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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

Multiphysics Demonstration of Temperature-Driven Assembly Bowing in SFRs using MOOSE-Based Codes

Core bowing is an important passive safety mechanism in liquid metal cooled fast reactors. When the core restraint system is properly designed, temperature and flux gradients influence assemblies in the core to bow into less reactive configurations during accident scenarios, resulting in negative reactivity feedback. Prediction of core bowing involves complex interplay of radiation transport, impacts of fluid flow and heat transfer on duct temperature, and mechanical responses to the induced temperature and flux gradients. Under the U.S. Department of Energy Office of Nuclear Energy’s Advanced Modeling and Simulation (NEAMS) Program [1], an integrated multiphysics approach is being developed to model the core bowing phenomena in liquid metal-cooled fast reactors with the Multiphysics Object Oriented Simulation Environment (MOOSE) [2]. In this methodology, the MOOSE-based reactor physics code Griffin [3] will solve the neutron transport equation and determine the power distribution. With the detailed power distribution from Griffin, the subchannel analysis codes MOOSE-Subchannel [4] and Pronghorn [5] are utilized to calculate the assembly temperature distribution. MOOSE’s Solid Mechanics [6] and Contact [7] Modules are leveraged to calculate the thermal expansion and duct bowing displacement with the duct wall temperature from thermal hydraulics calculation. In this work, an initial one-way coupling demonstration of the integrated multiphysics approach has been performed on a seven-assembly problem based on the sodium-cooled fast reactor ABR-1000 design [8]. The neutronics calculation with Griffin is not yet involved in the current simulation. MOOSE-Subchannel and Pronghorn evaluate fluid and solid temperature based on a fixed power distribution. In addition, one-way coupling is utilized in this coupled calculation, via Pronghorn passing the duct temperature data to the MOOSE Solid Mechanics calculation. An assessment of the Solid Mechanics module was performed in parallel to verify duct bowing behavior with duct-to-duct contact phenomenon [9]. The displacement from MOOSE Solid Mechanics is not yet transferred back and utilized in the Pronghorn and MOOSE-Subchannel calculation. This model will be available on the National Reactor Innovation Center (NRIC) Virtual Test Bed (VTB) repository [10]. Future stages of this work will involve solving problems of increasing complexity as well as adding more physics (e.g. reactor physics) to the integrated workflow to reach the end goal of modeling the core bowing phenomenon with an integrated multiphysics workflow.

22 - GENERAL STUDIES OF NUCLEAR REACTORS↗

Space Launch System Mission Flexibility Assessment

The Space Launch System (SLS) is envisioned as a heavy lift vehicle that will provide the foundation for future beyond low Earth orbit (LEO) missions. While multiple assessments have been performed to determine the optimal configuration for the SLS, this effort was undertaken to evaluate the flexibility of various concepts for the range of missions that may be required of this system. These mission scenarios include single launch crew and/or cargo delivery to LEO, single launch cargo delivery missions to LEO in support of multi-launch mission campaigns, and single launch beyond LEO missions. Specifically, we assessed options for the single launch beyond LEO mission scenario using a variety of in-space stages and vehicle staging criteria. This was performed to determine the most flexible (and perhaps optimal) method of designing this particular type of mission. A specific mission opportunity to the Jovian system was further assessed to determine potential solutions that may meet currently envisioned mission objectives. This application sought to significantly reduce mission cost by allowing for a direct, faster transfer from Earth to Jupiter and to determine the order-of-magnitude mass margin that would be made available from utilization of the SLS. In general, smaller, existing stages provided comparable performance to larger, new stage developments when the mission scenario allowed for optimal LEO dropoff orbits (e.g. highly elliptical staging orbits). Initial results using this method with early SLS configurations and existing Upper Stages showed the potential of capturing Lunar flyby missions as well as providing significant mass delivery to a Jupiter transfer orbit.

