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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 127 records · Page 7

Design of an Axial Flux Machine With an Integrated Hydraulic Pump for Off-Highway Vehicle Electrification

Axial flux machines offer an inherent torque density advantage over conventional radial flux machines and are increasingly being considered for transportation electrification applications. Electrification of off-highway vehicles is notoriously challenging due to extreme power density requirements. This paper investigates the use of axial flux machines for off-highway vehicle electrification. To maximize the power density, a hydraulic pump is integrated with the axial flux machine, resulting in a single modular, electric/hydraulic machine. This paper first compares three popular axial flux machine variants using an FEA-based design optimization approach. The single rotor, single stator variant is identified to be the most promising for integration with the hydraulic pump. Next, a multi-physics framework of the complete integrated hydraulic pump and axial flux machine is developed to search the design space. The results indicate promising potential for this concept to realize efficiency over 85% and power density over 5kW/kg for the complete machine (electric machine, hydraulic pump, and thermal management system), while utilizing conventional materials (thin gauge silicon steel, N45 magnets, and magnet wire)

Off-highway vehicles, Axial flux machines, Multi-p↗

High Power Density, Carbon Neutral Electrical Power Generation for Air Vehicles

The synergistic integration of a Solid Oxide Fuel Cell-Combustor (SOFC-C) with a turbogenerator (TG) will provide a very high fuel-to-electricity conversion efficiency while maintaining high power-to-weight ratio during high-altitude flight. The proposed SOFC-C-TG power generation technology exceeds the REEACH technical performance targets (TPT). This unique concept addresses many of the challenges faced in all electric propulsion-based aviation. The system has high part-load efficiency (more than 65% lower heating value (LHV)) during long cruise times, load following capability, high-power capacity at high altitudes adapting to low temperatures and pressures, rapid startup time of less than 30 minutes (proven with current SOFC technology), high power density (more than 3.2 kW/kg), efficient thermal management, and a foundation for a compact, efficient electrical storage and power generation system (ESPG). The SOFC-C concept achieves the technology targets by reducing the complexity of traditional fuel cell-gas turbine hybrid systems (FC-GT). The SOFC-C does not require heat exchangers and dramatically reduces the balance of plant increasing power density and performance in efficiency. The reduction in mass through elimination of heat exchangers, external reformer, and other components dramatically decreases the overall thermal dampening of the system which enables rapid startup and load following capability. Direct control of the cathode inlet temperature of the SOFC-C enables rapid warm-up of the SOFC tubes with the ability to reach operating temperature and full power in less than 30 minutes.

03 NATURAL GAS↗

A Novel Three-Phase Oak Ridge AC / DC Converter for Wireless EV Charger Applications

In this paper, a novel three-phase converter is proposed for ac to dc wireless power transfer (WPT) systems for electric vehicle (EV) charging applications. The proposed innovative solution, called as Oak Ridge Converter, reduces the design complexity and cost by eliminating the front-end converter stage compared to the conventional systems. Additionally, grid side requirements can be met with the proposed creative concept. In this concept, the three-phase single-stage Oak Ridge Converter directly converts the 60 Hz grid frequency into high-frequency voltage and utilizes hybrid grid-source and high-frequency to realize power transfer from AC source through resonant network and coupling coils to the battery load. Simulation validation of the proposed three-phase system is currently being carried on and the results will be will be provided to validate the theoretical studies with the input of 277 VAC,RMS and output of 675 VDC at 35 kW power. The system current total harmonic distortion (THD) is measured 5% with a power factor (PF) of 0.98 and overall hardware development of the system that will be used for experiments is presented.

Asa, Erdem↗

Integrated Optimization of Powertrain Energy Management and Vehicle Motion Control for Autonomous Hybrid Electric Vehicles

Hybrid Electric Vehicles (HEVs) and autonomous vehicles have been widely studied recently for on-road transportation. In the study of autonomous HEVs, the control of the vehicle's external dynamics and powertrain dynamics are often treated separately. Optimizing these two problems together can significantly improve fuel economy. In this paper, an autonomous HEV following a leader is considered. First, the augmented model to integrate the abovementioned dynamics is presented. Second, the optimization problem is defined to find the optimum fuel consumption of the follower in pursuit of a leader in a drive cycle. A customized control strategy based on Approximate Dynamic Programming (ADP) is then explored in which the optimal cost-to-go at each time step is approximated using neural networks. Also, the accuracy of the optimization solution is enhanced by applying the concept of the reachable sets. At last, three case studies show that the examined integrated control strategy outperforms the one with the separated optimization method by an additional 7.4%, 4.6%, and 11.8% improvement in fuel consumption, respectively.

