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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 271 records · Page 15
All sourcesNASA NTRSDOE OSTI
NASA NTRS1981

Propellant management for low thrust chemical propulsion systems

Low-thrust chemical propulsion systems (LTPS) will be required for orbital transfer of large space systems (LSS). The work reported in this paper was conducted to determine the propellant requirements, preferred propellant management technique, and propulsion system sizes for the LTPS. Propellants were liquid oxygen (LO2) combined with liquid hydrogen (LH2), liquid methane or kerosene. Thrust levels of 100, 500, and 1000 lbf were combined with 1, 4, and 8 perigee burns for transfer from low earth orbit to geosynchronous earth orbit. This matrix of systems was evaluated with a multilayer insulation (MLI) or a spray-on-foam insulation. Vehicle sizing results indicate that a toroidal tank configuration is needed for the LO2/LH2 system. Multiple perigee burns and MLI allow far superior LSS payload capability. Propellant settling, combined with a single screen device, was found to be the lightest and least complex propellant management technique.

Hamlyn, K. M.↗
DOE OSTI2026

Optimization of the FRIB beam dump: a hybrid genetic algorithm and reinforcement learning approach

The operational envelope of high-power-density systems, such as particle accelerators and advanced nuclear energy systems, is critically constrained by the need to manage extreme thermal loads. To address this, we present a novel hybrid optimization framework combining a genetic algorithm (GA) with a soft actor-critic (SAC) deep reinforcement learning agent. This framework was applied to a practical high-heat-flux problem: redesigning the beam dump at the Facility for Rare Isotope Beams (FRIB) for a power upgrade from 20 kW to 50 kW. The resulting design, validated by three-dimensional conjugate heat transfer simulations, suppresses hazardous hot spots and yields a markedly more uniform temperature distribution. This provides a robust operating margin, increasing the average power-handling capability by 72% relative to the current design, demonstrating the framework’s potential to solve complex thermal management challenges in both accelerator technology and advanced nuclear systems.

Accelerator↗
DOE OSTI2024

Advancing Molecular Weight Determination of Lignin by Multi-Angle Light Scattering

Due to the complexity and recalcitrance of lignin, its chemical characterization is a key factor preventing the valorization of this abundant material. Multi-angle light scattering (MALS) is becoming a sought-after technique for absolute molecular weight (MW) determination of polymers and proteins. Lignin is a suitable candidate for MW determination via MALS, yet further investigation is required to confirm its absolute MW values and molecular size. Studies aiming to break down lignin into a variety of renewable products will benefit greatly from a simple and reliable determination method like MALS. Recent pioneering studies, discussed in this review, addressed several key challenges in lignin’s MW characterization. Nevertheless, some lignin-specific issues still need to be considered for in-depth characterization. This study explores how MALS instrumentation manages the complexities of determining lignin’s MW, e.g., with simultaneous fractionation and fluorescence interference mitigation. Additionally, we rationalize the importance of a more detailed light scattering analysis for lignin characterization, including aspects like the second virial coefficient and radius of gyration.

differential refractive index increment↗
NASA NTRS2024

Architecture of High-Altitude Operations (HAO) Discovery and Synchronization Service (DSS)

The aviation industry is evolving at an unprecedented pace, necessitating the development of efficient, secure, and interoperable systems to manage increasingly complex air traffic. Moreover, the demand for High-Altitude Operations (HAO) is increasing. Furthermore, air traffic control services are limited in HAO environments. HAO industry participants will need airspace access and flexibility to perform their missions in this airspace that provides provisions for scalability. The Discovery and Synchronization Service (DSS) will be a cornerstone of the HAO ecosystem, enabling the effective sharing of critical airspace data, including operational intent, aircraft trajectories, and airspace usage among various stakeholders and operators. The DSS architecture addresses these challenges with a distributed, decentralized, and interoperable system that facilitates seamless integration across diverse airspaces. It prioritizes secure data exchange while safeguarding data ownership. This white paper presents the vision, architecture, and benefits of the DSS for HAO, underscoring its potential to streamline operations, reduce redundancies, and establish a foundation for safe and efficient airspace management.

