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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 253 records · Page 14

CONTROL AND DATA ACQUISITION IN A CYBER-PHYSICAL MIDSTREAM TESTBED

This thesis presents the development of a laboratory-scale cyber–physical midstream pipeline testbed designed to address this gap and support research in industrial control systems security. The platform integrates pumps, valves, sensors, programmable logic controllers (PLCs), and a human–machine interface (HMI) to emulate the monitoring and control architecture of real pipeline operations. The physical process is implemented as a closed-loop liquid circulation system designed to replicate flow behavior characteristic of midstream pipeline infrastructure. The testbed enables real-time data acquisition of key process variables, including flow rate and pressure facilitating the generation of datasets representative of normal pipeline operation. A threat model encompassing common ICS attack vectors was developed, including sensor spoofing, command injection, false data injection, denial-of-service attacks, and relay manipulation. Multiple attack scenarios were implemented and evaluated to demonstrate how cyber intrusions targeting sensors, actuators, networks, and software propagate into measurable physical consequences in pipeline flow and pressure. The developed platform serves as a practical, cost-effective environment for experimentation, education, and future cybersecurity research in midstream pipeline systems.

42 ENGINEERING↗

Spatio-temporal multivariate cluster evolution analysis for detecting and tracking climate impacts

Recent years have seen a growing concern about climate change and its impacts. While Earth System Models (ESMs) can be invaluable tools for studying the impacts of climate change, the complex coupling processes encoded in ESMs and the large amounts of data produced by these models, together with the high internal variability of the Earth system, can obscure important source-to-impact relationships. Here, this paper presents a novel and efficient unsupervised data-driven approach for detecting statistically-significant impacts and tracing spatio-temporal source-impact pathways in the climate through a unique combination of ideas from anomaly detection, clustering and Natural Language Processing (NLP). Using as an exemplar the 1991 eruption of Mount Pinatubo in the Philippines, we demonstrate that the proposed approach is capable of detecting known post-eruption impacts/events. We additionally describe a methodology for extracting meaningful sequences of post-eruption impacts/events by using NLP to efficiently mine frequent multivariate cluster evolutions, which can be used to confirm or discover the chain of physical processes between a climate source and its impact(s).

Anomaly detection↗

Predictor-corrector models for lightweight massive machine-type communications in Industry 4.0

Future Industry 4.0 scenarios are characterized by seamless integration between computational and physical processes. To achieve this objective, dense platforms made of small sensing nodes and other resource constraint devices are ubiquitously deployed. All these devices have a limited number of computational resources, just enough to perform the simple operation they are in charge of. The remaining operations are delegated to powerful gateways that manage sensing nodes, but resources are never unlimited, and as more and more devices are deployed on Industry 4.0 platforms, gateways present more problems to handle massive machine-type communications. Although the problems are diverse, those related to security are especially critical. To enable sensing nodes to establish secure communications, several semiconductor companies are currently promoting a new generation of devices based on Physical Unclonable Functions, whose usage grows every year in many real industrial scenarios. Those hardware devices do not consume any computational resource but force the gateway to keep large key-value catalogues for each individual node. In this context, memory usage is not scalable and processing delays increase exponentially with each new node on the platform. In this paper, we address this challenge through predictor-corrector models, representing the key-value catalogues. Models are mathematically complex, but we argue that they consume less computational resources than current approaches. The lightweight models are based on complex functions managed as Laurent series, cubic spline interpolations, and Boolean functions also developed as series. Unknown parameters in these models are predicted, and eventually corrected to calculate the output value for each given key. The initial parameters are based on the Kane Yee formula. An experimental analysis and a performance evaluation are provided in the experimental section, showing that the proposed approach causes a significant reduction in the resource consumption.

