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DOE OSTI2021

Ice Multiplication by Fragmentation during Quasi-Spherical Freezing of Raindrops: A Theoretical Investigation

Ice multiplication by fragmentation during collision–freezing of supercooled rain or drizzle is investigated. A zero-dimensional dynamical system describes the time evolution of number densities of supercooled drops and ice crystals in a mixed-phase cloud. The characteristic time scale for this collision–freezing ice fragmentation is controlled by the collision efficiency, the number of ice fragments per freezing event, and the available number concentration of supercooled drops. The rate of the process is proportional to the number of supercooled drops available. Thus, ice may multiply extensively, even when the fragmentation number per freezing event is relatively small. The ratio of total numbers of ice particles to those from the first ice, namely, the “ice-enhancement factor,” is controlled both by the number of fragments per freezing event and by the available number concentration of supercooled drops in a similar manner. Especially, when ice fragmentation by freezing of supercooled drops is considered in isolation, the number of originally existing supercooled drops multiplied by the fragmentation number per freezing event yields the eventual number of ice crystals. When supercooled drops are continuously generated by coalescence, ice crystals from freezing fragmentation also continuously increase asymptotically at a rate equal to the generation rate of supercooled drops multiplied by the fragmentation number per freezing event. All these results are expressed by simple analytical forms, thanks to the simplicity of the theoretical model. These parameters can practically be used as a means for characterizing observed mixed-phase clouds.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2023

Thermal Hydraulic Experimental Test Article - Fiscal Year 2023 (Final Report)

The Thermal Hydraulic Experimental Test Article (THETA) is a facility that is used to develop sodium components and instrumentation as well as acquire experimental data for validation of reactor thermal hydraulic and safety analysis codes. The facility simulates nominal conditions as well as protected/unprotected loss of flow accidents in a sodium-cooled fast reactor (SFR). High fidelity distributed temperature profiles of the developed flow field may be acquired with Rayleigh backscatter based optical fiber temperature sensors. The facility was designed in partnership with systems code experts to tailor the experiment to ensure the most relevant and highest quality data for code validation. THETA is comprised of a traditional primary coolant and secondary coolant system. The primary system is submerged in the pool of sodium and consists of a pump, electrically heated core, intermediate heat exchanger, and connected piping and thermal barriers (redan). The secondary system, located outside of the sodium pool, consists of a pump, sodium to air heat exchanger, and connected piping and valves. To date a test matrix has been completed utilizing the primary system of THETA. These tests, along with computational fluid dynamics and systems code models, determined the heat transfer across the core barrel and intermediate heat exchanger outlet was too great to effectively represent scaled thermal hydraulic phenomena of a liquid metal cooled reactor. Therefore, a significant effort was made to remove the primary system from the METL 28” test vessel #4 and clean the residual sodium from the primary system to facilitate upgrades. Thermal insulation was then incorporated in the core barrel and intermediate heat exchanger outlets. The primary system was then replaced, and a series of tests were performed to assess the performance of the thermal insulation. With primary system testing and upgrades complete, the secondary system could then be brought online. The tube side of the shell-and-tube intermediate heat exchanger was installed onto the primary system flange to begin installing the secondary system. The support structure for the secondary system was then erected on the METL mezzanine alongside the THETA primary system to facilitate installation of the secondary system components (sodium-to-air heat exchanger, flowmeter and pump). The piping and expansion tank were welded into the secondary system. Non-destructive examination of the secondary system welds was completed in order to satisfy ASME B31.3 pipe code for class M process fluids. The heating system and insulation were then added to prepare the system to be filled with sodium. The ancillary electrical equipment was installed which included the pump control box, blower VFD, pipe heater control system, etc. The secondary system will be filled, and a test matrix will be completed in early FY2024.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

DOE OSTI2025

VA EDH Advanced Software Pipeline Framework Report: Enhancing Automation and Scalability

