets 237 Np and 239 Np.Additional experimental data on the long-lived 237 Np target including (n,g), (n,2n), (n,total), and (n,elastic) isalso considered. This evaluation effort and theprocessing needed to render its results into data libraries is a necessary step in making the efforts of nuclear experimentalists useful to the broad community of researchers engaged in simulations of nuclear fusion for basic and applied science. Anotheraspect, verification and validation against various AGEX experiments, is also presented. The end-product is an updated library that includes the latest measurements of key fission cross sections for comparison against those measured via traditional techniques.All the steps in the evaluation, processing, validation and verification, and library release are described in the following sections. For completeness, the appendices contain all the parameters used in the TALYS evaluation for the 237 Np and 239 Np cross sections.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Jiangsu Nanjing – Lawrence Berkeley Life Sciences Center for Translational Medicine (CRADA AWD00000392)

Project 1: Our previous work demonstrated that the CES biomarker can be an approximate measure for the levels of chromosomal instability (CIN) in cancer, and that the CES (for Centromere and kinetochore gene Expression Score) biomarker effectively predicts which cancer patients benefit from adjuvant chemotherapies in lung and other cancer types. Such a utility can potentially reduce overtreatment that is common in lung cancer treatment. We determined performance of the multiplex Quantigene RNA assay platform for measuring mRNA levels of CES genes using clinical tumor samples. These experiments determined sensitivity, specificity and detection limit of 12 CES genes and 5 control genes using clinical tumor samples with paired normal tissue samples. We determined how sample concentration and storage conditions affect measurement sensitivity and specificity, and whether sample storage over time affects result reproducibility. Importantly, we confirmed that early stage lung cancer CES values are significantly higher than those of paired normal tissues in all cases. This result greatly extended our bioinformatic data mining by confirming that we can measure CES values directly from patient tumor tissue, and that tumors have higher CES values than normal tissues. Unfortunately, our CRADA partner in China did not finish measuring CES expression levels for a larger group of ~100 tumor samples, due to the long period time required for human subject review in China. This delay prevented us from generating enough additional data to generate a significant statistical model. We finished analyzing all the data acquired during the CRADA, and are trying to work collaboratively with the Shanghai University Lung Cancer Hospital to complete the analysis of more tumor samples. Although no publications have resulted from this research, the findings are crucial for ongoing efforts to obtain funding to develop the technology to address problems in deciding on appropriate treatment regimens for individual patients, in clinical settings. Project 2: The overarching milestones of CRADA Project 2 were to investigate the role of FAM83 family members in cancer progression. Two publications resulted from this work which are highlighted below. The first major goal of the CRADA was to broadly assess the role of FAM83 family oncogenes in human cancer using a multi-omic bioinformatic approach (Snijders et al 2017 Mol. Oncol 11). The second major goal was to specifically assess the role of FAM83D in a cancer progression and metastasis (Yin et al 2019 Cell Oncol; in revision). Role of FAM83 family oncogenes in human cancers Recent studies from our laboratory as well as other groups have demonstrated that FAM83 family members have oncogenic properties and have significantly elevated expression levels in multiple human tumor types, including breast cancers (BC). We performed an integrative multi-omics bio-informatic analysis of the role of FAM83 family oncogenes in human cancers. Our findings were published in the journal Molecular Oncology (Snijders et al; Mol Oncol. 2017 Feb;11(2):167-179). Highlights from this manuscript are: • Transcriptional levels of FAM83 family members are frequently and dramatically elevated across tumor types in human • DNA copy number increase appears to be a potential mechanism for increased expression of FAM83 genes • FAM83 family gene signature is associated with poor survival across human tumor types • FAM83 gene alterations are significantly correlated with TP53, PIK3CA and Ecadherin mutations. In conclusion, this analysis of FAM83 family members opened up a new horizon for further understanding the significance of FAM83 genes in cancer and clinical applications in diagnosis, prognosis and therapy. Role of FAM83D in human non-small cell lung cancer (NSCLC) metastasis and its impact on chemotherapy. Lung cancer is one of the most common malignant tumors in the world and non-small cell lung cancer (NSCLC) accounts for 80~85% of all diagnosed lung cancer cases, one of the deadliest cancers worldwide. FAM83D has been proposed as an oncoprotein in several types of human cancer, yet its role and molecular mechanism in human non-small cell lung cancer (NSCLC) metastasis and its impact on chemotherapy are poorly understood. We evaluated the expression of FAM83D in NSCLC cells and cancerous tissues and its prognostic significance, then investigated the effect of FAM83D on tumorigenic phenotypes such as cell proliferation, EMT and invasive capability, and finally assessed impact of FAM83D on NSCLC chemo-drug resistance. The results of this study are currently in revision at the journal Cellular Oncology. Highlights from this manuscript are: • FAM83D expression is elevated in NSCLC cells and tissues and associated with poor prognosis • FAM83D promotes NSCLC cell proliferation • FAM83D induces EMT in NSCLC cells • FAM83D promotes NSCLC cell migration and invasion • FAM83D promotes EMT and invasive capability of NSCLC cells by regulating AKT/mTOR pathway • FAM83D silencing increases cisplatin sensitivity of NSCLC cells In summary, this second study demonstrated for the first time that FAM83D promoted EMT and metastasis of NSCLC cells through AKT/mTOR signal pathway as well as increased the sensitivity of NSCLC to cisplatin. This study may provide potential targets for advanced NSCLC treatment and personalized therapy.