97 MATHEMATICS AND COMPUTING↗

A Dose Assessment Model for Radioactive Waste Exposed by Gully Erosion at West Valley - 20513

The Western New York Nuclear Service Center (WNYNSC), located approximately 48 km south of Buffalo, New York, is the site of a former nuclear fuel reprocessing and radioactive waste disposal facility. Spent nuclear fuel was processed there from 1966 to 1972, leaving behind radioactive and chemical wastes in two disposal areas and a waste tank farm. Site operations also resulted in releases of radioactivity to site soils, groundwater, and to surface waters draining the site. The New York State Energy Research and Development Authority (NYSERDA) and the U.S. Department of Energy (DOE) are collaborating in a process of decision making for decommissioning those facilities remaining at the WNYNSC following the completion of Phase 1 decommissioning. Neptune and Company, Inc. (Neptune) was contracted to develop a probabilistic performance assessment (PPA) computer model to assist the agencies in this process. The PPA Model includes a contaminant transport component focusing on the movement of contaminants within and among environmental media including groundwater and surface water transport, contaminant translocation by plants and animals, diffusion, and erosion. The model also includes evaluation of potential exposure and health effects for a Resident Farmer exposure scenario, where the Resident Farmer represents a critical group, described as that group of individuals reasonably expected to receive the greatest exposure to residual radioactivity for any applicable set of circumstances. The West Valley Site is located in the glaciated Allegheny Plateau region of western New York State. The waste reprocessing and disposal areas were constructed on a relatively fat area of plateau dissected by drainages of Buttermilk Creek, including Erdman Brook, Franks Creek, and Quarry Creek. An important aspect of the contaminant transport component of the PPA model is consideration of erosive processes such as slumping of the stream slopes and the advance of gullies from these streams. These erosion processes remove material from the plateau, growing the size of the creek valleys and making them wider and deeper. Of particular interest for the impact of erosion is radioactive waste contained in the Nuclear Regulatory Commission (NRC)-Licensed Disposal Area (NDA), the New York State-Licensed Disposal Area (SDA), and residual radiological inventory in the underground storage tanks at the Waste Tank Farm (WTF). The PPA Model is organized around geographically-defined facilities which were constructed upon the plateau, including the NDA, SDA, and WTF. Ongoing stream erosion processes will potentially transfer radioactive waste and residual inventory from these facilities to the ground surface on adjacent hillslope areas where erosion has breached the facility. Hence, it is important to evaluate the consequences of potential exposures to a Resident Farmer on the hillslopes below a breached facility. Two interrelated aspects of the dose assessment model related to hillslope exposure are discussed: 1) representation of the physical processes related to transport of radionuclides from facilities onto the hillslopes, and from the hillslopes into adjoining creeks where contaminated material migrates downstream with surface water and sediment, and; 2) adaptation of the activities associated with the Resident Farmer scenario to assess potential exposures to contamination in the hillslope areas. This discussion will cover the conceptual basis of the hillslope exposure and transport models, and also implementation in the PPA computer model. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Linear Boltzmann transport for jet propagation in the quark-gluon plasma: Inelastic processes and jet modification

A linear Boltzmann transport (LBT) Monte Carlo model has been developed to describe jet propagation and interaction with the quark-gluon plasma (QGP) in relativistic heavy-ion collisions. A complete set of elastic-scattering processes and medium-induced gluon emissions based on the higher-twist formalism are incorporated for both jet shower and medium recoil partons. It has been employed to describe experimental data on large transverse momentum hadron and jet spectra, correlation and jet substructures in high-energy heavy-ion collisions. Here, we document in detail the structure of the model and validation of the Monte Carlo implementations of the physics processes in LBT, in particular, the inelastic process of medium-induced gluon radiation. We carry out a comprehensive examination of the jet-medium interaction as implemented in LBT through energy loss and momentum broadening of a single hard parton, the energy and transverse momentum transfer from leading partons to medium-induced gluons and jet-induced medium excitation, and medium modification of reconstructed jets in a static and uniform medium. With realistic and event-by-event hydrodynamic medium in heavy-ion collisions, we compute and compare with experimental data on the jet cone-size dependence of the single inclusive jet suppression at both the BNL Relativistic Heavy-Ion Collider (RHIC) and the CERN Large Hadron Collider (LHC), the dijet asymmetry at the LHC and γ-jet correlation at RHIC. Effects of medium-induced gluon emissions and jet-induced medium excitation on jet observables are systematically examined. Rescatterings of the radiated gluons and recoil partons with the QGP are found essential to account for the enhancement of soft particle yield toward the edge of the jet cone.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Kinetic effects of self-organization in low-temperature magnetized plasmas (Final Report for DE-SC0019045: 9/1/2018-8/31/2019)

