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NASA NTRS2003

Monitoring of Observation Errors in the Assimilation of Satellite Ozone Data

The stratospheric ozone layer protects life on Earth from the harmful effects of solar ultravioiet radiation. The ozone layer is currently in a fragile state because of depletion caused by man-made chemicals, especially chlorofluorocarbons. The state of the ozone layer is being monitored and evaluated by scientific experts around the world, in order to help policy makers assess the impacts of international protocols that control the production and release of ozone depleting chemicals. Scientists use a variety ozone measurements and models in order to form a comprehensive picture about the current state of the ozone layer, and to predict the future behavior (expected to be a recovery, as the abundance of the depleting chemicals decreases). Among the data sets used, those from satellite-borne instruments have the advantage of providing a wealth of information about the ozone distribution over most of the globe. Several instruments onboard American and international satellites make measurements of the properties of the atmosphere, from which atmospheric ozone amounts are estimated; long-term measurement programs enable monitoring of trends in ozone. However, the characteristics of satellite instruments change in time. For example, the instrument lenses through which measurements are made may deteriorate over time, or the satellite orbit may drift so that measurements over each location are made later and later in the day. These changes may increase the errors in the retrieved ozone amounts, and degrade the quality of estimated ozone amounts and of their variability. Our work focuses on combining the satellite ozone data with global models that capture atmospheric motion and ozone chemistry, using advanced statistical techniques: this is known as data assimilation. Our method provides a three-dimensional global ozone distribution that is consistent with both the satellite measurements and with our understanding of processes (described in the models) that control ozone distribution. Through the monitoring of statistical properties of the agreement between the data and the model, this approach also enables us to detect changes in the quality of ozone data retrieved from satellite-borne instrument measurements. This paper demonstrates that calculations of the changes in satellite data quality, and the impact these changes on the estimates of the global ozone distribution, can assist in maintaining the uniform quality of the satellite ozone data throughout the lifetime of these instruments, thus contributing to our understanding of long-term ozone change.

Stajner, Ivanka↗

DOE OSTI2022

Monitoring and prediction of porosity in laser powder bed fusion using physics-informed meltpool signatures and machine learning

In this work we accomplished the monitoring and prediction of porosity in laser powder bed fusion (LPBF) additive manufacturing process. This objective was realized by extracting physics-informed meltpool signatures from an in-situ dual-wavelength imaging pyrometer, and subsequently, analyzing these signatures via computationally tractable machine learning approaches. Porosity in LPBF occurs despite extensive optimization of processing conditions due to stochastic causes. Hence, it is essential to continually monitor the process with in-situ sensors for detecting and mitigating incipient pore formation. In this work a tall cuboid-shaped part (10 mm × 10 mm × 137 mm, material ATI 718Plus) was built with controlled porosity by varying laser power and scanning speed. This test caused various types of porosity, such as lack-of-fusion and keyhole formation, with varying degrees of severity in the part. The meltpool was continuously monitored using a dual-wavelength imaging pyrometer installed in the machine. Physically intuitive process signatures, such as meltpool length, temperature distribution, and ejecta (spatter) characteristics, were extracted from the meltpool images. Subsequently, relatively simple machine learning models, e.g., K-Nearest Neighbors, were trained to predict both the severity and type of porosity as a function of these physics-informed meltpool signatures. These models resulted in a prediction accuracy exceeding 95% (statistical F1-score). The same analysis was carried out with a complex, black-box deep learning convolutional neural network which directly used the meltpool images instead of physics-informed features. The convolutional neural network produced a comparable F1-score in the range of 89–97%. Finally, these results demonstrate that using pragmatic, physics-informed meltpool signatures within a simple machine learning model is as effective for flaw prediction in LPBF as using a complex and computationally demanding black-box deep learning model.

