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All sources NASA NTRS DOE OSTI

NASA NTRS2014

Concepts to Support HRP Integration Using Publications and Modeling

Initial efforts are underway to enhance the Human Research Program (HRP)'s identification and support of potential cross-disciplinary scientific collaborations. To increase the emphasis on integration in HRP's science portfolio management, concepts are being explored through the development of a set of tools. These tools are intended to enable modeling, analysis, and visualization of the state of the human system in the spaceflight environment; HRP's current understanding of that state with an indication of uncertainties; and how that state changes due to HRP programmatic progress and design reference mission definitions. In this talk, we will discuss proof-of-concept work performed using a subset of publications captured in the HRP publications database. The publications were tagged in the database with words representing factors influencing health and performance in spaceflight, as well as with words representing the risks HRP research is reducing. Analysis was performed on the publication tag data to identify relationships between factors and between risks. Network representations were then created as one type of visualization of these relationships. This enables future analyses of the structure of the networks based on results from network theory. Such analyses can provide insights into HRP's current human system knowledge state as informed by the publication data. The network structure analyses can also elucidate potential improvements by identifying network connections to establish or strengthen for maximized information flow. The relationships identified in the publication data were subsequently used as inputs to a model captured in the Systems Modeling Language (SysML), which functions as a repository for relationship information to be gleaned from multiple sources. Example network visualization outputs from a simple SysML model were then also created to compare to the visualizations based on the publication data only. We will also discuss ideas for building upon this proof-of-concept work to further support an integrated approach to human spaceflight risk reduction.

Mindock, J.↗

DOE OSTI2022

Community Based Data of Uranium Adsorption onto Quartz

This data upload includes a compilation of experiments for quantifying uranium adsorption onto quartz. The provided .csv file has been compiled from the literature in a findable, accessible, interoperable, reusable (FAIR) data format. This was accomplished using the Lawrence Livermore National Laboratory Surface Complexation Database Converter (SCDC) code written in the R programming language (free licensing available at https://ipo.llnl.gov/technologies/software/llnl-surface-complexation-database-converter-scdc). This constitutes all current data compiled on uranium-quartz interactions in the L-SCIE (LLNL Surface Complexation/Ion Exchange) database (as of 02/28/2022). This data was used to develop surface complexation models that fit the global community dataset (https://doi.org/10.1021/acs.est.1c07109). The FAIR-formatted dataset also enables the implementation of alternative machine-learning approaches that can be explored in the future.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2019

Global meta-analysis of published river bank erosion and migration rates

This dataset is a compilation of 993 measurements of riverbank erosion or migration rates from 336 rivers and streams compiled from 169 published English language studies. The dataset spans rivers across latitudes ranging from 46 deg south to 71 deg north. The rivers range in drainage area from 0.6 to 3 million square kilometers. If provided in a published study, recorded channel width, river drainage area, and sediment load and/or yield were summarized. In the absence of these ancillary data from the original source, this data was compiled from other published studies, global and regional datasets, or measured from Google Earth images. The dataset also provides information on whether the rates were measured at an individual river bend or represent reach-based averages, as well as, whether the river is single or multi-threaded.Revisions 2023 January updateAdded 72 new erosion measurements. Dropped 10 records that did not have mean erosion values.“DrainageArea(km^2)_rabpro” added“DrainageArea(km^2)” – updated to only include published drainage area and values obtained from sources other than the rabpro analysis.“River_slope_pub” added to provide river slope values provided in the published erosion study or other source listed in the “Slope Reference” field“RiverSlope_Lin” added“FLO1K_MonthlyMax_LT” and “FLO1K_MontlyMax_PoR” added“KG_Zone” added from Köppen-geiger climate classification based on Beck et al. 2018

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS2000

Trainable Gene Regulation Networks with Applications to Drosophila Pattern Formation

