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DOE OSTI2025

Hydrological connectivity: a review and emerging strategies for integrating measurement, modeling, and management

This review synthesizes methods for measuring, modeling, and managing hydrologic connectivity, offering pathways to improve practices and address environmental challenges (e.g., climate change) and sustainability. As a key driver of water movement and nutrient cycling, hydrologic connectivity influences flood mitigation, water quality regulation, and biodiversity conservation. However, traditional field-based methods (e.g., dye tracing), indirect measurements (e.g., runoff analysis), and remote sensing techniques (e.g., InSAR) often struggle to capture the complexity of catchment-scale interactions. Similarly, modeling approaches—including process-based and percolation theory-based models, graph theory, and entropy-based metrics—face limitations in fully representing these interconnected processes. Both modeling and measurement techniques are constrained by inadequate spatial and temporal coverage, high data demands, computational complexity, and difficulties in representing subsurface connectivity. Subsequently, we critique current management practices that prioritize isolated variables (e.g., streamflow, sediment transport) over system-wide strategies and emphasize the need for adaptive, connectivity-based approaches in water resource planning and restoration. Moving forward, we highlight the importance of interdisciplinary collaboration, technological innovations (e.g., AI-driven modeling, real-time monitoring), and integrated frameworks to improve connectivity measurement, modeling, and adaptive management to restore fragmented hydrologic networks. This integrated approach sets the stage for transformative water resource management, fostering proactive policy development and stakeholder engagement.

Dwivedi, Dipankar↗

NASA NTRS1996

Medical and surgical applications of space biosensor technology

Researchers in space life sciences are rapidly approaching a technology impasse. Many of the critical questions on the impact of spaceflight on living systems simply cannot be answered with the limited available technologies. Research subjects, particularly small animal models like the rat, must be allowed to function relatively untended and unrestrained for long periods to fully reflect the impact of microgravity and spaceflight on their behavior and physiology. These requirements preclude the use of present hard-wired instrumentation techniques and limited data acquisition systems. Implantable sensors and miniaturized biotelemetry are the only means of capturing the fundamental and critical data. This same biosensor and biotelemetry technology has direct application to Earth-based medicine and surgery. Continuous, on-line data acquisition and improved measurement capabilities combined with the ease and flexibility offered by automated, wireless, and portable instruments and data systems, should provide a boon to the health care industry. Playing a key role in this technology revolution is the Sensors 2000! (S2K!) Program at NASA Ames Research Center. S2K!, in collaboration with space life sciences researchers and managers, provides an integrated capability for sensor technology development and applications, including advanced biosensor technology development, spaceflight hardware development, and technology transfer and commercialization. S2K! is presently collaborating on several spaceflight projects with dual-use medical applications. One prime example is a collaboration with the Fetal Treatment Center (FTC) at the University of California at San Francisco. The goal is to develop and apply implantable chemical sensor and biotelemetry technology to continuously monitor fetal patients during extra-uterine surgery, replacement into the womb, through birth and beyond. Once validated for ground use, the method will be transitioned to spaceflight applications to remotely monitor key biochemical parameters in flight animals. Successful application of NASA implantable biosensor and biotelemetry technologies should accelerate the advancement of this and other modern medical procedures while furthering the exploration of life in space.

NASA Discipline General Space Life Sciences↗

DOE OSTI2021

Capacity Investment under Bayesian Information Updates at Reporting Periods: Model and Application

