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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 OSTI2021

Optimal Energy Scheduling and Sensitivity Analysis for Integrated Power-Water-Heat Systems

The conventionally independent power, water, and heating networks are becoming more tightly connected, which motivates their joint optimal energy scheduling to improve the overall efficiency of an integrated energy system. However, such a joint optimization is known as a challenging problem with complex network constraints and couplings of electric, hydraulic, and thermal models that are nonlinear and nonconvex. We formulate an optimal power-water-heat flow (OPWHF) problem and develop a computationally efficient heuristic to solve it. The proposed heuristic decomposes OPWHF into subproblems, which are iteratively solved via convex relaxation and convex-concave procedure. Simulation results validate that the proposed framework can improve operational flexibility and social welfare of the integrated system, wherein the water and heating networks respond as virtual energy storage to time-varying energy prices and solar photovoltaic generation. Moreover, we perform sensitivity analysis to compare two modes of heating network control: by flow rate and by temperature. Our results reveal that the latter is more effective for heating networks with a wider space of pipeline parameters.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2021

Magnetization Process of Atacamite: A Case of Weakly Coupled S = 1/2 Sawtooth Chains

We present a combined experimental and theoretical study of the mineral atacamite Cu 2 Cl(OH) 3 . Density-functional theory yields a Hamiltonian describing anisotropic sawtooth chains with weak 3D connections. Experimentally, we fully characterize the antiferromagnetically ordered state. Here, magnetic order shows a complex evolution with the magnetic field, while, starting at 31.5 T, we observe a plateaulike magnetization at about M sat /2. Based on complementary theoretical approaches, we show that the latter is unrelated to the known magnetization plateau of a sawtooth chain. Instead, we provide evidence that the magnetization process in atacamite is a field-driven canting of a 3D network of weakly coupled sawtooth chains that form giant moments.

1-dimensional spin chains↗
NASA NTRS1996

Autonomous Navigation Apparatus With Neural Network for a Mobile Vehicle

An autonomous navigation system for a mobile vehicle arranged to move within an environment includes a plurality of sensors arranged on the vehicle and at least one neural network including an input layer coupled to the sensors, a hidden layer coupled to the input layer, and an output layer coupled to the hidden layer. The neural network produces output signals representing respective positions of the vehicle, such as the X coordinate, the Y coordinate, and the angular orientation of the vehicle. A plurality of patch locations within the environment are used to train the neural networks to produce the correct outputs in response to the distances sensed.

Quraishi, Naveed↗
DOE OSTI2020

One step removed shadow network

A system and method includes an operational network that communicates with an external network by opening a first transmission protocol socket. A data diode coupled to the operational network and a gateway enables the one-way transfer of all information received from the external network and transmitted by the operational network to the gateway such that no information travels from the gateway to the operational network or the external network. The gateway opens a second transmission protocol socket by mapping a sequence number to an acknowledgement number and increasing that mapped acknowledgement number by a value of one. A transmitter then transmits the acknowledgment to a remote network or a gateway.

Park, Brent K.↗
DOE OSTI2021

Multilayer Network Clarifies Prevailing Water Consumption Telecouplings in the United States

Virtual water flows are used to map the indirect water consumption connections implied by the supply chain of a city, region, or country. This information can be used to manage supply chains to achieve environmental policy objectives and mitigate environmental risks to critical supply chains. A limitation of prior work is that these flows are typically analyzed using monolayer networks, which ignores crucial intersectoral or interlayer couplings. Here, in this study, we use a multilayer network to account for such couplings when analyzing blue virtual water flows in the United States. Our multilayer network consists of 115 different regions (nodes), covering the entire conterminous United States; 41 coupled economic sectors (layers); and ∼2 × 10 7 possible links. To analyze the multilayer network, we focus on three fundamental network properties: topological connectivity, mesoscale structure, and node centrality. The network has a high connectivity, with each node being on average connected to roughly 2/3 of the network's nodes. Interlayer flows are a major driver of connectivity, representing ∼54% of all the network's connections. Five different groups of tightly connected nodes (communities) characterize the network. Each community represents a preferred spatial mode of long-range virtual water interaction within the United States. We find that large (populous) cities have a stronger influence than small ones on network functioning because they attract and recirculate more virtual water through their supply chains. Our results also highlight differences between the multilayer and monolayer virtual water network, which overall show that the former provides a more realistic representation of virtual water flows.

