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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 181 records · Page 10
All sourcesNASA NTRSDOE OSTI
DOE OSTI2015

Constraint-Based Routing Models for the Transport of Radioactive Materials

The Department of Energy (DOE) has a historic programmatic interest in the safe and secure routing, tracking, and transportation risk analysis of radiological materials in the United States. In order to address these program goals, DOE has funded the development of several tools and related systems designed to provide insight to planners and other professionals handling radioactive materials shipments. These systems include the WebTRAGIS (Transportation Routing Analysis Geographic Information System) platform. WebTRAGIS is a browser-based routing application developed at Oak Ridge National Laboratory (ORNL) focused primarily on the safe transport of spent nuclear fuel from US nuclear reactors via railway, highway, or waterway. It is also used for the transport planning of low-level radiological waste to depositories such as the Waste Isolation Pilot Plant (WIPP) facility. One particular feature of WebTRAGIS is its coupling with high-resolution population data from ORNL s LandScan project. This allows users to obtain highly accurate population count and density information for use in route planning and risk analysis. To perform the routing and risk analysis WebTRAGIS incorporates a basic routing model methodology, with the additional application of various constraints designed to mimic US Department of Transportation (DOT), DOE, and Nuclear Regulatory Commission (NRC) regulations. Aside from the routing models available in WebTRAGIS, the system relies on detailed or specialized modal networks for the route solutions. These include a highly detailed network model of the US railroad system, the inland and coastal waterways, and a specialized highway network that focuses on the US interstate system and the designated hazardous materials and Highway Route Controlled Quantity (HRCQ) -designated roadways. The route constraints in WebTRAGIS rely upon a series of attributes assigned to the various components of the different modal networks. Routes are determined via a constrained shortest-path Dijkstra algorithm that has an assigned impedance factor. The route constraints modify the various impedance weights to bias or prefer particular network characteristics as desired by the user. Both the basic route model and the constrained impedance function calculations are determined by a series of network characteristics and shipment types. The study examines solutions under various constraints modeled by WebTRAGIS including possible routes from select shut-down reactor sites in the US to specific locations in the US. For purposes of illustration, the designated destinations are Oak Ridge National Laboratory in Tennessee and the Savannah River Site in South Carolina. To the degree that routes express sameness or variety under constraints serves to illustrate either a) the determinism of particular transport modes by either configuration or regulatory compliance, and/or b) the variety of constrained routes that are regulation compliant but may not be operationally feasible.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2017

Pore network modeling of the electrical signature of solute transport in dual-domain media: Dual-Domain Electrical Signature

Dual-domain models are used to explain anomalous solute transport behavior observed in diverse hydrologic settings and applications, from groundwater remediation to hyporheic exchange. To constrain such models, new methods are needed with sensitivity to both immobile and mobile domains. Recent experiments indicate that dual-domain transport of ionic tracers has an observable geoelectrical signature, appearing as a nonlinear, hysteretic relation between paired bulk and fluid electrical conductivity. Here in this paper we present a mechanistic explanation for this geoelectrical signature and evaluate assumptions underlying a previously published petrophysical model for bulk conductivity in dual-domain media. Pore network modeling of fluid flow, solute transport, and electrical conduction (1) verifies the geoelectrical signature of dual-domain transport, (2) reveals limitations of the previously used petrophysical model, and (3) demonstrates that a new petrophysical model, based on differential effective media theory, closely approximates the simulated bulk/fluid conductivity relation. These findings underscore the potential of geophysically based calibration of dual-domain models.

58 GEOSCIENCES↗
DOE OSTI2023

A Scalable Quantum Cryptography Network for Protected Automation Communication (Final Report)

This is the final report for a CEDS-funded project aimed at developing a new quantum technology for securing utility communication networks used to control and monitor electrical grid equipment. Securing these control networks represents a unique challenge as the performance of the security solution has a direct impact on the stability and reliability of the electrical grid. Traditional, software-based solutions - developed for information networks - are not suitable for utility control networks because they introduce latency, require burdensome maintenance and upgrades, are often incompatible with legacy equipment, and introduce operational complexity that reduces grid reliability. Consequently, many U.S. utilities do not use existing solutions and, instead, protect their critical control networks through the careful isolation and obscuration of their networked equipment. With more utilities embracing grid automation, the attack surface that utilities must defend from hackers has grown to an unmanageable size. To address this situation, Qubitekk and its partners proposed and developed a hardware-based solution that can secure critical control networks without negatively impacting grid performance. This new solution is based on quantum key distribution (QKD) techniques that guarantee secure key generation and distribution across a utility control network. Through deployment and field testing of a prototype QKD system, we have shown that this solution delivers long-term network security, is technically feasible to implement and maintain on a utility’s distribution substation network and does not negatively impact grid operations. In addition, the project has identified and solved key challenges associated with generating, transmitting, and measuring coherent photonic quantum states on a real-world fiber optic network. These additional findings are playing a critical role in advancing quantum networks for quantum computing applications. An overview of the QKD prototype development effort, field testing activities and results, and additional findings relevant to emerging quantum networks are presented in this report.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2023