The research goal of this Early Career Research Program project is to advance the science of low temperature magnetized plasmas using first-principles kinetic, e.g., solving the Boltzmann equation, models. A better understanding of the plasma transport properties, such as electrical resistivity and thermal conductivity must be obtained to better control and design magnetized plasma sources. A key physical phenomenon in low-temperature magnetized plasmas is the self-organization of plasma flows, e.g., coherent plasma structures and transition between different discharge modes. Understanding the physics of coherent plasma structures has been identified as one of the four important frontier topics in a recent workshop by the Office of Fusion Energy Science. These self-emerging plasma patterns results from the nonlinear coupling between plasma constituents (ions, electrons, and neutral atoms), electromagnetic fields, and materials. The physics of low-temperature magnetized plasmas is particularly complex because (i) the collisionless instabilities affect collisional phenomena (ionization, transport, etc.) and vice versa and (ii) the presence of materials (sheath, electron injection, etc.) influences the bulk plasma properties in low-temperature plasma (LTP) devices. Computational models of these plasma flows remain challenging because the plasma density can vary several orders of magnitudes, a wide range of temporal and spatial scales must be resolved, the phenomena are inherently three-dimensional, and various physical processes, such as wall interaction, instabilities, inelastic collisions, etc., must be simultaneously and self-consistently taken into account. Understanding the fundamental transport mechanisms in cross-field configurations enables additional controllability of plasma properties and electron energy distribution functions (EEDFs).

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Using real-time data analysis to conduct next-generation synchrotron fatigue studies

Next-generation experimental techniques, like high energy X-ray diffraction microscopy (HEDM), usher in new opportunities to collect the grain-scale data necessary for understanding the evolving processes that drive fatigue failure. In this study, we present a framework for monitoring the evolution of a deforming polycrystal, in real-time, by applying principal component analysis (PCA) to raw X-ray diffraction image data. We applied this framework to inform in-situ HEDM measurements of a cyclically loaded Inconel-718 superalloy. Further, we discovered correlations between PCA of the diffraction data and the physical processes in the polycrystal. Lastly, we discuss extending this framework in future HEDM fatigue studies.

36 MATERIALS SCIENCE↗

Relativistic Magnetic Reconnection in Astrophysical Plasmas: A Powerful Mechanism of Nonthermal Emission

Magnetic reconnection—a fundamental plasma physics process, where magnetic field lines of opposite polarity annihilate—is invoked in astrophysical plasmas as a powerful mechanism of nonthermal particle acceleration, able to explain fast-evolving, bright high-energy flares. Near black holes and neutron stars, reconnection occurs in the relativistic regime, in which the mean magnetic energy per particle exceeds the rest mass energy. This review reports recent advances in our understanding of the kinetic physics of relativistic reconnection (RR): ▪ Kinetic simulations have elucidated the physics of plasma heating and nonthermal particle acceleration in RR. ▪ The physics of radiative RR, with its self-consistent interplay between photons and reconnection-accelerated particles—a peculiarity of luminous, high-energy astrophysical sources—is the new frontier of research. ▪ RR plays a key role in global models of high-energy sources, in terms of both global-scale layers and reconnection sites generated as a by-product of local magnetohydrodynamic instabilities. We summarize themes of active investigation and future directions, emphasizing the role of upcoming observational capabilities, laboratory experiments, and new computational tools.

acceleration of particles↗

Metal dissolution from first principles: Potential-dependent kinetics and charge transfer