33 ADVANCED PROPULSION SYSTEMS↗

Development and Demonstration of a Fuel-Efficient, Class 8 Tractor & Trailer Engine System (SuperTruck II)

Navistar presents the SuperTruck II (ST II) Final Report to the Unites States Department of Energy (US DOE), which covers the five Budget Periods (BPs) from 10-1-2016 through 6-30-2022. For ST II, Navistar built on the achievements of the SuperTruck I (ST I) Program as a catalyst to continue critical research, design and development, testing, and operations to reach the ambitious goals of the ST II project. This approach allowed Navistar to continue contributing to the essential needs of our nation for safe, efficient, and cost-effective delivery of goods and services, as we reduced negative environmental effects and improved operational productivity. This document contains information specified in DOE F 4600.2, Final Scientific/Technical Report DOE F 241.3, B. SCIENTIFIC/TECHNICAL REPORTS, explaining how we met and exceeded program requirements. Throughout this Final Report, Navistar extracted information from documents prepared during the project that represent our management, design and development, building, and testing efforts to meet and exceed SuperTruck II project goals. Navistar followed Plan requirements to achieve / exceed Project Objectives: a) >100% improvement in vehicle freight efficiency (FE) (on ton-MPG basis) relative to 2009 baseline with stretch goal of 140% improvement [actual: 170%); b) >55% engine brake thermal efficiency (BTE) demonstrated in operational engine at a 65-mph cruise point on a dynamometer – ≥31% increase from 2009 baseline [actual: 55.20% of combined BTE) ; and c) development and implementation of commercially cost effective technologies (in terms of a simple payback). Technology selection / development path focused on developing technologies applicable for production within 3-year approach, while ensuring technology readiness and cost of ownership for end users. The Program was organized into five budget periods: Requirements / Technology Assessment and Initial Hardware Testing; Technology Development and Concept Readiness Demonstration; Technology Finalization and Validation Tractor / Trailer Fabrication, Integration and Commissioning Demonstration; and Fuel Economy (FE) and Brake Thermal Efficiency (BTE) and Program Completion. Leadership was provided by DOE, with tasks performed by laboratories (Argonne National Laboratory, Lawrence Livermore National Laboratory); partners at Bosch, TPI, Dana, and J.B. Hunt; , and support from University of Michigan and Clemson University. Navistar lead this team with Principal Investigator / Contracting Officer; Project Manager (PM); Vehicle, Engine, and Aftertreatment Engineers; Finance Manager, Technical Program Leads, and Legal/IP; and other key personnel. Work also included personnel in risk management; funding / budget / finance. Work involved analysis, development, testing, and down selection of individual/system engine, aftertreatment, and vehicle technologies, with integration of selected technologies into a prototype vehicle for demonstration of fuel-efficiency gain. Work also included component/integrated system level development of truck and trailer aerodynamics, base engine efficiency, advanced aftertreatment, combustion efficiency, waste heat recovery, hybrid powertrain, reduced rolling resistance, weight reduction, idle reduction, and driver feedback. As ST II progressed, Navistar performed computer-based modeling / simulations of technologies focused on the primary operational areas: Engine, Aftertreatment, and Vehicle. During the ST II Program, the COVID Virus outbreak unexpectedly challenged by the effects of, which affected staffing, scheduling, design, supplies, availability of materials, production procedures, and testing. The DOE responded by extending the program by three quarters to ensure that project tasks were completed for this vital project. Focus continued on analyzing, developing, testing, and down selecting individual-/system-level engine and vehicle technologies for integration of the final selected technologies into a prototype vehicle that would demonstrate fuel-efficiency gains made possible through these technologies. This included component/integrated system-level development of truck and trailer aerodynamics, base engine efficiency, advanced aftertreatment, combustion efficiency, waste heat recovery, solar power, distributed and intelligent vehicle power, hybrid powertrain, reduced rolling resistance, weight reduction, idle reduction, and driver feedback. Throughout the program, function, reliability, and performance at all levels were ensured through testing. Proof of this approach was demonstrated in multiple, on-road demonstrations: Scenario A (Flatland) Fuel Economy, Scenario B (Hilly) Fuel Economy, and City Cycle Tests. Other benefits derived from ST II included new/improved products, publications, patents, and next-step capabilities related to electric/hydrogen vehicles and autonomous driving.