36 MATERIALS SCIENCE↗

DOE OSTI2023

Predicting Outcomes of Nanoparticle Attachment by Connecting Atomistic, Interfacial, Particle, and Aggregate Scales

Predicting nanoparticle aggregation and attachment phenomena requires a rigorous understanding of the interplay among crystal structure, particle morphology, surface chemistry, solution conditions, and interparticle forces, yet no comprehensive picture exists. We used an integrated suite of experimental, theoretical, and simulation methods to resolve the effect of solution pH on the aggregation of boehmite nanoplatelets, a case study with important implications for the environmental management of legacy nuclear waste. Real-time observations showed that the particles attach preferentially along the (010) planes at pH 8.5 and the (101) planes at pH 11. To rationalize these results, we established the connection between key physicochemical phenomena across the relevant length scales. Starting from molecular-scale simulations of surface hydroxyl reactivity, we developed an interfacial-scale model of the corresponding electrostatic potentials, with subsequent particle-scale calculations of the resulting driving forces allowing successful prediction of the attachment modes. Finally, we scaled these phenomena to understand the collective structure at the aggregate-scale . Here, our results indicate that facet-specific differences in surface chemistry produce heterogeneous surface charge distributions that are coupled to particle anisotropy and shape-dependent hydrodynamic forces, to play a key role in controlling aggregation behavior.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2022

Individualized Degradation Modeling and Prognostics in a Heterogeneous Group via Incorporating Intrinsic Covariate Information

Not provided.

Automation & Control Systems↗

DOE OSTI2022

Current status and grand challenges for small wind turbine technology

While modern wind turbines have become by far the largest rotating machines on Earth with further upscaling planned for the future, a renewed interest in small wind turbines (SWTs) is fostering energy transition and smart grid development. Small machines have traditionally not received the same level of aerodynamic refinement as their larger counterparts, resulting in lower efficiency, lower capacity factors, and therefore a higher cost of energy. In an effort to reduce this gap, research programs are developing worldwide. With this background, the scope of the present study is 2-fold. In the first part of this paper, an overview of the current status of the technology is presented in terms of technical maturity, diffusion, and cost. The second part of the study proposes five grand challenges that are thought to be key to fostering the development of small wind turbine technology in the near future, i.e. (1) improving energy conversion of modern SWTs through better design and control, especially in the case of turbulent wind; (2) better predicting long-term turbine performance with limited resource measurements and proving reliability; (3) improving the economic viability of small wind energy; (4) facilitating the contribution of SWTs to the energy demand and electrical system integration; (5) fostering engagement, social acceptance, and deployment for global distributed wind markets. To tackle these challenges, a series of unknowns and gaps are first identified and discussed. Based on them, improvement areas are suggested, for which 10 key enabling actions are finally proposed.

17 WIND ENERGY↗

NASA NTRS1999

A Simple Two Aircraft Conflict Resolution Algorithm

Conflict detection and resolution methods are crucial for distributed air-ground traffic management in which the crew in the cockpit, dispatchers in operation control centers and air traffic controllers in the ground-based air traffic management facilities share information and participate in the traffic flow and traffic control imctions.This paper describes a conflict detection and a conflict resolution method. The conflict detection method predicts the minimum separation and the time-to-go to the closest point of approach by assuming that both the aircraft will continue to fly at their current speeds along their current headings. The conflict resolution method described here is motivated by the proportional navigation algorithm. It generates speed and heading commands to rotate the line-of-sight either clockwise or counter-clockwise for conflict resolution. Once the aircraft achieve a positive range-rate and no further conflict is predicted, the algorithm generates heading commands to turn back the aircraft to their nominal trajectories. The speed commands are set to the optimal pre-resolution speeds. Six numerical examples are presented to demonstrate the conflict detection and resolution method.

Chatterji, Gano B.↗

NASA NTRS2015

Architecture, Voltage, and Components for a Turboelectric Distributed Propulsion Electric Grid

The development of a wholly superconducting turboelectric distributed propulsion system presents unique opportunities for the aerospace industry. However, this transition from normally conducting systems to superconducting systems significantly increases the equipment complexity necessary to manage the electrical power systems. Due to the low technology readiness level (TRL) nature of all components and systems, current Turboelectric Distributed Propulsion (TeDP) technology developments are driven by an ambiguous set of system-level electrical integration standards for an airborne microgrid system (Figure 1). While multiple decades' worth of advancements are still required for concept realization, current system-level studies are necessary to focus the technology development, target specific technological shortcomings, and enable accurate prediction of concept feasibility and viability. An understanding of the performance sensitivity to operating voltages and an early definition of advantageous voltage regulation standards for unconventional airborne microgrids will allow for more accurate targeting of technology development. Propulsive power-rated microgrid systems necessitate the introduction of new aircraft distribution system voltage standards. All protection, distribution, control, power conversion, generation, and cryocooling equipment are affected by voltage regulation standards. Information on the desired operating voltage and voltage regulation is required to determine nominal and maximum currents for sizing distribution and fault isolation equipment, developing machine topologies and machine controls, and the physical attributes of all component shielding and insulation. Voltage impacts many components and system performance.