Monk, Timothy↗

Weather and Random Forest-based Load Profiling Approximation Models and its Transferability across Climate Zones

This study is to provide predictive understanding of the associations of various weather attributes with residential and commercial load profiles, for a variety of climate zones and seasons. In this work, machine learning (ML) approaches were used to identify and quantify the impacts of various weather attributes on residential and commercial electricity demand and its components across the western United States. Performance and transferability of the developed ML models were then evaluated across different temperate zones (e.g., southern, middle, and northern US) and across coastal, mid-continent, and wet zones, with inputs of weather condition data from the National Oceanic and Atmospheric Administration (NOAA) at representative weather stations. The predictive models were developed based on the ranked/screened factors using the regression tree (RT) and random forest (RF) approaches, for five different scenarios (seasons).

load composite, Random Forest, regression tree, lo↗

Simulating PACE Global Ocean Radiances

The NASA PACE mission is a hyper-spectral radiometer planned for launch in the next decade. It is intended to provide new information on ocean biogeochemical constituents by parsing the details of high resolution spectral absorption and scattering. It is the first of its kind for global applications and as such, poses challenges for design and operation. To support pre-launch mission development and assess on-orbit capabilities, the NASA Global Modeling and Assimilation Office has developed a dynamic simulation of global water-leaving radiances, using an ocean model containing multiple ocean phytoplankton groups, particulate detritus, particulate inorganic carbon (PIC), and chromophoric dissolved organic carbon (CDOC) along with optical absorption and scattering processes at 1 nm spectral resolution. The purpose here is to assess the skill of the dynamic model and derived global radiances. Global bias, uncertainty, and correlation are derived using available modern satellite radiances at moderate spectral resolution. Total chlorophyll, PIC, and the absorption coefficient of CDOC (aCDOC), are simultaneously assimilated to improve the fidelity of the optical constituent fields. A 5-year simulation showed statistically significant (P < 0.05) comparisons of chlorophyll (r = 0.869), PIC (r = 0.868), and a CDOC (r =0.890) with satellite data. Additionally, diatoms (r = 0.890), cyanobacteria (r = 0.732), and coccolithophores (r = 0.716) were significantly correlated with in situ data. Global assimilated distributions of optical constituents were coupled with a radiative transfer model (Ocean-Atmosphere Spectral Irradiance Model, OASIM) to estimate normalized water-leaving radiances at 1 nm for the spectral range 250-800 nm. These unassimilated radiances were within 0.074 mW/sq cm/micron/sr of MODIS-Aqua radiances at 412, 443, 488, 531, 547, and 667 nm. This difference represented a bias of 10.4% (model low). A mean correlation of 0.706 (P < 0.05) was found with global distributions of MODIS radiances. These results suggest skill in the global assimilated model and resulting radiances. The reported error characterization suggests that the global dynamical simulation can support some aspects of mission design and analysis. For example, the high spectral resolution of the simulation supports investigations of band selection. The global nature of the radiance representations supports investigations of satellite observing scenarios. Global radiances at bands not available in current and past missions support investigations of mission capability. PACE, ocean color, water-leaving radiances, biogeochemical model, radiative transfer model

PIC↗

Unifying radiative transfer models in computer graphics and remote sensing, Part I: A Survey

The constellation of Earth-observing satellites continuously collects measurements of scattered radiance, which must be transformed into geophysical parameters in order to answer fundamental scientific questions about the Earth. Retrieval of these parameters requires highly flexible, accurate, and fast forward and inverse radiative transfer models. Existing forward models used by the remote sensing community are typically accurate and fast, but sacrifice flexibility by assuming the atmosphere or ocean is composed of plane-parallel layers. Monte Carlo forward models can handle more complex scenarios such as 3D spatial heterogeneity, but are relatively slower. We propose looking to the computer graphics community for inspiration to improve the statistical efficiency of Monte Carlo forward models and explore new approaches to inverse models for remote sensing. In Part 1 of this work, we examine the evolution of radiative transfer models in computer graphics and highlight recent advancements that have the potential to push forward models in remote sensing beyond their current periphery of realism.

Radiative transfer↗

Transfer-AE: A novel autoencoder-based impact detection model for structural digital twin

Accurately detecting the location and intensity of impacts is crucial for ensuring structural safety. Currently, AI-based structural impact detection methods are widely used for their excellent detection accuracy. However, their generalization capability is limited by the scenarios present in the training data. Many complex and dangerous impact scenarios are difficult to conduct real-world experiments on to collect sufficient samples. To capture all impact scenarios and fully leverage the advantages of AI-based detection technologies, advanced methods involve combining real-world structural monitoring data with corresponding numerical models to construct digital twins. These methods continuously refine the created numerical models with limited real-world data and provide diverse impact scenarios through numerical model simulations. However, there are inevitable differences between digital models and physical models that are challenging to correct through mechanical means. This discrepancy in data distribution between the two models significantly hinders the application of digital twin technology in impact/event identification tasks. To address this challenge, this study proposes a novel model based on autoencoders, named Transfer-AE. Transfer-AE encodes the common features of digital twins in the latent space to bridge the uncertainty gap at a macro scale between numerical models and physical models and synchronously fits the magnitude and location of the impact load in the decoder. This enables consistent detection results for the same impact event, whether the sample comes from the numerical model or the physical model. Transfer-AE includes two operating modes: Mode 1 has a fixed computational complexity with stable inference speed, but the training cost and difficulty increase with data distribution. Mode 2's computational complexity increases with data distribution, but it has a fixed training cost and speed. In both cases involving the geodesic dome structure simulating a deep space habitat and the IASC-ASCE benchmark structure, Transfer-AE demonstrated the best performance in impact localization and quantification tasks compared to mainstream domain-adaptive transfer models.