Zukouski, Russ↗

Detecting CAN Masquerade Attacks with Signal Clustering Similarity

Vehicular Controller Area Networks (CANs) are susceptible to cyber attacks of different levels of sophistication. Fabrication attacks are the easiest to administer—an adversary simply sends (extra) frames on a CAN—but also the easiest to detect because they disrupt frame frequency. To overcome time-based detection methods, adversaries must administer masquerade attacks by sending frames in lieu of (and therefore at the expected time of) benign frames but with malicious payloads. Research efforts have proven that CAN attacks, and masquerade attacks in particular, can affect vehicle functionality. Examples include causing unintended acceleration, deactivation of vehicle’s brakes, as well as steering the vehicle. We hypothesize that masquerade attacks modify the nuanced correlations of CAN signal time series and how they cluster together. Therefore, changes in cluster assignments should indicate anomalous behavior. We confirm this hypothesis by leveraging our previously developed capability for reverse engineering CAN signals (i.e., CAN-D [Controller Area Network Decoder]) and focus on advancing the state of the art for detecting masquerade attacks by analyzing time series extracted from raw CAN frames. Specifically, we demonstrate that masquerade attacks can be detected by computing time series clustering similarity using hierarchical clustering on the vehicle’s CAN signals (time series) and comparing the clustering similarity across CAN captures with and without attacks. We test our approach in a previously collected CAN dataset with masquerade attacks (i.e., the ROAD dataset) and develop a forensic tool as a proof of concept to demonstrate the potential of the proposed approach for detecting CAN masquerade attacks.

Moriano Salazar, Pablo↗

Digital Twinning and Predictive Modeling of Traffic for Safe, Efficient, and Reliable Intersections

Over the last decade, the advances in connected and autonomous vehicles (CAVs) have far surpassed the technological realm of transportation infrastructure. There is a growing need to have a technologically commensurate transportation infrastructure to enable safe and reliable movement of goods and people. The recent creation of Advanced Research Projects Agency - Infrastructure (ARPA-I) through the Infrastructure Investment and Jobs Act by the U.S. Department of Transportation (USDOT) has further amplified the need to revolutionize the transportation infrastructure system in the US. This need is perhaps felt most at traffic intersections, as more than 50 percent of the combined total of fatal and injury crashes occur at or near intersections. The proposed concept of Infrastructure Perception and Control (IPC) is aimed at bridging this technological gap by building a real-time digital twin of traffic by fusing detections from sensors installed at the intersection. This digital twin can then empower a wide variety of applications such as smart traffic signals or infrastructure-to-everything (I2X) communications. Smart signaling can help avoid crashes through early-prediction, while I2X can augment the CAV sensors under uncertain driving conditions and provide connected vehicles (CVs) with traffic information they can use to optimize their travel.

connected vehicles↗

The Technical and Economic Potential of the H2@Scale Hydrogen Concept within the United States

The U.S. energy system is evolving as society and technologies change. Renewable electricity generation - especially from wind and solar - is growing rapidly, and alternative energy sources are being developed and implemented across the residential, commercial, transportation, and industrial sectors to take advantage of their cost, security, and health benefits. Systemic changes present numerous challenges to grid resiliency and energy affordability, creating a need for synergistic solutions that satisfy multiple applications while yielding system-wide cost and emissions benefits. One such solution is an integrated hydrogen energy system. This is the focus of H2@Scale - a U.S. Department of Energy (DOE) initiative led by the Office of Energy Efficiency and Renewable Energy’s Hydrogen and Fuel Technologies Office. H2@Scale brings together stakeholders to advance affordable hydrogen production, transport, storage, and utilization in multiple energy sectors. The H2@Scale concept involves hydrogen as an energy intermediate. Hydrogen can be produced from various conventional and renewable energy sources including as a responsive load on the electric grid. Hydrogen has many current applications and many more potential applications, such as energy for transportation - used directly in fuel cell electric vehicles (FCEVs), as a feedstock for synthetic fuels, and to upgrade oil and biomass - feedstock for industry (e.g., for ammonia production, metals refining, and other end uses), heat for industry and buildings, and electricity storage. Owing to its flexibility and fungibility, a hydrogen intermediate could link energy sources that have surplus availability to markets that require energy or chemical feedstocks, benefiting both. This document builds upon a growing body of analyses of hydrogen as an energy intermediate by reporting the results from our initial analysis of the potential impacts of the H2@Scale vision by the mid-21 st century for the 48 contiguous U.S. states. Previous estimates have been based on expert elicitation and focused on hydrogen demands. We build upon them, first, by estimating hydrogen’s serviceable consumption potential for possible hydrogen applications and the technical potential for producing hydrogen from various resources. We define the serviceable consumption potential as the quantity of hydrogen that would be consumed to serve the portion of the market that could be captured without considering economics (i.e., if the price of hydrogen were $0/kg over an extended period); thus, it can be considered an upper bound for the size of the market. We define the technical potential as the resource potential constrained by real-world geography and system performance, but not by economics. We then compare the cumulative serviceable consumption potential with the technical potential of a number of possible sources. Second, we estimate economic potential: the quantity of hydrogen at an equilibrium price at which suppliers are willing to sell and consumers are willing to buy the same quantity of hydrogen. We believe this method provides a deeper understanding than was available in the previous analyses. We develop economic potentials for multiple scenarios across various market and technology-advancement assumptions.