We consider capacity addition decisions by a new product manufacturer faced with uncertain technology alternatives. The manufacturing capacity addition and technology development occurs in parallel, with preliminary results from a technology project's success providing valuable information to the manufacturer in adding capacity. We solve a stochastic dynamic program with Bayesian updates to obtain the manufacturer's expected profit‐maximizing capacity investment decision. Our model and applications are motivated by the Critical Materials Institute (CMI) (funded by the Department of Energy), which manages research projects focused on mitigating critical material constraints, vital to renewable energy technologies such as direct‐drive wind turbines, electric vehicles, and energy‐efficient lighting. We capture three unique aspects of the problem: first, the learning from project progress depends on task‐based stochastic outcomes and a project's percent‐done. Second, the underlying technology's profitability is based on a model of competition. Third, we evaluate the impact of progress across a portfolio of projects based on a manufacturer's capacity addition. We develop a heuristic that produces results that are close to optimal and can thus be used for large problem sizes. The managerial insights from an application of our model to CMI projects include: (i) technology projects that report the percent‐done of a project earlier increase expected manufacturer profit; (ii) careful choice of “safe bets,” that is, technologies with low profitability but a high probability of success, can increase expected manufacturer profit; (iii) a portfolio of projects can increase profits significantly over separate project evaluation; and (iv) dynamic management of project resources can increase overall profit.

Vedantam, Aditya↗

DOE OSTI2024

Profitability, Scalability and Optimized Siting for Waste-to-Energy Supply Chains: A Case Study on Hydrothermal Liquefaction

Waste-to-Energy (WtE) conversion technologies have the potential to simultaneously reduce waste volumes, treatment-related emissions, and carbon intensity while producing valuable energy services. However, questions remain regarding under which conditions emerging WtE technologies are feasible to deploy. In this project, we develop an optimized siting method for WtE technologies to assess cost-effective WtE processor locations, throughput scales, and profitability. We apply the model using Hydrothermal Liquefaction (HTL) as an example WtE technology. We develop calibrated capital and operating expense cost curves based on literature data to study the techno-economic characteristics of WtE supply chains. Prior to solving the siting optimization, we analyze the model parameters to describe organic waste management system behavior under four different HTL deployment configurations: Co-Processing, where HTL plants send biocrude to existing conventional refineries via assumed pipelines; Co-Location, where biorefineries are co-located with HTL plants; and two alternative Standalone Biorefining cases, where distributed HTL plants transport biocrude intermediate via either assumed pipelines or trucking to centralized biorefineries. We also define and apply several feedstock gate fee calculations, representing different revenue distribution options, to investigate how bioproduct value could impact WtE supply chain economics in terms of waste producer and processor profit or cost reduction.

09 BIOMASS FUELS↗

DOE OSTI2022

Helicity Injected Torus (HIT): Sustainment of Stable Equilibria Through Self-organization

This is the Final Progress Report of the Helicity Injected Torus (HIT) program covering May 2016 through December 2020. During this final period the HIT program continued to make advancements in computational modeling, theory, and experimental studies of global self-organization and inductively sustained spheromaks. This included many valuable contributions to the fusion, plasma and physics community, through peer-reviewed publications, PhD theses and conference presentations and posters.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

NASA NTRS2020

Multidisciplinary Systems Analysis of a Six Passenger Quadrotor Urban Air Mobility Vehicle Powertrain

There is a high degree of research interest in the design space for electric vertical takeoff and landing (eVTOL) vehicles, because these vehicles are seen as key enablers for urban air mobility (UAM). This work further explores the eVTOL design space, by presenting analysis of a six-passenger eVTOL quadrotor powertrain, with integrated power, propulsion, and thermal management systems modeled using the Numerical Propulsion System Simulation (NPSS) and the NPSS Power System Library. Four architectures are modeled at the same design point and compared over a design mission. Results from an architecture comparison study show that a hybrid architecture performs best in terms of cruise range, however, the hybrid needs batteries with high specific energy and specific power in order to obtain a benefit vs turboelectric architectures. Sensitivity studies are conducted to show correlations between component parameters and system metrics. This data provides useful indicators for further technological improvement. Lastly, an initial TMS model is presented, and sensitivity studies on TMS design parameters are presented as well, to show high level TMS design trends.