Metal dissolution and its inverse process are integral to both corrosion and electrodeposition; however, many mechanistic details regarding the dissolution process are challenging to decipher. These include how ion dissolution kinetics and charge transfer are influenced by the competition between metal and solvent interactions under an electrode potential. Here, in this work, we introduce a computational framework based on density functional theory with grand-canonical treatment of electrons to directly predict the potential energy landscape for metal dissolution at a constant potential. Using aluminum as an example, we demonstrate that dissolution kinetics is governed by competing kinetics between two physical processes associated with metal–metal bond breaking and ion-migration within the electrical double layer, respectively. We identify a kinetic transition between regimes dominated by each of these processes and show that this transition depends on the operating electrode potential, among other key factors. It is further found that kinetics and thermodynamics of these processes can be described with a simple, one-parameter Marcus-theory-type model. Beyond offering new understanding of charge transfer during dissolution, our simulation protocol provides a recipe for directly predicting other important quantities in electrochemical reactions from first principles that are difficult to measure, such as the symmetry factor.

36 MATERIALS SCIENCE↗

CFD Simulations of Metal Powder Production by Gas Atomization

Many crucial components in energy production, e.g., stationary gas turbines and A-USCS power plants, are desirable to manufacture by additive manufacturing (AM) with the full development of the materials and processes. Typical gas atomized (GA) feedstock for metal AM is produced in spherical powder form, but often inefficiently with a wide size distribution and with reduced quality, e.g., having internal porosity, heavily oxidized surfaces, and “satellites” that degrade printing and build quality. The proposed project aims to significantly enhance the efficiency/precision and, moreover, the quality of metal powder production by computational fluid dynamics (CFD) simulations, probing the details of the physical processes occurring in supersonic gas atomizers. The goals are improving the desired powder size range yield and quality of GA powder, reducing material and energy production costs, and helping fulfill the immense the potential of AM, thereby enhancing the competitiveness of US manufacturing and of energy and transport sectors.

36 MATERIALS SCIENCE↗

CLimate Impact: Determining Etiology thRough pAthways (CLDERA)

Climate impacts have broad economic, health, political, and national security ramifications. Societally relevant impacts are typically farther downstream, are the product of multiple interacting processes, and can arise over small regions and timeframes because their sources are short-term and localized. Short-term forcings (as can be seen in volcanic eruptions, climatic tipping points (e.g., the collapse of rainforests or the disappearance of sea ice), or in increasingly plausible climate interventions) fundamentally possess low signal-to-noise and could benefit from accounting for the multiple conditional processes through which a downstream impact arises. Under the Grand Challenge LDRD CLDERA (CLimate impacts: Discovering Etiology thRough pAthways), we have developed tools to enable downstream impact attribution from geographically and temporally localized source forcings in the climate. CLDERA developed methods that can distinguish how a localized source drives the climate system to respond with particular impacts. The how is embodied in pathways – the spatio-temporally evolving chain of physical processes that connects a source to a series of increasingly distant impacts. Novel analytic methods in pursuit of downstream impact attribution were developed and demonstrated on simulations and observations of the 1991 eruption of Mt. Pinatubo in the Philippines. As described within this report we have • developed stratospheric expertise and aerosol modeling capabilities in E3SM, • created original methods to detect and model pathways from source-to-impact, and • advanced climate attribution through novel methods, cases, and approaches. Further, CLDERA developed a tiered verification process consisting of controlled datasets to prototype, verify, and refine the original method development. CLDERA increased Sandia’s footprint in the climate analytics community and developed new climate collaborations whilst also creating a cadre of climate analysts at Sandia. The products from CLDERA have been extensive with a total of 9 journal articles published, 12 articles submitted and under review, and an additional 8 articles in preparation. We have produced 1750 simulated years and developed 9 code-bases. This report details these accomplishments and serves as a summary of the work completed during the CLDERA Grand Challenge.

