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At least 1,459 records · Page 81

Research Library Year in Review 2016

2016 was a year of strategy, analysis and moving forward. We launched January with a strategic planning process. Building on the Lab’s Strategic Plan and Purpose Statement, we created a process that reached out to Lab leadership, scientists & engineers, and Research Library (RL) staff. An external consultant was engaged to help drive the process and to lead a fullday staff retreat. A survey was created and administered to staff, seeking feedback on priorities and direction. A parallel survey was created for stakeholders. Stakeholder questions began with the macro – from the external climate to Lab and division priorities – to the micro concerning priorities and directions for the RL. Stakeholders were personally interviewed by teams of two that included an interviewer and a scribe. These thirty-plus interviews were collated into a spreadsheet. A sociologist provided semantic analysis for the feedback, creating an impact document of the interviews. The full day retreat provided an opportunity for staff to build on their feedback as well as stakeholder feedback. A great deal of brainstorming led to categorized priorities and scenarios. The RL Compass Team, encompassing library leadership, moved the next stage of the process forward by taking retreat feedback and creating a first draft of a plan. Two more rounds of feedback with smaller staff groups as well as the Library Advisory Board led to the final plan. The core plan is included in this report.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗

Learning Memento archive routing with Character-based Artificial Neural Networks

This white paper describes a series of tests that were performed to determine if a neural network could learn patterns from a service that maintains a cache of routing decisions for the discovery of version information for discrete web-at-large URLs. Labeled training data was derived from a log file that records the by-archive availability of Memento availability for a given URL. Training data sets were generated from this log file on a by-archive basis (thus making it a binary classification problem). Each training data set consisted of equal numbers of hit and miss URLs, selected at random. The URLs were converted to a normalized numeric representation where each integer in a URL training vector represents a character in that URL. The corresponding label indicates whether or not Mementos were available for that URL in the selected archive. The training data matrix and the label vector became input to a neural network. A number of neural network architectures and network hyperparameters were explored, however the log entries themselves were used as-is, without any feature engineering, beyond the aforementioned normalization.

97 MATHEMATICS AND COMPUTING↗

Bunker 801 Personnel Accountability System Upgrade

The experimentation facilities at Site 300 of the Lawrence Livermore National Laboratory (LLNL) all require a reliable, real-time accounting of personnel in each facility. In smaller facilities, this is often done simply by writing a name on a board. As our facilities develop, a whiteboard methodology becomes challenging because there are many names to list at one time, and multiple entry points may exist in a facility. In many cases, a facility resident may have a significant distance to travel (including stairs) to sign in to the facility and sometimes forget to do so. Allowing a sign in at another point of entry or from a personal computer could help to alleviate this. Personnel frequently move between multiple facilities. When this is the case, it would be useful for a user to be signed off automatically if they failed to do so upon leaving a previous facility and to give an indication of their present location at other facilities. There is no official consequence to individuals who fail to sign out upon departure, however intense peer pressure is applied to bring donuts to the bunker on the following business day. Currently, no electronic sign-in systems are in place at S300.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗

How to Snowmass

Particle physics, with its reliance on shared instruments, projects spanning decades, highly international character, and research teams that range from a few individuals to thousands, has a special need for inclusive, coherent planning. In the United States in recent decades, the High Energy Physics Advisory Panel has recommended priorities to the Department of Energy and the National Science Foundation, informed in part by wide-ranging community-based studies.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Summer 2021 Internship Report

The Library Research and Prototyping team (Proto Team) under the research library explores aspects of scholarly communication, covering aspects of infrastructure, interoperability, and persistence. One of the key contributions of the team is the contribution in standardizing and forming the infrastructure for Mementos in web archiving. The Memento framework in web archiving enables access to digital resources in prior versions serving both persistence and the interoperability of the information. During the internship program, I worked on improving the Memento infrastructure by updating the memento validator. The Memento validator provides the functionality of testing the compliance of the web resources to the Memento specification. The application is intended to be used by the community at large such as web archives, researchers, librarians, and general users, with different levels of technical expertise.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗

Summer 2021 Internship Report

During this internship program, I was assigned with developing a Web application to robustify web resources referenced by links (URI-Rs) in PDFs. It was intended for use in LANL Research 2 Library systems such as RASSTI (Review and Approval System for Scientific and Technical Information), where users submit scholarly PDFs that may contain URI-Rs. For such PDFs, the application should, using Web Archives, create robust snapshots (i.e., Mementos) of the web resources referenced by URI-Rs, and notify this robustification to LANL Research Library systems. The Mementos were to be created using the Robust Links Service, and the notifications were to be sent using the Linked Data Notifications (LDN) Protocol.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗

Summer 2021 Internship Report

The internship was a 12 week program which started on 7th of June 2021. During this internship program, I worked as a Research Intern on a project which focused on feature extraction from scientific PDF documents using open-source, machine-learning-based tools.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗

Developing Bloom Filters for Web Archives’ Holdings (Final Project Report)

The main goal of the project was to develop a framework for web archives to create Bloom filters based on their holdings of archived web resources. A Bloom filter (BF) is a data structure that, in our scenario, contains hash values of all (or a subset of) URLs, of which an archive has one or more archival copies. Two main use cases fall in scope for this project and are supported by a BF implementation: 1) Sharing of an archive’s holdings (URLs) and 2) Querying the holdings of one or more archives. Since URL strings are hashed before ingested into the BF, the index of an archive is not shared in plain text when the BF is shared with trusted parties. On the other hand, a BF implementation does allow queries for a URL to confirm if an archive indeed has one or more archival copies of that URL. This collaborative project between Los Alamos National Laboratory (LANL) and the Croatian Web Archive (HAW), from the National and University Library in Zagreb (NSK), developed by NSK and University of Zagreb University Computing Center SRCE), aimed at developing software to create BFs, evaluate the scalability of the approach, pilot a search service based on BFs, and design a framework for archives to share their filters with trusted parties. In the remainder of this document, we will report on the work completed with respect to the individual deliverables, outline aspects of future work, and conclude with our recommendations for the use of BFs for the web archiving community.

97 MATHEMATICS AND COMPUTING↗

Completion of initial reduced-order model for flammable refrigerant dispersal in residential spaces

Environmental regulations aimed at reducing global warming impacts of HVAC&R refrigerants have resulted in the phase-out of chlorofluorocarbons (CFCs) in 2010 and hydrochlorofluorocarbons (HCFCs) by 2030 in developed countries with additional restrictions on the use of hydrofluorocarbons (HFCs) set to take effect in 2036. Many of the remaining alternative refrigerants that have lower global warming potential (GWP) and that are suitable for use in HVAC&R systems (e.g., propane, difluoromethane) are flammable to some degree. Flammable refrigerants introduce new challenges and hazards to property and personal safety related to potential deflagration during system maintenance or due to leakage of the refrigerant accumulating in the conditioned space. Standards have been developed to set maximum charge limits for flammable refrigerants in HVAC&R systems; however, existing safety standards and codes still restrict their use. The bodies that maintain and update these codes need publicly available, science-based information to enable credible guidelines for setting safe charge limits for different flammable refrigerants in different HVAC&R applications. In 2016, the Alliance for Responsible Atmospheric Policy, the Air-Conditioning Heating and Refrigeration Institute (AHRI), ASHRAE, the U.S. Department of Energy (DOE), and the State of California began efforts to develop such information. As part of this effort, Oak Ridge National Laboratory (ORNL) began the current, ongoing project to examine imposed charge limits for flammable refrigerants and identify reasonable adjustments to these limits when found appropriate. Past tasks under this project have included development of experimentally vetted, computational fluid dynamics (CFD) simulation approaches to study the results of leakage of flammable refrigerants from various HVAC&R systems into different types of commercial and residential spaces. In this report, we discuss recent efforts to develop a predictive model of the flammable volume fraction and accumulated refrigerant mass in a single-room residential space resulting from the leak of a flammable refrigerant from a small room air conditioning (RAC) unit. The eventual goal is development of a model suitable for public release which could simulate a range of scenarios. In discussions with the AHRTI Flammable Refrigerant Subcommittee (FRS) at the beginning of this effort, a total of 9 input parameters were chosen for consideration including room area, room/door opening area, ventilation fan flow rate, unit/leak height, leak area, leak rate, total refrigerant charge, refrigerant molecular weight, and state of the unit fan.

42 ENGINEERING↗