HAO↗
DOE OSTI2023

Predictor-corrector models for lightweight massive machine-type communications in Industry 4.0

Future Industry 4.0 scenarios are characterized by seamless integration between computational and physical processes. To achieve this objective, dense platforms made of small sensing nodes and other resource constraint devices are ubiquitously deployed. All these devices have a limited number of computational resources, just enough to perform the simple operation they are in charge of. The remaining operations are delegated to powerful gateways that manage sensing nodes, but resources are never unlimited, and as more and more devices are deployed on Industry 4.0 platforms, gateways present more problems to handle massive machine-type communications. Although the problems are diverse, those related to security are especially critical. To enable sensing nodes to establish secure communications, several semiconductor companies are currently promoting a new generation of devices based on Physical Unclonable Functions, whose usage grows every year in many real industrial scenarios. Those hardware devices do not consume any computational resource but force the gateway to keep large key-value catalogues for each individual node. In this context, memory usage is not scalable and processing delays increase exponentially with each new node on the platform. In this paper, we address this challenge through predictor-corrector models, representing the key-value catalogues. Models are mathematically complex, but we argue that they consume less computational resources than current approaches. The lightweight models are based on complex functions managed as Laurent series, cubic spline interpolations, and Boolean functions also developed as series. Unknown parameters in these models are predicted, and eventually corrected to calculate the output value for each given key. The initial parameters are based on the Kane Yee formula. An experimental analysis and a performance evaluation are provided in the experimental section, showing that the proposed approach causes a significant reduction in the resource consumption.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

A simulation framework for evaluating electronic order workflows in integrated health records

Electronic health record (EHR) systems are critical to modern healthcare delivery, yet the dynamic workflows that govern electronic order processing remain underexplored. Inefficiencies in these digital pathways can cause delays in care, repetitive workloads, and even patient harm. This study presents a discrete-event simulation framework used to reconstruct and evaluate EHR-based order workflows in a large integrated healthcare system. Using real-world data extracted from the Veterans Health Administration’s Corporate Data Warehouse, the authors mapped order events to standardized state transitions and modeled their progression across different facilities of varying complexity levels. After being calibrated with empirical distributions of transition times and validated against observed time-in-system metrics, the simulation demonstrates close alignment with historical performance. Scenario analyses reveal that resource capacity constraints significantly amplify the impact of electronic order surges, which are reflected in the disproportionate growth in backlogs and processing delays. Adjustments in transition probabilities further increased recirculation and extended workflow paths. Network-based analysis identified Reserved, InProgress, and Completed as structurally critical states that function as hubs within the process network but the transitions in-between also act as major bottlenecks. These results showcased the effectiveness of simulation-based approaches in monitoring EHR order processing performance and evaluating consequences of workflow changes on healthcare network resources planning. The proposed simulation framework provides a scalable data-driven tool to support operational decision-making and improve the efficiency of electronic order management in complex healthcare environments.

Engineering↗
NASA NTRS2003

The Logical Extension

The same software controlling autonomous and crew-assisted operations for the International Space Station (ISS) is enabling commercial enterprises to integrate and automate manual operations, also known as decision logic, in real time across complex and disparate networked applications, databases, servers, and other devices, all with quantifiable business benefits. Auspice Corporation, of Framingham, Massachusetts, developed the Auspice TLX (The Logical Extension) software platform to effectively mimic the human decision-making process. Auspice TLX automates operations across extended enterprise systems, where any given infrastructure can include thousands of computers, servers, switches, and modems that are connected, and therefore, dependent upon each other. The concept behind the Auspice software spawned from a computer program originally developed in 1981 by Cambridge, Massachusetts-based Draper Laboratory for simulating tasks performed by astronauts aboard the Space Shuttle. At the time, the Space Shuttle Program was dependent upon paper-based procedures for its manned space missions, which typically averaged 2 weeks in duration. As the Shuttle Program progressed, NASA began increasing the length of manned missions in preparation for a more permanent space habitat. Acknowledging the need to relinquish paper-based procedures in favor of an electronic processing format to properly monitor and manage the complexities of these longer missions, NASA realized that Draper's task simulation software could be applied to its vision of year-round space occupancy. In 1992, Draper was awarded a NASA contract to build User Interface Language software to enable autonomous operations of a multitude of functions on Space Station Freedom (the station was redesigned in 1993 and converted into the international venture known today as the ISS)

