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DOE OSTI2026

LDRD FY25 Program Overview

As Lawrence Livermore National Laboratory’s (LLNL’s) Laboratory Directed Research and Development (LDRD) program enters its fifth decade of leading-edge research and development, its impact and importance have never been stronger. The program continues to advance strategic investments in pioneering science, technology, and engineering, ensuring LLNL will be ready to deliver on our mission as it evolves over the coming decades. Investing in LDRD research, and the people who perform this critical work, gives LLNL the ability to sustain our role as a leader in the Department of Energy and National Nuclear Security Administration enterprise. The LDRD program enables high-risk, high-payoff research that anticipates emerging threats and future mission needs. By nurturing the ingenuity of the Lab’s greatest asset, its people, LDRD funding advances not only our research but also grows and nurtures our workforce: engaging future innovators with student mentoring, challenging postdoctoral researchers to apply their skills to support national security, and strengthening the leadership skills of early career staff. This annual report documents how LDRD investments advance LLNL’s science, technology, and engineering across our mission space. To assess LDRD’s impact we track both short and long-term metrics such as peer-reviewed publications, number of students, or professional fellows. In addition to reviewing these metrics, I encourage you to delve deeper into the breadth of science and technology that illustrate the strategic value of this research portfolio. For instance, a recent exploratory research project used advanced manufacturing to construct miniaturized three-dimensional ion traps for a quantum computer with reduced quantum error rates to enable applications that address national security missions and support basic science. Another project has delved into studying detonation by examining deflagration to enhance the safety and security of the nuclear weapons stockpile. LDRD researchers are also deploying AI agents on two of the world’s most powerful supercomputers to automate and accelerate inertial confinement fusion experiments. Other teams are delivering more accurate optical constants to enable improved validation for aluminum to advance atomic and molecular physics models. LDRD-driven discoveries of how metals deform under extreme conditions strengthen our ability to model and design materials for demanding national security environments. National security challenges are increasingly complex and continuously evolving. LDRD focuses our most innovative science and technology on these challenges, ensuring the Laboratory is developing creative, forward-leaning solutions for our nation and the world. The following pages feature highlights of published scientific advances, patents, and honors that stem from LDRD investments. As you read this report, I hope you will understand how these investments position the Laboratory, and our partners, to meet the demands of the decades ahead.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Accurate Compression of Tabulated Chemistry Models with Partition of Unity Networks

Tabulated chemistry models are widely used to simulate large-scale turbulent fires in applications including energy generation and fire safety. Tabulation via piecewise Cartesian interpolation suffers from the curse-of-dimensionality, leading to a prohibitive exponential growth in parameters and memory usage as more dimensions are considered. Artificial neural networks (ANNs) have attracted attention for constructing surrogates for chemistry models due to their ability to perform high-dimensional approximation. However, due to well-known pathologies regarding the realization of suboptimal local minima during training, in practice they do not converge and provide unreliable accuracy. Partition of unity networks (POUnets) are a recently introduced family of ANNs which preserve notions of convergence while performing high-dimensional approximation, discovering a mesh-free partition of space which may be used to perform optimal polynomial approximation. In this work, we assess their performance with respect to accuracy and model complexity in reconstructing unstructured flamelet data representative of nonadiabatic pool fire models. Our results show that POUnets can provide the desirable accuracy of classical spline-based interpolants with the low memory footprint of traditional ANNs while converging faster to significantly lower errors than ANNs. For example, we observe POUnets obtaining target accuracies in two dimensions with 40 to 50 times less memory and roughly double the compression in three dimensions. We also address the practical matter of efficiently training accurate POUnets by studying convergence over key hyperparameters, the impact of partition/basis formulation, and the sensitivity to initialization.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

High-throughput ion irradiation of additively manufactured compositionally complex alloys