Chengjia Han↗

Developing a common approach for classifying building stock energy models

Buildings contribute 40% of global greenhouse gas emissions; therefore, strategies that can substantially reduce emissions from the building stock are key components of broader efforts to mitigate climate change and achieve sustainable development goals. Models that represent the energy use of the building stock at scale under various scenarios of technology deployment have become essential tools for the development and assessment of such strategies. Within the past decade, the capabilities of building stock energy models have improved considerably, while model transferability and sharing has increased. Given these advancements, a new scheme for classifying building stock energy models is needed to facilitate communication of modeling approaches and the handling of important model dimensions. In this article, we present a new building stock energy model classification framework that leverages international modeling expertise from the participants of the International Energy Agency's Annex 70 on Building Energy Epidemiology. Drawing from existing classification studies, here we propose a multi-layer quadrant scheme that classifies modeling techniques by their design (top-down or bottom-up) and degree of transparency (black-box or white-box); hybrid techniques are also addressed. The quadrant scheme is unique from previous classification approaches in its non-hierarchical organization, coverage of and ability to incorporate emerging modeling techniques, and treatment of additional modeling dimensions. The new classification framework will be complemented by a reporting protocol and online registry of existing models as part of ongoing work in Annex 70 to increase the interpretability and utility of building stock energy models for energy policy making.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Multiphysics simulations of Self-Regulating performance of an optimized molten metal fuel microreactor design

Advanced microreactors are expected to play an indispensable role in reliable energy solutions for civilian/ military applications in off-grid regions and space applications such as power supplies for Lunar and Mars bases. An innovative fast neutron spectrum heat pipe microreactor (HP-MR) concept was recently proposed with two unique features: molten U-Mn fuel and heat pipes as the heat removal mechanism. The microreactor was designed to be self-regulated, solely relying on reactivity feedbacks from fuel temperature. The reactor design has been further optimized to provide sufficient engineering safety margin and effective heat removal. In this study, the self-regulating performance of the optimized molten metal fuel microreactor was investigated by multi-physics simulations (neutronics, heat-transfer and heat pipe modeling) based on the MOOSE MultiApps system. In conclusion, the responses of the reactor to a series of transient scenarios were simulated to demonstrate the exceptional and inherent safety features of the novel microreactor concept.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Redesigning large-scale multimodal transit networks with shared autonomous mobility services

Here, this study addresses a large-scale multimodal transit network design problem, with Shared Autonomous Mobility Services (SAMS) as both transit feeders and an origin-to-destination mode. The framework captures spatial demand and modal characteristics, considers intermodal transfers and express services, determines transit infrastructure investment and path flows, and generates transit routes. A system-optimal multimodal transit network is designed with minimum total door-to-door generalized costs of users and operators, satisfying transit origin-destination demand within a pre-set infrastructure budget. Firstly, the geography, demand, and modes in each zone are characterized with continuous approximation. The decisions of network link investment and multimodal path flows in zonal connection optimization are formulated as a minimum-cost multi-commodity network flow (MCNF) problem and solved efficiently with a mixed-integer linear programming (MILP) solver. Subsequently, the route generation problem is solved by expanding the MCNF formulation to minimize intramodal transfers. The model is illustrated through a set of experiments with the Chicago network comprised of 50 zones and seven modes, under three scenarios. The computational results present savings in traveler journey time and operator cost demonstrating the potential benefits of collaboration between multimodal transit systems and SAMS.

