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At least 667 records · Page 37

IER 500: AWE-LLNL Measurement Campaign at DAF [Slides]

Presentation Hosted at Device Assembly Facility (DAF). Joint collaboration by Atomic Weapons Establishment (AWE) and Lawrence Livermore National Laboratory (LLNL). Multiple measurements were recorded through a two-week period with 12 unique objects measured. LLNL deployed Machine learning software program for diagnostic assessments. Current status notes the dedicated DAF team LLNL maintains. Additionally, LLNL is compiling a report on the AWE-LLNL measurements and designing security benchmark experiments. The presentation concludes with future work envisioned.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Resilient GaN-based Power Module with Improved Diagnostic for Future Accelerator

Los Alamos Neutron Science Center (LANSCE) and Dual-Axis Radiographic Hydrodynamic Test facility (DARHT) play a pivotal role in advancing scientific research and national security initiatives. As a premier facility for neutron science, LANSCE and DARHT provide invaluable insights into fundamental research, materials science, nuclear physics, high-energy physics, material science, and medical imaging. Existing (DC) power supply and pulse modulation technologies used in LANSCE and DARHT face limitations in terms of reliability, maintainability, and diagnostics which hinder the progress of these cutting-edge facilities. By proposing improvements to LANL accelerator facilities’ performance and addressing component failure, we aim to enhance scientific outcomes and minimize disruptions, allowing for more efficient and productive research activities while ensuring the continuity of valuable contributions to the user community. This proposal aims to revolutionize (DC) power supply and pulse power systems for future particle accelerators via the development of a resilient GaN-based power module with improved diagnostic and redundant submodules.

43 PARTICLE ACCELERATORS↗

Idaho National Laboratory Water Assessment

Established in 1949, Idaho National Laboratory (INL) is part of the U.S. Department of Energy’s (DOE) complex of national laboratories. INL performs work in each of the strategic goal areas of the department: energy, national security, science, and environment, and is the nation’s center for nuclear energy research and development. Located in southeastern Idaho, its physical footprint includes 569,180 acres of federally owned land. A water balance for the fiscal year (FY) 2022 year was conducted for INL to identify major water using equipment and calculate the end-use categories. FY 2022 was selected as the evaluation year per the DOE Sustainability Performance Office. This report provides an analysis of facilities on the INL Site operated by Battelle Energy Alliance, LLC (BEA). This water balance report focused on the Advanced Test Reactor (ATR) Complex, Materials and Fuels Complex, Idaho Falls campus, and Central Facilities Area campuses, which consumed 98% of the 540,611 thousand gallons (kGal) of water used by INL in FY 2022. The resulting water balance identified the use categories for 75.3% of the FY 2022 water consumption.

99 GENERAL AND MISCELLANEOUS↗

An overview of SAFENET and its implications for aerospace applications

The survivable, adaptable fiber optic embeddable network (SAFENET) is a draft standard for local area networking (LAN) developed by the Navy which, when adopted, will become a military standard. The standard is being developed for procurement specifications of computer resources to be used on ships and aircraft and has some of the real-time concerns that network standards for space vehicles have. Architecture and survivability are considered. It is noted that the token-ring LAN must implement the IEEE 802.5 recommended practice for dual ring reconfiguration, which is currently being reviewed for inclusion into the IEEE standard. A trunk coupling unit is used at each station to isolate a station from the ring in case of failure. Up to five stations can be bypassed in this fashion. Communication architecture has an OSI profile but differs from the standard concept of the seven layers by allowing alternate suits and breaking the layers into three groupings of services to allow for physical interfacing. It also provides several paths, even if only one profile is used. Management and synchronization protocols are discussed and security issues are addressed. Implications for aerospace applications are considered and it is projected that interoperability with the Navy and other U.S. Government systems may require SAFENET specifications for NASA systems.