Source record↗
DOE OSTI2022

Application of Margin-Based Methods to Assess System Health

Health management of complex systems such as nuclear power plants is an essential task to guarantee system reliability. This task can be greatly enhanced by constantly monitoring asset status and performances and process such data (through anomaly detection, diagnostic, and prognostic computational algorithms) to identify asset degradation trends and faulty states. While such information and data are typically available for many of the assets, they are not propagated from the asset to the system level in order to identify the most critical assets and prioritize maintenance and surveillance activities. The main reason is driven by the fact that current reliability modeling techniques are inadequate to process such information/data. This is due to the nature of these techniques which are based on the concept of failure rate/probability that do not serve an operational context where quantitative asset health information is available. Simply stated, current reliability techniques serve a run-to-failure operational setting and not a predictive maintenance one where the goal is to perform maintenance and surveillance activities only when they are needed based on asset health. The risk informed asset management (RIAM) project is focusing on the development of a different kind of reliability modeling techniques designed to adequately serve a predictive operational setting. Such reliability techniques move aways from a failure rate/probability to a margin-based mindset where margin is here used as a metric to quantify asset health based only on current and past operational experience of the asset under consideration. In addition, margin-based reliability techniques are able to propagate asset health information from the component to system level and provide importance measure to each asset. This report summarizes a recent activity performed in collaboration with plant modernization pathway designed to integrate monitoring data into margin-based reliability models. Such activity focuses on a specific system of an existing nuclear power plant where large amount of historic monitoring data is used to monitor asset and system health.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Comparison of Socio-Technical Threat Models

Given the adoption of emerging technologies and the increasing complexity of managing such systems with a lifecycle much shorter than that of critical infrastructure systems, there is a practical need to be able to analyze sociotechnical dependencies and their associated evolving risks. Threat models based on social influence techniques can be used to implement adversarial tactics analogous to the cyber kill chain and attested to within the MITRE ATT&CK for ICS framework including Initial Access, Persistence, Collection, and Impact. Furthermore, as with cyber disruptions, the impact of social influence threat models can have an asymmetric impact that is not spatially-localized. Finally, unlike cyber attacks with a reasonably short duration (ransomware takes days to months), social influence based attacks have the potential to persist for much longer as they are based on long-term strategic infrastructure investments within the private sector. Given the increased importance of electric vehicle charging stations as a long-term, strategic infrastructure investment within the Energy and Transportation Sectors, we provide initial results that compare the impact of a Loss of Availability (T0826) realized through cyber and social influence based threat models. The analysis employs techniques from automated reasoning and measures of network complexity to understand evolving dominance of EV payment and charging networks within geographic region of interest. Within this context, we compare the impact of a loss of availability due to ransomware versus that of loss of support due to a merger and acquisition. Results across several different metro areas will be provided.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2026

