Search NASA⌕ Search

SEARCH · Search NASA

Results for “ENVIRONMENT MODEL”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 361 records · Page 20
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Adsorption of molecular iodine and alkyl iodides from spent-nuclear-fuel-reprocessing off-gas using reduced silver mordenite

Radioactive iodine is a hazardous byproduct of spent-nuclear-fuel reprocessing that must be removed from the off-gas stream before it can be discharged. Reduced silver mordenite (Ag 0 Z) is currently the baseline material for iodine capture in the U.S. Although the performance characteristics and capture mechanisms of I 2 and CH 3 I have been established, similar investigations into long-chain organic iodides have yet to be performed. In this study, thin beds of Ag 0 Z were loaded with I 2 , CH 3 I, C 4 H 9 I, and C 12 H 25 I (5 ppm to 50 ppm) carried in a dry air stream at 150°C. The maximum iodine capacity was 105 ± 5 mg I/g Ag 0 Z for all species. Saturated Ag 0 Z samples were characterized using scanning electron microscopy, X-ray fluorescence, X-ray photoelectron spectroscopy, diffuse reflectance UV–visible spectroscopy, pair distribution function analysis, and thermogravimetric analysis. Further, near-complete Ag utilization and similar physical/chemical properties were observed for all samples. Through a comparison with previous studies and an investigation of aged Ag 0 Z, we propose that iodine species react with Ag + at exchange sites, forming α-AgI within the mordenite channels, and with surface Ag 0 nanoparticles, yielding β-/γ-AgI. The available Ag sites in the interior (Ag + ) and exterior (Ag 0 ) of mordenite determine the adsorption capacity since α-AgI formation is limited by the total pore volume. Potential iodine uptake routes were summarized for aging and non-aging environments. A scalable predictive model was implemented for deep-bed iodine removal, and predictions were in good agreement with experimental data. Sensitivity analysis suggests that iodine uptake kinetics is governed by pore diffusion.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2022

Actinides in complex reactive media: A combined ab initio molecular dynamics and machine learning analytics study of transuranic ions in molten salts

The predominant ionic chemistry and the similarity in ionic radius of actinides make it very difficult to structurally distinguish them in liquids. In this work, while ab initio molecular dynamics shows that the f-states clearly affects the electronic properties, their impact on structural properties is not obvious. For the series of trivalent actinides U 3+ , Pu 3+ , Cm 3+ , Cf 3+ , Fm 3+ in molten NaCl and FLiBe, actinide ligand bonds have a higher degree of covalency in NaCl (than in FLiBe), and a higher degree of ionicity in FLiBe. Furthermore, a machine learned classification model can distinguish atomic environments of chemically similar actinides, as long as atoms beyond the first solvation shells are considered. Our work shows that only two types of descriptors are necessary to account for all the fluctuations in heavy metal/molten salt mixtures: The first descriptor represents the electronic state of the heavy metal, while the second encompasses the local coordination environment.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Designing resilient IoT and Edge Computing with federated tinyML

The rapid growth of the Internet of Things (IoT) and Edge Computing (EC) has brought significant conveniences to modern society but has also greatly expanded the cyber attack surfaces, particularly as these technologies are being increasingly integrated into critical systems such as power grids, healthcare, and smart homes. Here, to improve IoT/EC’s cybersecurity posture, we leveraged Artificial Intelligence (AI) and Machine Learning (ML) by employing tinyML to monitor voluminous IoT data for cyber threats while addressing devices’ resource constraints, and utilizing Federated Learning (FL) to share local detection knowledge across the system while preserving privacy. Building on our three-layer architecture combining tinyML and FL to enhance autonomous cyber attack detection, this paper demonstrated that the architecture improves detection accuracy, reduces resource consumption, and enables lightweight, secure IoT device monitoring. These results were validated using the public N-BaIoT dataset as well as real IoT network traffic data collected under multiple attack scenarios from our testbeds. Additionally, we introduced an enhanced FL methodology with a novel preprocessing stage, including federated feature selection and global preprocessor construction, to address IoT/EC data heterogeneity. We developed a physical IoT testbed for attack simulations and data collection, implemented a tinyML-powered detector for realistic model validation, and also built a virtual testbed for scalable evaluations of FL models across diverse network environments.