Garcia Gonzalez, Susana↗
DOE OSTI2022

Surface‐Enforced Alignment of Reprogrammable Liquid Crystalline Elastomers

Abstract Liquid crystalline elastomers (LCEs) are stimuli‐responsive materials capable of undergoing large deformations. The thermomechanical response of LCEs is attributable to the coupling of polymer network properties and disruption of order between liquid crystalline mesogens. Complex deformations have been realized in LCEs by either programming the nematic director via surface‐enforced alignment or localized mechanical deformation in materials incorporating dynamic covalent chemistries. Here, the preparation of LCEs via thiol‐Michael addition reaction is reported that are amenable to surface‐enforced alignment. Afforded by the thiol‐Michael addition reaction, dynamic covalent bonds are uniquely incorporated in chemistries subject to surface‐enforce alignment. Accordingly, LCEs prepared with complex director profiles are able to be programmed and reprogrammed by (re)activating the dynamic covalent chemistry to realize distinctive shape transformations.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Quantitative interpretation of time-lapse seismic data at Farnsworth field unit: Rock physics modeling, and calibration of simulated time-lapse velocity responses

Here, this study investigates the contribution of fluid saturation variation to the time-lapse velocity response by performing fluid substitution modeling. The methodology is exemplified by the time-lapse seismic monitoring of carbon dioxide at Farnsworth field unit (FWU). In order to evaluate the fluid distribution in a matured oil reservoir, the Southwest Regional Partnership (SWP) acquired multiple vertical seismic profile (VSP) surveys at different times during the CO 2 –water alternatinggas (WAG) injection period. In this work, we present a thorough methodology for computing the elastic response of the saturated rock for different fluid saturations using a site-specific petro-elastic model (PEM). The output from the PEM was combined with results from a fluid compositional model to compute the seismic velocities at times corresponding to each VSP survey. To produce a calibrated simulated response, the measured time-lapse seismic velocities were integrated into the numerical simulation model. The mismatches between the predicted and measured time-lapse velocities were minimized through an iterative calibration process using a trained artificial neural network proxy (ANN) coupled with a particle swarm optimizer (PSO). Our study indicates that the hybrid optimization workflow can effectively perform the history matching. With an accurate prediction of the hydrodynamic properties, the migration of CO 2 within the subsurface was modeled by predicting the spatial velocity distribution for a radius of 305 m around the injection well. The technology demonstrated and the expertise gained from this study can guide similar CO 2 -WAG projects.

58 GEOSCIENCES↗
DOE OSTI2021

Nematic order driven by superconducting correlations

The interplay of nematicity and superconductivity has been observed in a wide variety of quantum materials. To explore this interplay, we consider a two-dimensional (2D) array of nematogens, local droplets with Z 3 nematicity, coupled to a network of Josephson junction wires. Using finite temperature classical Monte Carlo simulations, we elucidate the phase diagram of this model and show that the development of superconducting correlations and the directional delocalization of Cooper pairs can promote nematogen ordering, resulting in long-range nematic order. We obtain the transport properties of our model within an effective resistor network picture. We discuss these ideas in the context of the 2D electron gas at the (111) KTaO 3 interface and the doped topological insulators Nb x Bi 2 Se 3 and Cu x Bi 2 Se 3 . Overall, our work makes contact with Phil Anderson’s numerous contributions to broken symmetries driven by the saving of kinetic energy, including double exchange ferromagnetism and the interlayer tunneling theory of high Tc csuperconductivity.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2019