electrified propulsion↗

NASA NTRSDate not supplied

Multidisciplinary Systems Analysis of a Six Passenger Quadrotor Urban Air Mobility Vehicle Powertrain

evtol↗

NASA NTRS1999

Numerical Thermal Model of a 30-cm NSTAR Ion Thruster

A thermal computer model of the NSTAR (Nasa Solar Electric Propulsion Technology Applications Readiness) xenon ion thruster has been produced using a lumped parameter thermal nodal network scheme. This model contains 104 nodes on the thruster and was implemented using SINDA (Systems Improved Numerical Differencing Analyzer) and TRASYS (Thermal Radiation Analyzer System) on various UNIX workstations. The model includes radiation and conduction heat transfer, the effect of plasma interaction on the thruster, and an account for finely perforated surfaces. The model was developed in conjunction with an NSTAR thruster outfitted with approximately 20 thermocouples for thermal testing at the NASA Lewis Research Center. The results of these experiments were used to calibrate and confirm the computer model first without and then with the plasma interaction. The calibrated model was able to predict discharge chamber temperatures to within 10 C of measured temperatures. To demonstrate the ability of the model under various circumstances the heat flux was examined for a thruster operating in the environment of space.

VanNoord, Jon↗

NASA NTRS2018

Aircraft System Noise Assessment of the NASA D8 Subsonic Transport Concept

Avehicle-level noise assessment has been performed for theNASAD8 concept aircraft (ND8) in the NASA Advanced Air Transport Technology Project portfolio. The NASA research-level Aircraft NOise Prediction Program (ANOPP-Research) was used to predict the noise from each source component on the ND8 to build up a noise estimate for the full aircraft. The propulsion airframe aeroacoustic (PAA) effects of the ND8, namely boundary layer ingestion (BLI) with its influence on fan noise, and the noise shielding, reflection, and diffraction mechanisms of the unconventional airframe, were empirically modeled using experimental data. Noise reduction technologies appropriate to the 2025-2035 time frame were included in this study. Including all technologies and PAA effects, the ND8 is predicted to have a cumulative margin to the Stage 4 certification metric of only 7.4 EPNdB. Boundary layer ingestion is predicted to have a detrimental impact on cumulative noise levels on the order of 15 EPNdB. Fan noise is seen to be the primary noise source at all three certification points, even if the BLI noise impact could be entirely suppressed. The impact of engine noise shielding by the airframe is limited by a lack of aft shielding and the presence of horizontal tail reflections in the aft direction. The physical constraint on engine size by the pi-tail is seen as a potential barrier to engine noise reduction through the corresponding limitation on fan bypass ratio. Mildly reduced climb performance (compared to similar reference aircraft) does not provide any benefit through increased noise propagation distance. If the boundary layer ingestion noise penalty could be suppressed such that BLI would have no effect on noise, the cumulative margin to Stage 4 would increase to 22.4 EPNdB, still below the NASA Mid Term goal of 32-42 EPNdB.

Clark, Ian A.↗

NASA NTRS2019

Maturation of Dynamic Power Convertors for Radioisotope Power Systems

Dynamic Radioisotope Power Systems (DRPS) are being developed by NASA’s Radioisotope Power Systems (RPS) Program in collaboration with the U.S. Department of Energy (DOE) for space science and exploration missions. A development effort is currently underway to mature dynamic power convertors for infusion into a potential future flight generator. This convertor maturation effort was formulated by the RPS Program at NASA Headquarters based on successful maturation models and utilizes expertise from agency’s technology and mission centers to support requirements development and technology assessments. The effort is being executed by Glenn Research Center’s (GRC) DRPS Project and the Thermal Energy Conversion Branch. The Dynamic Power Convertor (DPC) contracts consist of three phases to enable design, fabrication, and independent assessment of prototypes after delivery to the government. The contracts are intended to gather data on candidate dynamic conversion technologies to fill knowledge gaps, support assessments of dynamic conversion technologies, and elicit generator requirements. The 110-watt Stirling Radioisotope Generator (SRG-110) and Advanced Stirling Radioisotope Generator (ASRG) flight development projects provided Stirling convertor demonstration units and engineering models to verify and validate convertors against performance specifications and mission requirements. These units utilize temperature resistant materials and non-contacting bearings to demonstrate wear-free, long-life operation. This maturation effort builds on past lessons-learned and new requirements focused on demonstrating convertor robustness to critical environments meant to stress key aspects of each convertor within the margins of the design. This effort seeks to realize the full potential of dynamic power conversion technologies for NASA’s space science and exploration missions.