Autonomous vehicles↗

Radiation exposure predictions for short-duration stay Mars missions

The human radiation environment for several short-duration stay manned Mars missions is predicted using the Mission Radiation Calculation program, which was developed at NASA Langley Research Center. This program provides dose estimates for Galactic cosmic rays (GCR) and large and ordinary solar proton flare events for various amounts of effective spacecraft shielding and a given time history of the spacecraft's heliocentric position. The results of this study show that most of the missions can survive the most recent large flares if a 25 g/sq cm storm shelter is assumed. The dose predictions show that missions during solar minima are not necessarily the minimum dose cases, due to increased GCR contribution during this time period. The direct transfer mission studied has slightly lower doses than the outbound Venus swingby mission, with the greatest dose differences for the assumed worst case scenario. The GCR dose for a mission can be reduced by having the crew spend some fraction of its day nominally in the storm shelter.

Striepe, Scott A.↗

Coronal heating, nanoflares and MHD turbulence

Coronal heating is at the origin of the X-ray emission and mass loss from the sun and many other stars. While different scenarios have been proposed to explain the heating of magnetically confined and open regions of the corona, they must all rely on the transfer, storage and dissipation of the abundant energy present in photospheric motions. Here we focus on theories which rely on magnetic fields and electric currents both for the energy transfer and storage in the corona. The dissipation of this energy, whether in the form of reconnection in current sheets (nanoflare?) or the dissipation of MHD waves, depends crucially on the development of extremely small scales in the coronal magnetic field, where kinetic effects are likely to be fundamental. The question of whether coronal heating and flares may be viewed respectively as the macroscopic, low-energy average and the high-energy, temporally intermittent aspect of the same underlying driven, dissipative, turbulent system is also addressed, with emphasis placed on the main observational and theoretical stumbling blocks in the way of a confinement or disproof of such a conjecture.

Velli, M.↗

Implementation of Charged Particle Behavior in Discrete Element Method (DEM) Simulations

Lunar landers will agitate the surface of the Moon with an exhaust plume during descent which will, due to the particulate nature of the lunar regolith, loosen and eject grains from the surface. This ejection is not only coupled with the charged plume gas, but also results in significant particle-particle interactions. Settling of these grains after plume effects have subsided takes much longer than expected in a ballistic trajectory. The prevailing hypothesis attributes this behavior to the accumulated charge on the particles. We are thus developing a discrete element method (DEM) approach to explore these charged particle interactions on the lunar surface. The Large-scale Atomic/Molecular Massively Parallel Simulator (LAMMPS) Improved for General Granular and Granular Heat Transfer Simulations (LIGGGHTS) software package provides a DEM modeling framework for granular interactions. It includes many complexities such as non-spherical particle shapes, cohesion and frictional forces, and heat transfer, but has no provision for inter-particle electrostatic forces and charge transfer that are important to examine in the lunar environment. In this work, a standard Coulomb potential and a Yukawa potential are integrated into the LIGGGHTS framework to provide a basis for particle-particle electrostatic interactions, as well as a gravitational potential to enable inter-grain gravitational interactions. A preliminary approach to charge transfer between grains incorporating properties such as work function and electrical conductivity to the library of available material characteristics will be presented. Several scenarios have been simulated that include charged particle interactions within a diffuse granular gas, settling of charged grains into a regolith bed, sliding of granular material along an incline, and vibration of settled grains to produce a behavior similar to fluidization. There are numerous challenges to incorporate realistic interactions between complex lunar particles. Currently, grains are modeled to behave as if the entirety of the charge acts at the center of mass, such as conductors with spherical symmetry and insulators with homogeneously distributed charge. We are developing improvements that will include the use of non-spherical particle geometries, as well as reasonable approximations of insulating/dielectric materials that have non-uniform charge distributions. The cases simulated thus far will be examined in a relevant environment within a vacuum chamber to validate the simulations. These simulations will be bounded by experiments utilizing high-speed camera observations of the motion for validation. The grains in the experiment will exchange charge during their motion and this can be quantified by collection within a charge measurement device such as a Faraday cup. Such a device may be modeled within the software by defining an integration region and computing the contained charge as a function of simulation time, allowing for side-by-side comparison of simulated and measured bulk charging results. Any differences will be reconciled by updating the mathematical mechanisms described within the simulation suite. Successfully combining results from experiments within a relevant environment into the LIGGGHTS framework will improve modeling of the charged grain dynamics experienced on the Moon to provide insights into dust behavior for future lunar exploration missions.

