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A Structurally-Adaptive Framework for Distributed Airborne Sensing over Real-time Collaborative Information Sharing Networks

The emergence and maturation of wireless communication technologies continue to transform the aviation industry and are enabling new solutions to challenges faced by NASA’s Advanced Air Mobility (AAM) initiative. AAM is leading towards high-density autonomous aircraft operations in areas underserved by traditional aviation, such as over densely populated urban centers. In this paper, we build on concepts from distributed sensing and smart spaces - where sensing, processing, and communication are embedded in an environment, and agents are operating within the space can exploit these capabilities in real-time through collaborative information sharing networks. Building from these concepts, we propose a framework to enable a dynamic, topologically-adaptive, and distributed estimation system for man-rated aviation to address challenges faced by autonomous AAM operations. This paper presents the initial concept of operations and system design for this framework, presents a mathematical formulation for abstraction of the problem, identifies requirements and constraints for operation, and presents algorithmic constructs to demonstrate operation. The initial framework design will focus on supporting precision navigation and independent surveillance supporting conformance monitoring of aircraft in airspace corridors and vertiport airspaces. Preliminary results from this framework shows promise in addressing gaps in current technologies needed to enable future AAM concepts, while promising greater capabilities, performance, robustness, and safety over current aviation systems and operations.

Distributed sensing↗
DOE OSTI2025

Evaluating Direct and Indirect Influence on EV Charging Stations Across the US

The adoption of new technology for electric vehicles (EV) and mobility applications can bring underappreciated vulnerabilities to the power grid. One area of potential fraud and adversarial influence is through the business ecosystem of startups that own and deploy EV technology. Yet, there are no models or analyses that map the network of organizations and people that have direct and indirect influence over technologies currently deployed in the grid. To fill this gap, we develop a multilayer network model to measure direct and indirect influence on EV charging stations. First, we create and adversarial socio-technical network (ASTN) model via a data fusion pipeline for different US regions of interest (ROI). Then, we develop an integrated ASTN for Chicago, Los Angeles, New York, and Philadelphia. We rank EV charging companies direct influence within each geographic region as well as indirect influence via social network analysis. While some companies have strong direct and indirect influence (i.e., ChargePoint) others show a mismatch between their influence over charging stations and their position within the social network. For example, Tesla has strong direct influence on stations and weak indirect influence over competitors. In contrast, 7Charge has weak direct influence over stations, but strong indirect influence over competitors.

29 - ENERGY PLANNING, POLICY AND ECONOMY↗
DOE OSTI2020

New candidates for regulated gene integrity revealed through precise mapping of integrative genetic elements

Abstract Integrative genetic elements (IGEs) are mobile multigene DNA units that integrate into and excise from host bacterial genomes. Each IGE usually targets a specific site within a conserved host gene, integrating in a manner that preserves target gene function. However, a small number of bacterial genes are known to be inactivated upon IGE integration and reactivated upon excision, regulating phenotypes of virulence, mutation rate, and terminal differentiation in multicellular bacteria. The list of regulated gene integrity (RGI) cases has been slow-growing because IGEs have been challenging to precisely and comprehensively locate in genomes. We present software (TIGER) that maps IGEs with unprecedented precision and without attB site bias. TIGER uses a comparative genomic, ping-pong BLAST approach, based on the principle that the IGE integration module (i.e. its int-attP region) is cohesive. The resultant IGEs from 2168 genomes, along with integrase phylogenetic analysis and gene inactivation tests, revealed 19 new cases of genes whose integrity is regulated by IGEs (including dut, eccCa1, gntT, hrpB, merA, ompN, prkA, tqsA, traG, yifB, yfaT and ynfE), as well as recovering previously known cases (in sigK, spsM, comK, mlrA and hlb genes). It also recovered known clades of site-promiscuous integrases and identified possible new ones.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

A Conceptual Design for a Desktop Application to Support Inventory Reconciliation Activities

