Science of Signatures: LANL Overview - pre recording
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Sarrao, John Louis↗
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Urban Energy Systems: Research at Oak Ridge National Laboratory
In the coming decades, our planet will witness unprecedented urban population growth in both established and emerging communities. The development and maintenance of urban infrastructures are highly energy-intensive. Urban areas are dictated by complex intersections among physical, engineered, and human dimensions that have significant implications for traffic congestion, emissions, and energy usage. In this chapter, we highlight recent research and development efforts at Oak Ridge National Laboratory (ORNL), the largest multipurpose science laboratory within the U.S. Department of Energy’s (DOE) national laboratory system, that characterizes the interactions between the human dynamics and critical infrastructures in conjunction with the integration of four distinct components: data, critical infrastructure models, and scalable computation and visualization, all within the context of physical and social systems. Discussions focus on four key topical themes: population and land use, sustainable mobility, the energy-water nexus, and urban resiliency, that are mutually aligned with DOE’s mission and ORNL’s signature science and technology capabilities. Using scalable computing, data visualization, and unique datasets from a variety of sources, the institute fosters innovative interdisciplinary research that integrates ORNL expertise in critical infrastructures including energy, water, transportation, and cyber, and their interactions with the human population.
Bhaduri, Budhu↗
Tele-Supervised Adaptive Ocean Sensor Fleet
The Tele-supervised Adaptive Ocean Sensor Fleet (TAOSF) is a multi-robot science exploration architecture and system that uses a group of robotic boats (the Ocean-Atmosphere Sensor Integration System, or OASIS) to enable in-situ study of ocean surface and subsurface characteristics and the dynamics of such ocean phenomena as coastal pollutants, oil spills, hurricanes, or harmful algal blooms (HABs). The OASIS boats are extended- deployment, autonomous ocean surface vehicles. The TAOSF architecture provides an integrated approach to multi-vehicle coordination and sliding human-vehicle autonomy. One feature of TAOSF is the adaptive re-planning of the activities of the OASIS vessels based on sensor input ( smart sensing) and sensorial coordination among multiple assets. The architecture also incorporates Web-based communications that permit control of the assets over long distances and the sharing of data with remote experts. Autonomous hazard and assistance detection allows the automatic identification of hazards that require human intervention to ensure the safety and integrity of the robotic vehicles, or of science data that require human interpretation and response. Also, the architecture is designed for science analysis of acquired data in order to perform an initial onboard assessment of the presence of specific science signatures of immediate interest. TAOSF integrates and extends five subsystems developed by the participating institutions: Emergent Space Tech - nol ogies, Wallops Flight Facility, NASA s Goddard Space Flight Center (GSFC), Carnegie Mellon University, and Jet Propulsion Laboratory (JPL). The OASIS Autonomous Surface Vehicle (ASV) system, which includes the vessels as well as the land-based control and communications infrastructure developed for them, controls the hardware of each platform (sensors, actuators, etc.), and also provides a low-level waypoint navigation capability. The Multi-Platform Simulation Environment from GSFC is a surrogate for the OASIS ASV system and allows for independent development and testing of higher-level software components. The Platform Communicator acts as a proxy for both actual and simulated platforms. It translates platform-independent messages from the higher control systems to the device-dependent communication protocols. This enables the higher-level control systems to interact identically with heterogeneous actual or simulated platforms.
Lefes, Alberto↗
Inferring Water Content from Neutron Die-away Curves for Planetary Science Applications
Signatures of liquid water on planetary bodies may provide evidence for past, present, or future life elsewhere in the solar system. Multiple current and upcoming planetary science missions are prioritizing the search for water, using innovative technologies and creative algorithms. For this project, we explore the capabilities of an instrument similar to the Dragonfly spacecraft to map water content on the surface of Titan, the largest moon of Saturn. We simulate Dragonfly’s neutron observations for a variety of soil compositions and develop multiple techniques to extract water content from the resultant neutron data. Additionally, we supplement neutron observations with gamma spectroscopy in an attempt to further refine water content estimates. This work is part of a larger study to employ Gaussian process regression to estimate a map of water content along the surface of Titan. Using the estimated map, an algorithm based on prediction difference mapping is employed to optimally move multiple Dragonfly detectors around the surface of Titan, fully autonomously.