This chapter will very briefly introduce and review some computational experiments in using trainable gene regulation network models to simulate and understand selected episodes in the development of the fruit fly, Drosophila melanogaster. For details the reader is referred to the papers introduced below. It will then introduce a new gene regulation network model which can describe promoter-level substructure in gene regulation. As described in chapter 2, gene regulation may be thought of as a combination of cis-acting regulation by the extended promoter of a gene (including all regulatory sequences) by way of the transcription complex, and of trans-acting regulation by the transcription factor products of other genes. If we simplify the cis-action by using a phenomenological model which can be tuned to data, such as a unit or other small portion of an artificial neural network, then the full transacting interaction between multiple genes during development can be modelled as a larger network which can again be tuned or trained to data. The larger network will in general need to have recurrent (feedback) connections since at least some real gene regulation networks do. This is the basic modeling approach taken, which describes how a set of recurrent neural networks can be used as a modeling language for multiple developmental processes including gene regulation within a single cell, cell-cell communication, and cell division. Such network models have been called "gene circuits", "gene regulation networks", or "genetic regulatory networks", sometimes without distinguishing the models from the actual modeled systems.

Mjolsness, Eric↗

DOE OSTI2017

An IAEA Initiative to Provide Effective Stakeholder Support Services for International Decommissioning and Environmental Remediation - 17341

The International Atomic Energy Agency (IAEA) has initiated a collaborative effort to promote stakeholder support activities through a stakeholder engagement advisory program (SEAP) as part of Phase II of the Constraints to Implementing Decommissioning and Environmental Remediation (CIDER II) program. CIDER II is a collaborative project involving a broad range of Member States, large and small, with ongoing and/or planned decommissioning and environmental remediation (D and ER) programs. The intent of this sub-group of CIDER II is to facilitate better sharing of information and knowledge in areas of stakeholder communication, engagement and participation, and a framework for directly using stakeholder input in the decision making process. The goal is to support trust building in D and ER decisions for radioactive contamination and facilities. A main premise of the CIDER II program is that stakeholder acceptance is necessary for successful D and ER decisions to be made. This paper introduces some of the major challenges to implementing such a broad scale of support for stakeholder engagement, and approaches to overcoming those challenges. Major challenges include the need to address D and ER decision making in different countries with their different languages, cultures, religions, management structures, and politics. For example, in some cases it might be important strategically to first garner support from upper levels of social, management or political hierarchies, including for example, approaching community leaders, and allowing those leaders to directly address their community. Other sites might have more success, for example, if stakeholder interaction starts with the community members. A specific project strategy also probably depends on who makes the request for stakeholder support services. Once the CIDER II SEAP gains traction, there will be a need to prioritize requests from Member States for assistance in connection with specific D and ER projects. A prioritization tool will be developed based on stakeholder engaged structured decision making (SDM). The projects in which support will initially be focused will span a wide range of D and ER problems, types of stakeholder groups, and technical issues such as potential risk to human health and the environment. A database management system will also be designed to capture information from the different proposed projects and will be expanded to house implemented projects for future reference. The case study database will be an integral part of a web-based system that also contains technical approaches for stakeholder involvement depending on the situational environment. A community of practice will be formed that will involve technical experts in stakeholder engagement and structured decision making, and informed representatives from Member States. This will address the need for SEAP to build capacity and provide education for solving D and ER problems. The web-based system will include technical tools for use by the projects, such as: identification of stakeholder groups; social network analysis (how stakeholders are connected); case study forms; best practice forms; information sheets; and 4tools that will directly support optimization of stakeholder guided solutions to D and ER problems. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2018

Need for LWR metrology standardization: the imec roughness protocol

© 2018 Society of Photo-Optical Instrumentation Engineers (SPIE). As semiconductor technology keeps moving forward, undeterred by the many challenges ahead, one specific deliverable is capturing the attention of many experts in the field: line width roughness (LWR) specifications are expected to be <2 nm in the near term, and to drop below 1 nm in just a few years. This is a daunting challenge and engineers throughout the industry are trying to meet these targets using every means at their disposal. However, although current efforts are surely admirable, we believe they are not enough. The fact is that a specification has a meaning only if there is an agreed methodology to verify if the criterion is met or not. Such standardization is critical in any field of science and technology and the question that we need to ask ourselves today is whether we have a standardized LWR metrology or not. In other words, if a single reference sample were provided, would everyone measuring it get reasonably comparable results? We came to realize that this is not the case and that the observed spread in the results throughout the industry is quite large. In our opinion, this makes the comparison of LWR data among institutions, or to a specification, very difficult. We report the spread of measured LWR data across the semiconductor industry. We investigate the impact of image acquisition, measurement algorithm, and frequency analysis parameters on LWR metrology. We review critically some of the International Technology Roadmap for Semiconductors (ITRS) metrology guidelines [such as measurement box length >2 μm and the need to correct for scanning electron microscope (SEM) noise]. We compare the SEM roughness results to AFM measurements. Finally, we propose a standardized LWR measurement protocol - the imec roughness protocol - intended to ensure that every time LWR measurements are compared (from various sources or to specifications), the comparison is sensible and sound. We deeply believe that the industry is at a point where it is imperative to guarantee that when talking about a critical parameter such as LWR, everyone speaks the same language, which is not currently the case.

