Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “RC NETWORK”

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 91 records · Page 5
All sourcesNASA NTRSDOE OSTI
DOE OSTI2019

Hierarchical Distributed Voltage Regulation in Networked Autonomous Grids: Preprint

We propose a novel algorithm to solve optimal power flow (OPF) that aims at dispatching controllable distributed energy resources (DERs) for voltage regulation at minimum cost. The proposed algorithm features unprecedented scalability to large distribution networks by utilizing an information structure based on networked autonomous grids (AGs). Specifically, each AG is a subtree of a large distribution network that has a tree topology. The topology and line parameters of each AG are known only to a regional coordinator (RC) that is responsible for communicating with and dispatching the DERs within this AG. The reduced network, where each AG is treated as a node, is managed by a central coordinator (CC), which knows the topology and line parameters of the reduced network only and communicates with all the RCs. We jointly explore this information structure and the structure of the linearized distribution power flow (LinDistFlow) model to derive a hierarchical, distributed implementation of the primal-dual gradient algorithm that solves OPF. The proposed implementation significantly reduces the computation burden compared to the centrally coordinated implementation of the primal-dual algorithm. Numerical results on a 4,521-node test feeder show that the proposed hierarchical distributed algorithm can achieve more than 10-fold improvement in the speed of convergence compared to the centrally coordinated primal-dual algorithm.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2019

Hierarchical Distributed Voltage Regulation in Networked Autonomous Grids

We propose a novel algorithm to solve optimal power flow (OPF) that aims at dispatching controllable distributed energy resources (DERs) for voltage regulation at minimum cost. The proposed algorithm features unprecedented scalability to large distribution networks by utilizing an information structure based on networked autonomous grids (AGs). Specifically, each AG is a subtree of a large distribution network that has a tree topology. The topology and line parameters of each AG are known only to a regional coordinator (RC) that is responsible for communicating with and dispatching the DERs within this AG. The reduced network, where each AG is treated as a node, is managed by a central coordinator (CC), which knows the topology and line parameters of the reduced network only and communicates with all the RCs. We jointly explore this information structure and the structure of the linearized distribution power flow (LinDistFlow) model to derive a hierarchical, distributed implementation of the primal-dual gradient algorithm that solves the OPF. The proposed implementation significantly reduces the computation burden compared to the centrally coordinated implementation of the primal-dual algorithm. Numerical results on a 4,521-node test feeder show that the proposed hierarchical distributed algorithm can achieve an improvement of more than tenfold in the speed of convergence compared to the centrally coordinated primal-dual algorithm.

24 POWER TRANSMISSION AND DISTRIBUTION↗
NASA NTRS1972

A linear voltage-tunable distributed null device.

A linear voltage-tunable null device was predicted, fabricated, and tested. This filter is conceptually a distributed parameter RC representation of the channel of a MOSFET in a network configuration with a second MOSFET that is treated as a variable resistor. Classical transmission-line theory is used to predict a linear tuning curve with applied bias for the device. This concept was used to design a null device having a null that is linearly tunable in the range of 100 kHz. Such devices were fabricated and tested. Typical MOS processing steps were used and the resulting structures are compatible with the planar technology. The compatibility leads towards extension of this work to different frequency ranges for other specific applications.