79 ASTRONOMY AND ASTROPHYSICS↗
Development of a Multi-Sensor Data Science System Used for Signature Development on Solvent Extraction Processes in support of safeguards- an overview
A new nuclear fuel cycle test bed is being built at Idaho National Laboratory to support the purification of special nuclear material recovered from used fuel. The test bed provides an opportunity to research process flow and the application of computational tools in solvent extraction processes. A deeper understanding of process and equipment behavior coupled with real time data collection can indicate whether a process failure is accidental or purposeful. The goal of this project is to develop a system that utilizes non-traditional measurement sources such as vibration, acoustics, current, light, flow, and temperature in conjunction with data-based, machine learning techniques that will allow for signal discovery. This multi-sensor data can support the development of safeguards by design and security by design measures for such a facility. Additionally, it can aid in early detection and identification of removed materials indicating diversion, which is essential for initiating material recovery and actor identification. This overview encompasses the current research and testing of sensors to develop a spectrum of process signatures. To be followed by planned experiments aimed to characterize said signatures and study potential feature extraction techniques to identify a fault in the system (i.e. flow diversion).
98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗
DEVELOPMENT OF A MULTI-SENSOR DATA SCIENCE SYSTEM USED FOR SIGNATURE DEVELOPMENT ON SOLVENT EXTRACTION PROCESSES IN SUPPORT OF SAFEGUARDS – AN OVERVIEW (Presentation)
This presentation is for the paper INL/CON-22-65800
98 - NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL↗
Review of multi-faceted morphologic signatures of actinide process materials for nuclear forensic science
Particle morphology is an emerging signature that has the potential to identify the processing history of unknown nuclear materials. Using readily available scanning electron microscopes (SEM), the morphology of nearly any solid material can be measured within hours. Coupled with robust image analysis and classification methods, the morphological features can be quantified and support identification of the processing history of unknown nuclear materials. The viability of this signature depends on developing databases of morphological features, coupled with a rapid data analysis and accurate classification process. With developed reference methods, datasets, and throughputs, morphological analysis can be applied within days to (i) interdicted bulk nuclear materials (gram to kilogram quantities), and (ii) trace amounts of nuclear materials detected on swipes or environmental samples. In conclusion, this review aims to develop validated and verified analytical strategies for morphological analysis relevant to nuclear forensics.
36 MATERIALS SCIENCE↗
Geochemistry in support of LANL's national and energy security missions [Slides]
Geochemistery is a field of science that uses chemistry to explain processes occurring within geological systems. It can encompass interconnected fields of geology, hydrology, biology, and atmospheric science as they relate to natural processes in the environment. Geochemistry can play an important role in mission-critical LANL research areas of science of signatures and complex natural and engineered systems.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
New signature method for identifying organic material in atmosphere and water samples
The levels of plastic contamination in the earth’s oceans have steadily increased over the past century, creating a threat to marine life and increasing climate change. Several methods have been developed over the past decade to try to determine the amount and accumulation rate of plastic impurities in the ecosystem. These methods have proven promising but suffer from long measurement times, bulky non-mobile systems, and sample degradation. We propose a smaller, faster system that employs an electron beam to examine seawater samples for polyethylene contamination levels. This process generates a full electron and photon energy spectrum analyses based on the subatomic particles generated from electron interactions. Our simulations have already been developed based on the known molecular composition of seawater and polyethylene, showing the possibility of discerning molecular plastics from microorganisms. With a system the size of a suitcase, this system would be easily deployable to remote locations around the world or installed as a monitoring system for manufacturing facilities. This concept could lead to a new methodology for the science of signatures and be applied to other biological hazard investigations, such as general virus detection.