Several advanced nuclear reactor designs promise efficiency and safety improvements over the current reactor fleet but are limited by the current set of ASME code-qualified materials. Novel alloys including high-entropy alloys (HEAs), and more broadly compositionally complex alloys (CCAs), have shown promising irradiation-tolerance. However, the vast range of alloy compositions adds to an already time-consuming alloy development process. In this study, to accelerate the development of novel alloys for nuclear applications, a high-throughput (HTP) methodology has been employed. Additive manufacturing has been used to produce a compositional array of unary, binary, ternary, and quaternary alloys, including several CCAs, which span the Cr-Fe-Mn-Ni composition space. Additionally, the compositional array was homogenized at 1000°C for 24 hours and each sample was irradiated using 4-MeV Ni2+ ions at room temperature to a peak damage of 50 dpa, as estimated using SRIM, at the University of Wisconsin Ion Beam Laboratory. A custom XY stage was built to accommodate the large compositional array and half of each sample was masked during irradiation enabling both the irradiated and unirradiated properties of each alloy to be characterized side-by-side. Each alloy was characterized using X-ray fluorescence (XRF), X-ray diffraction (XRD), scanning electron microscopy (SEM), energy dispersive spectroscopy (EDS), and nanoindentation. CALPHAD simulations spanning the entire Cr-Fe-Mn-Ni composition space at 1000°C were performed to compare predicted equilibrium phases with phases identified experimentally from the unirradiated regions of each alloy. Nanoindentation measurements indicate radiation-induced hardening ranging from ~1-1.5 GPa in each of Cr-Fe-Mn-Ni CCAs, which is relatively insensitive to modest changes in alloy composition and comparable to hardening observed in neutron irradiated Cr-Fe-Mn-Ni CCAs in the literature. Overall, a substantial time savings was realized by employing HTP synthesis, irradiation, and characterization in this study compared to conventional techniques, the implications of which are discussed.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Impact of Spontaneous Fission Neutron Emission Energy on Neutron Detector Response

A parametric study was simulated in MCNP to investigate the impact of spontaneous fission neutron energy on neutron detector response. A total of 880 configurations were simulated by varying 3 He pressure and polyethylene reflector thickness for 8 different isotopes. Results showed that deviations between the simulated isotopes become more prevalent at higher energies with 238 U showing the greatest deviation. It was also observed that configurations comparable to most detection setups, 10 atm and 6 - 8 cm polyethylene, were closer to the upper bound of deviations from a 252 Cf. 240 Pu, a common spontaneous fission source of interest, ranged from 2% - 3% within this space. This suggests that further investigation is required to determine exact correction factors when calibrating neutron detectors with a 252 Cf. Although demonstrated here for a 4π-detection system, future plans include simulating a more detailed model of the MC-15 detection setup to determine exact correction factors for future experiments.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2022

Deterministic and Monte Carlo Nuclear Data Adjustment Methods [Slides]

For the Bayesian Monte Carlo methodology, a need to understand convergence of the posterior moments as a function of the number of parameter realizations is required. In high-dimensional systems, it can be very costly to sample entire parameter space and perform functional evaluation for every realization. Bayesian Monte Carlo allows one to relax the GLLS approximations of model linearity and prior/posterior PDF shape. The Bayesian Stochastic Collocation Method is a deterministic approach to “sample” the parameter space. It allows one to relax the GLLS approximations of model linearity and posterior PDF shape. Higher-order posterior moments (i.e., skewness, kurtosis, etc.) can be studied through polynomial expansion. Tensor product quadrature scales poorly and can use sparse grid quadrature methods.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2020

Sensitivity Studies, Gap Analysis, and Benchmark Experiment Optimization for Reactor Applications

In regards to nuclear data, some reactor applications may lack validation experiments, which reduces confidence in predicted results. This is especially true for emerging advanced reactor, micro reactor, and Accelerator Driven System (ADS) designs. This work presents an approach to design new criticality experiments that have similar k eff cross section sensitivities to an application of interest. This process involves simulations to generate cross-section sensitivities to a parameter of interest (such as k eff ), a gap analysis to determine which existing benchmarks are most similar to the application, and an experiment optimization. This work focuses on cross-section sensitives and gap analysis for three examples relevant to the reactor physics community including a Travelling Wave Reactor (TWR) type-design, Kilopower (a space reactor design), and a lead-bismuth eutectic cooled accelerator-driven system (ADS) to transmute minor actinides.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2023

A Novel Deep Reinforcement Learning Approach to Traffic Signal Control with Connected Vehicles

The advent of connected vehicle (CV) technology offers new possibilities for a revolution in future transportation systems. With the availability of real-time traffic data from CVs, it is possible to more effectively optimize traffic signals to reduce congestion, increase fuel efficiency, and enhance road safety. The success of CV-based signal control depends on an accurate and computationally efficient model that accounts for the stochastic and nonlinear nature of the traffic flow. Without the necessity of prior knowledge of the traffic system’s model architecture, reinforcement learning (RL) is a promising tool to acquire the control policy through observing the transition of the traffic states. In this paper, we propose a novel data-driven traffic signal control method that leverages the latest in deep learning and reinforcement learning techniques. By incorporating a compressed representation of the traffic states, the proposed method overcomes the limitations of the existing methods in defining the action space to include more practical and flexible signal phases. The simulation results demonstrate the convergence and robust performance of the proposed method against several existing benchmark methods in terms of average vehicle speeds, queue length, wait time, and traffic density.

