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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 451 records · Page 25
All sourcesNASA NTRSDOE OSTI
NASA NTRS2011

Correlation Function Analysis of Fiber Networks: Implications for Thermal Conductivity

The heat transport in highly porous fiber structures is investigated. The fibers are supposed to be thin, but long, so that the number of the inter-fiber connections along each fiber is large. We show that the effective conductivity of such structures can be found from the correlation length of the two-point correlation function of the local conductivities. Estimation of the parameters, determining the conductivity, from the 2D images of the structures is analyzed.

Martinez-Garcia, Jorge↗
DOE OSTI2023

Experimental Analysis of Distribution Network Voltage Regulation Using Smart Inverters: Preprint

Smart inverters (SI) have huge potential in providing grid services which has not been fully realized yet. One of these grid services, distribution network voltage regulation by SI, can improve the network voltage by regulating the SI reactive and active power output. Voltage regulation by SI is much faster compared to traditional voltage regulating devices, e.g. tap changing transformer, capacitor banks. However, there is gap in available published literature on the characteristics of SIs when the SI is controlled by local controller or external control signal. This paper presents the experimental study to characterize SI reactive power regulation response to two different control methods: autonomous control method and remote dispatch method. It was found that IS reactive power regulation response could be significantly different in terms of delay, and ramp rate for these two methods. Finally, Power-Hardware-in-The-Loop (PHIL) tests were conducted to evaluate the performance of these two methods. The PHIL tests results show that SI response characteristics for autonomous control method and remote dispatch method need to be considered during planning for distribution network voltage regulation using SI.

autonomous control↗
NASA NTRS1999

Wavelet and Multiresolution Analysis for Finite Element Networking Paradigms

This paper presents a final report on Wavelet and Multiresolution Analysis for Finite Element Networking Paradigms. The focus of this research is to derive and implement: 1) Wavelet based methodologies for the compression, transmission, decoding, and visualization of three dimensional finite element geometry and simulation data in a network environment; 2) methodologies for interactive algorithm monitoring and tracking in computational mechanics; and 3) Methodologies for interactive algorithm steering for the acceleration of large scale finite element simulations. Also included in this report are appendices describing the derivation of wavelet based Particle Image Velocity algorithms and reduced order input-output models for nonlinear systems by utilizing wavelet approximations.

Kurdila, Andrew J.↗
NASA NTRS1992

Nested Neural Networks

Report presents analysis of nested neural networks, consisting of interconnected subnetworks. Analysis based on simplified mathematical models more appropriate for artificial electronic neural networks, partly applicable to biological neural networks. Nested structure allows for retrieval of individual subpatterns. Requires fewer wires and connection devices than fully connected networks, and allows for local reconstruction of damaged subnetworks without rewiring entire network.

Baram, Yoram↗
DOE OSTI2024

Verifying Cyber Implementation Best Practices With Malcolm

Network traffic analysis can reveal a lot about what's right or wrong with a network's cybersecurity footing. Using Malcolm, a powerful open-source network traffic analysis tool suite for network security monitoring, cyber analysts and asset owners can validate cybersecurity best practices and uncover red flags in network configuration, including: proper network segmentation east-west (cross-segment) and north-south traffic unsecure or outdated network protocols authentication using clear text credentials rogue devices and services unexpected protocols (e.g., IPv6, DNS, DHCP, update checks, etc.) suspicious file transfers

99 GENERAL AND MISCELLANEOUS↗
NASA NTRS2001

Extension of a System Level Tool for Component Level Analysis

This paper presents an extension of a numerical algorithm for network flow analysis code to perform multi-dimensional flow calculation. The one dimensional momentum equation in network flow analysis code has been extended to include momentum transport due to shear stress and transverse component of velocity. Both laminar and turbulent flows are considered. Turbulence is represented by Prandtl's mixing length hypothesis. Three classical examples (Poiseuille flow, Couette flow, and shear driven flow in a rectangular cavity) are presented as benchmark for the verification of the numerical scheme.

Majumdar, Alok↗
NASA NTRS2002

Extension of a System Level Tool for Component Level Analysis

This paper presents an extension of a numerical algorithm for network flow analysis code to perform multi-dimensional flow calculation. The one dimensional momentum equation in network flow analysis code has been extended to include momentum transport due to shear stress and transverse component of velocity. Both laminar and turbulent flows are considered. Turbulence is represented by Prandtl's mixing length hypothesis. Three classical examples (Poiseuille flow, Couette flow and shear driven flow in a rectangular cavity) are presented as benchmark for the verification of the numerical scheme.