This paper describes desktop software being developed at Oak Ridge National Laboratory (ORNL) to empower users to reconcile observations about items at nuclear facilities more accurately, reliably, and quickly. Inventory activities at nuclear facilities are often conducted using pen and paper, which can be time-consuming, tedious, and susceptible to reading or transcription errors. The proposed inventory assistant would be a replacement for the paper-based process that could be used by International Atomic Energy Agency (IAEA) inspectors, nuclear facility operators, or treaty verification monitors to conduct an inventory of nuclear and non-nuclear items in a more timely and accurate manner. Garner, McGirl, and Whitaker previously reported their work about a conceptual design for a mobile app to assist users in the field. In general, the inventory assistant would ingest an inventory list, distribute assigned items from the inventory list to one or more mobile devices, enable inventory teams to record their observations in the field, and then enable an inventory lead to integrate and reconcile the observations to produce a final report. The assistant consists of two software components - one for the inventory teams to record observations in the field (In-Field Observations App [IFOA]) and one for the inventory lead to (1) distribute the inventory list to each team, (2) integrate the observations from each team, and (3) reconcile the inventory list with observations (Distribution, Integration, and Reconciliation Application [DIRA]). This paper reviews the inventory assistant workflow and describes the DIRA user experience in more detail. As an example, the authors have chosen to follow the use case of IAEA inspectors conducting item counting and tag checking activities of UF 6 cylinders at a gas centrifuge enrichment plant with a large number of UF 6 cylinders (e.g., thousands). These activities can currently require 30 - 40 person-days of inspection to complete. The authors believe an inventory assistant could allow the IAEA to complete item counting and tag checking using the global identifier or the operator’s barcode in 8 - 10 person-days of inspection. We would expect other users (e.g., facility operators or treaty verification monitors) to also benefit from significant time savings.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
NASA NTRS2015

The Hopper: A Wearable Robotic Device Testbed for Micro-Gravity Bone-Loading Proof-of-Concept

Wearable robotic systems are showing increased potential for addressing crew countermeasures needs. Wearable robots offer a compactness, programmability, and eccentric loading capability not present in more conventional exercise equipment. Correspondingly, advancements in the man to machine interface has progressed, allowing for higher loads to be applied directly to the person in new and novel ways. Recently, the X1 exoskeleton, a lower extremity wearable robot originally designed for mobility assistance and rehabilitation, underwent human subject testing to assess its potential as a knee dynamometer. This was of interest to NASA physiologists because currently strength is not assessed in flight due to hardware limitations, and thus there is a poor understanding of the time course of in-flight changes to muscle strength. The study concluded that the X1 compared well with the Biodex, the "gold standard" in terrestrial dynamometry, with coefficients of variation less than 6.0%. In a following study, the X1 powered ankle was evaluated for its efficacy in exercising calf muscles. Current on-orbit countermeasures equipment does not adequately protect the calf from atrophy. The results of this study were also positive (targeted muscle activity demonstrated via comparing pre- and post-exercise magnetic resonance imaging T2 measurements), again showing the efficacy of wearable robotic devices for addressing the countermeasure needs of our astronauts. Based on these successes and lessons learned, the Grasshopper was co-developed between IHMC (Florida Institute for Human and Machine Cognition) and NASA. The Grasshopper, or the Hopper for short, is a wearable robotic device designed to address muscle and bone density loss for astronauts spending extended periods of time in micro-gravity. The Grasshopper connects to the user's torso like a hiking backpack, over the shoulders and around the waist. At the feet are footplates that strap to the user. There are two actuators, one at each "knee" joint, which are capable of high fidelity torque control. Because the Hopper uses motors instead of gravity to create the load on the user, the device is suited for use on space missions. Exercise in zero-gravity conditions is critical to maintain muscle strength and bone mass. In operation, the actuators try to fold up, or collapse, the device, putting a compressive load between the user's feet and torso. This force is similar to carrying a heavy backpack. The user then bends and extends his or her knees, replicating a weightlifting squat exercise. The applied load is precisely controlled by a computer, and can be programmed to simulate gravitation loads or any desired load prescription, such as free-weight squat exercise. It is even possible to perform eccentric exercises, or negatives, without the need for a spotter. Because the hip joints, as well as the spine and long leg bones, are in the applied load path, there is the potential to stimulate bone growth, countering the typical bone loss when astronauts return from extended duration space travel.