The VA Environmental Determinants of Health (EDH) Advanced Software Pipeline Framework is designed to enhance the efficiency, scalability, and security of geospatial data processing workflows. This framework integrates modern data orchestration and containerization technologies, including Prefect for workflow automation, Docker for containerization, and PostgreSQL/PostGIS for geospatial data storage and analysis. It ensures standardized, reproducible, and automated data processing, supporting VA objectives related to substance use risk assessment and recovery research. The pipeline addresses key scalability and performance challenges through horizontal and vertical scaling, high-performance computing (HPC) integration, parallel processing, task caching, and dynamic resource allocation. These optimizations improve throughput and reduce latency, allowing the system to efficiently manage large and complex datasets. Additionally, security and compliance measures—such as data encryption (SSL), Role-Based Access Control (RBAC), and adherence to GDPR and HIPAA standards—safeguard sensitive information throughout data transmission and storage. A key implementation of this framework includes the automation of shelter list geolocation workflows, ensuring that up-to-date data is readily available for VA decision-making. Lessons learned from this project include the transition from in-memory processing to incremental storage writes, improving resource management and reliability. Future enhancements aim to expand automation, integrate AI-driven anomaly detection, and incorporate high-performance computing resources. This framework provides a scalable, secure, and adaptable solution for managing geospatial datasets, reinforcing the VA’s ability to support clinical and strategic initiatives through data-driven decision-making.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2024

Limitations for Quantum Algorithms to Solve Turbulent and Chaotic Systems

We investigate the limitations of quantum computers for solving nonlinear dynamical systems. In particular, we tighten the worst-case bounds of the quantum Carleman linearisation (QCL) algorithm answering one of their open questions. We provide a further significant limitation for any quantum algorithm that aims to output a quantum state that approximates the normalized solution vector. Given a natural choice of coordinates for a dynamical system with one or more positive Lyapunov exponents and solutions that grow sub-exponentially, we prove that any such algorithm has complexity scaling at least exponentially in the integration time. As such, an efficient quantum algorithm for simulating chaotic systems or regimes is likely not possible.

97 MATHEMATICS AND COMPUTING↗

NASA NTRS1980

Emergency in-flight egress opening for general aviation aircraft

An emergency in-flight egress system was installed in a light general aviation airplane. The airplane had no provision for egress on the left side. To avoid a major structural redesign for a mechanical door, an add on 11.2 kg (24.6 lb) pyrotechnic-actuated system was developed to create an opening in the existing structure. The skin of the airplane was explosively severed around the side window, across a central stringer, and down to the floor, creating an opening of approximately 76 by 76 cm. The severed panel was jettisoned at an initial velocity of approximately 13.7 m/sec. System development included a total of 68 explosive severance tests on aluminum material using small samples, small and full scale flat panel aircraft structural mockups, and an actual aircraft fuselage. These tests proved explosive sizing/severance margins, explosive initiation, explosive product containment, and system dynamics. This technology is applicable to any aircraft of similar construction.

Bement, L. J.↗

NASA NTRS1981

Medium-range, objective predictions of thunderstorm location and severity for aviation

This paper presents a computerized technique for medium-range (12-48h) prediction of both the location and severity of thunderstorms utilizing atmospheric predictions from the National Meteorological Center's limited-area fine-mesh model (LFM). A regional-scale analysis scheme is first used to examine the spatial and temporal distributions of forecasted variables associated with the structure and dynamics of mesoscale systems over an area of approximately 10 to the 6th sq km. The final prediction of thunderstorm location and severity is based upon an objective combination of these regionally analyzed variables. Medium-range thunderstorm predictions are presented for the late afternoon period of April 10, 1979, the day of the Wichita Falls, Texas tornado. Conventional medium-range thunderstorm forecasts, made from observed data, are presented with the case study to demonstrate the possible application of this objective technique in improving 12-48 h thunderstorm forecasts for aviation.

Wilson, G. S.↗

NASA NTRS1982

Identification of aerodynamic indicial functions using flight data

It is pointed out that the use of indicial function representation provides a model superior to the aerodynamic derivative model. Specific derivatives can be approximated from the indicial models. The model can also be used to compute equivalent stability and control parameters not usually available from flight data. It is shown that derivatives regarding the angle-of-attack and the side slip angle can be derived directly from the indicial functions without any identifiability problem. Attention is given to the pitch moment coefficient, linear indicial function representation, the identification problem for the pitch moment equation, the identifiability of linear systems, parametric representations of the indicial functions, an identification technique, angle-of-attack and pitch rate dynamics in the pitch plane, multivariate linear models, nonlinear aerodynamic indicial functions, measurement system accuracy, and poststall and spin-entry data from a scaled research vehicle.