59 BASIC BIOLOGICAL SCIENCES↗

Potential Impacts of Accelerated Climate Change (Annual Report of Work)

This research project is part of the U.S. Nuclear Regulatory Commission’s (NRC’s) Probabilistic Flood Hazard Assessment (PFHA) research plan in support of developing a risk-informed licensing framework for flood hazards and design standards at proposed new facilities and significance determination tools for evaluating potential deficiencies related to flood protection at operating facilities. The PFHA plan aims to build upon recent advances in deterministic, probabilistic, and statistical modeling of extreme precipitation events to develop regulatory tools and guidance for NRC staff with regard to PFHA for nuclear facilities. The tools and guidance developed under the PFHA plan will support and enhance the NRC’s capacity to perform thorough and efficient reviews of license applications and license amendment requests. They will also support risk-informed significance determination of inspection findings, unusual events, and other oversight activities. For Year 1, specifically, Pacific Northwest National Laboratory (PNNL) staff: Prepared an annual report that summarizes recent scientific findings, reports on activities of federal agencies with direct responsibility for climate change science, and provide a qualitative assessment of these findings relevant to NRC concerns on a regional level (i.e., increasing air and water temperatures, decreasing water availability, increasing frequency and intensity of storms and flooding, and sea level rise). Participated in annual webinars with NRC staff at NRC Headquarters in Rockville, Maryland. Presented updates summarizing recent scientific findings at the NRC PFHA Workshop Headquarters in Rockville, Maryland. PNNL staff have identified neither technical nor programmatic issues in proceeding with Year 2 activities. PNNL staff updated this report in March and April 2019.

54 ENVIRONMENTAL SCIENCES↗

Data Evaluation of Actinide Cross Sections: 230 Th and 231 Th

A new evaluation of the ENDL cross section set for Thorium (Z=90) is developed using the TALYS statistical model cross section code. The primary goal of this effort is to produce an evaluation that attempts to match as closely as possible fission cross sections developed through surrogate reaction techniques on actinide targets 230 Th and 231 Th. This evaluation effort and the processing needed to render its results into data libraries is a necessary step in making the efforts of nuclear experimentalists useful to the broad community of researchers engaged in simulations of nuclear fusion for basic and applied science. Another aspect, verification and validation against various AGEX experiments, is also presented. The end-product is an updated library that includes the latest measurements of fission cross sections for comparison against those measured via traditional techniques. All the steps in the evaluation, processing, validation and verification, and library release are described in the following sections. For completeness, the appendix contains all the parameters used in the TALYS cross section evaluation for neutrons incident on 230 Th and 231 Th.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Bayesian Optimal Sensor Augmentation Via Estimated Mutual Information