Collins, George C.↗

Pyroelectric Materials for Uncooled Infrared Detectors: Processing, Properties, and Applications

Uncooled pyroelectric detectors find applications in diverse and wide areas such as industrial production; automotive; aerospace applications for satellite-borne ozone sensors assembled with an infrared spectrometer; health care; space exploration; imaging systems for ships, cars, and aircraft; and military and security surveillance systems. These detectors are the prime candidates for NASA s thermal infrared detector requirements. In this Technical Memorandum, the physical phenomena underlying the operation and advantages of pyroelectric infrared detectors is introduced. A list and applications of important ferroelectrics is given, which is a subclass of pyroelectrics. The basic concepts of processing of important pyroelectrics in various forms are described: single crystal growth, ceramic processing, polymer-composites preparation, and thin- and thick-film fabrications. The present status of materials and their characteristics and detectors figures-of-merit are presented in detail. In the end, the unique techniques demonstrated for improving/enhancing the performance of pyroelectric detectors are illustrated. Emphasis is placed on recent advances and emerging technologies such as thin-film array devices and novel single crystal sensors.

Aggarwal, M. D.↗

TRIM: AI Guided Random Number Generation for Resource-Constrained IoT Systems

Random numbers often serve as the backbone for many security solutions in diverse domains such as cryptography, side channel leakage prevention, and moving target defense. However, generating true random numbers requires a physical source of entropy (e.g. hardware, quantum, environmental phenomenon) making it difficult to realize at a large scale and at a low cost. On the flip side, pseudorandom number generators (easy to implement) following a specific distribution (e.g. Gaussian) can be easily compromised given a sufficient amount of traces. In this work, we have developed a machine learning-guided generative approach that can be used to create portable, resource-efficient, and cost-effective random number generators with high throughput and true randomness characteristics. We implement the proposed approach as a highly parameterized framework and perform extensive evaluation for different settings. The framework was able to learn from true random sources such as irrational numbers and environmental audio noise and imitate those sources towards generating new good quality random numbers on demand. We have generated more than 1 billion bits and observed robust performance in terms of true randomness metrics obtained from NIST SP 800-22 and FIPS 140-1 randomness test suites achieving a throughput of up to 142.85 Mbps. Compared to the state-of-the-art (SOTA) technique, the iso-cost setup of our framework can achieve more than 500 Mbps in a distributed setting. We have evaluated the efficacy of running the true randomness imitation AI models on target edge devices such as Raspberry Pi 4 (Model B), Nvidia Jetson Nano, Nvidia Jetson Orin Nano and Nvidia Jetson Xavier. We have also looked at the security of the TRIM framework itself against different adversarial threat models.

Cybersecurity↗

EVALUATING NUCLEAR SECURITY IMPLICATIONS OF THE SPLINTERNET

The internet, which for years has been viewed as a global online commons with standardized protocols but few regulations is, according to some experts, starting to mirror the contentious political and commercial contours of the physical world. Contributing to this is the rise in data breaches, cyber-enabled attacks on critical infrastructure, government surveillance operations, theft of intellectual property, manipulation of electoral processes, and perceived erosion of privacy, all of which are resulting in a growing skepticism that an open internet will naturally serve the best interests of users, communities, countries, and the global economy. In addition, the rapidly emerging and increasingly lucrative power of data has global superpowers scrambling to protect their informational sovereignty as an urgent matter of national security. Underscoring this urgency is the fact that, despite its global reach and cosmopolitan contributor base, internet infrastructure and governance of the World Wide Web remain largely under U.S. corporate auspices, which reinforces the perception of U.S. control. Whether fragmentation is politically, economically, or socially motivated, there appears to be a growing appetite for an internet that is partitioned and controlled at the national level. From “the Great Firewall of China” to the “Halal” internet of Iran, the trend towards a “Splinternet” has courts and governments embarking on what some call a "legal arms race" to impose a maze of national or regional rules, often conflicting, in the digital realm. The paper explores the emerging Splinternet phenomenon, analyses the implications of this trend on nuclear security, and identifies questions that present opportunities for future research.