Used Nuclear Fuel Management Using the Next Generation System Analysis Model

The U.S. Department of Energy (DOE) is leading the National effort to manage the back end of the nuclear fuel cycle, encompassing the safe transportation, storage/staging, and/or eventual disposal of used nuclear fuel (UNF) and high-level radioactive waste. The Next Generation System Analysis Model (NGSAM) is DOE’s discrete-event, agent-based simulation tool designed to model the full life cycle of UNF from reactor discharge to final disposal. NGSAM supports the DOE Office of Spent Fuel and High-Level Waste Disposition by enabling a detailed, scenario-based analysis of logistics, infrastructure, and shipping strategies. NGSAM replaces legacy models with a modern, flexible platform built on Repast Simphony and enhanced by the Process Analysis Tool. NGSAM simulates the movement and interaction of individual fuel assemblies with system components such as canisters, casks, railcars, and facilities. The model integrates with the Java Transportation Operations Model to plan and execute transportation scenarios, supporting both constrained and unconstrained resource allocation. Key features include customizable allocation and acceptance algorithms, detailed facility-level operations, and a Quick Edit tool for rapid scenario adjustments. NGSAM supports multimodal transportation modeling (e.g. rail, road, barge) and provides comprehensive cost, schedule, and infrastructure data. NGSAM utilizes data from sources such as DOE’s STANDARDS UNF database and DOE’s Stakeholder Tool for Assessing Radioactive Transportation, while also allowing user-defined inputs for scenario customization. NGSAM enables stakeholders to evaluate complex UNF management strategies, assess system performance under varying assumptions, and inform decision making for future infrastructure investments. Its modular architecture and integration with other Integrated Waste Management System tools make it a critical asset for planning the safe and efficient disposition of the Nation’s growing UNF inventory.

Craig, Brian [Argonne National Laboratory (ANL)]↗
DOE OSTI2017

Does the Perfect Waste Package Exist? Development of a Decisional Tool Addressing this Challenge - 17053

The definition of a safe, technically, economically and societally acceptable waste management strategy is highly dependent on the Waste Acceptance Criteria in each country and on the already available disposal routes. It is the reason why there is not a single solution but a combination of optimized solutions depending on the type of waste and on each country's considerations. In fact, when operating a nuclear plant or performing its decommissioning or legacy waste management, one has to consider a large waste diversity in term of natures, types, volumes and radioactivity spectra. All nuclear operators have to take-up the challenge of implementing solutions for conditioning its waste in packages suitable for transport short to long term interim storage and final disposal of it (or prepare for final disposal if the repository is not yet available). Operators have then to answer the following dilemma: either define a complete strategy packaging the waste for final disposal, or 'containerising' it temporarily, pending final disposal. The strategy is highly country dependent; in the first case, one has to take into account the available information and future orientations relative to acceptability of the packages in order to define a robust solution. The approach implemented in France requires a close dialogue between the Operators, the Safety Authority, the Administration and the stakeholders. Moreover it pushes forward whenever possible standardization, contributing to cost minimization. If the second approach has the advantage of leaving the options open, and reducing the initial investments, it inevitably requires future retrieval and re-packaging with potential evolutions/degradation of the initial waste form. It also induces the potential risk to produce additional secondary waste. As an additional drawback, it introduces uncertainties and unknowns related to the future waste management criteria and to the costs. The general idea is that, depending on context, a given route (i.e., treatment, conditioning, and transport), could be considered as efficient or not. Assessing a waste package is certainly highly context dependent. However it should be possible to recognize and to lead an evaluation based on a number of fixed criteria, whatever the context, to be addressed when assessing the development of a final waste package in connection to the overall management route. A waste package is always a combination of a waste container and a waste form and will have to be transported one day from the production site to the final repository or to off-site interim storage facilities. AREVA's approach consists in defining an evaluation grid based on a set of criteria which aim (i) to evaluate whether the different waste treatments, conditionings, transport and packages deserve to be considered within different national contexts, and (ii) to evaluate R and D actions to be performed for improving existing solutions or developing new ones. One of the key lessons to be drawn from AREVA's experience in developing waste packages is that the perfect waste doesn't exist even though the vitrified canister is probably the most efficient one. The performance of a package resulting from a compromise depends on context and is a strength combination between the waste container and the waste form. The approach is to evaluate a waste package development against different set of criteria and to draw optimization diagrams. In such diagram, a given waste package is assessed with respect to selected criteria such as waste form and waste container, stability, level of waste incorporation, integrity lifetime, secondary waste generation, transport, long term behavior, and economical effectiveness, etc. Addressing a waste form is a very key point. This evaluation grid and comparative approach will be presented through examples and comparison providing from AREVA feedback on waste package development related to complex waste management such as problematic waste or legacy waste. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2017