electric faults↗

DOE OSTI2023

Grand Challenges for Small Wind: Results of the European Academy Study

ENGINEERING,WIND ENERGY↗

NASA NTRS2005

Permeable Surface Corrections for Ffowcs Williams and Hawkings Integrals

The acoustic prediction methodology discussed herein applies an acoustic analogy to calculate the sound generated by sources in an aerodynamic simulation. Sound is propagated from the computed flow field by integrating the Ffowcs Williams and Hawkings equation on a suitable control surface. Previous research suggests that, for some applications, the integration surface must be placed away from the solid surface to incorporate source contributions from within the flow volume. As such, the fluid mechanisms in the input flow field that contribute to the far-field noise are accounted for by their mathematical projection as a distribution of source terms on a permeable surface. The passage of nonacoustic disturbances through such an integration surface can result in significant error in an acoustic calculation. A correction for the error is derived in the frequency domain using a frozen gust assumption. The correction is found to work reasonably well in several test cases where the error is a small fraction of the actual radiated noise. However, satisfactory agreement has not been obtained between noise predictions using the solution from a three-dimensional, detached-eddy simulation of flow over a cylinder.

Lockard, David P.↗

NASA NTRS1995

Flow structure generated by perpendicular blade vortex interaction and implications for helicopter noise predictions

This report summarizes accomplishments and progress for the period ending April 1995. Much of the work during this period has concentrated on preparation for an analysis of data produced by an extensive wind tunnel test. Time has also been spent further developing an empirical theory to account for the effects of blade-vortex interaction upon the circulation distribution of the vortex and on preliminary measurements aimed at controlling the vortex core size.

Devenport, William J.↗

NASA NTRS2015

CFD Modeling of the Multipurpose Hydrogen Test Bed (MHTB) Self-Pressurization and Spray Bar Mixing Experiments in Normal Gravity: Effect of the Accommodation Coefficient on the Tank Pressure

A CFD model for simulating the self-pressurization of a large scale liquid hydrogen storage tank is utilized in this paper to model the MHTB self-pressurization experiment. The kinetics-based Schrage equation is used to account for the evaporative and condensi ng interfacial mass flows in this model. The effect of the accommodation coefficient for calculating the interfacial mass transfer rate on the tank pressure during tank selfpressurization is studied. The values of the accommodation coefficient which were considered in this study vary from 1.0e-3 to 1.0e-1 for the explicit VOF model and from 1.0e-4 to 1.0e-3 for the implicit VOF model. The ullage pressure evolutions are compared against experimental data. A CFD model for controlling pressure in cryogenic storage tanks by spraying cold liquid into the ullage is also presented. The Euler-Lagrange approach is utilized for tracking the spray droplets and for modeling the interaction between the droplets and the continuous phase (ullage). The spray model is coupled with the VOF model by performing particle tracking in the ullage, removing particles from the ullage when they reach the interface, and then adding their contributions to the liquid. Droplet-ullage heat and mass transfer are modeled. The flow, temperature, and interfacial mass flux, as well as droplets trajectories, size distribution and temperatures predicted by the model are presented. The ul lage pressure and vapor temperature evolutions are compared with experimental data obtained from the MHTB spray bar mixing experiment. The effect of the accommodation coefficient for calculating the interfacial and droplet mass transfer rates on the tank pressure during mixing of the vapor using spray is studied. The values used for the accommodation coefficient at the interface vary from 1.0e-5 to 1.0e-2. The droplet accommodation coefficient values vary from 2.0e-6 to 1.0e-4.

cryogenic fluid storage↗

DOE OSTI2022

Origins of magnetic memory and strong exchange bias bordering magnetic compensation in mixed-lanthanide systems

Here, the unexpected physical phenomena resulting from the seemingly inconsequential substitutions of chemically similar lanthanide elements in the Pr 1-x Gd x ScGe system are exploited to further the understanding of rare-earth magnetism and inform materials design. By directly probing magnetic moments of crystallographically indistinguishable Pr and Gd we solve the puzzles of how an unusual magnetic memory and strong exchange bias emerge at specific, easily predictable chemistries. Both effects are rooted in a robust antiparallel arrangement of large 4f magnetic moments of light and heavy lanthanides. This enables precise control of nearly zero net magnetization either opposed to, or aligned with, the external magnetic field that persists over a wide range of temperatures and fields. Further, spontaneous perturbations in the random distribution of lanthanide ions makes strong exchange bias possible in bulk single-phase compounds bordering magnetic compensation, consequently expanding the materials base beyond artificial magnetic multilayers and broadening the range of potential applications of the phenomenon.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