Benz, H. F.↗
DOE OSTI2016

Modular Homogeneous Chromophore–Catalyst Assemblies

Photosynthetic reaction center (RC) proteins convert incident solar energy to chemical energy through a network of molecular cofactors which have been evolutionarily tuned to couple efficient light-harvesting, directional electron transfer, and long-lived charge separation with secondary reaction sequences. These molecular cofactors are embedded within a complex protein environment which precisely positions each cofactor in optimal geometries along efficient electron transfer pathways with localized protein environments facilitating sequential and accumulative charge transfer. By contrast, it is difficult to approach a similar level of structural complexity in synthetic architectures for solar energy conversion. However, by using appropriate self-assembly strategies, we anticipate that molecular modules, which are independently synthesized and optimized for either light-harvesting or redox catalysis, can be organized into spatial arrangements that functionally mimic natural photosynthesis. In this Account, we describe a modular approach to new structural designs for artificial photosynthesis which is largely inspired by photosynthetic RC proteins. We focus on recent work from our lab which uses molecular modules for light-harvesting or proton reduction catalysis in different coordination geometries and different platforms, spanning from discrete supramolecular assemblies to molecule–nanoparticle hybrids to protein-based biohybrids. Molecular modules are particularly amenable to high-resolution characterization of the ground and excited state of each module using a variety of physical techniques; such spectroscopic interrogation helps our understanding of primary artificial photosynthetic mechanisms. In particular, we discuss the use of transient optical spectroscopy, EPR, and X-ray scattering techniques to elucidate dynamic structural behavior and light-induced kinetics and the impact on photocatalytic mechanism. Two different coordination geometries of supramolecular photocatalyst based on the [Ru(bpy)3]2+ (bpy = 2,2'-bipyridine) light-harvesting module with cobaloxime-based catalyst module are compared, with progress in stabilizing photoinduced charge separation identified. These same modules embedded in the small electron transfer protein ferredoxin exhibit much longer charge-separation, enabled by stepwise electron transfer through the native [2Fe-2S] cofactor. We anticipate that the use of interchangeable, molecular modules which can interact in different coordination geometries or within entirely different structural platforms will provide important fundamental insights into the effect of environment on parameters such as electron transfer and charge separation, and ultimately drive more efficient designs for artificial photosynthesis.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS1985

Diurnal variations of cosmic ray geomagnetic cut-off threshold rigidities

The spectrographic global survey method was used to investigate the rigidity variations Rc of geomagnetic cut-off as a function of local time and the level of geomagnetic disturbance for a number of stations of the world wide network. It is shown that geomagnetic cut-off threshold rigidities undergo diurnal variations. The diurnal wave amplitude decreases with increasing threshold rigidity Rc, and the wave maximum occurs at 2 to 4 hr LT. The amplitude of diurnal variations increases with increasing geomagnetic activity. The results agree with those from trajectory calculations made for an asymmetric model of the magnetosphere during different geomagnetic disturbance conditions.

Dvornikov, V. M.↗
DOE OSTI2025

Entropy is an important design principle in the photosystem II supercomplex

Photosystem II (PSII) can achieve near-unity quantum efficiency of light harvesting in ideal conditions and can dissipate excess light energy as heat to prevent the formation of reactive oxygen species (ROS) under light stress. Understanding how this pigment–protein complex accomplishes these opposing goals is a topic of great interest that has so far been explored primarily through the lens of the system energetics. Despite PSII’s known flat energy landscape, a thorough consideration of the entropic effects on energy transfer in PSII is lacking. In this work, we aim to discern the free energetic design principles underlying the PSII energy transfer network. To accomplish this goal, we employ a structure-based rate matrix and compute the free energy terms in time following a specific initial excitation to discern how entropy and enthalpy drive ensemble system dynamics. We find that the interplay between the entropy and enthalpy components differ among each protein subunit, which allows each subunit to fulfill a unique role in the energy transfer network. This individuality ensures that PSII can accomplish efficient energy trapping in the reaction center (RC), effective nonphotochemical quenching (NPQ) in the periphery, and robust energy trapping in the other-monomer RC if the same-monomer RC is closed. We also show that entropy, in particular, is a dynamically tunable feature of the PSII free energy landscape accomplished through regulation of LHCII binding. These findings help rationalize natural photosynthesis and provide design principles for more efficient solar energy harvesting technologies.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS1992

A low noise 230 GHz heterodyne receiver employing .25 sq micron area Nb/AlO(x)/Nb tunnel junctions

Recent results for a full height rectangular waveguide mixer with an integrated IF matching network are reported. Two 0.25 sq micron Nb/AlO(x)/Nb superconducting insulating superconducting (SIS) tunnel junctions with a current density of about 8500 A/sq cm and omega RC of about 2.5 at 230 GHz have been tested. Detailed measurements of the receiver noise have been made from 200-290 GHz for both junctions at 4.2 K. The lowest receiver noise temperatures were recorded at 239 GHz, measuring 48 K DSB at 4.2 K and 40 K DSB at 2.1 K. The 230 GHz receiver incorporates a one octave wide integrated low pass filter and matching network which transforms the pumped IF junction impedance to 50 ohms over a wide range of impedances.