Beck, C. E.↗
DOE OSTI2023

Agilent AgileBioFoundry CRADA (Final Report)

The mission of this CRADA with Agilent was to couple powerful MS platforms (QQQ, IM-QTOF-MS) with Agilent’s novel Ultra-High-Performance Liquid Chromatography (UHPLC) fast metabolomic workflows and perform ABF Machine Learning (ML) to generated datasets. Agilent transferred UHPLC methods to PNNL and LBNL and methods were implemented and demonstrated in both labs, achieving total acquisition times of < 10 min. Metabolites analyzed using Agilent’s shared methods included metabolites from central carbon metabolism, common across hosts, and metabolites unique to engineered strains. Standards were acquired in an UHPLC-Drift Tube Ion Mobility Mass Spectrometer (DTIMS) system for the first time within the context of ABF and methods were optimized based on Agilent’s protocols. Samples from ABF hosts Pseudomonas putida, Aspergillus pseudoterreus, Aspergillus niger and Rhodosporidium toruloides were analyzed using the UHPLC-DTIMS platform for a total of 276 runs. A data analysis workflow compatible with the Experimental Data Depot (EDD) and completely shareable was developed for the acquired UHPLC-DTIMS data. Samples were analyzed using a Data Independent Acquisition Approach (DIA), which for most of the standards provided more transitions therefore increasing detection confidence. Using the data acquired by PNNL, LBNL, and Agilent’s specifications from previous ML projects, SNL applied an ensemble ML strategy to pick the best performing model for automated LC-method selection. Finally, with the contribution of the participant labs and Agilent, SNL developed an Automated Method Selection (AMS) software tool to predict the best liquid chromatography method for analysis of any new molecules of interest. Samples with novel pathways and new metabolite targets of interest are generated at a high pace in the ABF. Therefore, our accomplishment in this CRADA improved the efficiency and accuracy of strain testing by developing and implementing fast analytical methods, robust processing tools, and software for predicting the best methods for UHPLC analysis.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Studying information recurrence, gatekeeping, and the role of communities during internet outages in Venezuela

Many authoritarian regimes have taken to censoring internet access in order to stop the spread of misinformation, restrict citizens from discussing certain topics, and prevent mobilization, among other reasons. There are several theories about the effectiveness of censorship. Some suggest that censorship will effectively limit the flow of information, whereas others predict that a backlash will form, resulting in ultimately more discussion about the topic. In this work, we analyze the role of communities and gatekeepers during multiple internet outages in Venezuela in January 2019. First, we measure how critical information (e.g., entities and hashtags) spreads during outages focusing on information recurrence and burstiness within and across language and location communities. We discover that information bursts tend to cross both language and location community boundaries rather than being limited to a single community during several outages. Then we identify users who play central roles and propose a novel method to detect gatekeepers—users who prevent critical information from spreading across communities during outages. We show that bilingual and English-speaking users play more central roles compared to Spanish-speaking users, but users inside and outside Venezuela have similar distribution of centrality. Finally, we measure the differences in social network structure before and after each outage event and discuss its effect on how information spreads. We find that with each outage event social connections tend to get less connected with higher mean shortest path, indicating that the effect of censorship makes it harder for information to spread.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS2016

Experimental Evaluation of the Scale Model Method to Simulate Lunar Vehicle Dynamics