Cross-scale intercomparison of climate change impacts simulated by regional and global hydrological models in eleven large river basins

Ideally, the results from models operating at different scales should agree in trend direction and magnitude of impacts under climate change. However, this implies that the sensitivity of impact models designed for either scale to climate variability and change is comparable. In this study, we compare hydrological changes simulated by 9 global and 9 regional hydrological models (HM) for 11 large river basins in all continents under reference and scenario conditions. The foci are on model validation runs, sensitivity of annual discharge to climate variability in the reference period, and sensitivity of the long-term average monthly seasonal dynamics to climate change. One major result is that the global models, mostly not calibrated against observations, often show a considerable bias in mean monthly discharge, whereas regional models show a much better reproduction of reference conditions. However, the sensitivity of two HM ensembles to climate variability is in general similar. The simulated climate change impacts in terms of long-term average monthly dynamics evaluated for HM ensemble medians and spreads show that the medians are to a certain extent comparable in some cases with distinct differences in others, and the spreads related to global models are mostly notably larger. Summarizing, this implies that global HMs are useful tools when looking at large-scale impacts of climate change and variability, but whenever impacts for a specific river basin or region are of interest, e.g. for complex water management applications, the regional-scale models validated against observed discharge should be used.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2019

Functional and Anatomical Imaging in Patients with Ischemic Symptoms and Known Coronary Artery Disease

Purpose of Review: This review is aimed at summarizing recent advances in functional, anatomical, and hybrid imaging techniques used in the assessment of ischemic complaints in patients with known coronary artery disease (CAD). Recent Findings: Cardiovascular imaging has seen significant growth over the last decade in the fields of coronary computed tomography angiography (CCTA), FFR derived from CCTA, cardiac magnetic resonance, radionuclide myocardial perfusion imaging, and hybrid imaging for the purposes of evaluating symptoms concerning for ischemia. This growth stems from refinement of imaging techniques and hardware and software advances that have made current techniques more accurate with less acquisition time. However, every anatomic and functional imaging modality has important technical and patient-specific limitations. This review assesses these issues, guides a patient-centered imaging approach, and identifies important research questions to resolve. Summary: Recent advances in non-invasive cardiovascular imaging can provide important information in patients with known CAD beyond traditional imaging techniques; the use of these novel tools refines the clinical management of complex patients with ischemic symptoms and known CAD.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2017

Clinical Research Ethics: Considerations for the Radiation Oncologist

Consideration of clinical research ethics in radiation oncology is underexplored relative to other areas of oncology. A number of ethical challenges related to informed consent, randomization, conflicts of interest, and scientific validity and social value are shared with other areas of medicine, although their exact inflections are specific to radiation oncology. In addition, there are unique concerns in radiation oncology arising from the rapid evolution and uneven distribution of radiation technologies; the greater unfamiliarity of the general public and research oversight committees in regard to radiation oncology clinical practice; and the high complexity of managing most radiation oncology research, much of which is carried out in high-acuity multidisciplinary oncologic settings. To produce the best research, adherence to the highest ethical standards should be pursued as an integral component of all radiation oncology research.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2026

Upcycling Polycrystalline LiNi1/3Mn1/3Co1/3O2 to High-Performance Large-Grained LiNi0.6Mn0.2Co0.2O2 via Simplified Polyol-Mediated Recycling