Kooi, Jacob W.↗
NASA NTRS1972

An approach for generation of second order RC-active filters.

It is shown that node (or loop) matrix equations can be written which yield second order low-pass, band-pass, and high-pass network functions. Networks corresponding to the equations can in turn be formulated by inspection of the equations. The networks employ ideal VCT or CVT sources which can be physically realized using transistors and/or operational amplifiers. The technique yields several structures which are believed to be new.

Dunn, W. R., Jr.↗
DOE OSTI2021

Grey-box modeling and application for building energy simulations - A critical review

Grey-box modeling, as one of the three fundamental modeling techniques for building energy models, has many advantages compared with black-box modeling and white-box modeling. Additionally, it has been widely applied to solve problems of building technologies, such as building load estimation, control and optimization, and building-grid integration. However, a thorough review of grey-box modeling is not available. This review study systematically investigated various aspects of grey-box modeling for buildings. First, the fundamental aspects of grey-box modeling are presented, including the theoretical background, modeling of building elements, modeling order, modeling diagram, and order reduction. Second, the detailed modeling approaches are discussed. Third, multiple applications of grey-box modeling are investigated for building energy domain, which are categorized into the following groups: heat dynamics analysis, thermal load estimation, building control and optimization, district/urban scale energy modeling, and building-grid integration. Finally, the available software packages for grey-box modeling are compared. Overall, the challenges of using grey-box modeling can be summarized as follows: (1) the theoretical limitations and assumptions of grey-box modeling are unclear; (2) grey-box model naming convention and structure are confusing; (3) grey-box model creation is vague; (4) suitable applications of grey-box models are unknown; and (5) grey-box models lack unified software solutions for wider adoption.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2016

Microstructural analysis of recycled concrete using X-ray microtomography

This paper reports an investigation of the recycled concrete (RC) microstructure using synchrotron microtomography (μCT) at the Advanced Light Source combined with Scanning Electron Microscopy analysis. The study evaluated the influence of 50% of recycled concrete aggregate (RCA) and its water absorption compensation on the RC microstructure. The following variables were studied: a) the compressive strength of the original concrete used to obtain the RCA (40 and 80 MPa) and b) the initial moisture condition of the RCA (Saturated Surface Dry and Oven Dry). The microtomographic images showed the mixtures cast with RCA in the dry condition developed an evident macropore network surrounding the RCA particle that was not observed in the mixtures using RCA in the SSD condition. SEM images confirmed the initial findings from μCT and showed that the thickness of the interfacial transition zone in RC is in the same order of magnitude as the reference concrete.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Capability of Impedance Measurement Using Spread Spectrum Time-Domain Reflectometry

Spread spectrum time-domain reflectometry (SSTDR) has been proposed for measuring electrical impedance on live, energized systems, in electrically noisy environments, or for measuring multiple channels simultaneously. Here we evaluate the capability of SSTDR for impedance measurement from near dc to 96 MHz and find that they agree very well with measurements from a vector network analyzer (VNA). Time gating is used to remove (calibrate out) transmission line effects. We evaluate the frequency ranges over which SSTDR at different modulation frequencies is accurate for the measurement of series resistive–capacitive ( RC ) loads and observe that fusing measurements from multiple modulation frequencies can broaden the effective measurement bandwidth.