Wilson, Scott↗

NASA NTRS1991

MisTec: A software application for supporting space exploration scenario options and technology development analysis and planning

The structure and composition of a new, emerging software application, which models and analyzes space exploration scenario options for feasibility based on technology development projections is presented. The software application consists of four main components: a scenario generator for designing and inputting scenario options and constraints; a processor which performs algorithmic coupling and options analyses of mission activity requirements and technology capabilities; a results display which graphically and textually shows coupling and options analysis results; and a data/knowledge base which contains information on a variety of mission activities and (power and propulsion) technology system capabilities. The general long-range study process used by NASA to support recent studies is briefly introduced to provide the primary basis for comparison for discussing the potential advantages to be gained from developing and applying this king of application. A hypothetical example of a scenario option to facilitate the best conceptual understanding of what the application is, how it works, or the operating methodology, and when it might be applied is presented.

Horsham, Gary A. P.↗

NASA NTRS1992

MisTec - A software application for supporting space exploration scenario options and technology development analysis and planning

This structure and composition of a new, emerging software application, which models and analyzes space exploration scenario options for feasibility based on technology development projections is presented. The software application consists of four main components: a scenario generator for designing and inputting scenario options and constraints; a processor which performs algorithmic coupling and options analyses of mission activity requirements and technology capabilities; a results display which graphically and textually shows coupling and options analysis results; and a data/knowledge base which contains information on a variety of mission activities and (power and propulsion) technology system capabilities. The general long-range study process used by NASA to support recent studies is briefly introduced to provide the primary basis for comparison for discussing the potential advantages to be gained from developing and applying this kind of application. A hypothetical example of a scenario option to facilitate the best conceptual understanding of what the application is, how it works, or the operating methodology, and when it might be applied is presented.

Horsham, Gary A. P.↗

DOE OSTI2020

Quantifying the impacts of micro- and mild- hybrid vehicle technologies on fleetwide fuel economy and electrification

Micro- and mild-hybridization (jointly labeled as M-HEV) is gaining popularity as a cost-effective technology for fuel economy improvement, but whether and how M-HEV may compete against less efficient conventional internal combustion engine vehicles (ICEV), more efficient full hybrid electric vehicles (HEV), and plug-in electric vehicles (PEV) is not well understood. As such, this study aims at evaluating the impact of the market adoption of M-HEV on the average fuel economy of the new vehicle fleet and on the sales share of PEVs. The study reviews recent sales trends and market forecasts, and uses published estimates of manufacturing cost and fuel economy of M-HEV with an existing discrete choice model (Market Acceptance of Advanced Automotive Technologies or MA3T) to project the market penetration and impacts of M-HEV under different scenarios of M-HEV choice positions, designed to enhance conclusion robustness. It is found that among engine-based powertrain choices, micro-HEV appears to be the most cost-effective, followed by ICEVs, mild-HEV and finally full HEVs. M-HEV technologies are likely to improve fleetwide average fuel economy without significant adverse effects on sales of plug-in electric vehicles, and are likely to remain highly competitive outside PEVs through 2050.

33 ADVANCED PROPULSION SYSTEMS↗

DOE OSTI2022

Demonstration of NREL Modeling Capability to Design the Next Generation of Floating Offshore Wind Turbines with Stiesdal and Magellan Wind (Cooperative Research and Development Final Report)

This Technology Commercialization Fund (TCF) CRADA involved demonstration of NREL modeling capability using OpenFAST (formerly known as FAST) to design the next generation of floating offshore wind turbines (FOTW) with Stiesdal’s TetraSpar design. The objective of the project was to enable the design and optimization of next generation FOWT that show promise to make FOWT cost-competitive with other energy technologies by upgrading, verifying, and validating improvements to OpenFAST. This objective was achieved by (1) upgrading OpenFAST to compute floating substructure flexibility and member-level loads, which is critical to enable the design of floating substructures—especially newer designs that are streamlined, flexible, and cost-effective; (2) verifying the new OpenFAST capabilities through model-to-model comparisons and validating the capabilities through comparisons to empirical data generated with wave-tank testing, using TetraSpar data provided by Stiesdal; and (3) making available the upgraded OpenFAST tool to the wind energy community to enable next-generation floating wind designs.