Development and application of a machine learning based multi-objective optimization workflow for CO 2 -EOR projects

Carbon dioxide-Enhanced Oil Recovery (CO 2 -EOR) is known as one of techniques for hydrocarbon production improvement as wells as an important candidate to reduce greenhouse gas emissions. Thus, an ideal development strategy for a CO 2 -EOR project would consider multiple objectives including to maximize oil recovery, CO 2 storage volume and project economic outcomes. This work proposes a robust computational framework that couples artificial neural network (ANN) and multi-objective optimizers to optimize the aforementioned objectives in CO 2 -EOR processes simultaneously. Expert ANN systems are trained and employed as surrogate models of the high-fidelity compositional simulator in the optimization workflow. The robustness of the development optimization protocol is confirmed via a synthetic injection-pattern-base case study. Afterward a field implementation to Morrow-B formation to optimize the tertiary recovery stage of the field development is discussed. This work compares the optimum solution found using an aggregate objective function and the solution repository (Pareto front) generated by the multi-objective optimization process. The comparison indicates the existence of potential multi-solutions satisfying certain criteria in a CO 2 -EOR project designing, which cannot be found using traditional weighted sum method. The optimization results provide significant insight into the decision-making process of CO 2 -EOR project when multiple objective functions are considered.

02 PETROLEUM↗
DOE OSTI2022

Supervised learning and the finite-temperature string method for computing committor functions and reaction rates

A central object in the computational studies of rare events is the committor function. Though costly to compute, the committor function encodes complete mechanistic information of the processes involving rare events, including reaction rates and transition-state ensembles. Under the framework of transition path theory, Rotskoff et al. [Proceedings of the 2nd Mathematical and Scientific Machine Learning Conference, Proceedings of Machine Learning Research (PLMR, 2022), Vol. 145, pp. 757–780] proposes an algorithm where a feedback loop couples a neural network that models the committor function with importance sampling, mainly umbrella sampling, which collects data needed for adaptive training. Here, in this work, we show additional modifications are needed to improve the accuracy of the algorithm. The first modification adds elements of supervised learning, which allows the neural network to improve its prediction by fitting to sample-mean estimates of committor values obtained from short molecular dynamics trajectories. The second modification replaces the committor-based umbrella sampling with the finite-temperature string (FTS) method, which enables homogeneous sampling in regions where transition pathways are located. We test our modifications on low-dimensional systems with non-convex potential energy where reference solutions can be found via analytical or finite element methods, and show how combining supervised learning and the FTS method yields accurate computation of committor functions and reaction rates. We also provide an error analysis for algorithms that use the FTS method, using which reaction rates can be accurately estimated during training with a small number of samples. The methods are then applied to a molecular system in which no reference solution is known, where accurate computations of committor functions and reaction rates can still be obtained.

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

Circuit-level design principles for transmission-mode microwave impedance microscopy

A recently developed technique of transmission-mode microwave impedance microscopy (T-MIM) has greatly extended the capabilities of standard reflection-mode MIM to novel applications, such as the in operando study of nanoscale electro-acoustic devices. As is common for new techniques, systematic design principles for boosting sensitivity and balancing bandwidth are lacking. Here, we show numerically and analytically that the T-MIM signal is proportional to the reflection-mode voltage enhancement factor η of the circuit, as long as the output impedance of the local voltage source is properly treated. We show that this proportionality holds in the currently achievable “weak sampling” regime and beyond, for which we demonstrate a realistic path with commercially available superconducting components and critically coupled impedance matching networks. Furthermore, we demonstrate that for these next-generation designs, the sensitivity is generally maximized at a slightly different frequency from the unloaded S 11 resonance, which can be explained by the maximum power transfer theorem.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2024

Isolating Signatures of Cyberattacks under Stressed Grid Conditions

In a controlled cyber-physical network, such as a power grid, any malicious data injection in the sensor measurements can lead to widespread impact due to the actions of the closed-loop controllers. While fast identification of the attack signatures is imperative for reliable operations, it is challenging to do so in a large dynamical network with tightly coupled nodes. A particularly challenging scenario arises when the cyberattacks are strategically launched during a grid stress condition, caused by non-malicious physical disturbances.