Neural Network-Based Variational Methods for Solving Quadratic Porous Medium Equations in High Dimensions

Here, in this paper, we propose and study neural network-based methods for solutions of high-dimensional quadratic porous medium equation (QPME). Three variational formulations of this nonlinear PDE are presented: a strong formulation and two weak formulations. For the strong formulation, the solution is directly parameterized with a neural network and optimized by minimizing the PDE residual. It can be proved that the convergence of the optimization problem guarantees the convergence of the approximate solution in the $L^1$ sense. The weak formulations are derived following (Brenier in Examples of hidden convexity in nonlinear PDEs, 2020) which characterizes the very weak solutions of QPME. Specifically speaking, the solutions are represented with intermediate functions who are parameterized with neural networks and are trained to optimize the weak formulations. Extensive numerical tests are further carried out to investigate the pros and cons of each formulation in low and high dimensions. This is an initial exploration made along the line of solving high-dimensional nonlinear PDEs with neural network-based methods, which we hope can provide some useful experience for future investigations.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Prediction of local concentration fields in porous media with chemical reaction using a multi scale convolutional neural network

The study of solute transport in porous media is of interest in many chemical engineering systems. Some example applications include packed bed catalytic reactors, filtration devices, and batteries. The pore scale modeling of these systems is time consuming and may require large computing resources, for this reason computational fluid dynamics (CFD) simulations are not practical if a large number of simulations is required, like in multiscale modeling, where a model at a large scale calls for pore scale simulations. It has been shown that neural networks can be trained with a dataset of flow simulations and then predict fields orders of magnitude faster, and with less computational resources, in new domains. However, it is crucial to provide the neural network with an effective description of the domain and the undergoing operating conditions to be able to train models that generalize accurately in unseen samples. Therefore, research is needed to employ neural networks in new complex systems. The appropriate training of a network for predicting coupled flow and solute transport processes is an outstanding problem due to the complex interplay between geometry and operating conditions. In this work, we train a multi scale convolutional neural network (MSNet) with a diverse dataset of simulations of transport and chemical reaction in porous media to predict the local concentration fields in images of porous media. Our dataset contains a wide diversity of sphere pack arrangements under different operating conditions (Péclet and Reynolds numbers). Further, we train a robust model by employing different input descriptors that represent the medium and the different operating conditions of each system. Our trained model is able to provide nearly instantaneous predictions, compared to around twenty hours of the CFD workflow, with less than 3.5% error on new geometries and transport conditions. Thus the model could be easily integrated in a multiscale workflow where fast response is needed.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS1998

Lightning Radio Source Retrieval Using Advanced Lightning Direction Finder (ALDF) Networks

A linear algebraic solution is provided for the problem of retrieving the location and time of occurrence of lightning ground strikes from an Advanced Lightning Direction Finder (ALDF) network. The ALDF network measures field strength, magnetic bearing and arrival time of lightning radio emissions. Solutions for the plane (i.e., no Earth curvature) are provided that implement all of tile measurements mentioned above. Tests of the retrieval method are provided using computer-simulated data sets. We also introduce a quadratic planar solution that is useful when only three arrival time measurements are available. The algebra of the quadratic root results are examined in detail to clarify what portions of the analysis region lead to fundamental ambiguities in source location. Complex root results are shown to be associated with the presence of measurement errors when the lightning source lies near an outer sensor baseline of the ALDF network. In the absence of measurement errors, quadratic root degeneracy (no source location ambiguity) is shown to exist exactly on the outer sensor baselines for arbitrary non-collinear network geometries. The accuracy of the quadratic planar method is tested with computer generated data sets. The results are generally better than those obtained from the three station linear planar method when bearing errors are about 2 deg. We also note some of the advantages and disadvantages of these methods over the nonlinear method of chi(sup 2) minimization employed by the National Lightning Detection Network (NLDN) and discussed in Cummins et al.(1993, 1995, 1998).