17 WIND ENERGY↗

NASA NTRS2017

150 kW Class Solar Electric Propulsion Spacecraft Power Architecture Model

The National Aeronautics and Space Administration (NASA) Solar Electric Propulsion Technology Demonstration Mission (SEP TDM), in conjunction with PC Krause and Associates, has created a Simulink-based power architecture model for a 50 kilo-Watt (kW) solar electric propulsion system. NASA has extended this model to investigate 150 kW solar electric propulsion systems. Increasing the power capability to 150 kW is an intermediate step to the anticipated power requirements for Mars and other deep space applications. The high-power solar electric propulsion capability has been identified as a critical part of NASA’s future beyond-low-Earth-orbit for human-crewed exploration missions. This paper presents four versions of a 150 kW architecture, simulation results, and a discussion of their merits.

Power Control↗

DOE OSTI2022

An Application of a Modified Beta Factor Method for the Analysis of Software Common Cause Failures

This paper presents an approach for modeling software common cause failures (CCFs) within digital instrumentation and control (I&C) systems. CCFs consist of a concurrent failure between two or more components due to a shared failure cause and coupling mechanism. This work emphasizes the importance of identifying software-centric attributes related to the coupling mechanisms necessary for simultaneous failures of redundant software components. The groups of components that share coupling mechanisms are called common cause component groups (CCCGs). Most CCF models rely on operational data as the basis for establishing CCCG parameters and predicting CCFs. This work is motivated by two primary concerns: (1) a lack of operational and CCF data for estimating software CCF model parameters; and (2) the need to model single components as part of multiple CCCGs simultaneously. A hybrid approach was developed to account for these concerns by leveraging existing techniques: a modified beta factor model allows single components to be placed within multiple CCCGs, while a second technique provides software-specific model parameters for each CCCG. This hybrid approach provides a means to overcome the limitations of conventional methods while offering support for design decisions under the limited data scenario.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