43 PARTICLE ACCELERATORS↗
Beyond sequence similarity: toward function-based screening of nucleic acid synthesis
Synthetic nucleic acids are a key input to modern biotechnology, yet they represent dual-use materials that require robust screening to mitigate biosecurity risks. The prevailing screening paradigm, which identifies sequences of concern (SoCs) through sequence similarity to controlled pathogens and toxins, may not fully capture risks posed by AI tools that can decouple biomolecular function from reliance on known sequences. Rapidly advancing biodesign capabilities enable the generation of genes and proteins that might evade sequence-based detection. We highlight the critical need for function-based screening approaches that can detect sequences capable of hazardous biological functions, regardless of similarity to known SoCs. We examine the feasibility of function-based screening with an initial focus on proteins, arguing that, while protein sequence space is vast, biologically functional proteins are significantly constrained by biophysical and biochemical requirements that can be learned and modeled. We propose a concrete implementation framework organized along a continuum of complexity, starting with toxins as the most tractable targets before expanding to more complex pathogenic functions. We then discuss open challenges and describe a research and development strategy to address them.
59 BASIC BIOLOGICAL SCIENCES↗
A Generalized Bio-inspired Method for Discovering Sequence-based Signatures
Many phenomena that we wish to discover are comprised of sequences of events or event primitives. Often signatures are constructed to identify such phenomena using either distributions or frequencies of attributes, or specific subsequences that are known to correlate to the phenomena. Distribution-based identification does not capture the essence of the sequence of behaviors and therefore may suffer from lack of specificity. At the other extreme, using specific subsequences to identify target phenomena is often too specific and suffers from lower sensitivity when natural variations arise in the phenomena, measuring process, or data analysis. We introduce here a method for discovering signatures for phenomena that are well characterized by sequences of event primitives. In this paper, we describe the steps taken and lessons learned in generalizing a sequence analysis method, BLAST, for use on non-biological datasets including expressing and operating on alphabets of varying length, constructing a reward/penalty model for arbitrary datasets, and discovering low complexity segments in sequence data by extending BLAST’s native low-complexity estimating algorithms. We also present several case studies that demonstrate the utility of this method to discovering signatures in a wide array of applications including network traffic, software analysis, server characterization, and others. Finally, we demonstrate how signatures discovered using this method can be expressed using a variety of model formalisms, each having its own relative benefit.
Signature Science↗
Chemical signatures from Mars and beyond: Science and engineering in extreme environments
No abstract provided.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Electrolytic Oxide Reduction of Plutonium Oxide Surrogates
Our research team has investigated electrolytic oxide reduction (EOR) as an improved metal production process versus the currently employed multiple cycle direct oxide reduction (MCDOR) process for the conversion of plutonium oxide to plutonium metal. Inherent advantages in safety, waste generation, efficiency, and operational ease make EOR an attractive alternative to traditional metal production practices. Phase I of the project consisted of the construction of a prototype electrochemical cell, and proof of concept experiments towards the reduction of SnO 2 and CeO 2 compounds. Phase II of the project was focused on the optimization of the cerium system in preparation for future plutonium EOR experiments. We observed the electrolytic reduction of cerium oxide resulting in mixed degrees of success, and discovered this was a result of parasitic side reactions and partial reduction. We employed cyclic voltammetry (CV) to identify the products of these side reactions and characterize partially reduced species. We also observed that, when metal was successfully produced by EOR, a large amount of passed charge was required. We concluded that this observation was due to several inefficiencies of the process relating to the reduction mechanism (e.g. inefficient use of cathodically produced calcium). We used our CV results to guide our optimization of the EOR of CeO 2 by refining our electrochemical method, cell geometry, and materials of construction. Finally, we developed a next generation cell, worked to establish a new molten salt electrochemical capability in the Plutonium Facility, and completed a strategy for plutonium experiments. Our electrochemical method to produce plutonium metal clearly supports the core mission of the laboratory. Furthermore, this project has allowed for the development of capabilities that will provide valuable data to programs interested in characterization and detection, as well as science of signatures. Additionally, establishing this capability in the plutonium facility will facilitate future safeguard studies that can assist with safeguard development in molten salt reprocessing flowsheets, and molten salt reactor designs.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Los Alamos National Laboratory Laboratory Directed Research and Development Program: FY23 Annual Progress Report- Compendium of Project Summaries
The project summaries are organized by Capability Pillar – Complex Natural and Engineered Systems, Information Science and Technology, Materials for the Future, Nuclear and Particle Futures, Science of Signatures, and Weapons Systems. Project summaries for continuing projects appear first, followed by project summaries and technical outcomes for projects that ended in FY23.