Koshak, William J.↗
DOE OSTI2023

Hydrogen Bond Network Disruption by Hydration Layers in Water Solutions with Salt and Hydrogen-Bonding Polymers (PEO)

A mean field theory model describing the interaction of ion hydration layers with the network of hydrogen bonds of both water and the nonionic polymer poly(ethylene oxide) (PEO) is presented. The predictions of the model for types and statistics of hydrogen bonds, the number of water molecules bound to PEO, or their dependence on temperature are successfully verified from all-atom simulations at different NaCl and PEO concentrations. Furthermore, our simulations show that the binding of cations to PEO increases monotonically with salt concentration, in agreement with recent experimental results, through a mechanism in which the sum of the number of bound water and cations is independent of salt concentration. Here, the model introduced is general and can describe any salt or hydrogen-bond-forming polymer.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS1989

Distributed Finite Element Analysis Using a Transputer Network

The principal objective of this research effort was to demonstrate the extraordinarily cost effective acceleration of finite element structural analysis problems using a transputer-based parallel processing network. This objective was accomplished in the form of a commercially viable parallel processing workstation. The workstation is a desktop size, low-maintenance computing unit capable of supercomputer performance yet costs two orders of magnitude less. To achieve the principal research objective, a transputer based structural analysis workstation termed XPFEM was implemented with linear static structural analysis capabilities resembling commercially available NASTRAN. Finite element model files, generated using the on-line preprocessing module or external preprocessing packages, are downloaded to a network of 32 transputers for accelerated solution. The system currently executes at about one third Cray X-MP24 speed but additional acceleration appears likely. For the NASA selected demonstration problem of a Space Shuttle main engine turbine blade model with about 1500 nodes and 4500 independent degrees of freedom, the Cray X-MP24 required 23.9 seconds to obtain a solution while the transputer network, operated from an IBM PC-AT compatible host computer, required 71.7 seconds. Consequently, the $80,000 transputer network demonstrated a cost-performance ratio about 60 times better than the $15,000,000 Cray X-MP24 system.

Watson, James↗
DOE OSTI2012

Permeability and Dispersion Coefficients in Rocks with Fracture Network - 12140

Fluid flow and solute transport are considered for a rock medium with a fracture network with regard to the effective permeability and the dispersion coefficients. To investigate the effects of individual fractures a three-fracture system is chosen in which two are parallel and the third one connects the two at different angles. Specifically the micro-cell boundary-value problems(defined through multiple scale analysis) are solved numerically by using finite elements to calculate the permeability and dispersion coefficients. It is shown that the permeability depends significantly on the pattern of the fracture distribution and the dispersion coefficient is influenced by both the externally imposed pressure gradient (which also reflects the flow field) and the direction of the gradient of solute concentration on the macro-scale. From the calculations of the permeability and dispersion coefficients for solute in a rock medium with a fracture network the following conclusions are drawn. 1. The permeability of fractured medium depends on the primary orientation of the fracture network and is influenced by the connecting fractures in the medium. 2. The cross permeability, e.g., permeability in the direction normal to the direction of the external pressure gradient is rather insensitive to the orientation of the fracture network. 3. Calculation of permeability is most efficiently achieved with optimal discretization across individual fractures and is rather insensitive to the discretization along the fracture.. 4. The longitudinal dispersion coefficient Dxx of a fractured medium depends on both the macro-scale concentration gradient and the direction of the flow (pressure gradient). Hence both features must be considered when investigating solute transport in a fractured medium. (authors)

42 ENGINEERING↗
NASA NTRS2011

TPSAS-NF1676L-12321-DND

The operation of some networks, such as air transportation networks, can be complicated by congestion through a small subset of nodes. The congestion may be influenced by the connectivity of the network, or by the presence of constraints restricting the flow through particular nodes. This work investigates the effects of both connectivity and node flow constraints on the operation of a network. We develop the Minimax Node Load Problem (MNLP), a multicommodity flow model which minimizes the worst-case flow through any node in a given input network. The optimal solution to this problem provides us with the minimax node load, which we propose as a measure of network congestion. Keeping the number of nodes fixed, we first increase connectivity in a series of networks, and observe that topologies with more distributed connections result in a reduction in the minimax node load. However, when connectivity is increased further, the reductions diminish and are accompanied by solutions with undesirable qualities such as longer commodity paths. We then perform a second set of experiments over the same network, constraining flow through different subsets of nodes at different magnitudes of flow restriction, finding that (1) more constrained nodes lead to the largest increases in minimax node load and (2) constraints on the most connected nodes have the greatest effect on both congestion and commodity path length.