NASA NTRS2010

Physics-Based Methods of Failure Analysis and Diagnostics in Human Space Flight

The Integrated Health Management (IHM) for the future aerospace systems requires to interface models of multiple subsystems in an efficient and accurate information environment at the earlier stages of system design. The complexity of modern aeronautic and aircraft systems (including e.g. the power distribution, flight control, solid and liquid motors) dictates employment of hybrid models and high-level reasoners for analysing mixed continuous and discrete information flow involving multiple modes of operation in uncertain environments, unknown state variables, heterogeneous software and hardware components. To provide the information link between key design/performance parameters and high-level reasoners we rely on development of multi-physics performance models, distributed sensors networks, and fault diagnostic and prognostic (FD&P) technologies in close collaboration with system designers. The main challenges of our research are related to the in-flight assessment of the structural stability, engine performance, and trajectory control. The main goal is to develop an intelligent IHM that not only enhances components and system reliability, but also provides a post-flight feedback helping to optimize design of the next generation of aerospace systems. Our efforts are concentrated on several directions of the research. One of the key components of our strategy is an innovative approach to the diagnostics/prognostics based on the real time dynamical inference (DI) technologies extended to encompass hybrid systems with hidden state trajectories. The major investments are into the multiphysics performance modelling that provides an access of the FD&P technologies to the main performance parameters of e.g. solid and liquid rocket motors and composite materials of the nozzle and case. Some of the recent results of our research are discussed in this chapter. We begin by introducing the problem of dynamical inference of stochastic nonlinear models and reviewing earlier results. Next, we present our analytical approach to the solution of this problem based on the path integral formulation. The resulting algorithm does not require an extensive global search for the model parameters, provides optimal compensation for the effects of dynamical noise, and is robust for a broad range of dynamical models. In the following Section the strengths of the algorithm are illustrated illustrated by inferring the parameters of the stochastic Lorenz system and comparing the results with those of earlier research. Next, we discuss a number of recent results in application to the development of the IHM for aerospace system. Firstly, we apply dynamical inference approach to a solution of classical three tank problems with mixed unknown continuous and binary parameters. The problem is considered in the context of ground support system for filling fuel tanks of liquid rocket motors. It is shown that the DI algorithm is well suited for successful solution of a hybrid version of this benchmark problem even in the presence of additional periodic and stochastic perturbation of unknown strength. Secondly, we illustrate our approach by its application to an analysis of the nozzle fault in a solid rocket motor (SRM). The internal ballistics of the SRM is modelled as a set of one-dimensional partial differential equations coupled to the dynamics of the propellant regression. In this example we are specifically focussed on the inference of discrete and continuous parameters of the nozzle blocking fault and on the possibility of an application of the DI algorithm to reducing the probability of "misses" of an on-board FD&P for SRM. In the next section re-contact problem caused by first stage/upper stage separation failure is discussed. The reaction forces imposed on the nozzle of the upper stage during the re-contact and their connection to the nozzle damage and to the thrust vector control (TVC) signal are obtained. It is shown that transient impact induced torquean be modelled as a response of an effective damped oscillator. A possible application of the DI algorithm to the inference of damage parameters and predicting fault dynamics ahead of time using the actuator signal is discussed. Finally, we formulate Bayesian inferential framework for development of the IHM system for in-flight structural health monitoring (SHM) of composite materials. We consider the signal generated by piezoelectric actuator mounted on composite structure generating elastic waves in it. The signal received by the sensor is than compared with the baseline signal. The possibility of damage inference is discussed in the context of development of the SHM.

Smelyanskiy, Vadim N.↗

DOE OSTI2024

MetaPoL: Immersive VR based Indoor Patterns of Life (PoL) and Anomalies Data Generation for Insider Threat Modeling in Nuclear Security

Insider threats are perhaps the most serious challenges that nuclear and radiological security systems face. Insiders pose such a great threat due to their access, authority, and knowledge, granting them opportunities to bypass dedicated nuclear and radiological security elements. For example, in one of the latest major insider threat incidents to nuclear security, the Doel-4 nuclear powerplant in Belgium suffered a shutdown, the threat of nuclear materials diversion, and long-term loss of tens of millions of dollars. Seven years of investigation concluded that it was an inside job and attempted sabotage. In this regard, there is an immediate need for R&D and technology integration in the domain of modeling indoor Patterns-of-Life (PoL) and anomaly detection. This can be achieved by using datasets of facility users’ mobility and activity, which can support the design of algorithms for insider threat modeling and detection. However, due to classification, privacy, sensitivity, and safety protocols, such datasets from real physical nuclear reactor facilities are not only hard to share, but also not always feasible to deploy and collect. Aiming to find an alternate solution, our proposed demonstration work - MetaPoL, is the first-ever (for the application space) immersive VR (virtual reality) environment of a real-world secure facility and allows users to move-and-stay through the designed indoor physical layout and also encounter NPCs (non-player characters) that emulate other facility users. In the MetaPoL an interactive user performs realistic spatio-temporal movement, dwelling and activities using a Meta Quest Pro VR headset, and that generates high-frequency (in time) high-resolution (in space) indoor spatial-temporal datasets that are valuable for PoL modeling and anomaly detection research specifically for insider threat modeling and detection mission. Such generated realistic, rich in context, and mission specific datasets can boost AI/Machine Learning based research for modeling and detecting insider threats in nuclear security and nonproliferation.

Gunaratne, Chathika↗