NASA NTRS1989

An evaluative model of system performance in manned teleoperational systems

Manned teleoperational systems are used in aerospace operations in which humans must interact with machines remotely. Manual guidance of remotely piloted vehicles, controling a wind tunnel, carrying out a scientific procedure remotely are examples of teleoperations. A four input parameter throughput (Tp) model is presented which can be used to evaluate complex, manned, teleoperations-based systems and make critical comparisons among candidate control systems. The first two parameters of this model deal with nominal (A) and off-nominal (B) predicted events while the last two focus on measured events of two types, human performance (C) and system performance (D). Digital simulations showed that the expression A(1-B)/C+D) produced the greatest homogeneity of variance and distribution symmetry. Results from a recently completed manned life science telescience experiment will be used to further validate the model. Complex, interacting teleoperational systems may be systematically evaluated using this expression much like a computer benchmark is used.

Haines, Richard F.↗

NASA NTRS2006

A Simple Two Aircraft Conflict Resolution Algorithm

Conflict detection and resolution methods are crucial for distributed air-ground traffic management in which the crew in, the cockpit, dispatchers in operation control centers sad and traffic controllers in the ground-based air traffic management facilities share information and participate in the traffic flow and traffic control functions. This paper describes a conflict detection, and a conflict resolution method. The conflict detection method predicts the minimum separation and the time-to-go to the closest point of approach by assuming that both the aircraft will continue to fly at their current speeds along their current headings. The conflict resolution method described here is motivated by the proportional navigation algorithm, which is often used for missile guidance during the terminal phase. It generates speed and heading commands to rotate the line-of-sight either clockwise or counter-clockwise for conflict resolution. Once the aircraft achieve a positive range-rate and no further conflict is predicted, the algorithm generates heading commands to turn back the aircraft to their nominal trajectories. The speed commands are set to the optimal pre-resolution speeds. Six numerical examples are presented to demonstrate the conflict detection, and the conflict resolution methods.

Chatterji, Gano B.↗

NASA NTRS2012

Peak-Seeking Optimization of Spanwise Lift Distribution for Wings in Formation Flight

A method is presented for the optimization of the lift distribution across the wing of an aircraft in formation flight. The usual elliptical distribution is no longer optimal for the trailing wing in the formation due to the asymmetric nature of the encountered flow field. Control surfaces along the trailing edge of the wing can be configured to obtain a non-elliptical profile that is more optimal in terms of minimum drag. Due to the difficult-to-predict nature of formation flight aerodynamics, a Newton-Raphson peak-seeking controller is used to identify in real time the best aileron and flap deployment scheme for minimum total drag. Simulation results show that the peak-seeking controller correctly identifies an optimal trim configuration that provides additional drag savings above those achieved with conventional anti-symmetric aileron trim.

Hanson, Curtis E.↗

DOE OSTI2025

Initial Uncertainty Analysis of Carbon Tetrachloride Contamination and Remediation in the Ringold A and Lower Mud Units at the Central Plateau

The long-term effectiveness of groundwater cleanup at the Hanford Site Central Plateau depends on predictive models that can capture key uncertainties in contaminant fate and transport. Carbon tetrachloride (CCl 4 ), a persistent and toxic compound, presents particular challenges due to variability in degradation rates, uncertainty in initial plume distribution, and subsurface heterogeneity. These uncertainties directly influence plume persistence, migration pathways, and remedy performance, and thus must be systematically evaluated to support long-term remediation planning. To address these gaps, a large-scale Monte Carlo analysis was conducted using the Plateau to River (P2R) model framework. The modeling approach parameterized three primary uncertainty factors: (1) degradation rate, (2) initial plume distribution, and (3) hydraulic conductivity. Degradation was represented as a first-order process, with half-lives ranging from 70 to 700 years. Initial plume distributions were created using a geostatistical simulation method (sgsim), which generates many equally plausible versions of how contaminants might be distributed underground. From this, 100 different scenarios were mapped onto the P2R grid. Variability in hydraulic conductivity was represented in a similar way, with 100 scenarios each for the Ringold Lower Mud and Ringold A units (layers 6 and 7), based on fitted exponential variograms and conditioned to well data. In total, more than 1000 realizations were simulated to assess plume behavior under uncertainty. Results demonstrate that degradation kinetics exert the strongest control over plume persistence: Shorter half-lives produced rapid mass reduction, while longer half-lives yielded persistent plumes with limited attenuation. A nonlinear response was observed, with steep mass reductions at half-lives greater than 200 years and near-linear declines beyond this threshold, reflecting interactions between degradation and pumping. The initial plume distribution strongly influenced early transport patterns, with broader sources generating larger plume footprints, although pump-and-treat operations constrained plume migration to managed areas. By comparison, hydraulic conductivity variability in the Ringold units had only a secondary influence, modifying spreading behavior without altering the dominant migration pathways governed by source configuration and hydraulic controls. Overall, the analysis highlights that uncertainty in degradation rate and initial plume configuration are the primary drivers of variability in plume predictions, while conductivity heterogeneity plays a limited role. These findings underscore the need for improved site-specific data on degradation processes and source characterization to enhance the reliability of long-term performance assessments and to better inform remedial decision-making at the Central Plateau.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2022