Lorusso, Gian Francesco↗

DOE OSTI2024

Normative Ranges for Oculomotor and Reaction Time Tests in U.S. Military Service Members and Veterans

AbstractBackground Oculomotor and reaction time tests are frequently used assessments of vestibular symptoms, traumatic brain injury (TBI), or other neurological disorders in both clinical and research contexts. When interpreting these tests it is important to have a reference interval (RI) as a comparison for what constitutes a typical/expected response; however, the current body of research has only limited information regarding normative ranges calculated according to established standards or for a military-specific sample.Purpose The purpose of the present study was to describe RIs for oculomotor and reaction time tests in a cohort of service members and veterans (SMVs) for use as comparators by clinicians and scientists.Research Design Descriptive.Study Sample Participants were prospectively enrolled in the Defense and Veterans Brain Injury Center-Traumatic Brain Injury Center of Excellence 15-year Longitudinal Traumatic Brain Injury Study. Only SMVs without a history of TBI or blast exposure were included in the RI calculations.Data Collection and Analysis The test paradigms included in this analysis were: smooth pursuit, prosaccades, antisaccades, saccades and reaction time, predictive saccades, optokinetic nystagmus, auditory reaction time, and visual reaction time. Nonparametric methods, based on the U.S. Food and Drug Administration's recognized consensus standards, were used to calculate 95% RIs. A comparison between the calculated RIs and those available from previously published research is provided.Results Summary statistics and RIs were calculated for 47 outcome parameters from 13 oculomotor and reaction time tests. Sample sizes and age ranges varied across outcome parameters depending on the availability of reference values for RI calculations. The sample sizes used to calculate RIs ranged from 51 to 69. The age of SMVs included in each RI ranged from 19 to 61 years with mean ages ranging from 37 to 39 years. Similarities/differences between the RIs in the present study and those in previously published research are highly dependent on the outcome parameter; however, in general, the RIs in the present study tended to be somewhat wider.Conclusion The RIs provided in this paper can serve as comparisons for clinicians and scientists who are utilizing these oculomotor and reaction time testing paradigms in similar cohorts of patients or research participants.

Audiology & Speech-Language Pathology↗

DOE OSTI2017

Testing of Strategies for the Acceleration of the Cost Optimization

The general problem addressed in the Nuclear-Renewable Hybrid Energy System (N-R HES) project is finding the optimum economical dispatch (ED) and capacity planning solutions for the hybrid energy systems. In the present test-problem configuration, the N-R HES unit is composed of three electrical power-generating components, i.e. the Balance of Plant (BOP), the Secondary Energy Source (SES), and the Energy Storage (ES). In addition, there is an Industrial Process (IP), which is devoted to hydrogen generation. At this preliminary stage, the goal is to find the power outputs of each one of the N-R HES unit components (BOP, SES, ES) and the IP hydrogen production level that maximizes the unit profit by simultaneously satisfying individual component operational constraints. The optimization problem is meant to be solved in the Risk Analysis Virtual Environment (RAVEN) framework. The dynamic response of the N-R HES unit components is simulated by using dedicated object-oriented models written in the Modelica modeling language. Though this code coupling provides for very accurate predictions, the ensuing optimization problem is characterized by a very large number of solution variables. To ease the computational burden and to improve the path to a converged solution, a method to better estimate the initial guess for the optimization problem solution was developed. The proposed approach led to the definition of a suitable Monte Carlo-based optimization algorithm (called the preconditioner), which provides an initial guess for the optimal N-R HES power dispatch and the optimal installed capacity for each one of the unit components. The preconditioner samples a set of stochastic power scenarios for each one of the N-R HES unit components, and then for each of them the corresponding value of a suitably defined cost function is evaluated. After having simulated a sufficient number of power histories, the configuration which ensures the highest profit is selected as the optimal one. The component physical dynamics are represented through suitable ramp constraints, which considerably simplify the numerical solving. In order to test the capabilities of the proposed approach, in the present report, the dispatch problem only is tackled, i.e. a reference unit configuration is assumed, and each one of the N-R HES unit components is assumed to have a fixed installed capacity. As for the next steps, the main improvement will concern the operation strategy of the ES facility. In particular, in order to describe a more realistic battery commitment strategy, the ES operation will be regulated according to the electricity price forecasts.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2022