We consider the problem of designing a sensor network to most efficiently locate the source of a seismic event. The left panel of Figure 1 shows 982 possible sensor locations in a region of interest. The objective is to infer the unknown location of an earthquake, indicated by the gold dot for illustration purposes. Assume that three sensors have already been placed for data collection. Travel times of the P-wave from the source to the three sensors are observed and used to infer the unknown source location via a Bayesian statistical model described subsequently. The right panel of Figure 1 shows samples from the resulting posterior distribution for source location along with a posterior estimate of this location.

47 OTHER INSTRUMENTATION↗

Theoretical study of various nonlinear phenomena in plasma systems and scaling of magneto-inertial-fusion targets

Plasma physics is an exciting field of study with a wide variety of nonlinear processes that come into play. Examples of such processes include the interaction of small-scale turbulence with large-scale plasma structures and the nonlinear saturation of plasma instabilities, for example those of magneto-hydrodynamical nature. During this Truman LDRD project, I studied a collection of nonlinear problems that are of interest to the field of plasma physics. This LDRD report summarizes four main research accomplishments. First, a new statistical model for describing inhomogeneous drift-wave turbulence inter- acting with zonal flows was developed. This new model includes the effects of nonlinear wave-wave collisions, which are expected to change the spectrum of the underlying DW turbulence and therefore the generation of zonal flows. Second, a new mathematical formalism was proposed to systematically apply the non- linear WKB approximation to general field theories, including those often used in fluid dynamics. This formalism represents an interesting tool for studying physical systems that show an explicit scale separation. Third, a weakly nonlinear model was developed to describe the magneto-Rayleigh-Taylor instability. This instability is of paramount importance to understand as it can reduce the performance of magnetic-inertial-fusion (MIF) platforms. The developed models captures the effects of harmonic generation and saturation of the linear growth of the instability. Finally, a framework was proposed for scaling magneto-inertial fusion (MIF) targets to larger pulsed-power drivers. From this framework, a set of scaling rules were derived that conserve the physical regimes of MIF systems when scaling up in peak current. By doing so, deleterious nonlinear processes that affect MIF performance may be kept at bay.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Feature Detection

Focal Area(s): This proposal aims to develop and evaluate statistical models and machine learning algorithms for detecting and tracking features in spatiotemporal remotely sensed data with uncertainty quantification. We focus a particular application on the detection of sea ice leads and ridges in the Arctic and use these key sea ice features for model calibration and to gain insight into the physics of sea ice thermodynamics and deformation.

54 ENVIRONMENTAL SCIENCES↗

Evaluating Offshore Infrastructure Integrity

Drilling in the offshore environment involves a complex network of infrastructure including pipelines, platforms, rigs, subsea installations, ports, and terminals. Government and industry partners have developed this network over many decades and it remains a critical part of the United States (U.S.) energy portfolio. Many of the major components of this system have been designed with a 20- to 30-year lifespan, yet consistent and growing energy demands support the need to extend the design life of existing infrastructure or repurpose it for secondary needs (i.e. enhanced oil recovery, carbon storage, and new wells). As a result, a growing portion of the offshore infrastructure in the U.S. is approaching or has exceeded its original design life. A critical step in ensuring the continued safe and effective operation of offshore infrastructure is developing a comprehensive understanding of the state of offshore infrastructure and the factors that effect it. The purpose of this project is to assess the current state of existing infrastructure and identify the factors involved in infrastructure degradation through the development and application of big data analytics, machine learning, and advanced spatio-temporal analysis. The project leverages existing data at NETL and combines it with new information on offshore oil and gas structures and the ambient offshore environment in an effort to identify patterns associated with infrastructure integrity. Building on the identified trends and patterns, this project incorporates exploratory analytics and spatial analysis tools in conjunction with machine learning and statistical models to characterize the condition of existing platforms in the offshore environment and predict their risk of failure.