As compared to driving on Earth, the presence of lower gravity and uneven terrain on planetary bodies makes high speed driving difficult. In order to maintain ground contact and control vehicles need to be designed with special attention to dynamic response. The challenge of maintaining control on the Moon was evident during high speed operations of the Lunar Roving Vehicle (LRV) on Apollo 16, as at one point all four tires were off the ground; this event has been referred to as the Lunar Grand Prix. Ultimately, computer simulation should be used to examine these phenomena during the vehicle design process; however, experimental techniques are required for the validation and elucidation of key issues. The objectives of this study were to evaluate the methodology for developing a scale model of a lunar vehicle using similitude relationships and to test how vehicle configuration, six or eight wheel pods, and local tire compliance, soft or stiff, affect the vehicles dynamic performance. A wheel pod consists of a drive and steering transmission and wheel. The Lunar Electric Rover (LER), a human driven vehicle with a pressurized cabin, was selected as an example for which a scale model was built. The scaled vehicle was driven over an obstacle and the dynamic response was observed and then scaled to represent the full-size vehicle in lunar gravity. Loss of ground contact, in terms of vehicle travel distance with tires off the ground, was examined. As expected, local tire compliance allowed ground contact to be maintained over a greater distance. However, switching from a six-tire configuration to an eight-tire configuration with reduced suspension stiffness had a negative effect on ground contact. It is hypothesized that this was due to the increased number or frequency of impacts. The development and testing of this scale model provided practical lessons for future low-gravity vehicle development.

Moon↗
DOE OSTI2026

Design and simulation of a muon detector to characterize geological overburden

This study presents the design, construction, and simulation of a mobile muon detector tailored for geological overburden characterization. The detector employs plastic scintillator paddles with silicon photomultipliers (SiPMs) and a QuarkNet data acquisition system, offering a portable solution suitable for remote field deployment. The simulator’s modular aluminum frame allows for adjustable geometry and directional sensitivity, while its battery system supports over a week of autonomous operation. Preliminary experimental tests confirmed that its muon flux measurements were consistent with theoretical expectations. A comprehensive simulation framework using Geant4 and CORSIKA was developed to model detector response and overburden effects. Analytical and Monte Carlo methods were used to assess quadrant resolution and infer muon directionality. This work lays the foundation for future overburden mapping and supports the development of reconstruction algorithms for geological applications.

72 - PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
NASA NTRS2020

Solid-state Architecture Batteries for Enhanced Rechargeability and Safety (SABERS)

All-electric vertical take-off and landing vehicles (eVTOL) for urban air mobility (UAM) concepts face numerous challenging technical barriers before their introduction into the consumer marketplace. The most challenging of these technical barriers to overcome is developing an energy storage system capable of meeting the rigorous aerospace safety and performance criteria. The performance metrics for eVTOL craft, such as specific energy and cycle life, are at least 2 times greater than those of electric automobiles. Furthermore, safety is essential for operation of commercial electric aerovehicles. Preliminary systems level analysis studies have indicated that there are five key properties which must be optimized for successful implementation of battery systems. Those five key criteria are safety, energy density, power, packaging design and scalability. Current state-of-the-art (SOA) lithium-ion batteries meet or exceed the requirements for electric aviation in the areas of power and scalability, yet are insufficient in the key performance criteria of energy, safety and packaging design. The SABERS concept proposes a battery that meets all five key performance criteria through the development of a solid-state architecture cell design utilizing high energy density and power density sulfur-selenium cathode with a lithium metal anode. Data will be presented demonstrating high performing sulfur - selenium cathode that offers a balanced energy to power density ratio, which can be tailored to the specific application by altering the stoichiometric ratios of sulfur to selenium. This cathode is being developed by implementing NASA patented holey graphene technology as a highly conductive, ultra-lightweight electrode scaffold. Novel processing methods allow developing solid-state electrolyte that is a safe, non-flammable replacement to the highly flammable liquid organic electrolytes currently used in SOA lithium-ion batteries. The all solid-state lithium-sulfur-selenium cell design enables the implementation of a bipolar stack configuration, which has the advantages of reducing overall cell weight, reducing the amount of interfaced connections for the cell, and minimizing cooling requirements for the battery. In particular, the solid-state design allows for a serial stacking configuration to enable dense packaging of the cells within the bipolar stack. Lastly, optimization of battery components occurs through a robust and rigorous combination of various computational modeling techniques covering multiple length scales. The expected result will be a solid-state battery with operational temperatures from 0 °C to 150 °C which provides the required energy density, discharge rate, and inherent safety to meet strict aerospace performance criteria.