EXFOR-NSR PDF database: a system for nuclear knowledge preservation and data curation

Current needs of nuclear science and technology include complete, well-documented, and easily verifiable nuclear data. The complete data records require supporting nuclear bibliography, presently stored in dedicated libraries, in addition, to actual data. Additionally, experimental nuclear reaction data (EXFOR) and Nuclear Science References (NSR) databases contain compilations based on primary (journals) and secondary (conference proceedings, theses, preprints, etc.) publications, and data received from authors via private communications. The secondary library materials and private communications often represent a bottleneck for nuclear data verification, compilation, evaluation, and dissemination activities. To address this issue, bibliographic materials were scanned into PDF (Portable Document Format) files and uploaded in a relational database. The traditional scope of nuclear databases that includes meta-data and numbers derived from data in specialized formats was broadened to accommodate the large volumes of original nuclear data publications. The complete PDF publication files were stored in a relational database as Binary Large OBjects (BLOB). This unique collection of nuclear data compilations and supporting publications generate many opportunities for machine learning applications. The Web interfaces for authorized and public access to the EXFOR-NSR nuclear publications database were implemented at the U.S. National Nuclear Data Center, https://www.nndc.bnl.gov/ and IAEA Nuclear Data Section, https://www-nds.iaea.org/ . The current system is complementary to major nuclear libraries and narrowly focused on nuclear data compilation and evaluation procedures. The contents of the PDF database, details of implementation, and Web interface are described. New capabilities for data curation, knowledge preservation, worldwide dissemination, and natural language processing (NLP) applications are given.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2026

OpenStudio®-MCP [SWR-26-035]

OpenStudio®-MCP is a Model Context Protocol (MCP) server that lets AI assistants perform building energy modeling through natural language. Rather than requiring users to learn the OpenStudio® SDK, EnergyPlus® scripting, or Ruby/Python automation, the server translates conversational requests into sequences of tool calls that create models, design HVAC systems, run simulations, and extract results — all within a single chat session. The server's 124 tools are organized into a skills architecture where each skill encapsulates a domain of building energy modeling (envelope, HVAC, loads, weather, simulation, results) behind typed, LLM-friendly interfaces. High-leverage operations like applying ASHRAE 90.1 baseline systems or generating standards-compliant typical buildings are exposed as single tool calls that internally wire dozens of OpenStudio® objects. Bundled measures from ComStock™ and Openstudio® -common-measures-gem are wrapped with dedicated tools and typed arguments rather than exposed through a generic measure interface, so AI models get consistent, error-resistant recipes without needing to discover measure arguments at runtime. A key design decision is structured results extraction: six SQL-based tools return surgical ~300–1,000 token responses (end-use breakdowns, envelope summaries, HVAC sizing, timeseries data) instead of requiring the AI to parse ~100K-token raw HTML reports, making iterative design exploration practical within context window limits. The codebase is designed as a reference implementation — explicit, well-commented, and modular — so that other simulation engines (EnergyPlus® standalone, TRNSYS, DOE-2) can use it as a template for building their own MCP servers.