02 PETROLEUM↗

Statistical Distributions for Mesh Independent Solutions in ALEGRA

The representation of material heterogeneity (also referred to as "spatial variation") plays a key role in the material failure simulation method used in ALEGRA. ALEGRA is an arbitrary Lagrangian-Eulerian shock and multiphysics code developed at Sandia National Laboratories and contains several methods for incorporating spatial variation into simulations. A desirable property of a spatial variation method is that it should produce consistent stochastic behavior regardless of the mesh used (a property referred to as "mesh independence"). However, mesh dependence has been reported using the Weibull distribution with ALEGRA's spatial variation method. This report describes efforts towards providing additional insight into both the theory and numerical experiments investigating such mesh dependence. In particular, we have implemented a discrete minimum order statistic model with properties that are theoretically mesh independent.

36 MATERIALS SCIENCE↗

Stochastic Modeling in a Multimaterial Continuum Mixture Shock Physics Code

Stochastic modelling approaches are presented to capture random effects at multiple time and length scales. Random processes that occur at the microscale produce nondeterministic effects at the macroscale. Here we present three stochastic modeling approaches that describe random processes at microscopic length scales and map these processes to the macroscopic length scale. The first stochastic modeling approach is based upon a particle based numerical technique to solve a Stochastic Differential Equation (SDE) using an arbitrary diffusion process to capture random processes at the microstructural level. The second approach prescribes a Probability Density Function (PDF) for the drift and diffusion of the random variable derived using the forward and backward Kolmogorov equations. This method requires mean and drift evolution PDF transport equations. The third approach is the coupling of multiple random variables which are dependent on each other. The relationship of the PDFs and a coupling function, known as a copula, produces a Joint Probability Density Function (JPDF). These stochastic modeling approaches are implemented into a Multiple Component (MC) shock physics computational code and used to model statistical fracture and reactive flow applications.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

A Structural engineering Graduate Degree Program with specialization in structural health monitoring & non-destructive evaluation [Slides]

The promotional presentation discusses the graduate degree program at the University of California, San Diego, Jacobs School of Engineering, related to structural engineering. Structural Health Monitoring (SHM) encompasses the integration of a broad range of technologies from sensing/actuating, data interrogation, and statistical modeling to enable system-level or component-level health assessment and predictive modeling. The course is available via distance learning to Los Alamos National Laboratory engineers.

42 ENGINEERING↗

Uncertainty in Annual Energy Resulting from Uncertain Irradiance Measurements

We report an analysis quantifying the contribution to uncertainty in annual energy projections from uncertainty in ground-measured irradiance. Uncertainty in measured irradiance is quantified for eight instruments by the difference from a well maintained, secondary standard pyranometer which is regarded as truthful. We construct a statistical model of irradiance uncertainty and apply the model to generate a sample of 100 annual time series of irradiance for each instrument. The sample is propagated through a common performance model for a reference photovoltaic system to quantify variation in annual energy. Although the measured irradiance varies from the reference by a few percent (standard deviation of 1-2%) the uncertainty in annual energy is on the order of a fraction of one percent. We propose a model for a factor that represents uncertainty in modeled annual energy that arises from uncertainty in ground-measured irradiance.

14 SOLAR ENERGY↗

Microscopic Evidence for Scission Neutrons

We discuss the neck rupture stage of fission and the emission of particles afterwards, two extremely rapid and highly non-equilibrium processes. Currently, the neck rupture cannot be directly probed by experiment, highlighting the importance of reliable theoretical predictions for this stage of fission. Time-dependent density functional theory (TDDFT) is used to simulate the spontaneous fission of 252 Cf. In conjunction with statistical models, inputs from microscopic calculations can be used to make predictions for prompt neutron and gamma emission spectra, quantities which can be experimentally measured. Here we characterize the scission mechanism within TDDFT and estimate the number of scission neutrons and their kinetic energies.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Improving Self-Driving Labs: Quantifying System-Level Experiment Repeatability and Broadening Instrument-Level Compatibility