42 ENGINEERING↗
DOE OSTI2022

Automated Mobility Platforms (AMPs) for Versatile, Energy Efficient, Facility and District Scale Transport

The Automated Mobility Platforms (AMPs) concept is envisioned as an on-demand network of automated lightweight electric vehicles serving mobility needs in a large facility or district-scale setting. Supplanting the function of legacy automated people mover systems, AMPs is scalable to meet the needs of moving people in large interior spaces with destinations that are too distant for walking and in which larger motor vehicles would be unfeasible or undesirable. The AMPs system is designed for automated management and operation, extending to how and where the vehicles are sent to serve mobility needs, as organized through a supervisory management system. AMPs vehicles are requested by users via smartphone app or buttons located on interactive infrastructure elements. AMPs vehicles function similarly to elevators, though in the horizontal plane, wherein users summon vehicles, and are moved point-to-point, with user requested destinations set through intuitive interfaces. The concept targets extensibility, manageability, and performance improvements over legacy technologies, with accessibility and safety features integrally designed into the system.

ADA supportive modes↗
DOE OSTI2024

Integrated Spatial, Spectral, & Temporal Optical Reflectance System for Precision Occupancy & Location Sensing to Improve Building Energy Efficiency

Buildings consume approximately 35% of the electricity used in the U.S. and building owners can significantly reduce this energy use by providing services like heating, electrical power and lighting only when people are present. The ARPAe funded program titled “INTEGRATED SPATIAL, SPECTRAL, & TEMPORAL OPTICAL REFLECTANCE SYSTEM FOR PRECISION OCCUPANCY & LOCATION SENSING TO IMPROVE BUILDING ENERGY EFFICIENCY” demonstrates how a low cost sensor technology developed for measuring distances can be used to count and locate occupants with a high degree of precision with a very low error rates. This platform tells a building control system where occupants are located (but not who they are) so that energy consuming services can be provided only when the services are needed by building occupants. The original proof of concept involved using low cost, commercially available time-of-flight (TOF) sensors that measure distance, but the performance of these existing sensors was lacking, as they could not operate properly in the presence of sunlight, which blinded the simple TOF sensors and limited their utility in buildings. This project proposed a powerful new class of TOF sensors that used state-of-the-art integrated circuit (IC) fabrication processes that combined advanced photonics with conventional silicon chip circuitry for improved sensor performance. An equally important part of this project was to find ways to maximize occupant count and location accuracy while using the fewest number of sensors possible, in order to keep costs low. By using building blueprints to create digital twins of commercial building spaces, the team developed new algorithms to maximize occupant count and tracking accuracy by properly locating the minimum number of sensors at just the right spots in the building. This capability not only minimizes system costs but also simplified sensor installation and system commissioning. Our simulations of our sensor networks for a range of commercial floorplan designs demonstrated that our installed cost target of $0.08/sqft was attainable, though not fully demonstrated during the project. Finally, we noted that the TOF sensor concept could provide a valuable role in health and eldercare by tracking patients without the need for worn sensors and would be useful for fall detection and other patient safety metrics, including tracking healthcare/patient interactions. We feel that, when fully developed, this new class of sophisticated TOF sensors and support software will be a powerful new approach to improving building energy efficiency based on occupant centric control platforms and will also open new levels of patient safety in healthcare operations. To realize this potential, the team formed the Troy Sensor Company LLC to oversee licensing of the programs patents and continue to seek commercialization of this program’s activity sensing technologies.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2024