54 ENVIRONMENTAL SCIENCES↗

Summary of Multiphysics Modeling for Sublimation Mass Transfer

This report summarizes the effort to develop a multiphysics modeling framework for sublimation mass transfer processes. The aim of the project was to develop a multiphysics code capable of predicting phase change between solid and gas in a closed container, and the movement of material within such a container when exposed to various exterior environmental conditions. Two modeling frameworks were developed towards this aim: one with a high-fidelity computational fluid dynamics (CFD) structure, and the other as a fast reduced-order model. Ultimately, both attempts were unsuccessful due to instabilities in the code and physical processes for which there is no adequate numerical representation. Both modeling attempts are briefly detailed before providing a brief survey of recent updates in the literature, and a recommendation for future work on this subject.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

The high explosives & affected targets (HEAT) dataset

Artificial Intelligence (AI) surrogate models offer a computationally efficient alternative to full-physics simulations, yet no existing datasets are publicly available for training, testing, and validation of machine learning models of the dynamics of high-explosive driven shocks through multiple materials. Shock propagation through materials is a computationally challenging problem because simulations must include material-specific equations of state (EOS) along with descriptions of other physical processes such as plastic deformation, phase change, damage processes, fluid instabilities, and multi-material interactions. Shocks are typically initiated by high-velocity impacts or explosive loading. The latter case necessitates the addition of models of reactive materials to represent high-explosive (HE) detonation. Here, to address the lack of an expansive dataset for multi-material shock propagation in the AI/ML community, we present the High-Explosives and Affected Targets (HEAT) Dataset. HEAT is a physics-rich collection of two-dimensional, cylindrically symmetric, simulations generated using an Eulerian, multi-material, shock-propagation code developed at Los Alamos National Laboratory. The dataset includes two partitions: (1) the expanding shock-cylinder (CYL) simulations, Figs. 1, and (2) the Perturbed Layered Interface (PLI) simulations, Fig. 2. Entries in both partitions consist of time series of arrays of thermodynamic fields (pressure, density, and temperature), kinematic fields (position and velocity), and additional fields that depend on thermodynamic and/or kinematic fields (e.g., material stress). Materials in the CYL partition include solids (aluminium, copper, depleted uranium, stainless steel, tantalum, and a generic polymer), a liquid (water), gases (air, nitrogen), and a generic detonating material (high explosive, HE). The PLI partition spans a highly varying geometry but consists of fixed materials across entries: Copper, aluminium, stainless steel, generic polymer, and generic HE. HEAT captures critical phenomena such as momentum transfer, shock propagation, plastic deformation, and thermal effects, making HEAT a valuable benchmark for development of AI/ML emulation of multi-material shock propagation.

36 MATERIALS SCIENCE↗

A Mass‐Conserving‐Perceptron for Machine‐Learning‐Based Modeling of Geoscientific Systems

Although decades of effort have been devoted to building Physical-Conceptual (PC) models for predicting the time-series evolution of geoscientific systems, recent work shows that Machine Learning (ML) based Gated Recurrent Neural Network technology can be used to develop models that are much more accurate. However, the difficulty of extracting physical understanding from ML-based models complicates their utility for enhancing scientific knowledge regarding system structure and function. Here, we propose a physically interpretable Mass-Conserving-Perceptron (MCP) as a way to bridge the gap between PC-based and ML-based modeling approaches. The MCP exploits the inherent isomorphism between the directed graph structures underlying both PC models and GRNNs to explicitly represent the mass-conserving nature of physical processes while enabling the functional nature of such processes to be directly learned (in an interpretable manner) from available data using off-the-shelf ML technology. As a proof of concept, we investigate the functional expressivity (capacity) of the MCP, explore its ability to parsimoniously represent the rainfall-runoff (RR) dynamics of the Leaf River Basin, and demonstrate its utility for scientific hypothesis testing. To conclude, we discuss extensions of the concept to enable ML-based physical-conceptual representation of the coupled nature of mass-energy-information flows through geoscientific systems.