Ghosh, Sanchita [BATTELLE (PACIFIC NW LAB)]↗
DOE OSTI2020

Endophyte-Promoted Phosphorus Solubilization in Populus

Phosphorus is an important plant nutrient, but in soils the majority of phosphorus, present in the form of a phosphate, forms metal complexes in soil making it relatively unavailable to plants. Therefore, inorganic phosphate solubilization is an important process of plant growth promotion by plant associated bacteria and fungi. Non nodulating plant species have been shown to thrive in low-nutrient environments, in some instances by relying on plant associated microorganisms called endophytes. These microorganisms live within the plant and help supply nutrients for the plant. Despite their potential enormous environmental importance, there are a limited number of studies looking at the direct molecular impact of phosphate solubilizing endophytic bacteria on the host plant. In this work, we studied the impact of two endophyte strains of wild poplar (Populus trichocarpa) that solubilize phosphate. Using a combination of x-ray imaging, spectroscopy methods, and proteomics we report direct evidence of endophyte-promoted phosphorus uptake in poplar. We found that the solubilized phosphate inside the plant may react and become insoluble again suggesting that the phosphate could be re-released within the plant by endophytes. Using synchrotron x-ray fluorescence spectromicroscopy combined with x-ray absorption near-edge structure, we visualized the nutrient phosphorus inside poplar roots inoculated by the selected endophytes and found the phosphorus in both forms of organic and inorganic phosphates inside the root. Tomography-based root imaging revealed a markedly different root biomass and root architecture for poplar samples inoculated with the phosphate solubilizing bacteria strains. Proteomics characterization on poplar roots coupled with protein network analysis revealed novel proteins and metabolic pathways with possible involvement in endophyte enriched phosphorus uptake. These findings suggest an important role of endophytes for phosphorus acquisition and provide a deeper understanding of the critical symbiotic associations between poplar and the endophytic bacteria.

36 MATERIALS SCIENCE↗
NASA NTRS1989

Worldnet

The expanding use of powerful workstations coupled to ubiquitous networks is transforming scientific and engineering research and the the ways organizations around the world do business. By the year 2000, few enterprises will be able to succeed without mastery of this technology, which will be embodied in an information infrastructure based on a worldwide network. A recurring theme in all the discussions of what might be possible within the emerging Worldnet is people and machines working together in new ways across distance and time. A review is presented of the basic concepts on which the architecture of Worldnet must be built: coordination of action, authentication, privacy, and naming. Worldnet must provide additional functions to support the ongoing processes of suppliers and consumers: help services, aids for designing and producing subsystems, spinning off new machines, and resistance to attack. This discussion begins to reveal the constituent elements of a theory for Worldnet, a theory focused on what people will do with computers rather than on what computers do.

Denning, Peter J.↗
NASA NTRS1994

High performance real-time flight simulation at NASA Langley

In order to meet the stringent time-critical requirements for real-time man-in-the-loop flight simulation, computer processing operations must be deterministic and be completed in as short a time as possible. This includes simulation mathematical model computational and data input/output to the simulators. In 1986, in response to increased demands for flight simulation performance, personnel at NASA's Langley Research Center (LaRC), working with the contractor, developed extensions to a standard input/output system to provide for high bandwidth, low latency data acquisition and distribution. The Computer Automated Measurement and Control technology (IEEE standard 595) was extended to meet the performance requirements for real-time simulation. This technology extension increased the effective bandwidth by a factor of ten and increased the performance of modules necessary for simulator communications. This technology is being used by more than 80 leading technological developers in the United States, Canada, and Europe. Included among the commercial applications of this technology are nuclear process control, power grid analysis, process monitoring, real-time simulation, and radar data acquisition. Personnel at LaRC have completed the development of the use of supercomputers for simulation mathematical model computational to support real-time flight simulation. This includes the development of a real-time operating system and the development of specialized software and hardware for the CAMAC simulator network. This work, coupled with the use of an open systems software architecture, has advanced the state of the art in real time flight simulation. The data acquisition technology innovation and experience with recent developments in this technology are described.