Flavor fragmentation function factorization

A definition of partonic jet flavor that is both theoretically well-defined and experimentally robust would have profound implications for measurements and predictions especially for heavy flavor applications. Recently, a definition of jet flavor was introduced as the net flavor flowing along the direction of the Winner-Take-All axis of a jet which is soft safe to all orders, but not collinear safe. Here, we exploit the lack of collinear safety and propose a factorization theorem of perturbative flavor fragmentation functions that resum collinear divergences and describe the evolution of flavor from the short distance of jet production to the long distance at which hadronization occurs. Collinear flavor evolution is governed by a small modification of the DGLAP equations. We present a detailed all-orders analysis and identify exact relations that must hold amongst the various anomalous dimensions by probability conservation and the existence of fixed points of the renormalization group flow. We explicitly validate the factorization theorem at one-loop order, and demonstrate its consistency at two loops in particular flavor channels. Starting at two-loops, constraints on phase space imposed by flavor measurements potentially allow for non-trivial soft contributions, but we demonstrate that they are scaleless and so explicitly vanish, ensuring that soft particles are summed inclusively and all divergences are exclusively collinear in nature. This factorization theorem opens the door to precision calculations with identified flavor in the infrared.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2024

Flavor Fragmentation Function Factorization

A definition of partonic jet flavor that is both theoretically well-defined and experimentally robust would have profound implications for measurements and predictions especially for heavy flavor applications. Recently, a definition of jet flavor was introduced as the net flavor flowing along the direction of the Winner-Take-All axis of a jet which is soft safe to all orders, but not collinear safe. Here, we exploit the lack of collinear safety and propose a factorization theorem of perturbative flavor fragmentation functions that resum collinear divergences and describe the evolution of flavor from the short distance of jet production to the long distance at which hadronization occurs. Collinear flavor evolution is governed by a small modification of the DGLAP equations. We present a detailed all-orders analysis and identify exact relations that must hold amongst the various anomalous dimensions by probability conservation and the existence of fixed points of the renormalization group flow. We explicitly validate the factorization theorem at one-loop order, and demonstrate its consistency at two loops in particular flavor channels. Starting at two-loops, constraints on phase space imposed by flavor measurements potentially allow for non-trivial soft contributions, but we demonstrate that they are scaleless and so explicitly vanish, ensuring that soft particles are summed inclusively and all divergences are exclusively collinear in nature. This factorization theorem opens the door to precision calculations with identified flavor in the infrared.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2020

Novel Foaming Solutions for High Level Waste (HLW) Processing - 20195

Foaming occurs during treatment of high level waste (HLW) at Savannah River Site's Defense Waste Processing Facility (DWPF) in the Chemical Process Cell (CPC) due to high gas generation from process steam and chemical offgas products [1]. The presence of amphiphilic particles in the waste slurry stabilizes the foam [2], [3]. Efficient processing of HLW requires foam control, as foam-overs lead to lower productivity and potential radioactive contamination of condensate streams. DWPF currently employs Siovation Antifoam 747, a surfactant produced by Momentive Performance Materials, as an antifoaming agent during waste treatment. Despite its ability to control foam generation, processing issues have arisen from its use [4]. During DWPF chemical processing, a chemical antifoam agent must be effective at temperatures up to 103 deg. C between pH 3-13. Antifoam 747 is effective at pH 7 but degrades as pH deviates [5]. Antifoam 747 is 90% by weight Momentive{sup TM} L77 and 10% by weight Momentive{sup TM} Y-17580. These ingredients are trisiloxane products, which are especially vulnerable to attack in acidic and caustic environments. Since Antifoam 747 readily degrades, periodic addition is required. Several processing concerns related to Antifoam 747 have affected DWPF operation. Its overuse warranted concern of potential flammable melter offgas under upset conditions due to the generation of carbon dioxide and hydrogen. As a result, a Potential Inadequacy in the Safety Analysis (PISA) was declared [6]. Antifoam contribution has been included in the melter offgas flammability strategy and the quantity of antifoam is monitored to ensure limits are not exceeded. Testing at Savannah River National Laboratory (SRNL) determined that propanal, tri-methylsilanol, and hexamethyldisiloxane are generated as Antifoam 747 degrades, leading to a second PISA [7]. The formation of these byproducts poses additional flammability risks. Furthermore, the methyl and ethyl groups of these compounds may be responsible for the formation of the methyl and ethyl mercury discovered in DWPF [8], [9]. The formation of organomercury has specifically been called out by DOE as a need for increased research. The effectiveness of non-chemical methods for foam control and the efficiency of alternative antifoam agents were evaluated as part of an effort to improve HLW treatment operations at DWPF and to reduce, or eliminate, the flammability hazards associated with Antifoam 747 currently in use. Foaming of high-level waste (HLW) slurries is an issue at the Defense Waste Processing Facility (DWPF) Chemical Process Cell (CPC) which is currently mitigated with a chemical antifoam agent. The effectiveness of non-chemical methods for foam control and the efficiency of alternative antifoams were examined to improve HLW treatment at DWPF and to eliminate the flammability hazards associated with Siovation Antifoam 747 currently in use. Non-chemical foam control methods were deemed unviable for chemical processing at DWPF, as the spray/mist technique requires too much water and space limitations make installation and implementation of headspace agitators unfeasible. The use of ultrasonic energy thickened and further stabilized the foam. Two suitable alternative defoaming agents, Momentive{sup TM} Y- 17112 and Evonik Surfynol{sup R} MD-20, were identified. Both defoamers control foam over a pH range of 4- 13 at boiling, with no flammable degradation products, and only minimal quantities (100-200 mg/kg) are required under glycolic acid conditions. In order to validate the effectiveness of these defoaming agents, SRNL recommends irradiation testing and laboratory scale SRAT/SME experiments with actual radioactive waste. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2023