14 SOLAR ENERGY↗
NASA NTRSDate not supplied

Gateway Command and Data Handling Network Implementation and Validation

As initial Lunar Gateway modules approach design maturity, the Artemis Network Validation and Integration Lab (ANVIL) has begun demonstrations to validate avionics network dataflows. The flight architecture design includes utilizing Time-Triggered Ethernet (TTE) and layer-3 switching capabilities to enable greater automation and flexibility of critical and best effort traffic. Critical traffic is considered as Time-Triggered (TT), Rate Constrained (RC) and prioritized Best Effort (BE) traffic classes. End systems, such as mission computers, power control, and robotics, use three planes and all traffic classes while other devices interface via Best Effort. Typical best effort devices include video, laptops, wireless access points, and payloads. Other devices have a various hybrid approach of interfaces including alarms, telemetry/logging, and communication units. In the paper, we will present an update of the Gateway network architecture and how the system will operate nominally and during a stack topology reconfiguration. We will also discuss the network risks, and trade-offs of performance, flexibility, and redundancy. Finally, we will show the process for validation, demonstration, and verification approaches to the vehicle network.

Gateway↗
DOE OSTI2026

Leveraging Inequality-Constrained Data for Enhanced Liquidus Temperature Prediction in Nuclear Waste Glass Melts

Inequality-constrained data are frequently discarded in engineering, leading to significant information loss in data-scarce domains like glass characterization in nuclear waste vitrification. This paper presents a nonparametric censored-data regression framework based on an l1-norm optimization criterion that leverages slack variables to integrate left-, right-, and interval-constrained observations into training without distributional assumptions. Validated on synthetic data and a Physics-Informed Neural Network (PINN) for predicting liquidus temperature (TL), the method improved R2 from 0.60 to 0.89 and reduced Mean Absolute Error (MAE) by 48% (51.46 to 26.89?rC) on deterministic values. The traditional models failed to satisfy any inequality constraints while the proposed l1-norm PINN satisfies 81.25% of the constraints. The proposed framework effectively extracts actionable information from previously unusable data to enhance predictive accuracy, reduce epistemic uncertainty, and ensure physical consistency in complex industrial applications.

Garcia-Morado, Erick↗
DOE OSTI2021

Reservoir Computing as a Tool for Climate Predictability Studies

Reduced-order dynamical models play a central role in developing our understanding of predictability of climate irrespective of whether we are dealing with the actual climate system or surrogate climate models. In this context, the linear inverse modeling (LIM) approach, by capturing a few essential interactions between dynamical components of the full system, has proven valuable in providing insights into predictability of the full system. We demonstrate that reservoir computing (RC), a form of learning suitable for systems with chaotic dynamics, provides an alternative nonlinear approach that improves on the predictive skill of the LIM approach. We do this in the example setting of predicting sea surface temperature in the North Atlantic in the preindustrial control simulation of a popular earth system model, the Community Earth System Model so that we can compare the performance of the new RC-based approach with the traditional LIM approach both when learning data are plentiful and when such data are more limited. The improved predictive skill of the RC approach over a wide range of conditions—larger number of retained EOF coefficients, extending well into the limited data regime, etc.—suggests that this machine-learning technique may have a use in climate predictability studies. While the possibility of developing a climate emulator—the ability to continue the evolution of the system on the attractor long after failing to be able to track the reference trajectory—is demonstrated in the Lorenz-63 system, it is suggested that further development of the RC approach may permit such uses of the new approach in more realistic predictability studies.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2016