Cleveland, Jeff I., II↗
NASA NTRS1997

Integrins, tensegrity, and mechanotransduction

Physical forces, such as those due to gravity, play an important role in tissue development and remodeling. Yet, little is known about how individual cells sense mechanical signals or how they transduce them into a chemical response. Rather than listing the numerous signal pathways that have been found to be sensitive to mechanical stimulation, we need to place potential molecular signaling mechanisms within the context of the entire cell. The model presented is based on the concept that cells use tensegrity architecture to organize their cytoskeleton and stabilize their form. Studies with stick and string tensegrity cell models predict that living cells are hard-wired to respond immediately to external mechanical stresses. This hard-wiring exists in the form of discrete cytoskeletal filament networks that mechanically couple specific cell surface receptors, such as integrins, to nuclear matrix scaffolds and to potential transducing molecules that physically associate with the cytoskeleton. If these signaling molecules do function in a "solid-state", then mechanical stresses may be transduced into biochemical responses through force-dependent changes in cytoskeletal geometry or through local alterations in thermodynamic or kinetic parameters. Changes in cytoskeletal tension (prestress) also may play a role in signal amplification and adaptation. Recent experimental results are described which provide direct support for the tensegrity theory.

Review↗
NASA NTRS2007

Carbon Nanotubes for Space Photovoltaic Applications

Carbon nanotubes (CNTs) can be envisioned as an individual graphene sheet rolled into a seamless cylinder (single-walled, SWNT), or concentric sheets as in the case of a multi-walled carbon nanotube (MWNT) (1). The role-up vector will determine the hexagonal arrangement and "chirality" of the graphene sheet, which will establish the nanotube to be metallic or semiconducting. The optoelectronic properties will depend directly on this chiral angle and the diameter of the SWNT, with semiconductor types exhibiting a band gap energy (2). Characteristic of MWNTs are the concentric graphene layers spaced 0.34 nm apart, with diameters from 10-200 nm and lengths up to hundreds of microns (2). In the case of SWNTs, the diameters range from 0.4 - 2 nm and lengths have been reported up to 1.5 cm (3). SWNTs have the distinguishable property of "bundling" together due to van der Waal's attractions to form "ropes." A comparison of these different structural types is shown in Figure 1. The use of SWNTS in space photovoltaic (PV) applications is attractive for a variety of reasons. Carbon nanotubes as a class of materials exhibit unprecedented optical, electrical, mechanical properties, with the added benefit of being nanoscale in size which fosters ideal interaction in nanomaterial-based devices like polymeric solar cells. The optical bandgap of semiconducting SWNTs can be varied from approx. 0.4 - 1.5 eV, with this property being inversely proportional to the nanotube diameter. Recent work at GE Global Research has shown where a single nanotube device can behave as an "ideal" pn diode (5). The SWNT was bridged over a SiO2 channel between Mo contacts and exhibited an ideality factor of 1, based on a fit of the current-voltage data using the diode equation. The measured PV efficiency under a 0.8 eV monochromatic illumination showed a power conversion efficiency of 0.2 %. However, the projected efficiency of these junctions is estimated to be > 5 %, especially when one considers the enhanced absorption (from nanotubes whose bandgap is tailored to illumination) and electromagnetic coupling in a network of nanotubes.

Efstathiadis, Harry↗