Gupta, N. K.↗

NASA NTRS1989

Parallel and vector computation for stochastic optimal control applications

A general method for parallel and vector numerical solutions of stochastic dynamic programming problems is described for optimal control of general nonlinear, continuous time, multibody dynamical systems, perturbed by Poisson as well as Gaussian random white noise. Possible applications include lumped flight dynamics models for uncertain environments, such as large scale and background random atmospheric fluctuations. The numerical formulation is highly suitable for a vector multiprocessor or vectorizing supercomputer, and results exhibit high processor efficiency and numerical stability. Advanced computing techniques, data structures, and hardware help alleviate Bellman's curse of dimensionality in dynamic programming computations.

Hanson, F. B.↗

NASA NTRS1993

Next generation initiation techniques

Four-dimensional data assimilation strategies can generally be classified as either current or next generation, depending upon whether they are used operationally or not. Current-generation data-assimilation techniques are those that are presently used routinely in operational-forecasting or research applications. They can be classified into the following categories: intermittent assimilation, Newtonian relaxation, and physical initialization. It should be noted that these techniques are the subject of continued research, and their improvement will parallel the development of next generation techniques described by the other speakers. Next generation assimilation techniques are those that are under development but are not yet used operationally. Most of these procedures are derived from control theory or variational methods and primarily represent continuous assimilation approaches, in which the data and model dynamics are 'fitted' to each other in an optimal way. Another 'next generation' category is the initialization of convective-scale models. Intermittent assimilation systems use an objective analysis to combine all observations within a time window that is centered on the analysis time. Continuous first-generation assimilation systems are usually based on the Newtonian-relaxation or 'nudging' techniques. Physical initialization procedures generally involve the use of standard or nonstandard data to force some physical process in the model during an assimilation period. Under the topic of next-generation assimilation techniques, variational approaches are currently being actively developed. Variational approaches seek to minimize a cost or penalty function which measures a model's fit to observations, background fields and other imposed constraints. Alternatively, the Kalman filter technique, which is also under investigation as a data assimilation procedure for numerical weather prediction, can yield acceptable initial conditions for mesoscale models. The third kind of next-generation technique involves strategies to initialize convective scale (non-hydrostatic) models.

Warner, Tom↗

NASA NTRS2008

Electron Precipitation Parameters and Ionospheric Conductances Inferred from Auroral Images Acquired by the Visible Imaging Systems (VIS) on the Polar Spacecraft

The Visible Imaging System (VIS) on the polar spacecraft provided time sequences of auroral images at multiple wavelengths that yield information of auroral dynamics on a global scale with a spatial resolution of - 20 km and temporal resolution of approx. 1 minute. Time sequences of VIS images in which the aurora was highly dynamic are used to infer global maps for the electron precipitation parameters, energy flux and characteristic energies, and ionospheric conductances. The maps are inferred from the corresponding VIS images using an auroral model (Lumerzheim et al., 1987). The temporal and spatial resolution of the VIS inferred patterns are unprecedented. The inferred patterns are highly structured and vary significantly on a time scale of less than 5 minutes. These patterns can be very beneficial for global physics-based numerical models for the high-latitude ionosphere which previously had to rely on statistical models for the electron precipitation and ionospheric conductance.

Sigwarth, John B.↗

NASA NTRS2019

Physically-Informed Artificial Neural Networks for Atomistic Modeling of Materials

A new approach is presented for the development of classical interatomic potentials using physically-informed neural networks (PINN) combined with an analytical bond-order atomic interaction model. Due to the strong physical underpinnings, the PINN potentials demonstrate much better transferability than the existing machine-learning potentials while drastically improving the accuracy in comparison with traditional potentials. PINN potentials can be constructed for both metallic and covalent materials in a unified manner. A number of applications of PINN potentials to large-scale molecular dynamics and Monte Carlo simulations and calculation of thermal and mechanical properties of diverse materials are demonstrated. Some of the specific materials systems include silicon and aluminum, as well as alloys and compounds. Computational aspects of PINN potentials are discussed and future developments in this field are outlined.