08 HYDROGEN↗

Dyno-in-the-Loop: An Innovative Hardware-in-the-Loop Development and Testing Platform for Emerging Mobility Technologies

Today’s transportation is quickly transforming with the nascent advent of connectivity, automation, shared-mobility, and electrification. These technologies will not only affect our safety and mobility, but also our energy consumption, and environment. As a result, it is of unprecedented importance to understand the overall system impacts due to the introduction of these emerging technologies and concepts. Existing modeling tools are not able to effectively capture the implications of these technologies, not to mention accurately and reliably evaluating their effectiveness with a reasonable scope. To address these gaps, a dynamometer-in-the-loop (DiL) development and testing approach is proposed which integrates test vehicle(s), chassis dynamometer, and high fidelity traffic simulation tools, in order to achieve a balance between the model accuracy and scalability of environmental analysis for the next generation of transportation systems. With this DiL platform, a connected eco-operation system for the plug-in hybrid electric bus (PHEB) has been developed and tested, which can optimize the vehicle dynamics (and potentially powertrain control via smart energy management) to reduce the operational energy consumption as well as tailpipe emissions of the target PHEB. The system performance has been evaluated on the DiL platform with respect to a variety of traffic congestion levels. The results have shown that the developed system can save fuel by more than 13% while reducing the electricity consumption by 2% in the test scenarios.

Wu, Guoyuan↗

Exploring the Performance Boundaries of a Small Reconfigurable Multi-Mission UAV through Multidisciplinary Analysis

The performance of a small reconfigurable unmanned aerial vehicle (UAV) is evaluated, combining a multidisciplinary approach in the computational analysis of additive manufactured structures, fluid dynamics, and experiments. Reconfigurable UAVs promise cost savings and efficiency, without sacrificing performance, while demonstrating versatility to fulfill different mission profiles. The use of computational fluid dynamics (CFD) in UAV design produces higher accuracy aerodynamic data, which is particularly important for complex aircraft concepts such as blended wing bodies. To address challenges relating to anisotropic materials, the Tsai–Wu failure criterion is applied to the structural analysis, using CFD solutions as load inputs. Aerodynamic performance results show the low-speed variant attains an endurance of 1 h, 48 min, whereas its high-speed counterpart is 29 min at a 66.7% higher cruise speed. Each variant serves different aspects of small UAS deployment, with low speed envisioned for high-endurance surveying, and high speed for long-range or time-critical missions such as delivery. The experimental and simulation results suggest room for design iteration, in wing area and geometry adjustments. Structural simulations demonstrated the need for airframe improvements to the low-speed configuration. This paper highlights the potential of reconfigurable UAVs to be useful across multiple industries, advocating for further research and design improvements.

42 ENGINEERING↗

Building a Trusted Roaming Hub [Slides]

The Trusted Roaming Hub is a U.S. Department of Energy-backed initiative led by the National Laboratory of the Rockies (NLR) to address one of the most persistent challenges in electric vehicle (EV) charging: fragmented roaming, inconsistent interoperability, and insufficient digital trust across charging networks. As EV adoption accelerates and charging infrastructure scales nationwide, today's many-to-many integration model between eMobility Service Providers (eMSPs) and Charge Point Operators (CPOs) has become increasingly brittle, costly, and difficult to secure. The Trusted Roaming Hub introduces a neutral, cybersecurity-forward "switchboard" architecture that enables standardized, secure, and scalable roaming interactions across the EV charging ecosystem. Rather than replacing existing networks or commercial relationships, the hub acts as a trusted intermediary that enforces consistent identity, authentication, authorization, and routing across participants improving reliability for drivers, lowering integration burden for industry, and creating a foundation for future grid-interactive charging services. This read-ahead provides an overview of the problem the hub is designed to solve, the core functional and security concepts behind the architecture, the value proposition to key stakeholders, and the near-term trajectory of the work.