Modular Autonomous Research System (MARS) is a self-driving laboratory (SDL) which performs wet-lab science with peptide-lanthanide combinations in an automated and, ultimately, an autonomous manner to aid in soil analysis for domestic lithium mining. Autonomous experimentation involves automated experimentation, experiment planning, and active learning. MARS consists of a 6-axis robotic arm (UR5e) on a linear rail, pipette robots (Opentrons 2), and microplate readers. These components transport, operate on, and collect data with chemical solutions in standard labware. For effective autonomy, MARS must perform system-level labware operations repeatably, plan experiments autonomously, and be portable between research-domains. Repeatability is evaluated by labware placement precision, such that future operations can properly locate labware, as well as the elapsed time, so that low variance mean estimates of experiment duration can inform high-level researcher decision making. Autonomous experiment planning is the next step to decouple experimentation from human management; however, there is a conflict between the ideal system-level experiment goals and the constraints imposed by instruments’ limitations. Sub-domain portability is a long-term goal to extend MARS’ research beyond the chemistry of peptide-lanthanide binding to other sub-domains without having to invest significant overhead to system retrofitting. To address these goals, we manually trained the robotic arm labware placement and modelled statistical failurerate and uncertainty Additionally, we benchmarked the duration and variance of each experiment sub-operation as a heuristic for research decision making. Next, we use a parameterized geometric program (PGP) approach to design experiments that optimize system-level objectives and satisfy instrument-level constraints. Lastly, we proposed a Python framework to maximize MARS’ extensibility to other scientific sub-domains through a JSON-based experiment specification.

36 MATERIALS SCIENCE↗

A Framework for the Optimization of Water Treatment Processes Under Uncertainty Assessed through Process Operability

Conference presentation conveying work conducted on developing a framework for the optimization of water treatment processes after applying robust optimization and process operability tools. The objective of this framework is to optimize treatment processes under the uncertainty of source water conditions. This work contributes to robust optimization and process operability methodologies, allowing for the extension of probability from statistical models to operability calculations.

Barber, Hunter↗

Many-body Nuclear Dynamics

The principal goal of this work was to better understand the fusion of neutron-rich nuclei a topic relevant to the fields of both nuclear physics and nuclear astrophysics. The work provides insight into the structure and reactions of neutron-rich nuclei namely the extent of their neutron density distribution and its polarizability. By comparing the fusion excitation functions for a chain of isotopes with a common target nucleus changes in the attractive nuclear potential are assessed. This change in the attractive potential is related to changes in the neutron density distribution with increasing number of neutrons or changes in fusion dynamics with increasing neutron number. The impact of the pairing of valence neutrons and protons on the fusion cross-section is also examined. Measurement of an isotopic chain is a powerful tool to address this topic. The experimental program made use of several different accelerator facilities. The core of the experimental work involved experiments at the ReA3 accelerator and the Facility for Rare Isotope Beams (FRIB) situated at Michigan State University, at GANIL, the French national nuclear physics laboratory, and the University of Notre Dame. At ReA3 the degree to which α-clusters associated with fusion of 28,30,32 Si + 28 Si result from the collision dynamics or reflect an initial α-cluster structure was explored. Alpha clusters observed in fusion reactions exceed the predictions of the standard statistical model. This experiment provides a measure of how clusterization is impacted by the increasing neutron-richess of the system. In the experiment at GANIL we investigated fusion in 19 O + 12 C and 20 O + 12 C. This experiment utilized the recently developed active-target detector MuSIC@Indiana. Using this proven, highly efficient, active-target detector we measured the fusion excitation function for these neutron-rich systems. Grounded by these experimental measurements, theoretical models were used to examine the role of unpaired valence neutrons on the fusion cross-section at energies just above the fusion barrier.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