Determination of Ceres Physical Parameters Using Radiometric and Optical Data

The Dawn spacecraft was launched on September 27th, 2007. Its mission is to rendezvous with and observe the two largest bodies in the main asteroid belt, Vesta and Ceres. It has completed over a year’s worth of direct observations of Vesta from early 2011 through late 2012. In the spring of 2015, the Dawn spacecraft entered orbit around the asteroid Ceres for the start of what is expected to be more than a year of science operations. The science data collected from this encounter consist of infrared (IR) images and spectra, visible images through a number of color filters, gamma ray detections and measurements of the Ceres gravity field. These data will be collected during several science phases: an Approach phase (1500000-4860 km from Ceres), a Survey orbit (4860 km radius), a High Altitude Mapping Orbit (HAMO) (1940 km radius) and a Low Altitude Mapping Orbit (LAMO) (855 km radius). The Approach phase included three Rotational Characterization (RC) opportunities. Designing each science orbit and successfully transferring into that orbit requires a sufficiently accurate estimate of Ceres physical parameters (body fixed frame, GM and harmonics). This paper focuses on work performed to estimate Ceres physical parameters using Deep Space Network (DSN) radiometric tracking data and optical measurements derived from science camera imagery. This paper describes planning for the data acquisition, as well as processing techniques and methodology. The trajectories predicted by the gravity field estimations are also compared with the actual as-flown trajectories. Observations of the gravity at high altitudes are found to be sufficient to design precision orbits at lower altitudes. Follow-up analysis after successfully reaching LAMO is included, as is a discussion of lessons learned.

Kennedy, Brian M.↗
DOE OSTI2021

Development and validation of a second-order thermal network model for residential buildings

Heating, Ventilation, and Air Conditioning (HVAC) systems can maintain the space air temperature of residential buildings, either directly by heating/cooling the air, or indirectly via heat transfer to and from the building structure that acts as a thermal mass. Hence, HVAC systems can help achieve load shifting, peak load reduction, and/or energy cost saving, thus enabling grid-interactive HVAC operation. A home thermal model that can accurately reflect the dynamics of the space air and interior wall surface temperatures, is therefore valuable. This paper develops such a model using the standard RC (resistance-capacitance) approach. The model contains a virtual envelope node and an internal space node and is thus second-order. A hybrid parameter identification scheme, made up of the least-squares and optimal search methods, is also developed. The proposed model and scheme were validated using data collected from a test home. It was found that a modest amount of training data was sufficient to yield reliable parameter estimates and accurate prediction. It was also found that when making 24-hour-ahead prediction of the space air temperature, both methods had comparable performances when the training data began in a transition season. However, when they began in an HVAC season, the optimal search method performed better. Furthermore, the least-squares method is recommended during a transition season due to its lower computational burden, while the optimal search method is recommended during an HVAC season due to its better estimation performance.

24 POWER TRANSMISSION AND DISTRIBUTION↗
NASA NTRS1995

Remote sensing of smoke, clouds, and radiation using AVIRIS during SCAR experiments

During the past two years, researchers from several institutes joined together to take part in two SCAR experiments. The SCAR-A (Sulfates, Clouds And Radiation - Atlantic) took place in the mid-Atlantic region of the United States in July, 1993. remote sensing data were acquired with the Airborne Visible Infrared Imaging Spectrometer (AVIRIS), the MODIS Airborne Simulator (MAS), and a RC-10 mapping camera from an ER-2 aircraft at 20 km. In situ measurements of aerosol and cloud microphysical properties were made with a variety of instruments equipped on the University of Washington's C-131A research aircraft. Ground based measurements of aerosol optical depths and particle size distributions were made using a network of sunphotometers. The main purpose of SCAR-A experiment was to study the optical, physical and chemical properties of sulfate aerosols and their interaction with clouds and radiation. Sulfate particles are believed to affect the energy balance of the earth by directly reflecting solar radiation back to space and by increasing the cloud albedo. The SCAR-C (Smoke, Clouds And Radiation - California) took place on the west coast areas during September - October of 1994. Sets of aircraft and ground-based instruments, similar to those used during SCAR-A, were used during SCAR-C. Remote sensing of fires and smoke from AVIRIS and MAS imagers on the ER-2 aircraft was combined with a complete in situ characterization of the aerosol and trace gases from the C-131A aircraft of the University of Washington and the Cesna aircraft from the U.S. Forest Service. The comprehensive data base acquired during SCAR-A and SCAR-C will contribute to a better understanding of the role of clouds and aerosols in global change studies. The data will also be used to develop satellite remote sensing algorithms from MODIS on the Earth Observing System.

Gao, Bo-Cai↗