Majumdar, Alok↗
NASA NTRS2008

Multichannel Networked Phasemeter Readout and Analysis

Netmeter software reads a data stream from up to 250 networked phasemeters, synchronizes the data, saves the reduced data to disk (after applying a low-pass filter), and provides a Web server interface for remote control. Unlike older phasemeter software that requires a special, real-time operating system, this program can run on any general-purpose computer. It needs about five percent of the CPU (central processing unit) to process 20 channels because it adds built-in data logging and network-based GUIs (graphical user interfaces) that are implemented in Scalable Vector Graphics (SVG). Netmeter runs on Linux and Windows. It displays the instantaneous displacements measured by several phasemeters at a user-selectable rate, up to 1 kHz. The program monitors the measure and reference channel frequencies. For ease of use, levels of status in Netmeter are color coded: green for normal operation, yellow for network errors, and red for optical misalignment problems. Netmeter includes user-selectable filters up to 4 k samples, and user-selectable averaging windows (after filtering). Before filtering, the program saves raw data to disk using a burst-write technique.

Edmonds, Karina↗
DOE OSTI2022

Mechanism Analysis of Wind Turbine Var Oscillations

Electromagnetic transient simulation of parallel connected 4-MW type-3 wind turbines based on original equipment manufacturer's real-code turbine model shows 1.2-Hz turbine-turbine oscillations in reactive power. This letter reveals why such oscillations occur in the individual var measurement, while being insignificant in the total var measurement, regardless of the varying grid impedance. We adopt two analysis approaches: open-loop single-input single-output analysis and network decomposition. The two approaches differ in their treatment of turbine-network interaction. The open-loop analysis shows that the turbine-turbine oscillation mode is due to an open-loop system pole being attracted to an open-loop system zero. Furthermore, we use network decomposition method to explain why this mode is observable in individual vars while not observable in the total var. The entire system of n -turbines can be viewed as n decoupled circuits. For the two-turbine case, the system has an aggregated mode and a turbine-turbine oscillation mode. Here, the aggregated mode is associated with a circuit associated with the total var, while the turbine-turbine oscillation mode is associated with the var difference and is insensitive to the grid parameters.

17 WIND ENERGY↗
DOE OSTI2023

Comparative Study of High-Resolution LysB29(Nε-myristoyl) des(B30) Insulin Structures Display Novel Dynamic Causal Interrelations in Monomeric-Dimeric Motions

The treatment of insulin-dependent diabetes mellitus is characterized by artificial supplementation of pancreatic β-cell ability to regulate sugar levels in the blood. Even though various insulin analogs are crucial for reasonable glycemic control, understanding the dynamic mechanism of the insulin analogs may help to improve the best-protracted insulin analog to assist people with type 1 diabetes (T1D) to live comfortably while maintaining tight glycemic control. Here, we present the high-resolution crystal structure of NN304, known as insulin detemir, to 1.7 Å resolution at cryogenic temperature. We computationally further investigated our crystal structure’s monomeric-dimeric conformation and dynamic profile by comparing it with a previously available detemir structure (PDB ID: 1XDA). Our structure (PDB ID: 8HGZ), obtained at elevated pH, provides electrostatically triggered minor movements in the equilibrium between alternate conformational substates compared to the previous structure, suggesting it might induce an intermediate state in the dissociation pathway of the insulin detemir’s hexamer:dihexamer equilibrium. Supplemented with orientational cross-correlation analysis by a Gaussian network model (GNM), this alternate oligomeric conformation offers the distinct cooperative motions originated by loose coupling of distant conformational substates of a protracted insulin analog that has not been previously observed.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRSDate not supplied

A Framework for the Analysis of Deep Neural Networks in Autonomous Aerospace Applications using Bayesian Statistics

Deep Neural Networks (DNNs) are considered to be key components in many autonomous systems. Applications range from vision-based obstacle avoidance to intelligent/learning control and planning. Safety-critical applications as found in the aerospace domain require that the behavior of the DNN is validated and tested rigorously for safety of the autonomous system (AUS). In this paper, we present a framework to support testing of DNNs and the analysis of the network structure. Our framework employs techniques from statistical modeling and active learning to effectively generate test cases for DNN safety testing and performance analysis. We will present results of a case study on a physics-based Deep recurrent residual neural network (DR-RNN), which has been trained to emulate the aerodynamics behavior of a fixed-wing aircraft.

Deep Neural networks↗
NASA NTRS2012

Network Connectivity for Permanent, Transient, Independent, and Correlated Faults

This paper develops a method for the quantitative analysis of network connectivity in the presence of both permanent and transient faults. Even though transient noise is considered a common occurrence in networks, a survey of the literature reveals an emphasis on permanent faults. Transient faults introduce a time element into the analysis of network reliability. With permanent faults it is sufficient to consider the faults that have accumulated by the end of the operating period. With transient faults the arrival and recovery time must be included. The number and location of faults in the system is a dynamic variable. Transient faults also introduce system recovery into the analysis. The goal is the quantitative assessment of network connectivity in the presence of both permanent and transient faults. The approach is to construct a global model that includes all classes of faults: permanent, transient, independent, and correlated. A theorem is derived about this model that give distributions for (1) the number of fault occurrences, (2) the type of fault occurrence, (3) the time of the fault occurrences, and (4) the location of the fault occurrence. These results are applied to compare and contrast the connectivity of different network architectures in the presence of permanent, transient, independent, and correlated faults. The examples below use a Monte Carlo simulation, but the theorem mentioned above could be used to guide fault-injections in a laboratory.

White, Allan L.↗