96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗
HEAO - Signature of a successful space science program
The HEAO (High Energy Astronomy Observatory) Program consists of three large automated scientific observatories launched between 1977 and 1979 to observe from near-earth orbit stellar X-ray and gamma-ray sources and to measure incoming cosmic ray particles. The HEAO-2 and HEAO-3 spacecraft are expected to exceed their design lifetimes by a factor of three, as did HEAO-1, which operated for 18 months. All three missions are considered successful in that target dates have essentially been met, launch and flight operations have been relatively smooth, instrumentation has performed well, and there have been no cost overruns. The paper lists ten factors contributing to the missions' success, among them a thorough definition before program start, commonality of spacecraft design, redundancy of mission critical equipment, ample design margins, and tight control of system changes. Specific mission parameters are included in the paper as well as the technological advances engendered by the HEAO Program in such areas as high-resolution X-ray optics and solid-state spectrometry.
Speer, F. A.↗
Novel Visual and Analytical Methods in Repurposing Legacy Scientific Code - A Case Study
Scientific computing is dominated by team-authored legacy code that has evolved over decades with the purpose of capturing the evolving understanding of a scientific discipline. Accumulated deprecated code, various optimization techniques, and evolving algorithms lead to convoluted source code that is impractical to reverse engineer using mainstream methods. This prevents codes from being truly repeatable or understandable, which are two of the most essential needs in scientific computing. We refactored a long-standing implementation of a common biosequence alignment algorithm in an effort to reproduce its salient behaviors in usable form. Because of the sheer size and complexity of this code base, we developed custom tools to visualize and manipulate the source code behavior under a variety of conditions. We present a case study of extracting and refactoring the algorithmic core and a novel process of discovery/prototyping/testing using a combination of openly available and custom-built tools. The result is a reduction in code size of over 2 orders of magnitude while reconstructing the key protein alignment function in BLAST
bioinformatics, scientific computing↗
Curating a Standardized Dataset for Statistical Biosignature Classification
In recent years, machine learning has been explored as a toolkit for planetary science and operations [Helbert, Azari]. Machine learning has been used to improve our understanding of possible biosignatures and mineral signatures to improve science return on future missions [Warren-Rhodes, Cleaves].
Biosignatures↗
Propulsive Trajectory Optimization to Minimize Surface Contamination
Descent retroburns using hydrazine thrusters will generate contaminants in their exhaust that can alter underlying samples, such as water-rich surfaces coinciding with possible life signatures or other science measurements of interest. We present an optimization technique that aims to autonomously minimize contamination during surface approach and landing for propulsive vehicles. In addition to short-range hoppers, the optimization technique is also fully applicable to traditional orbit-to-surface landers. This study addresses scenarios where surface alterations from propulsion events are counterproductive or hazardous to the mission objectives. This is of interest for landers (whether human or robotic), that may rely on pristine soils collected in the immediate vicinity of landing sites to accomplish science investigations, mining, or In Situ Resource Utilization (ISRU) surface operations. Such missions are averse to various surface-plume interactions such as thermal scoring, physical agitation, and contamination. The capability can be applied with minimal impact to the baseline concept.
Plume↗