J Hickman↗

NASA NTRSDate not supplied

Detecting Risk and Anomalies in Airplane Dynamics Through Entropic Analysis of Time Series Data

Despite recent efforts to move away from traditional threshold exceedance detection methods for aircraft state monitoring, modern aircraft still rely on safety thresholds to communicate to pilots the identification of an anomaly in the aircraft when a threshold is surpassed. Current anomaly detection methods mainly depend on uninterpretable machine learning models to learn complex patterns and relationships contained in the time series data of aircraft. Although these methods are capable of identifying known anomalies, their deficiency in interpretability presents a challenge when translating them to different aircraft. To overcome this deficiency, entropic analysis of aircraft dynamics seeks to characterize the complexity, or lack thereof, of the aircraft dynamics prior to the development of a risk scenario. This complexity characterization provides a more straightforward summary of state changes in the dynamics of flight variables. To build a foundation for entropic analysis, we analyzed the complexity of unstable approaches, an anomalous event present in many of today’s aviation accidents. The analysis revealed a statistically significant difference in the complexity distribution of flight variables under a stable approach versus an unstable approach. These differences in complexity were especially notable minutes before an approach was identified as unstable. Moreover, the multiscale entropic analysis revealed the presence of signal complexity at multiple time scales across multiple time windows before landing. By capturing state changes and corrections in the aircraft dynamics using entropy, advanced, yet still interpretable, sensor systems based on entropic frameworks from this study can be constructed in the future using classical machine learning approaches.

Risk detection↗

NASA NTRSDate not supplied

Advanced Information Systems Technology for NASA Earth System Digital Twins (ESDT)

ESA and NASA have both started programs to design and develop Digital Twins of the Earth and/or Earth systems. Organized around interconnected, multi-domain, high-scale modeling capabilities, the three major components of an Earth System Digital Twin are a continuously updated Digital Replica of the Earth System of interest, dynamic Forecasting models, and Impact Assessment capabilities. Earth System Digital Twins integrate diverse Earth and human activity models, continuous observations, and information system capabilities to provide unified, comprehensive representations and predictions that can be utilized for monitoring the health of the Planet, as well as for developing actionable information to support decision making. More generally, Digital Twins will help researchers better understand the fundamental Earth systems that impact everything from wildfires to climate change. This Townhall will first provide a short description of ESA’s, NASA’s and CNES’s current efforts in Digital Twins: • Destination Earth (DestinE) is the first initiative of the European Union to create a Digital Twin of the Earth, particularly focused on weather and climate, and as a coordinated effort between the European Centre for Medium-Range Weather Forecasts (ECMWF), ESA and the European Organization for the Exploitation of Meteorological Satellites (EUMETSAT). • Additionally, ESA is developing several Digital Twin Earth Precursor Activities to study some of the key scientific and technical challenges associated with building a “Digital Twin Earth”. These include forests, hydrology, Antarctica, food systems, oceans, and climate hot spots Digital Twin prototypes. • NASA Earth Science Technology Office (ESTO)’s Advanced Information Systems Technology (AIST) Program has started an initiative in Earth System Digital Twins (ESDT), with 14 current projects in this area, developing various information systems technologies and prototypes that will help prepare the development of future NASA Digital Twins. • CNES is currently developing the concept of a Digital Twin Factory (DTF), which relies on a data lake, a high computing capability using clouds and/or HPC and has thematic algorithms and methodologies able to generate registered and coherent layers of information in order to enrich a datacube from which physical indicators can be computed spatially. NASA, ESA and CNES are also currently defining science use cases that will be presented during the townhall; those and a few short discussions of current projects will serve as a starting point to engage a dialogue about Digital Twins of the Earth with the IGARSS community.

earth science remote sensing; Information systems↗

NASA NTRSDate not supplied

NASA Earth System Digital Twins (ESDT) Use Cases

NASA AIST Program is now designing and developing Digital Twins of the Earth and/or Earth systems. Organized around interconnected, multi-domain, high-scale modeling capabilities, the three major components of an Earth System Digital Twin are a continuously updated Digital Replica of the Earth System of interest, dynamic Forecasting models, and Impact Assessment capabilities. In order to define ESDT's benefits to Earth Science, as well as the AIST capabilities required to develop such systems, the AIST Program has been developed 6 science use cases corresponding to 6 of the main Earth Science domains.