The Use of the High-density UN Fuel in Heat-pipe Microreactors

Heat-pipe microreactors (HPMRs) are very small-scale nuclear reactors that employ heat pipes for heat removal. HPMRs can be easily integrated with other forms of renewable energies, used for emergency responses to disaster relief zones, deployed in remote locations not connected to the grid, and removed from sites and replaced by new ones. HPMRs can also be used for space missions as heat pipes do not rely on gravity for heat transfer. Conventional fuel materials, such as UO 2 and UCO, are currently considered in most existing HPMR designs, but ceramic UN fuel that has high uranium density, high thermal conductivity, and a high melting point may become a better fuel candidate.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2022

Expanding Structural Space for Immunomodulatory Nucleic Acid Nanoparticles via Spatial Arrangement of Their Therapeutic Moieties

Different therapeutic nucleic acids (TNAs) can be unified in a single structure by their elongation with short oligonucleotides designed to self-assemble into nucleic acid nanoparticles (NANPs). With this approach, therapeutic cocktails with precisely controlled composition and stoichiometry of active ingredients can be delivered to the same diseased cells for enhancing pharmaceutical action. In this study, an additional nanotechnology-based therapeutic option that enlists a biocompatible NANP-encoded platform for their controlled patient-specific immunorecognition is explored. For this, a set of representative functional NANPs is extensively characterized in vitro, ex vivo, and in vivo and then further analyzed for immunostimulation of human peripheral blood mononuclear cells freshly collected from healthy donor volunteers. The results of the study present the advancement of the current TNA approach toward personalized medicine and offer a new strategy to potentially address top public health challenges related to drug overdose and safety through the biodegradable nature of the functional platform with immunostimulatory regulation.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2024

Assessment of Bird Strike Likelihood to Refine Bird Strike Risk Models

In its most basic form, bird strike risk is comprised of a frequency component that reflects the likelihood of a collision and a severity component that reflects the cost (monetary or otherwise) of the incident. The bird strike risk model currently used by United State Department of Agriculture (USDA) Wildlife Services to evaluate the risk posed by individual bird species at airports and establish priorities for management was developed in 2018. The model uses airport-specific data on the number of reported strikes for a species recorded in the Federal Aviation Administration (FAA)’s National Wildlife Strike Database as a measure of frequency and the species’ relative hazard score as a measure of severity. The model was tested against independent data, found to perform well overall, and is being implemented widely across the United States. However, the model has limitations, including that species known to pose risk to aircraft locally, but not present in the strike record database, are not reflected as a major component of risk. Standard bird survey methodology commonly used at airports (e.g. point counts or transects) potentially can be used to complement wildlife strike records to calculate frequency or relative abundance of species. However, these methods generally focus on airport-wide population estimation and often ignore vital information that contributes to the true likelihood of a strike, such as use of runway protection zones and other critical areas, and spatial and temporal overlap with departing or approaching aircraft. As such, a more detailed understanding of space use by birds across landcovers and population fluctuations across the year is needed to accurately estimate the likelihood of bird strikes at airports. In this manuscript, we will review the extant risk model, including a discussion on its limitations. We then discuss approaches for refining our understanding of strike likelihood and briefly touch on needs for estimating probability of strike severity (cost).