58 GEOSCIENCES↗

Engineering Controls Database

Cyber-Informed Engineering (CIE) addresses the reality that cyber attacks on engineered systems can have consequences far beyond data loss or disruption of digital networks. When control systems are compromised, safety, reliability, and performance of the physical process itself may be threatened. This database is meant to establish clear examples and guidance for defining and applying engineered controls in CIE. It explains what engineered controls are, how they differ from information security measures, and how they are integrated into system design. The goal is to ensure that resilience is engineered into systems from the outset. Unlike cybersecurity protections that defend the digital layer, engineered controls act directly at the physical and algorithmic levels to guarantee that unacceptable consequences are prevented or limited. CIE keeps the consequences of a cyber attack from impacting the safety, reliability, and performance of engineered systems.

Source record↗

Cyber-Informed Engineering (CIE) – Engineered Controls Database and Use

Cyber-Informed Engineering (CIE) addresses the reality that cyber-attacks on engineered systems can have consequences far beyond data loss or disruption of digital networks. When control systems are compromised, safety, reliability, and performance of the physical process itself may be threatened. This database is meant to establish clear examples and guidance for defining and applying engineered controls in CIE. It explains what engineered controls are, how they differ from information security measures, and how they are integrated into system design. The goal is to ensure that resilience is engineered into systems from the outset. Unlike cybersecurity protections that defend the digital layer, engineered controls act directly at the physical and algorithmic levels to guarantee that unacceptable consequences are prevented or limited. CIE keeps the consequences of a cyber attack from impacting the safety, reliability, and performance of engineered systems.

42 - ENGINEERING↗

An overview of the ORACLES (ObseRvations of Aerosols above CLouds and their intEractionS) project: aerosol–cloud–radiation interactions in the southeast Atlantic basin

Southern Africa produces almost a third of the Earth's biomass burning (BB) aerosol particles, yet the fate of these particles and their influence on regional and global climate is poorly understood. ORACLES (ObseRvations of Aerosols above CLouds and their intEractionS) is a 5-year NASA EVS-2 (Earth Venture Suborbital-2) investigation with three intensive observation periods designed to study key atmospheric processes that determine the climate impacts of these aerosols. During the Southern Hemisphere winter and spring (June-October), aerosol particles reaching 3-5 km in altitude are transported westward over the southeast Atlantic, where they interact with one of the largest subtropical stratocumulus (Sc) cloud decks in the world. The representation of these interactions in climate models remains highly uncertain in part due to a scarcity of observational constraints on aerosol and cloud properties, as well as due to the parameterized treatment of physical processes. Three ORACLES deployments by the NASA P-3 aircraft in September 2016, August 2017, and October 2018 (totaling ~350 science flight hours), augmented by the deployment of the NASA ER-2 aircraft for remote sensing in September 2016 (totaling ~100 science flight hours), were intended to help fill this observational gap. ORACLES focuses on three fundamental science themes centered on the climate effects of African BB aerosols: (a) direct aerosol radiative effects, (b) effects of aerosol absorption on atmospheric circulation and clouds, and (c) aerosol–cloud microphysical interactions. This paper summarizes the ORACLES science objectives, describes the project implementation, provides an overview of the flights and measurements in each deployment, and highlights the integrative modeling efforts from cloud to global scales to address science objectives. Significant new findings on the vertical structure of BB aerosol physical and chemical properties, chemical aging, cloud condensation nuclei, rain and precipitation statistics, and aerosol indirect effects are emphasized, but their detailed descriptions are the subject of separate publications. The main purpose of this paper is to familiarize the broader scientific community with the ORACLES project and the dataset it produced.

54 ENVIRONMENTAL SCIENCES↗

New Apparatus for Neutron Capture Measurements on Extra Small Radioactive Samples: The DICER Instrument at LANSCE

We report the neutron capture cross section, the probability per unit area a neutron is absorbed by a nucleus followed by the emission of gamma ray(s), is an important quantity in several fields such as astrophysics, nuclear criticality safety, radiochemical diagnostics, nuclear medicine, nuclear forensics and nuclear security. Accurate knowledge of how neutrons interact with matter is a crucial component to understand physical processes in depth. A great example is the understanding of how our universe was created, a quest that requires accurate modeling in which neutron capture cross sections are a key ingredient

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