Douglas W Lee↗
NASA NTRS2011

TPSAS-NF1676L-12264-DND

The operation of some networks, such as air transportation networks, can be complicated by congestion through a small subset of nodes. The congestion may be influenced by the connectivity of the network, or by the presence of constraints restricting the flow through particular nodes. This work investigates the effects of both connectivity and node flow constraints on the operation of a network. We develop the Minimax Node Load Problem (MNLP), a multicommodity flow model which minimizes the worst-case flow through any node in a given input network. The optimal solution to this problem provides us with the minimax node load, which we propose as a measure of network congestion. Keeping the number of nodes fixed, we first increase connectivity in a series of networks, and observe that topologies with more distributed connections result in a reduction in the minimax node load. However, when connectivity is increased further, the reductions diminish and are accompanied by solutions with undesirable qualities such as longer commodity paths. We then perform a second set of experiments over the same network, constraining flow through different subsets of nodes at different magnitudes of flow restriction, finding that (1) more constrained nodes lead to the largest increases in minimax node load and (2) constraints on the most connected nodes have the greatest effect on both congestion and commodity path length.

Douglas Lee↗
DOE OSTI2020

Report for Department of State (DoS) V-Fund Project "Tying Moment Tensor Solutions to Explosive Yield"

The goal of this study was to use U.S. nuclear explosions with known source parameters (yield, depth, shot point material and/or parameters) to determine moment-derived yield estimates. This work has been accomplished by performing full moment tensor solutions using regional network data from the LLNL network, and other regional broadband stations. As part of this study, we have calculated solutions for 130 U.S. nuclear explosions and 12 additional chemical explosions. We then take several approaches to using moment tensors to estimate yield, considering both the full and isotropic moment tensors, doing straight regression analysis on the whole dataset, then successively refining the calibration with additional information about material and overburden. We have also tried a completely new approach of using the seismic moment to help estimate the radiated seismic energy and tying this to yield through a seismic efficiency. Results appear to be promising, but more work might be required to make this more useful in an operational sense.

58 GEOSCIENCES↗
DOE OSTI2020

The reservoir network: A new network topology for district heating and cooling

Thermal district networks are effective solutions to substitute fossil fuels with renewable energy sources for heating and cooling. Moreover, thermal networking of buildings allows energy efficiency to be further increased. The waste heat from cooling can be reused for heating in thermal district systems. Because of bidirectional energy flows between prosumers, thermal networks require new hydraulic concepts. In this work, we present a novel network topology for simultaneous heating and cooling: the reservoir network. The reservoir network is robust in operation due to hydraulic decoupling of transfer stations, integrates heat sources and heat sinks at various temperature levels and is flexible in terms of network expansion. Furthermore, we used Modelica simulations to compare the new single-pipe reservoir network to a basecase double-pipe network, taking yearly demand profiles of different building types for heating and cooling. The electric energy consumed by the heat pumps and circulations pumps differs between the reservoir and base case networks by less than 1%. However, if the reservoir network is operated with constant instead of variable mass flow rate, the total electrical consumption can increase by 48% compared to the base case. As with any other network topology, the design and control of such networks is crucial to achieving energy efficient operation. Investment costs for piping and trenching depend on the district layout and dimensioning of the network. If a ring layout is applied in a district, the reservoir network with its single-pipe configuration is more economical than other topologies. For a linear layout, the piping costs are slightly higher for the reservoir network than for the base case because of larger pipe diameters.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2023

AI-based Detection and Defense Against Cyberattacks in Distributed Energy Resources

This study will provide comprehensive artificial intelligence (AI)-based solution tools for network security, malware prevention, and sensor data anomaly detection for distributed energy resource (DER) research, development, and demonstration. DER technologies are energy systems (e.g., solar panels, wind turbines, and energy storage systems) that are often connected to the internet and thus vulnerable to cyberattacks. Cybersecurity should be of primary concern for DERs, which is why we propose an integrated multi-layer cyber-defense system for DERs. This system encompasses risk assessments, network security, malware prevention, and detection of anomalies in the sensor data. Implementation of a comprehensive risk assessment with an overview of the model architecture should be the primary step, and should include the potential impact of experiencing, at a given time, one or more cyberattacks on the system. The second step is to ensure that the network security includes firewalls, intrusion detection, and malware prevention. The third step is to provide solution tools that enable sensor data anomaly detection for DERs. By incorporating these considerations into DER research, development, and demonstration, organizations can help ensure the safety and security of their systems and protect against potential cyberattacks.

20 FOSSIL-FUELED POWER PLANTS↗