The escalating demand for lithium-ion batteries (LIBs) necessitates advanced recycling strategies that can address both resource scarcity and environmental impact. While conventional hydrometallurgy shows promise, it is challenged by complexity, impurity management, and environmental footprint. Here, we report a strategic polyol-metallurgy recycling process that efficiently transforms spent polycrystalline LiNi1/3Mn1/3Co1/3O2 (NMC111) into high-performance large-grained LiNi0.6Mn0.2Co0.2O2 (NMC622), offering dual benefits of compositional upcycling and morphology upgradation. Our approach leverages a polyol system with meticulous control over nickel salt addition and the precipitation process. This yields upcycled cathode materials possessing excellent structural integrity, well-defined large-grained particles (5-10?..mu..m), and robust electrochemical performance, including a specific capacity of ~182 mAh g-1 at C/10 and 88.0% capacity retention after 100 cycles. This facile and multifunctional process provides an environmental-friendly pathway for advanced cathode recycling, significantly contributing to a circular economy for LIBs through precise control over critical material attributes.

25 ENERGY STORAGE↗
DOE OSTI2018

3D printing via ambient reactive extrusion

Here, Additive Manufacturing (AM) has the potential to offer many benefits over traditional manufacturing methods in the fabrication of complex parts with advantages such as low weight, complex geometry, and embedded functionality. In practice, today’s AM technologies are limited by their slow speed and highly directional properties. To address both issues, we have developed a reactive mixture deposition approach that can enable 3D printing of polymer materials at over 100X the volumetric deposition rate, enabled by a greater than 10X reduction in print head mass compared to existing large-scale thermoplastic deposition methods, with material chemistries that can be tuned for specific properties. Additionally, the reaction kinetics and transient rheological properties are specifically designed for the target deposition rates, enabling the synchronized development of increasing shear modulus and extensive cross linking across the printed layers. This ambient cure eliminates the internal stresses and bulk distortions that typically hamper AM of large parts, and yields a printed part with inter-layer covalent bonds that significantly improve the strength of the part along the build direction. The fast cure kinetics combined with the fine-tuned viscoelastic properties of the mixture enable rapid vertical builds that are not possible using other approaches. Through rheological characterization of mixtures that were capable of printing in this process as well as materials that have sufficient structural integrity for layer-on-layer printing, a “printability” rheological phase diagram has been developed, and is presented here. We envision this approach implemented as a deployable manufacturing system, where manufacturing is done on-site using the efficiently-shipped polymer, locally-sourced fillers, and a small, deployable print system. Unlike existing additive manufacturing approaches which require larger and slower print systems and complex thermal management strategies as scale increases, liquid reactive polymers decouple performance and print speed from the scale of the part, enabling a new class of cost-effective, fuel-efficient additive manufacturing.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Nuclear safety Enhanced: A Deep dive into current and future RAVEN applications

As the horizon of nuclear energy expands with the advent of small modular reactors, IV generation reactors, and fusion reactors, there is a growing perspective that the licensing process could benefit from a more comprehensive approach. Moving beyond traditional deterministic and PRA analysis might pave the way for a novel safety analysis paradigm propelled by the increasing computational power at our disposal. This paper explores different methodologies that can improve the outcomes of nuclear safety analysis. These range from uncertainty quantification techniques, aimed at enhancing the precision of safety margins, to deploying dynamic event trees by driving system code simulations, capturing the potential evolutions of severe accidents. These methodologies introduce innovative dimensions to safety analysis, considering the consequences of postulated events and the dynamics of accident sequences. However, they also bring forth challenges, especially in managing the complexity and sheer volume of potential scenarios. The paper touches upon some strategies to counter these challenges, emphasizing the importance of adaptability and continuous evolution in the face of emerging nuclear safety concerns. Additionally, the paper sheds light on the need for advanced tools to apply these methodologies. Among these tools is RAVEN, an open-source software designed for parametric and probabilistic analyses. Its core components, including distribution, sampler, and reduced order model, enable various applications, from risk assessment and mitigation to dynamic learning and plant control logic simulations.

97 - MATHEMATICS AND COMPUTING↗