Internet, Data Security, Cyber Security, Nuclear S↗

Multi-Game Modeling for Counter-Smuggling

International trade provides an avenue for terrorists to smuggle illicit materials into a target country. Policymakers need models and decision support tools that are both reliable and germane to inform their responses to this. Game theoretic approaches have been used in the analysis of counterterrorism strategies, but the models involved have often been small and abstracted. To address this need, we have developed a multi-game model to account for both security-related and economic aspects of counter-smuggling interdiction efforts. Additionally, we use different games to represent different types of interactions, and these games are then coupled to each other to form an integrated model. In this paper, we demonstrate the model's capabilities on a representative system of ports (both foreign and domestic), trade routes, and commodities. We specifically investigate the impacts of changes in screening policies at domestic ports, detection device capabilities, shipping subsidies, and worldwide corruption levels. In these studies, we find that economic factors play a large role in the interdiction task and provide correspondingly important tools for deterrence.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗

Project DarkStar: Vision for LLNL in 2030

DarkStar was a Strategic Initiative (FY2021-FY2024) to investigate applications of Artificial Intelligence (AI) and Machine Learning (ML) to scientific problems of complex hydrodynamics, shockwave physics and energetic materials. The research focused on physics and engineering design as a process that can be tremendously accelerated through merging AI with advanced physics simulation on exascale-class platforms, and to experimentally validate this revolutionary new approach through dynamic materials campaigns. A central thread of scientific inquiry was in the application of AI to enable human understanding of how to control hydrodynamic instability (which has impacts to areas such as inertial confinement fusion) via engineering features and time-dependent sources. Motivated by an unfinished line of research started by Dr. Johnny von Neumann, AI-enabled simulation approaches were developed that allowed DarkStar researchers to uncover several ground-breaking discoveries regarding hydrodynamic instability, including how to completely suppress Richtmyer-Meshkov instability (RMI). These S&T discoveries, along with other advances, have shown the way for an entirely new approach to time-dependent problems known as inverse design – the idea that complex systems can be developed directly from a final state that is to be achieved and resolve the initial design via satisfying several constraints simultaneously via AI/ML. Through experimental campaigns conducted across a wide range of facilities in the NNSA complex (the High Explosive Application Facility at LLNL, the Dynamic Compression Sector/Advanced Photon Source at Argonne National Lab, and Special Technologies Laboratory at MSTS) the radical new AI/ML approach to engineering complex material dynamics was verified, establishing a new field of study within the realm of shock physics. As advanced manufacturing capabilities continue to develop, the great importance of inverse design as a means to apply that technology effectively for NNSA missions will feature prominently over this decade. DarkStar has positioned NNSA as a world-leader in this newly emerging cross-disciplinary area of AI methods for advanced physics simulation and pioneered multiple novel approaches that have enabled the broader scientific community. By allowing us to see past the horizon, to 2030 and beyond, DarkStar has illuminated the vast potential of AI/ML to impact a wide range of new national security missions and, consequently, multiple areas of further research have already emerged across the NNSA and DOD complex.

42 ENGINEERING↗

Quantum materials for nanosensing and fault-tolerant quantum computing

New concepts of symmetry related to topological order emerged from the discovery of the fractional quantum Hall effect and high-temperature superconductivity in strongly correlated electron systems. This led to the study of quantum materials-- materials exhibiting emergent quantum phenomena with no classical analogues. While these materials have engendered exciting basic materials science and physics, realizing novel devices is a key challenge in the field. The goal of this proposal is to harness the unique properties of topological materials for quantum computing and quantum sensing applications. In this project, we investigated a variety of topological superconducting platforms and identified three technologies that can benefit from their quantum properties: quantum memory, single-photon detection, and non reciprocal electronics. The platforms developed in this work will be broadly useful to National Security and Basic Science.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

System Security Authorization Agreement (SSAA) for the WIRE Archive and Research Facility

The Wide-Field Infrared Explorer (WIRE) Archive and Research Facility (WARF) is operated and maintained by the Department of Physics, USAF Academy. The lab is located in Fairchild Hall, 2354 Fairchild Dr., Suite 2A103, USAF Academy, CO 80840. The WARF will be used for research and education in support of the NASA Wide Field Infrared Explorer (WIRE) satellite, and for related high-precision photometry missions and activities. The WARF will also contain the WIRE preliminary and final archives prior to their delivery to the National Space Science Data Center (NSSDC). The WARF consists of a suite of equipment purchased under several NASA grants in support of WIRE research. The core system consists of a Red Hat Linux workstation with twin 933 MHz PIII processors, 1 GB of RAM, 133 GB of hard disk space, and DAT and DLT tape drives. The WARF is also supported by several additional networked Linux workstations. Only one of these (an older 450 Mhz PIII computer running Red Hat Linux) is currently running, but the addition of several more is expected over the next year. In addition, a printer will soon be added. The WARF will serve as the primary research facility for the analysis and archiving of data from the WIRE satellite, together with limited quantities of other high-precision astronomical photometry data from both ground- and space-based facilities. However, the archive to be created here will not be the final archive; rather, the archive will be duplicated at the NSSDC and public access to the data will generally take place through that site.