solid state batteries↗
DOE OSTI2016

Seasonal controls on dynamic hyporheic zone redox biogeochemistry

Hyporheic zones (where surface water and groundwater mix in streambeds) play a critical role in the movement of chemicals within watersheds, particularly in upland headwater streams. Seasonal hydrology controls the expansion and contraction of hyporheic zones, with greater downwelling oxic river water influence during periods of peak river discharge (linked to snowmelt), and greater influence of upwelling anoxic groundwater during periods of low- and base-flow. Through this work, we aimed to quantify upwelling and downwelling fluxes across seasons and assess the impact of these dynamics on microbial community assembly and geochemical gradients at East River, Colorado. Further, we performed high spatial resolution sampling to capture heterogeneous mixing patterns around a characteristic meander on the river and developed reactive transport models to explain seasonal patterns of manganese (Mn) cycling in riverbed sediments. We were able to measure a dominant period of downwelling river water associated with high river discharge in Spring 2017 that led to the mixing of microbial communities across a 60-cm depth profile through the riverbed at three locations around the meander, and higher rates of aerobic respiration via delivery of dissolved oxygen (O2) and dissolved organic carbon (DOC). Conversely, we demonstrated that depth-resolved microbial communities became more distinct and stratified across a depth gradient during periods of low- and base-flow when upwelling groundwater exerted more influence in the riverbed. We also observed an increase in Mn concentrations within deeper streambed sediments during the baseflow season. Reactive transport models were developed to understand seasonal changes in Mn cycling in the streambed because Mn oxides influence the mobility of other metals in streams. In field observations and models, dissolved Mn is flushed from the streambed during spring snowmelt. A shift to upwelling conditions over the subsequent baseflow period allows for groundwater rich in dissolved Mn to mix with oxygenated river water in the shallow subsurface, resulting in net accumulation of Mn-oxides until the bed freezes in winter. We also developed models for hydrograph scenarios with snowmelt events of various size and timing. Our scenarios suggest that in years with less snowpack and a longer baseflow season, Mn oxidation will be favored in the upper riverbed sediments over more of the year, which may increase the sorption capacity of the streambed for other metals. Finally, we assessed fine-scale geochemical and hydrologic heterogeneity in the meandering riverbed by sampling pore water at 20 cm depth across more than 100 locations in August 2018. Sample locations span distinct zones of up-welling groundwater that contrast against dominant down-welling conditions. Clear differences in carbon quality and concentrations of redox sensitive solutes were detected between these zones, highlighting the importance of understanding heterogeneity at small scales across streambeds. Geochemical differences were associated with differences in microbial assemblage, but microbial diversity was generally uniform and high across all locations at the same depth, regardless of the extent of groundwater influence.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2023

Computational Study of Vortex-Induced Separation for a 5-Bladed Rotor

This work computationally investigated the rotor blade vortex-induced separation recently observed during an aerodynamic rotor test campaign in the NASA Langley Research Center 14- by 22-Foot Subsonic Tunnel. Two separate approaches (i.e., airfoil modification and blade tip modification) were studied to mitigate the vortex-induced separation. Low-fidelity tools based on blade element momentum theory were shown to mispredict the rotor inflow and were also shown to not capture the vortex-induced separation caused by perpendicular blade-vortex interaction. This misprediction was exploited to isolate the aerodynamic thrust deficit caused by the vortex-induced separation (i.e., 20%) from the thrust deficit due to inflow variation (i.e., 31%). High-fidelity tools were shown to reasonably predict aerodynamic forces within 13% and flow separation when compared to experimental results. The modified airfoil variant of the baseline rotor effectively mitigated the vortex-induced separation while the blade tip modified variant still showed separation, though the size and strength of the vortex was reduced. Acoustic predictions were underpredicted by 10 dB from preliminary measurements taken in the untreated wind tunnel. Broadband noise contributions from different rotor blade sections showed that self-noise due to flow separation and other turbulent boundary layer mechanisms was the dominant noise source for all three rotor cases, followed by blade-wake interaction noise caused by perpendicular blade-vortex interactions.