Cognitive cyber↗
DOE OSTI2024

DFT Analysis of the Binding of Rare Earth Nitrates at Internal and External Surfaces of MCM-22

MCM-22-type zeolites constitute a well-characterized tunable class of aluminosilicates suitable for elucidating the fundamental aspects of the binding of rare earth elements (REEs) in layered materials. Starting from the pure silica version ITQ-1 with a unit cell of Si 72 O 144 , a model for periodic bulk crystalline MCM-22 with a finite Al concentration is provided by replacing a Si atom with an Al atom in the unit cell at suitable tetrahedral sites near an internal pore surface. Then, a H atom is added to an O atom bridging Si and Al atoms to create a Brønsted acid site (BAS). There are no internal silanol groups in this bulk model. To generate a model for an external surface, we adopt the fully hydroxylated surface structure of a layer within the ITQ-1 precursor with two silanols per lateral unit cell. A BAS on the external surface can be generated by replacing a near-surface Si atom with an Al atom and adding a H atom, as above. The strength of binding at a BAS of REE, X, taken to be present in the solution phase as nitrates, is determined from the energy change in the reaction X(NO 3 ) 3 + ≡Si–{OH}–Al≡ → ≡Si–{OX(NO 3 ) 2 }–Al≡+ HNO 3 . The strength of binding at the silanols is determined similarly. Binding energies are determined from two approaches. The first performs periodic plane-wave density functional theory (DFT) total energy analysis for an entire unit cell of MCM-22. The second utilizes cluster models capturing the local environment of REE binding sites and performs DFT analysis with localized basis sets. The two approaches yield consistent results for Nd, revealing similarly strong binding at either an external or internal BAS, but much weaker binding at a silanol site. This is consistent with the picture deduced from recent experiments. Here, we also comment on binding at Al-bridged siloxane sites, which have been suggested as alternative binding sites to BAS.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

An Open‐Source, Physics‐Based, Tropical Cyclone Downscaling Model With Intensity‐Dependent Steering

Abstract An open‐source, physics‐based tropical cyclone (TC) downscaling model is developed, in order to generate a large climatology of TCs. The model is composed of three primary components: (a) a random seeding process that determines genesis, (b) an intensity‐dependent beta‐advection model that determines the track, and (c) a non‐linear differential equation set that determines the intensification rate. The model is entirely forced by the large‐scale environment. Downscaling ERA5 reanalysis data shows that the model is generally able to reproduce observed TC climatology, such as the global seasonal cycle, genesis locations, track density, and lifetime maximum intensity distributions. Inter‐annual variability in TC count and power‐dissipation is also well captured, on both basin‐wide and global scales. Regional TC hazard estimated by this model is also analyzed using return period maps and curves. In particular, the model is able to reasonably capture the observed return period curves of landfall intensity in various sub‐basins around the globe. The incorporation of an intensity‐dependent steering flow is shown to lead to regionally dependent changes in power dissipation and return periods. Advantages and disadvantages of this model, compared to other downscaling models, are also discussed.

Meteorology & Atmospheric Sciences↗
DOE OSTI2024

Avoiding fusion plasma tearing instability with deep reinforcement learning

For stable and efficient fusion energy production using a tokamak reactor, it is essential to maintain a high-pressure hydrogenic plasma without plasma disruption. Therefore, it is necessary to actively control the tokamak based on the observed plasma state, to manoeuvre high-pressure plasma while avoiding tearing instability, the leading cause of disruptions. This presents an obstacle-avoidance problem for which artificial intelligence based on reinforcement learning has recently shown remarkable performance. However, the obstacle here, the tearing instability, is difficult to forecast and is highly prone to terminating plasma operations, especially in the ITER baseline scenario. Previously, we developed a multimodal dynamic model that estimates the likelihood of future tearing instability based on signals from multiple diagnostics and actuators. Here we harness this dynamic model as a training environment for reinforcement-learning artificial intelligence, facilitating automated instability prevention. We demonstrate artificial intelligence control to lower the possibility of disruptive tearing instabilities in DIII-D, the largest magnetic fusion facility in the United States. The controller maintained the tearing likelihood under a given threshold, even under relatively unfavourable conditions of low safety factor and low torque. In particular, it allowed the plasma to actively track the stable path within the time-varying operational space while maintaining H-mode performance, which was challenging with traditional preprogrammed control. This controller paves the path to developing stable high-performance operational scenarios for future use in ITER.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2020

Radiation driven Hohlraum using 2 ω for ICF implosions at the NIF

Radiation flux symmetry in laser-irradiated Hohlraum environments is difficult to model and control and relies on the details of plasma evolution and laser energy deposition in the harsh plasma-filled Hohlraum over the duration of the laser pulse. This study presents a conceptual design and assesses the feasibility of using lasers to create a radiation drive where the implosion symmetry relies mainly on radiation transport. In this design, the ends of a capsule containing Hohlraum are irradiated by drive laser beams that are shielded from the view of the capsule. This configuration enables the use of frequency doubled light that has a higher power and energy threshold for the current capability of NIF, up to 670 TW and ∼3.5 MJ. We estimate, using VISRAD benchmarked against HYDRA calculations, that the same drive conditions that are currently being achieved in hybridE experiments at the NIF 270–290 at the equator can be reached in this new geometry and large 6.4 mm diameter Hohlraums. The radiation drive asymmetries in this design can be mitigated by shimming the capsule ablator thickness or through tailoring the shape of the shielding to the laser spots.