Ball, Brian [National Laboratory of the Rockies (N↗

DOE OSTI2026

Graphical User Interface for a Biasing Board for the PSEC6

The PSEC6 is an application-specific integrated circuit (ASIC) designed for a readout system for a large area picosecond photodetector (LAPPD). The PSEC6 is currently in fabrication and pending testing. The testing system for the PSEC5, the previous iteration of the ASIC, required expensive and non-portable equipment, because the ASIC needs twelve adjustable reference voltages. The new testing system consists of an low-cost, open-source, cross-platform graphical user interface (GUI), a digital system, and a biasing board. The digital system is the interface between the GUI and biasing board, and can be implemented on a microcontroller or field-programmable gate array (FPGA). The biasing board contains twelve digital-to-analog converters (DACs) that are configurable via the GUI, which gives users the ability to write voltage values to all or specific DACs. The GUI was developed in C on Linux using the widget library GTK4 and cross-compiled for Windows compatibility. I2C and SPI protocols were implemented on an Adafruit Feather ESP32-S3 microcontroller to write commands to the DACs and PSEC6. A hardware implementation of the I2C protocol is in development on an FPGA. Since LAPPDs will be used by the Accelerator Neutrino Neutron Interaction Experiment (ANNIE) at Fermilab, the PSEC6 testing system in this internship project can potentially benefit future neutrino research. The project is relevant to the Department of Energy’s microelectronics mission, because the PSEC6 is an ASIC that will handle fast time signals arriving from the detector for readout. It also provided experience with building a cross-platform user interface, practicing digital design and implementation in hardware description language (HDL), and using simulations to inform new design iterations.

Guerrero, Sasha Camila [North Central Coll.]↗

DOE OSTI2026

Graphical User Interface for a Biasing Board for the PSEC6

Guerrero, Sasha Camila [North Central Coll.]↗

DOE OSTI2023

Normative Ranges for, and Interrater Reliability of, Rotational Vestibular and Balance Tests in U.S. Military Service Members and Veterans

Purpose: The objectives of this study were to (a) describe normative ranges—expressed as reference intervals (RIs)—for vestibular and balance function tests in a cohort of Service Members and Veterans (SMVs) and (b) to describe the interrater reliability of these tests. Method: As part of the Defense and Veterans Brain Injury Center (DVBIC)/Traumatic Brain Injury Center of Excellence 15-year Longitudinal Traumatic Brain Injury (TBI) Study, participants completed the following: vestibulo-ocular reflex suppression, visual-vestibular enhancement, subjective visual vertical, subjective visual horizontal, sinusoidal harmonic acceleration, the computerized rotational head impulse test (crHIT), and the sensory organization test. RIs were calculated using nonparametric methods and interrater reliability was assessed using intraclass correlation coefficients between three audiologists who independently reviewed and cleaned the data. Results: Reference populations for each outcome measure comprised 40 to 72 individuals, 19 to 61 years of age, who served either as noninjured controls (NIC) or injured controls (IC) in the 15-year study; none had a history of TBI or blast exposure. A subset of 15 SMVs from the NIC, IC, and TBI groups were included in the interrater reliability calculations. RIs are reported for 27 outcome measures from the seven rotational vestibular and balance tests. Interrater reliability was considered excellent for all tests except the crHIT, which was found to have good interrater reliability. Conclusion: This study provides clinicians and scientists with important information regarding normative ranges and interrater reliability for rotational vestibular and balance tests in SMVs.

Audiology & Speech-Language Pathology↗

NASA NTRS2015

Rule-Based Flight Software Cost Estimation

This paper discusses the fundamental process for the computation of Flight Software (FSW) cost estimates. This process has been incorporated in a rule-based expert system [1] that can be used for Independent Cost Estimates (ICEs), Proposals, and for the validation of Cost Analysis Data Requirements (CADRe) submissions. A high-level directed graph (referred to here as a decision graph) illustrates the steps taken in the production of these estimated costs and serves as a basis of design for the expert system described in this paper. Detailed discussions are subsequently given elaborating upon the methodology, tools, charts, and caveats related to the various nodes of the graph. We present general principles for the estimation of FSW using SEER-SEM as an illustration of these principles when appropriate. Since Source Lines of Code (SLOC) is a major cost driver, a discussion of various SLOC data sources for the preparation of the estimates is given together with an explanation of how contractor SLOC estimates compare with the SLOC estimates used by JPL. Obtaining consistency in code counting will be presented as well as factors used in reconciling SLOC estimates from different code counters. When sufficient data is obtained, a mapping into the JPL Work Breakdown Structure (WBS) from the SEER-SEM output is illustrated. For across the board FSW estimates, as was done for the NASA Discovery Mission proposal estimates performed at JPL, a comparative high-level summary sheet for all missions with the SLOC, data description, brief mission description and the most relevant SEER-SEM parameter values is given to illustrate an encapsulation of the used and calculated data involved in the estimates. The rule-based expert system described provides the user with inputs useful or sufficient to run generic cost estimation programs. This system's incarnation is achieved via the C Language Integrated Production System (CLIPS) and will be addressed at the end of this paper.