aerodynamics↗
DOE OSTI2025

Zero Trust Strategies for Chemical, Biological, Radiological, and Nuclear Detection Systems: D.1 Cyber Scenarios

The evolving landscape of cybersecurity necessitates a paradigm shift to a Zero Trust (ZT) model, which assumes breaches and continuously verifies trust. This approach reshapes how trust boundaries are established, focusing on identities, devices, networks, applications, and data, rather than solely relying on perimeter defenses such as firewalls. Central to this transformation is the National Institute of Standards and Technology's (NIST) Special Publication 800-207, outlining the Zero Trust Architecture (ZTA), along with Executive Order 14028, which mandates federal agencies to adopt ZT principles. Complementary to these efforts, the Cybersecurity and Infrastructure Security Agency (CISA) developed the Zero Trust Maturity Model (ZTMM), providing a framework with five pillars and three cross-cutting capabilities to guide agencies toward enhanced cybersecurity maturity. In support of these initiatives, the DHS Countering Weapons of Mass Destruction Office (CWMD) is applying ZT principles to secure Chemical, Biological, Radiological, and Nuclear (CBRN) detection systems. Recognizing the diverse deployment models and network connectivity of these systems—from stationary, non-networked units to mobile, cloud-connected devices—the Pacific Northwest National Laboratory (PNNL) is developing cybersecurity scenarios specifically for CBRN environments. These scenarios examine various configurations and technological capabilities, offering insights into the application of ZTMM pillars in enhancing the security postures of CBRN devices. The cybersecurity scenarios presented by PNNL are hypothetical, crafted to explore theoretical situations and stimulate discussion on the potential use or compromise of CBRN detection systems in varied contexts. These narratives are illustrative and do not reference any real events or actual networks. Instead, they employ generalized reference models to highlight concepts and potential issues within CBRN security, focusing on how Zero Trust strategies can be adapted to address these challenges effectively.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗
DOE OSTI2019

Port Hope Area Initiative: Information Management for A Very Large Radiation Survey - 19567

The Port Hope Area Initiative (PHAI) represents the Government of Canada's commitment to the cleanup and safe, local, long-term management of historic low-level radioactive waste (LLRW) in two Southern Ontario municipalities - Port Hope. The PHAI is based on community-recommended solutions for the cleanup and safe long-term management of approximately 1.7 million cubic meters of LLRW. It is currently one of Canada's largest environmental remediation projects at a cost of over one billion dollars. The PHAI is being implemented by Canadian Nuclear Laboratories (CNL) on behalf of Atomic Energy of Canada Limited, a federal Crown corporation. The waste is the result of radium and uranium processing in Port Hope by the former federal crown corporation Eldorado Nuclear Limited between 1933 and 1988. The waste has been distributed in the Municipality of Port Hope through placement of contaminated materials (e.g. fill), reuse of contaminated objects (e.g. tailings use in concrete, steel posts, structural wood) and air-borne deposition. Signature contaminants of potential concern (COPCs) are Ra-226, Th-230, uranium and arsenic; however, there are an additional 17 COPCs that also need to be considered. A very large amount of information has been collected during the survey and effectively managing and analyzing this information is critical to the success for the property owners, CNL's implementation of the PHAI, and Arcadis. Data collected during the survey includes information pertaining to long-term interior radon gas measurements, interior gamma radiation surveys, contaminated objects and surfaces, exterior gamma radiation and subsurface investigations. exterior gamma radiation surveys. The information management (IM) is structured with SharePoint as a focal point supported by an EQuIS database, mobile data collection and GIS support. The IM process for this project is being advanced using recent software developments to assist with internal activities (e.g. QA) and interactions with CNL including notifications and scheduling and status of property completion. Different applications have been developed to help automate, visualize, actively track, and QA different processes using recent software developments by Microsoft. We have used SharePoint to organize and track our data. Power BI has been used to actively track and visualize our data from Interior gamma surveying to exterior drilling. The creation of dynamic/advanced visualizations in Power BI gathers data daily from our multiple sources and analyzes it for anomalous data and trends. Microsoft Flow syncs with Power BI and has been implemented to automate many processes including the QA of surveys and soil results for identification of LLRW. To tie everything together, our GIS and EQuIS systems are our primary data compilation source that makes our advanced analytics/visualization and automation/tracking our data possible. Specific examples will be discussed, as will challenges encountered during the continuing development of the IM system. The incorporation of software advancements to the existing IM system for Port Hope characterization has improved the quality of the surveys, the tracking of completion, meeting schedule requirements and providing the required data for tracking, report preparation and supporting remediation of contamination on the properties. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2020