bird strike, aircraft collision, damage by wildlif↗
DOE OSTI2023

Enabling Structure/Interface Regulation for High Performance Ni-Rich Cathodes

Here, further commercialization of Ni-rich layered cathodes is hindered by severe structure/interface degradation and kinetic hindrance that occur during electrochemical operation, which leads to safety risks and reduced range in electric vehicles (EVs). Herein, by selecting elements with different solubility properties, a multifunctional strategy that synchronously fabricates perovskite-type SrZrO 3 coating and Sr/Zr co-doping is employed to strengthen the structure/interface stability and the Li + transport mobility of LiNi 0.85 Co 0.10 Mn 0.05 O 2 (NCM). Perovskite-type SrZrO 3 protective layers formed on the particle surface can substantially mitigate the unexpected interfacial side reactions and surface phase transitions. In addition, a robust crystal framework is constructed by optimizing local O coordination through the introduction of strong Zr-O bonds. Notably, Li + diffusion kinetics is effectively improved due to expanded cell parameters and O-Li-O slab spacing with the incorporation of large-diameter Sr pillar ions, as revealed by X-ray diffraction. As a result, the Sr/Zr-modified NCM achieves a remarkable capacity retention of 99.4% after 200 cycles at 1 C, and a high rate capacity of 168.9 mAh g -1 at 10 C. This work opens new avenues to develop high-performance NCM cathodes with high energy and high power for EVs with long calendar life.

25 ENERGY STORAGE↗
DOE OSTI2026

Integrated Transmission-Distribution Multi-Period Switching for Wildfire Risk Mitigation: Improving Speed and Scalability with Distributed Optimization: Preprint

With increasingly severe wildfire conditions driven by climate change, utilities must manage the risk of wildfire ignitions from electric power lines. During "public safety power shutoff'" events, utilities de-energize power lines to reduce wildfire ignition risk, which may result in load shedding. Distributed energy resources provide flexibility that can help support the system to reduce load shedding when lines are de-energized. We investigate a coordinated transmission-distribution optimization problem that balances wildfire risk mitigation and load shedding. We model distribution systems that include battery energy storage systems which may support loads when transmission lines are de-energized. This multi-period integrated transmission-distribution optimal switching problem jointly optimizes line switching decisions, the generators' setpoints, load shedding, and the batteries' states of charge, resulting in significant computational challenges. To improve scalability, we decompose the problem over both space and time and apply a distributed optimization algorithm. Using a large-scale synthetic California test case with realistic distribution models and real wildfire risk data, we show that distributed optimization can solve large-scale multi-period switching problems that are otherwise intractable for centralized solvers. We also discuss challenges and future directions for improving the distributed algorithm's convergence performance as the number of time periods increases.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2023

Mitigating Extremist Maritime Threats to Radiological Material Transport Vessels

The 21st century has experienced a rise in the threat of global radicalism and extremist organizations, and there has been oft-reported interest from these groups in obtaining or exploiting radiological materials. The threat of extremists acquiring radiological materials while in transit or sabotaging a transport vessel carrying materials at sea is one that requires increased attention. Transport is already one of the most vulnerable times for any cargo but including the difficulties in securing a large ship on the open ocean makes oceanic transport of radiological materials a space of elevated vulnerability for sabotage, theft, or other attacks. The risks of violent extremist attacks on trade ships and trading routes are serious, as shipping routes sustain the global economy, but an attack on a radiological transport vessel could be a magnitude worse, impacting national and international security. While radicalists have largely remained on land in the past due to minimal maritime expertise or inability to project power out of their immediate vicinity, the world has witnessed past attacks on ships such as the USS Cole and the MV Limburg and it is likely only a matter of time before groups extend further into the sea and engage in more maritime campaigns against material transport vessels. This paper suggests methods for increasing safety and security on oceanic transport voyages through behavioral science principles and insider threat recognition training, as well as a better understanding of adversarial and extremist psychology. By providing transport personnel with the knowledge and support to identify and respond to unique maritime threats by extremists, these principles and training suggestions should advance and increase security on the high seas.

Kinney, Justin↗