computational intelligence↗

DOE OSTI2024

Digital Analytics, Causal Knowledge Acquisition and Reasoning for Technical Language Processing

Complex engineering systems such as nuclear power plants (NPPs) generate and collect large amounts of equipment reliability (ER) data elements that contain information on the status of components, assets, and systems. Some of this information is textual in form and can be found in documents such as incident reports (IRs) and work orders (WOs). Analyses of textual data in current NPPs-using natural language processing (NLP) methods-have been expanded over the last decade, and it is only recently that the true potential of such analyses has emerged. So far, applications of NLP methods have mostly been limited to classification and prediction, the goal being to identify the nature of the textual element (e.g., safety or non-safety related). Here, we target a more complex problem: automatically extracting knowledge from a textual element in order to assist system engineers in conducting system health assessments. Knowledge extraction is a very broad concept, and its definition may vary depending on the application context. Our methods are a blend of both rule-based and machine learning (ML) algorithms. For our purposes, knowledge extraction means identifying the systems or assets mentioned in a given textual element, as well as the type of event described (e.g., component failure or maintenance activity). In addition, we want to capture details such as measured quantities and the temporal/cause-effect relations between events. In this tool, we also demonstrate how textual data elements are preprocessed in order to handle typos, acronyms, and abbreviations. One main feature of these methods is that they are not based solely on data, but are in fact model-based. In other words, they also rely on MBSE models that are designed to capture-from a functional point of view-the architecture of the systems/assets under consideration. The main purpose of such models is to digitally emulate system engineers' knowledge of system and asset architecture and to identify dependencies among systems, assets, and components. Provided these models, analyses of textual and numeric ER data can be performed by first identifying the OPM model elements to which the ER data elements are referring. The relationships between ER data elements are then identified by checking for any temporal or logical dependencies.

Mandelli, Diego [Idaho National Laboratory (INL), ↗

DOE OSTI2019

Creating Training Data for Scientific Named Entity Recognition with Minimal Human Effort

Scientific Named Entity Referent Extraction is often more complicated than traditional Named Entity Recognition (NER). For example, in polymer science, chemical structure may be encoded in a variety of nonstandard naming conventions, and authors may refer to polymers with conventional names, commonly used names, labels (in lieu of longer names), synonyms, and acronyms. As a result, accurate scientific NER methods are often based on task-specific rules, which are difficult to develop and maintain, and are not easily generalized to other tasks and fields. Machine learning models require substantial expert-annotated data for training. Here we propose polyNER: a semi-automated system for efficient identification of scientific entities in text. PolyNER applies word embedding models to generate entity-rich corpora for productive expert labeling, and then uses the resulting labeled data to bootstrap a context-based word vector classifier. Evaluation on materials science publications shows that the polyNER approach enables improved precision or recall relative to a state-of-the-art chemical entity extraction system at a dramatically lower cost: it required just two hours of expert time, rather than extensive and expensive rule engineering, to achieve that result. This result highlights the potential for human-computer partnership for constructing domain-specific scientific NER systems.

Crowdsourcing↗

DOE OSTI2017

STARlight: A Monte Carlo simulation program for ultra-peripheral collisions of relativistic ions