Development of Gamma Background Radiation Digital Twin with Machine Learning Algorithms: Application of Unsupervised Machine Learning to Detection of Anomalies and Nuisances in Gamma Background Radiation Environmental Screening Data

Environmental screening of gamma radiation consists of detecting weak nuisance and anomaly signal in the presence of strong and highly varying background. In a typical scenario, a mobile detector-spectrometer continuously measures gamma radiation spectra in short, e.g., one-second, signal acquisition intervals. The measurement data is a 2D matrix, where one dimension is gamma ray energy, and the other dimension is the number of measurements or total time. In principle, gamma radiation sources can be detected and identified from the measured data by their unique spectral lines. Detecting sources from data measured in a search scenario is difficult due to the highly varying background because of naturally occurring radioactive material (NORM), and low signal-to-noise ratio (S/N) of spectral signal measured during one-second acquisition intervals. The objective of this work is to explore unsupervised machine learning (ML) algorithms for development of a digital twin of gamma radiation background, and for detection and identification of weak nuisances and anomalies events in the presence of highly fluctuating background. In one segment of work, we developed a gamma background estimation model using a Longshort term memory (LSTM) network for one-step CPS time series prediction. The LSTM model was validated with two data sets of measurements from two independent NaI detectors positioned on a mobile platform. The data sets contained background radiation only and no orphan isotope sources. The LSTM model was constructed and tested using data from one of the detectors. Performance of the LSTM model was validate through one-step prediction of CPS time series of another NaI detector without re-training. This approach allows to create a digital twin for nuclear background estimation. Using LSTM, it could be possible to detect a source through subtraction of the estimated counts from the measured background. In another segment of work, we investigated detection of gamma emitting sources in the presence of complex background using unsupervised machine learning. Spectral lines of isotopes are difficult to observe in one-second measurements. Averaging over the entire measurement campaign data set reveals spectral lines of most common background isotopes. Spectral lines of orphan sources, which might appear only in a few measurements during the campaign, will be washed out if averaging is performed over the entire measurement data set. The approach we have explored consists of extracting one-second measurements containing weak spectral features through data clustering. Averaging one-second spectra in a cluster should reveal the presence of anomaly sources. We created two ML models using K-means clustering and Neural Network Self-organizing Map (SOM). Performance of these ML models was benchmarked using search data. One data set contained 137 Cs source, and another dataset contained 131 I source.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Demand-Side Grid (dsgrid) TEMPO Light-Duty Vehicle Charging Profiles v2022