Electrostatics↗

Flight Test Design and Implementation for Airspace Independent Surveillance Through a Distributed Ground Based Sensor Network

The paper presents a system architecture for distributed sensing, networking and computing, its hardware implementation, and execution of initial flight experiments to validate theoretical findings. It induces development of distributed sensing requirements, framework, and architecture, development of distributed ground node hardware prototypes, integration of all nodes and testing of baseline functionalities, integration of in-house developed perception, migration and tracking software packages, establishing flight scenario and flyable path for a selected UAS, flying the air vehicle along the path, recording sensors measurements, pre-processing them and transferring the resulting data to an optimal computing center. It also addresses the challenges related to pre-flight hardware calibration, clock synchronization, sensor registration and establishing a communication network. Sensors data processing results demonstrate the functionality of the presented distributed architecture and satisfactory performance of the applied technologies.

Target tracking↗

Flight Test Design and Implementation for Independent Surveillance of an Airspace Through a Distributed Ground Sensing Network

The paper presents a system architecture for distributed sensing, networking and computing, its hardware implementation, and execution of initial flight experiments to validate theoretical findings. It induces development of distributed sensing requirements, framework, and architecture, development of distributed ground node hardware prototypes, integration of all nodes and testing of baseline functionalities, integration of in-house developed perception, migration and tracking software packages, establishing flight scenario and flyable path for a selected UAS, flying the air vehicle along the path, recording sensors measurements, pre-processing them and transferring the resulting data to an optimal computing center. It also addresses the challenges related to pre-flight hardware calibration, clock synchronization, sensor registration and establishing a communication network. Sensors data processing results demonstrate the functionality of the presented distributed architecture and satisfactory performance of the applied technologies.

Distributed sensing↗

DeepFreeze: Towards Scalable Asynchronous Checkpointing of Deep Learning Models

In the age of big data, deep learning has emerged as a powerful tool to extract insight and exploit its value, both in industry and scientific applications. One common pattern emerging in such applications is frequent checkpointing of the state of the learning model during training, needed in a variety of scenarios: analysis of intermediate states to explain features and correlations with training data, exploration strategies involving alternative models that share a common ancestor, knowledge transfer, resilience, etc. However, with increasing size of the learning models and popularity of distributed data-parallel training approaches, simple checkpointing techniques used so far face several limitations: low serialization performance, blocking I/O, stragglers due to the fact that only a single process is involved in checkpointing. This paper proposes a checkpointing technique specifically designed to address the aforementioned limitations, introducing efficient asynchronous techniques to hide the overhead of serialization and I/O, and distribute the load over all participating processes. Experiments with two deep learning applications (CANDLE and ResNet) on a pre-Exascale HPC platform (Theta) shows significant improvement over state-of-art, both in terms of checkpointing duration and runtime overhead.

checkpointing↗

Economic and programmatic considerations for advanced transportation propulsion technology

Requirements for space transportation will increase after the Space Shuttle becomes operational. Shuttle derivatives and new earth-to-orbit vehicles are compared economically. The addition of both one and two new vehicle types are considered. Programmatic considerations are included in deriving a scenario which appears reasonable and includes the Space Shuttle, a heavy-lift cargo derivative of the Shuttle, a unique dual-fuel orbit transfer vehicle, and a small new earth-to-orbit vehicle in the foreseeable future. Large new orbital transfer and earth-to-orbit vehicles would be added when needed.

Martin, J. A.↗

National Launch System KSC facilities and operations

The current planning for the launch site ground operations and facilities required at the Kennedy Space Center to accommodate the National Launch System (NLS) are described. Special consideration is given to the program activities associated with reducing costs for ground operations and with the ground operations vehicle processing scenarios for launching the NLS vehicles from KSC. The KSC facilities described include the Payload Encapsulation Facility, the Mobile Launcher Platform, and the Cargo Transfer Vehicle Checkout Facility. Attention is also given to the modifications of existing facilities required to accommodate the NLS facilities and the transportation and handling equipment.

Evans, R. T., Jr.↗

Analytic orbit plane targeting for orbit transfers about an oblate planet

This paper develops closed-form expressions which accurately model variations in orbital inclination and longitude of the ascending node due to the influence of the J2 oblateness perturbation. These analytic expressions are particularly useful in defining perturbed orbit transfer planes which naturally regress into the target intercept position for Lambert-type transfers and in compensating for differential nodal regression between two orbiting vehicles in rendezvous targeting problems. Results of example problems for each of these scenarios demonstrate that they accurately compensate for these oblateness effects.

Mchenry, R. L.↗