33 ADVANCED PROPULSION SYSTEMS↗

Eco-driving Profile Optimization by Dynamic Programming for Battery Electric Vehicles

Although full automation has not yet been achieved, automated vehicles are a valid research area. Not only would automated vehicles provide ultimate driver convenience, but they would maximize energy efficiency by eliminating undesired human driving behaviors and optimally controlling the powertrain. From the perspective of control related to energy saving, speed profile optimization is important for improving system efficiency and satisfying passenger demands. This study employs Dynamic Programming (DP) to solve the constrained optimal problem for travel time, distance, and speed limit by exploring all possible control options. The solutions obtained by DP demonstrate consistent control patterns combining four control modes-acceleration, cruising, coasting, and braking, with cruising or coasting being selective depending on the boundary conditions. Further, this study introduces DP-based simulation results and attempts to provide comprehensive interpretations of the optimal policy by analyzing the essential factors that affect the control problem, including boundary conditions, road load, and powertrain characteristics. Based on these interpretations, the control concepts can be explained as the optimal policy selecting the best control option based on system efficiency and boundary conditions. The results of DP are compared with a human-like driver model to show that the optimal speed profiles can effectively reduce energy consumption.

Autonomous vehicles↗

Ad-Mat: Adaptations of Mature Manufacturing Strategies for Accelerated Redox Flow Battery Deployment

The concept of the Ad-Mat approach is to leverage existing adjacent markets across a broad scope of technologies in order to reduce the manufacturing learning curve and ultimately accelerate redox flow battery (RFB) deployment at scale. Lithium-ion batteries (LIBs) are currently the dominant energy storage technology, and they came to technological maturity under unique market conditions when there was no meaningful competition in the consumer electronic and electric vehicle (EV) space. Today, alternative chemistries that may be technologically better-suited for long-duration storage applications are experiencing a high barrier to entry. This is in large part due to the substantial bias towards the scaled-up production and supply chain that now exists for LIBs. In the case of RFBs in particular, numerous analyses have suggested that RFBs should theoretically have a much lower system cost than LIBs - however, this relies on a mature and competitive manufacturing landscape, which has been extremely challenging to achieve for both flow batteries and other LIB competitors. At the moment, LIB alternatives tend to have isolated small-scale manufacturing pathways, which preclude the economies of scale that would be required to compete with the mature LIB industry. In the present state of the industry, niche manufacturing tools and approaches have evolved to support each alternative technology, such that there is substantial replication and duplication in effort. Continuing to pursue a strategy of isolated manufacturing processes/approaches for each LIB-alternative may never allow for at-scale deployment. In order for RFBs to meaningfully compete with LIBs in the realm of LDES, a new disruptive approach based on cross-industry learning and coordination is needed - and this is exactly what our Ad-Mat concept aims to tackle. In this re-envisioned manufacturing landscape, tools and processes from mature industries can be adapted and deployed across the range of alternative energy storage technologies. Adapting tools, equipment, processes, and industrial learning from mature industries to meet the technological requirements of RFBs would open new markets for existing OEMs in adjacent industries, would prevent unnecessary duplication and re-development, would improve efficiency across the manufacturing chain, and would ultimately support reduced costs and accelerated deployment of RFBs at scale.

adaptive manufacturing↗

Motor with Advanced Concepts for High power density and INtegrated cooling for Efficiency (MACHINE)

Raytheon Technologies Research Center (RTRC) is the central research and development (R&D) organization for RTX, and has extensive expertise in the design, modeling and analysis of high-performance electrical machines and thermal management for all its business units. The proposing team consists of researchers from RTRC and John Deere (JD), will be referred as “Team”. Each organization a has long track record of successful R&D of materials, manufacturing, components, and systems for energy efficiency applications. Motor power density and efficiency are limited by fundamental physical trade-offs between electromagnetics, thermal management, and structural design considerations. The team is proposing to utilize novel technologies and multi-physics design methods to develop a Motor with Advanced Concepts for High power density and INtegrated cooling for Efficiency (MACHINE), demonstrating an 8X improvement in power density.