Simulated hourly electric vehicle charging profiles for light-duty household passenger vehicles in the contiguous United States, 2018-2050. Profiles are differentiated by scenario, county, household and vehicle types, and charging type. Data was produced in 2022 using the Transportation Energy & Mobility Pathway Options (TEMPO) model and published in demand-side grid (dsgrid) toolkit format. Data are available for three adoption scenarios: "AEO Reference Case", which is aligned with the U.S. EIA Annual Energy Outlook 2018 (linked below), "EFS High Electrification", which is aligned with the High Electrification scenario of the Electrification Futures Study (linked below), and "All EV Sales by 2035", which assumes that average passenger light-duty EV sales reach 50% in 2030 and 100% in 2035. The charging shapes are derived from two key assumptions of which data users should be aware: "ubiquitous charger access", meaning that drivers of vehicles are assumed to have access to a charger whenever a trip is not in progress, and "immediate charging", meaning that immediately after trip completion, vehicles are plugged in and charge until they are either fully recharged or taken on another trip. These assumptions result in a bounding case in which vehicles' state of charge is maximized at all times. This bounding case would minimize range anxiety, but is unrealistic from the point of view of both electric vehicle service equipment (EVSE) (i.e., charger) access, and plug-in behavior as it can result in dozens of charging sessions per week for battery electric vehicles (BEVs) that in reality are often only plugged in a few times per week.

Array↗
DOE OSTI2018

Review of Authentication Strategies and Trends for Distributed Energy Resources (DERs)

In this study we review literature on machine to machine (M2M) authentication and encryption pertaining to communication with grid-attached power inverters. We regard security recommendations from NIST, constrained device recommendations from CoAP, as well as influences from the existing markets. We will not focus on passwordless or multifactor schemes of user authentication, the handover/roaming authentication of mobile systems, or the group authentication of WiMAX/LTE communications. The de-facto standards for authentication and encryption are certificate-based public key cryptography and AES, respectively. While certificate-based public key cryptography is widely adopted, certificate management is seen as an Achilles heel of public key infrastructure (PKI). State of the art authentication system research includes work on certificateless authentication; however, much work in the areas of privacy preservation, efficient or lightweight systems continue to be based in public key methods. We will see efforts such as bilinear pairing, aggregate message authentication codes, one-time signatures, and Merkle trees surface and resurface with improved authentication approaches. Though research continues to produce new encryption schemes, AES prevails as a viable choice, as it can be implemented across a variety of resource constrained devices. Other lightweight encryption algorithms often employ the same fundamental addition-rotation-xor operations as AES while achieving higher efficiency, but at steep tradeoffs to security. Despite mathematical proofs of the security of cryptographic algorithms, in practice the greatest weaknesses continue to be incurred during implementation. Security researchers will find edge cases and bugs that allow unintentional behavior. In the following sections, accepted methodologies of authentication and encryption are discussed. Due diligence for securing M2M communications requires consideration during planning, design, implementation and product lifetime, as opposed to a set-it and forget-it policy. Best practices can be gleaned from published successes and failures, with no single end-all, be-all detailed solution.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

Non-Invasive Electrode Impedance Estimation for Optimized Charge Profile Parameterization of Lithium-Ion Batteries

This work presents a non-invasive method for parameterizing a physically motivated equivalent circuit model of lithium-ion batteries using operando electrochemical impedance spectroscopy and time-domain data. The proposed model consists exclusively of linear circuit elements, enabling computationally efficient simulation and real-time implementation on battery management system chips. By integrating frequency- and time-domain measurements, the model accurately estimates internal states such as the negative electrode potential, achieving a root mean square error of 12.3 mV during fast charging validation. Parameterization requires only rate tests with sinusoidal perturbations at three different ambient temperatures, making the approach experimentally accessible. The model reveals key insights into battery behavior, including rate-dependent overpotentials primarily governed by charge transfer kinetics at the positive electrode, and temperature-dependent impedance contributions from both charge transfer and solid-state diffusion processes. Validation using reference electrodes confirms the model’s ability to detect lithium plating onset and reproduce impedance behavior across a wide range of operating conditions. The approach enables in situ optimization of fast charging profiles and lays the foundation for future extensions incorporating aging effects and plating dynamics.

25 ENERGY STORAGE↗