J. Le Moigne↗

NASA NTRS2023

Earth System Digital Twin (ESDT) Architecture Framework

NASA AIST Program is now designing and developing Digital Twins of the Earth and/or Earth systems. Organized around interconnected, multi-domain, high-scale modeling capabilities, the three major components of an Earth System Digital Twin are a continuously updated Digital Replica of the Earth System of interest, dynamic Forecasting models, and Impact Assessment capabilities. This document identifies the key features and capabilities needed in an ESDT and describes the major notional components of the system and some key relationships, while providing room for a variety of architectures to respond to them. It provides a generic system diagram of an ESDT, including the interfaces to external observing systems and models.

Jacqueline Le Moigne↗

NASA NTRSDate not supplied

Earth System Digital Twins (ESDT) Definition and Science Use Cases

Earth Science Remote Sensing; Information Systems↗

DOE OSTI2026

iDDS: intelligent distributed dispatch and scheduling for workflow orchestration

The intelligent distributed dispatch and scheduling (iDDS) service is a versatile workflow orchestration system designed for large-scale, distributed scientific computing. iDDS extends traditional workload and data management by integrating data-aware execution, conditional logic, and programmable workflows, enabling automation of complex and dynamic processing pipelines. Originally developed for the ATLAS experiment at the large hadron collider, iDDS has evolved into an experiment-agnostic platform that supports both template-driven workflows and a Function-as-a-Task model for Python-based orchestration. This paper presents the architecture and core components of iDDS, highlighting its scalability, modular message-driven design, and integration with systems such as PanDA and Rucio. We demonstrate its versatility through real-world use cases: fine-grained tape resource optimization for ATLAS, orchestration of large Directed Acyclic Graph (DAG) workflows for the Rubin Observatory, distributed hyperparameter optimization for machine learning applications, active learning for physics analyses, and AI-assisted detector design at the electron–ion collider. By unifying workload scheduling, data movement, and adaptive decision-making, iDDS reduces operational overhead and enables reproducible, high-throughput workflows across heterogeneous infrastructures. We conclude with current challenges and future directions, including interactive, cloud-native, and serverless workflow support.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2024

Modular Staged Pressurized Oxy-Combustion (SPOC) Power Plant for Coal and Biomass – Integration of Combustor Boiler and DCC

Utilities and grid operators worldwide are under significant pressure to incorporate intermittent renewable sources while strategizing on how to maintain the necessary stability and reliability of the grid. The development of a power plant which will be capable of flexible operation to meet the needs of the grid as more intermittent sources like wind and solar energy are incorporated is key to maintain the reliability of the grid. Through the use of innovative and cutting-edge technologies that improve efficiency and reduce carbon emissions, and being small compared to today's conventional utility-scale power plants, the modular Staged, Pressurized Oxy-Combustion (SPOC) process envisioned by and under development at Washington University in St. Louis (WUSTL) has the potential to achieve these goals. Specifically, the process offers: 1) a modular plant design that allows for better operational flexibility; 2) the utilization of fuel-staging and pressurized oxy-combustion, resulting in smaller plant size, improved plant efficiency, and reduced costs for pollutant and CO2 removal compared to traditional power plants with post-combustion capture technology; and 3) the use of small modular boilers and pollutant removal units that can be constructed off-site leading to reduced capital costs for the plant. WUSTL is advancing the development of the critical components for the SPOC power plant, including the integrated combustor-boiler system and the direct contact cooler. To demonstrate the boiler convective section and to obtain critical data for commercial-scale pressurized boiler design, a simulated convective heat transfer boiler test section was designed and integrated with the combustor (radiant section). A direct contact cooler (DCC) was integrated with the combustor-boiler to demonstrate the dynamic operation of the integrated system and the performance of the DCC, including the efficiency for simultaneous removal of NOx and SOx. This talk will present an update on the evaluation of the critical components for system integration, including heat transfer data from the simulated boiler, scrubbing efficiency for the DCC under different operating conditions, and CFD modeling and validation for burner and boiler development.

Magalhaes, Duarte↗