33 ADVANCED PROPULSION SYSTEMS↗

Cutting-Edge Operations Concepts: Intelligent Infrastructure, Cooperative Driving, Signal Control, and Curbside Management

The objective of this breakout session at the NREL Mobility workshop was to examine emerging traffic operations concepts built on key detection technology such as radars, lidars, and imaging recognition - and identify challenges and paths forward to integrate into our current roadway system. The key objective were to identify the opportunities for intelligent infrastructure to support near-term safety, equity, energy, and congestion mitigation goals, while supporting longer term connected-automated vehicle objectives. In the plenary session, Eric Raamot, from the USDOT Highly Automated Safety Systems Office challenged the participants to think broadly about the roll of standards and reference architecture to provide both an accelerated rollout of intelligent infrastructure, but also a repeatable and supportable framework upon which many infrastructure owners and operators (IOOs) could utilize for their implementation purposes.

ADVANCED PROPULSION SYSTEMS↗

Material Developments for 3D/4D Additive Manufacturing (AM) Technologies

Additive Manufacturing (AM), or 3D printing, is a unique technology in which structurally complex objects can be easily manufactured. While AM allows for the creation of intricate 3D objects, these objects are inactive and motionless. With recent incorporation of a “pre-programmed functionality’’ to the 3D printed objects, a new concept has emerged, 4D printing. Specifically, the 4D printing technology enables a static 3D printed object to change its shape, functionality or property over time upon exposure to a specific stimulus such as heat, stress, light, pH, and moisture, etc. We designed and produced compact 3D/4D printable materials that can be used as (a) structural components of the unmanned aerial vehicles (UAVs), and (b) as hydrogen storage materials that supply hydrogen to a fuel cell to expand the operational reach, namely flight time, and endurance of the UA Vs.

36 MATERIALS SCIENCE↗

Material Developments for 3D/4D Additive Manufacturing (AM) Technologies

Additive Manufacturing (AM), or 3D printing, is a unique technology in which structurally complex objects can be easily manufactured. While AM allows for the creation of intricate 3D objects, these objects are inactive and motionless. With recent incorporation of a “pre-programmed functionality” to the 3D printed objects, a new concept has emerged, 4D printing. Specifically, the 4D printing technology enables a static 3D printed object to change its shape, functionality or property over time upon exposure to a specific stimulus such as heat, stress, light, pH, and moisture, etc. We designed and produced compact 3D/4D printable materials that can be used as (a) structural components of the unmanned aerial vehicles (UAVs), and (b) as hydrogen storage materials that supply hydrogen to a fuel cell to expand the operational reach, namely flight time, and endurance of the UAVs.

08 HYDROGEN↗

Neutronic Performance of a Compact 10 MWe Nuclear Reactor with Low Enrichment (ThxU1−x)N Fuel

Abstract Recent interest in compact nuclear reactors for applications in space or in remote locations drives innovation in nuclear fuel design, especially non-oxide ceramic nuclear fuels. This work details neutronic modeling designed to support the development of a new nuclear fuel concept based on a mixture of thorium and uranium nitride. A Monte Carlo N-Particle Version 6.2 (MCNP-6) model of a compact 10 MWe reactor design which incorporates (Th x U 1− x )N fuel is presented. In this context, a “compact” reactor is a completely assembled reactor which may be emptied of coolant and transported by specialized commercial vehicle, deployed by a C130J aircraft, or launched into space. Core geometry, reflector barrels, and the heat exchange zones are designed to support reduction of overall reactor volume of core components while maintaining criticality with a fixed total fuel mass of 4500 kg. Dense mixed nitrides of thorium nitride (ThN) additions in uranium nitride (UN) in 5 wt.% increments between $$0.05 \le x \le 0.5$$ 0.05 ≤ x ≤ 0.5 have been considered for calculation of $$k_{\infty }$$ k ∞ and $$k_{{{\text{effective}}}}$$ k effective . ThN additions in UN results in a slight increase in the magnitude of the temperature coefficient of reactivity, which is negative by design. The isotopic distribution of the principal actinide inventory as a function of burnup, time, and initial fuel composition is presented and discussed within the context of the proliferation risk of this core design.

Parker, S. S. (ORCID:000000018597440X)↗