Kritcher, A. L. (ORCID:0000000296941088)↗
DOE OSTI2021

Multilevel-in-Space-and-Energy CMFD in VERA

For full-core modeling in the Virtual Environment for Reactor Analysis (VERA), the three-dimensional multigroup eigenvalue neutron transport problem is solved by MPACT. To improve the efficiency of MPACT, advancements have been made in the transport accelerator. Multilevel-in-energy and multilevel-in-space coarse mesh finite difference (CMFD) solvers were developed to improve the efficiency of the CMFD accelerator. In this paper a new multilevel-in-space-and-energy CMFD solver is developed with coarsening in both space and energy on every level. Several different strategies are investigated for coarsening groups in energy. Modified V-cycle and multiple-cycle algorithms are evaluated for solving the multilevel equations. The performance of these solvers is compared for typical full-core reactor physics problems.

42 ENGINEERING↗
DOE OSTI2024

Advanced EXAFS analysis techniques applied to the L -edges of the lanthanide oxides

The unique properties of the lanthanide (Ln) elements make them critical components of modern technologies, such as lasers, anti-corrosive films and catalysts. Thus, there is significant interest in establishing structure–property relationships for Ln-containing materials to advance these technologies. Extended X-ray absorption fine structure (EXAFS) is an excellent technique for this task considering its ability to determine the average local structure around the Ln atoms for both crystalline and amorphous materials. However, the limited availability of EXAFS reference spectra of the Ln oxides and challenges in the EXAFS analysis have hindered the application of this technique to these elements. The challenges include the limited k-range available for the analysis due to the superposition of L-edges on the EXAFS, multielectron excitations (MEEs) creating erroneous peaks in the EXAFS and the presence of inequivalent absorption sites. Herein, we removed MEEs to model the local atomic environment more accurately for light Ln oxides. Further, we investigated the use of cubic and non-cubic lattice expansion to minimize the fitting parameters needed and connect the fitting parameters to physically meaningful crystal parameters. The cubic expansion reduced the number of fitting parameters but resulted in a statistically worse fit. The non-cubic expansion resulted in a similar quality fit and showed non-isotropic expansion in the crystal lattice of Nd 2 O 3 . In total, the EXAFS spectra and the fits for the entire set of Ln oxides (excluding promethium) are included. The knowledge developed here can assist in the structural determination of a wide variety of Ln compounds and can further studies on their structure–property relationships.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Hardware-in-the-Loop Evaluation of an Advanced Distributed Energy Resource Management Algorithm

This paper presents the laboratory performance evaluation of voltage regulation under a new distributed energy resource management system (DERMS) algorithm via an advanced hardware-in-tbe-loop (HIL) platform. The HIL platform provides realistic testing in a laboratory environment, including the accurate modeling of a full-scale real-world distribution system from a utility partner, the DERMS software controller, and power hardware photovoltaic (PV) inverters. The new DERMS algorithm is developed based on online multiobjective optimization (OMOO) algorithms that perform fast dispatch of distributed solar PV simulated in a real-time digital simulator and real physical hardware devices. Experimental tests confirm the correct functioning of the HIL platform for evaluating controller algorithms and satisfactory voltage regulation performance of the developed OMOO algorithms.

41 EE - Solar Energy Technologies Office (EE-4S)↗
DOE OSTI2021

Performance Evaluation of Distributed Energy Resource Management Algorithm in Large Distribution Networks

This paper presents performance evaluation of hierarchical optimization and control for distributed energy resource management system (DERMS) in large distribution networks via an advanced hardware-in-the-loop (HIL) platform. The HIL platform provides realistic testing in a laboratory environment, including the accurate modeling of a full-scale distribution system of 11,000 nodes, the DERMS software controller, and 90 power hardware photovoltaics (PVs) and battery inverters. The applied DERMS algorithm is designed based on a realtime optimal power flow algorithm and implemented with acceleration design that performs fast dispatch of simulated PVs and real physical hardware DER devices every 4 seconds.