The Future of Energy Efficiency for U.S. Buildings - Drivers and Market Scenarios

This paper identifies likely drivers of building efficiency over the next ten years and expectations for how efficiency markets may evolve over this period. To prepare these predictions, we conducted an extensive literature review, interviewed 22 experts, reviewed legislation and executive orders in 12 states, and implemented a detailed questionnaire completed by 41 efficiency practitioners. The two most important drivers revealed by our research are (1) public policies and regulations, particularly those associated with climate change mitigation and adaptation and (2) the cost of energy relative to the cost of delivering efficiency. Other important drivers are technology changes, economic conditions, social priorities, and industry (including utility) business practices for increasing the uptake of efficiency in buildings. Our research indicates that efficiency markets will increasingly focus on supporting building decarbonization and enabling demand flexibility through the use of controls in grid-interactive efficient buildings and communities. Efficiency improvements for specific technologies (e.g., heat pumps, controls, and windows) and technological advances not specific to energy technologies (e.g., interoperability, artificial intelligence, and universal internet access) will improve the efficacy of efficiency measures and actions. Marketing of efficient products and services will increasingly focus on grid services, decarbonization, non-energy benefits for consumers, and integration with other distributed energy resources (DERs). We anticipate increased investment in disadvantaged and historically underserved communities, recognizing the social, health, and safety benefits of efficient energy usage and remediating historical biases. Lastly, we predict that while state and local government actions will vary, jurisdictions will increase their efficiency goals overall.

Schiller, Steven R↗

DOE OSTI2023

Predicting Safety Rod Reactivity Insertion in the Advanced Test Reactor

The Advanced Test Reactor (ATR), and complimentary zero-power ATR Critical (ATRC) reactor, located at Idaho National Labs (INL), are undergoing conversion from Highly Enriched Uranium (HEU) to Low Enriched Uranium (LEU). Both have a variety of testing locations that can receive large variations in flux due to its unique serpentine design, consisting of five lobes surrounding nine flux traps (see Figure 1). Initial criticality and power distribution throughout the core are controlled by core-external outer shim control cylinders (OSCCs). Distinct test loops allow for testing at specific temperatures, pressures, and irradiation conditions such as flux and fission density. The ATR is one of the key nuclear engineering research and testing facilities within the DOE National Laboratory Complex, and the ATRC supports its operation [1]. Currently, the Office of Material Management and Minimization (M3) within the National Nuclear Security Administration of the DOE is working to convert the remaining research reactors, including the ATR, from 93% HEU fuel to 19.75% LEU fuel (LEU) to support non-proliferation [2]. Extensive materials testing at INL and internationally has demonstrated that a high-density uranium molybdenum (U 10Mo) alloy can meet the performance requirements of the remaining high powered research reactors. The current LEU fuel element design is named the LOWE element. However, there are many technical challenges to address before the conversion to LEU can be successful, including the accurate characterization of the reactor core physics with LEU fuel. To ensure safe operation of the ATR, reactor engineers prepare a CSAP (Core Safety Assurance Package) before each cycle. The purpose of the CSAP is to verify the reactor performance calculation used to determine if the selected fuel loading meets operational, experimental, and safety criteria. Many of the criteria in the CSAP are limits on reactivity insertion in various accident scenarios.

42 ENGINEERING↗