© 2016 Elsevier B.V. Ultra-peripheral collisions (UPCs) have been a significant source of study at RHIC and the LHC. In these collisions, the two colliding nuclei interact electromagnetically, via two-photon or photonuclear interactions, but not hadronically; they effectively miss each other. Photonuclear interactions produce vector meson states or more general photonuclear final states, while two-photon interactions can produce lepton or meson pairs, or single mesons. In these interactions, the collision geometry plays a major role. We present a program, STARlight, that calculates the cross-sections for a variety of UPC final states and also creates, via Monte Carlo simulation, events for use in determining detector efficiency. Program summary Program Title: STARlight (v2.2) Program Files doi: http://dx.doi.org/10.17632/xjpf4rxtbj.1 Licensing provisions: GNU GPLv3 Programming Language: C++ External Routines: PYTHIA 8.2 and DPMJET 3.0 are needed for some final states. Nature of problem: The cross-section for ultra-peripheral collisions is obtained by integrating the photon fluxes in transverse impact parameter space, subject to the requirement (which is also impact parameter dependent) that the colliding nuclei do not interact hadronically. The program is a two step process. First, it calculates the cross-sections for the reaction of interest, as a function of W (photon–Pomeron or two-photon center of mass energy), Y (final state rapidity) and pT (final state transverse momentum). Second, STARlight generates Monte Carlo events which can be used to determine cross-sections within specific kinematic constraints or for studies of detector efficiencies. The second step includes the decay of any unstable particles produced in the reaction, with appropriate consideration of particle spins and parity. It outputs these events in ASCII format. Solution method: The program generates a two dimensional look-up table of the production cross-section as a function of final state rapidity and mass. The dimensions of the table are selectable, allowing the user to choose the desired accuracy. For certain final states, a second two-dimensional look-up table, giving the transverse momentum distribution, as a function of rapidity, is also used. With these look-up tables, the program generates final states. Particle decays and the final angular distributions are calculated for each event. Restrictions: The program is focused on ultra-relativistic collisions at Brookhaven's RHIC (Relativistic Heavy Ion Collider) and CERN's LHC (Large Hadron Collider), with final states that are visible in a central detector. At lower energies (i.e., at the CERN SPS), caution should be exercised because STARlight does not account for the longitudinal momentum transfer to the nucleus; this is larger at low beam energies. References: http://starlight.hepforge.org and references in this article.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2023

Precursor Analysis Report: SQL Slammer Worm Infection of Davis-Besse Nuclear Power Plant 2003

The SQL Slammer Worm Infection of Davis-Besse Nuclear Power Plant 2003 Precursor Analysis Report leverages publicly available information about Davis-Besse’s 2003 cyber attack and catalogs anomalous observables for each technique employed in the attack. This analysis is based upon the methodology of the Cybersecurity for the Operational Technology Environment (CyOTE) program. On 25 January 2003, the SQL Slammer worm infected more than 90% of vulnerable hosts and crashed the internet in 10 to 15 minutes, making it one of the fastest spreading worms in history. SQL Slammer is a fileless, memory-resident worm that remotely exploits a stack-based buffer overflow vulnerability on local hosts to intensively scan and rapidly self-propagate across the internet. The worm infected approximately 300,000 unpatched hosts running Microsoft Structured Query Language (SQL) Server 2000 or Microsoft Desktop Engine (MSDE) 2000 with SQL Server Resolution Service. The SQL Slammer worm indirectly infected FirstEnergy’s Davis-Besse nuclear power plant by first infecting a consultant’s company network server and then propagating through an external misconfigured connection into Davis-Besse’s site network. The infection caused major network congestion, slow performance, data overloads, and the inability of local hosts to communicate with each other, which eventually caused a loss of availability and a loss of view when the Safety Parameter Display System (SPDS) and Plant Process Computer (PPC) crashed. At the time of the infection, the plant was already offline, the digital monitoring systems had redundant analog backups, and the plant control and safety functions were not affected, so there were no concerns of a safety breach. However, this incident resulted in many lessons learned and spawned important discussions about cybersecurity’s role in nuclear safety and electric power reliability regulation, policy, and guidance. Researchers and analysts identified 10 unique techniques utilized during the attack with a total of 640 observables using MITRE ATT&CK® for Industrial Control Systems. The CyOTE program assesses observables accompanying techniques used prior to the triggering event to identify opportunities to detect malicious activity. If observables accompanying the attack techniques are perceived and investigated prior to the triggering event, earlier comprehension of malicious activity can take place. Eight of the identified techniques used during Davis-Besse cyber attack were precursors to the triggering event. Analysis identified 596 observables associated with these precursor techniques, 428 of which were assessed to have an increased likelihood of being perceived in the 331 days preceding the triggering event. The response and comprehension time could have been reduced if the observables had been identified earlier. The information gathered in this report contributes to a library of observables tied to a repository of artifacts, data sources, and technique detection references for practitioners and developers to support the comprehension of indicators of attack. Asset owners and operators can use these products if they experience similar observables or to prepare for comparable scenarios.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