DERMS↗
DOE OSTI2020

Exploratory Investigation of Disengagements and Crashes in Autonomous Vehicles Under Mixed Traffic: An Endogenous Switching Regime Framework

Autonomous Vehicles (AVs) have a large potential to improve traffic safety but also pose some critical challenges. While AVs may help reduce crashes caused by human error, they still may experience failures of technologies and sensing, as well as decision-making errors in a mixed traffic environment. A disengagement refers to an AV transitioning control from autonomous systems to the trained test driver. The safety critical nature of disengagements makes it imperative to analyze disengagements and crashes together. In this study, we analyze both crashes and disengagements from real-world AV driving in California to fill the knowledge gap regarding the relationship between disengagements and crashes in a mixed traffic environment. A nested logit model was calibrated using three different outcomes: (1) disengagement with a crash, (2) disengagement with no crash, and (3) no disengagement with a crash. Furthermore, endogenous switching regime models were also calibrated to draw distinctions between the relation of disengagements and crashes while accounting for endogeneity effects. The results show that factors related to AV systems (such as software failures) and other roadway participants increase the propensity of a disengagement without a crash. Furthermore, AVs were observed to disengage less often as the technology matured over time. Marginal effects revealed an 8% decrease. The results thus suggest that disengagements are a part of AVs' safe performance and disengagement alerts may need to be triggered in order to avoid certain failures with current technology.

42 ENGINEERING↗
DOE OSTI2026

JANUS: Resilient and Adaptive Data Transmission for Enabling Timely and Efficient Cross-Facility Scientific Workflows

In modern science, the growing complexity of large-scale scientific projects has led to an increasing reliance on cross-facility scientific workflows, where resources and expertise from multiple institutions and geographic locations are leveraged to accelerate scientific discovery. These workflows often require transmitting huge amounts of scientific data through wide-area networks. Although high-speed networks like ESnet and transfer services such as Globus have improved data mobility, several challenges remain. The sheer volume of data can overwhelm network bandwidth, widely used transport protocols such as TCP suffer from inefficiencies due to retransmissions triggered by packet loss, and existing fault-tolerance mechanisms like erasure coding introduce substantial overhead. In this paper, we propose Janus, a resilient and adaptable data transmission approach designed for cross-facility scientific workflows. Unlike traditional TCP-based methods, Janus leverages UDP, integrates erasure coding for fault tolerance, and combines it with error-bounded lossy compression to reduce overhead. This novel design allows users to balance data transmission time and accuracy, optimizing transfer performance based on specific scientific requirements. Additionally, Janus dynamically adjusts erasure coding parameters in response to real-time network conditions, ensuring efficient data transfers even in fluctuating environments. We develop optimization models for determining ideal configurations and implement adaptive data transfer protocols to enhance reliability. Through extensive simulations and real-network experiments, we demonstrate that Janus significantly improves transfer efficiency while maintaining data fidelity.

Esaulov, Vladislav [Georgia State University, Atla↗
DOE OSTI2020

Gemma

Gemma is a linear electromagnetic code developed at Sandia National Laboratories based on the method of moments in the frequency domain, with the objective of supporting next-generation high-performance computing (HPC) platforms. Gemma provides full-wave computational electromagnetic modeling. As an example, Gemma models electromagnetic radiation (EMR) environments, including those resulting from radar (both hostile and friendly) and high-power-electromagnetic (HPEM) sources. Gemma refers to a suite of source code and scripts that aid in compiling, running, and testing the primary Gemma executable, which can be compiled for diverse platforms including CPUs, GPUs, and MICs by leveraging Sandia's Kokkos library.SAND2019-15221 M Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.

Zinser, Brian↗
DOE OSTI2021

Role-Based Access Control for Distributed Energy Resources v.1.0

The Role-Based Access Control (RBAC) for Distributed Energy Resources (DER) software is an automated and transparent stack for RBAC administrators to interact with RBAC policy. The package includes demonstrations of centralized and decentralized RBAC implementation. Both include simulated DER entities that are stored automatically in a centralized Lightweight Directory Access Protocol (LDAP) server. It also includes a REST-API to serve the HTTP requests of the RBAC administrators. A complete front-end is included to serve the users' needs. This software may be used by industry (DER vendors/utilities) as well as the research community to determine if a centralized or decentralized solution fits better the needs of an RBAC model in a DER environment. Additionally, parts of this software may be useful for developing implementations for specific needs. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525. SAND2021-8292 O

Johnson, Jay↗