Source record↗

A Roadmap for a Lightning Modeling Grand Challenge

This document is a roadmap for building an interconnected model of the physical processes that produce a lightning discharge, and its observable optical and radio signals. We call this a Lightning Modeling Grand Challenge, recognizing that significant effort and coordination of human and financial resources is required to realize the capability. The roadmap serves to outline the coordination of resources necessary to enable stitching together existing knowledge and model components to make a lightning prediction, and to test these predictions with observations. Such a capability does not currently exist. The roadmap is motivated not only by a spirit of scientific inquiry, but by practical challenges faced by US Federal and societal stakeholders. Advancements in lightning observations have outpaced our tests of integrated understanding, leaving many stakeholders unsure how to design their missions to properly detect and discriminate lightning, and unsure how to apply the sometimes-disagreeing lightning signals from diverse instruments. The time is right to connect existing theories and models to support stakeholders in understanding the signals they observe, for needs as diverse as climate monitoring, national security, weather forecasting, public safety, and protection of natural and built environments. The roadmap’s two main technical sections describe the components of a linked physical model, followed by a description of models of lightning signals and sensors that are driven by outputs from the physical model. The goal is to predict the time-varying physical properties of lightning that are self-consistent with the thunderstorm’s structure and dynamics. These lightning signals then propagate through the storm, with realistic dispersion and attenuation, to receivers on the ground or in space. At a high level, the model begins with weather (cloud) model output, including explicit prediction of the electrification of cloud particles. The cloud’s electrical structure drives a model of lightning physics, from initiation, through channel development, and discharges along those channels. Key lightning parameters, such as the temperature and currents in the channel, and their space and time distribution, are then used to produce optical and electromagnetic signal sources that propagate to modeled receivers. This architecture therefore generates a dataset suitable for comparison to existing and envisioned observing systems. The need for additional measurements and field campaigns to support model development is described. In each model sub-component, inputs, outputs, uncertainties, evaluation methods, and next steps are summarized, interleaved with references to the scientific literature. Identifying boundaries between the model sub-components aids in segmenting an integrated, complex model into practical work packages and system sub-components, allowing a diverse team to contribute and maintain the system. We estimate that at least five years of effort and a $\$$10M initial investment is necessary to make a significant step forward. Mechanisms to facilitate community coordination, including annual workshops and open-source code repositories, are described.

54 ENVIRONMENTAL SCIENCES↗

Towards generic memory forensic framework for programmable logic controllers

A Programmable Logic Controller (PLC) is a microprocessor-based controller that is used to automate physical processes in critical infrastructure and various other industries and manufacturing sectors. Initially, PLCs were completely isolated from the Internet, and cyber security was not incorporated at the time of development. The introduction of industry 4.0 and the evolution of ICS systems to communicate over public IP addresses from the Internet enhanced productivity and efficiency, but Internet connectivity exposed the systems and their vulnerabilities, which led to an increase in cyber attacks. When a system is sabotaged/compromised, security analysts need to get to the root cause of the attack as quickly as possible to recover the system. To do so, memory forensic analysis is critical to provide a unique insight into the run-time memory activities and extract a reliable source of evidence. In this paper, we analyze the memory structure of the Schneider Electric Modicon M221 PLC. To build a memory profile, we reverse engineer the communication protocol and conduct differential analysis to gain knowledge about the structure of the memory and the low-level representation of control logic instructions. We then identify dynamic and static memory regions by modifying different project fields and conducting differential analysis, which allows us to identify boundaries of critical memory structures and extract important forensic artifacts that can be found in the memory. The Python implementation of the memory profile can help reduce the time and effort required for manual analysis in case of cyber incident or system failure.

97 MATHEMATICS AND COMPUTING↗