Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “network solutions”

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 847 records · Page 47

Data-Driven Distribution System Coordinated PV Inverter Control Using Deep Reinforcement Learning

The deployment of distributed solar photovoltaic (PV) systems has increased consistently over the past decades. High penetrations of PVs could cause a series of adverse grid impacts, such as voltage violations. The recent development of smart inverter technologies rises the incentives of developing PV control solutions that regulate the inverter output power and seeking the optimization on system operational objectives. This paper proposes a data-driven control solution based on deep reinforcement learning (DRL) to optimize PV inverters for voltage regulation. The proposed solution can minimize PV real power curtailment while maintaining network voltage at an acceptable range. Comparison results between the proposed DRL control algorithms with deep deterministic policy gradient (DDPG) and volt-var control on a real feeder in west Colorado highlight the advantage of the proposed framework in controlling the system voltage while minimizing the PV real power curtailment.

deep reinforcement learning↗

Physics-Informed Graph Neural Networks for Collaborative Dynamic Reconfiguration and Voltage Regulation in Unbalanced Distribution Systems

Network reconfiguration has long been employed as a strategic approach to minimize power distribution system losses and effectively regulate voltage levels. Tap-changing voltage regulators are also critical for controlling bus voltages, especially in accommodating the increasing integration of distributed energy resources (DERs) with intermittent outputs. This paper introduces novel methodologies to address the challenges of dynamic reconfiguration and optimal tap setting in unbalanced three-phase distribution systems. We propose an approximated mixed-integer quadratically constrained program (MIQCP) to model dynamic reconfiguration, along with a pioneering formulation for voltage regulator (VR) tap-setting based on Special Ordered Set type 1 (SOS1). To mitigate computational complexity, we propose a physics-informed spatial-temporal graph convolutional network (STGCN) with an integrated link classifier. The proposed approach enables efficient solution generation by fixing specific variables in the MIQCP instance and solving the simplified sub-MIP using an MIP solver. Numerical studies demonstrate the superior prediction accuracy of our STGCN model compared to baseline neural network models, resulting in reduced DER curtailment and voltage deviation with shorter computation time.

dynamic reconfiguration↗

Self-organization of helium precipitates into elongated channels within metal nanolayers

Material degradation due to precipitation of implanted helium (He) is a key concern in nuclear energy. Decades of research have mapped out the fate of He precipitates in metals, from nucleation and growth of equiaxed bubbles and voids to formation and bursting of surface blisters. By contrast, we show that He precipitates confined within nanoscale metal layers depart from their classical growth trajectories: They self-organize into elongated channels. These channels form via templated nucleation of He precipitates along layer surfaces followed by their growth and spontaneous coalescence into stable precipitate lines. The total line length and connectivity increases with the amount of implanted He, indicating that these channels ultimately interconnect into percolating “vascular” networks. In conclusion, vascularized metal composites promise a transformative solution to He-induced damage by enabling in operando outgassing of He and other impurities while maintaining material integrity.

36 MATERIALS SCIENCE↗

Game Theory for Proactive Dynamic Defense and Attack Mitigation in Cyber-Physical Systems

While there has been a great deal of security research focused on preventing attacks, there has been less work on how one should balance security and resilience investments. In this work we developed and evaluated models that captured both explicit defenses and other mitigations that reduce the impact of attacks. We examined these issues both in more broadly applicable general Stackelberg models and in more specific network and power grid settings. Finally, we compared these solutions to existing work in terms of both solution quality and computational overhead.

97 MATHEMATICS AND COMPUTING↗

Securing Inverter Communication: Proactive Intrusion Detection and Mitigation System to Tap, Analyze, and Act

The electric grid has undergone rapid, revolutionary changes in recent years; from the addition of advanced smart technologies to the growing penetration of distributed energy resources (DERs) to increased interconnectivity and communications. However, these added communications, access interfaces, and third-party software to enable autonomous control schemes and interconnectivity also expand the attack surface of the grid. To address the gap of DER cybersecurity and secure the grid-edge to motivate a holistic, defense-in-depth approach, a proactive intrusion detection and mitigation system (PIDMS) device was developed to secure PV smart inverter communications. The PIDMS was developed as a distributed, flexible bump-in-the-wire (BITW) solution for protecting PV smart inverter communications. Both cyber (network traffic) and physical (power system measurements) are processed using network intrusion monitoring tools and custom machinelearning algorithms for deep packet analysis and cyber-physical event correlation. The PIDMS not only detects abnormal events but also deploys mitigations to limit or eliminate system impact; the PIDMS communicates with peer PIDMSs at different locations using the MQTT protocol for increased situational awareness and alerting. The details of the PIDMS methodology and prototype development are detailed in this report as well as the evaluation results within a cyber-physical emulation environment and subsequent industry feedback.

14 SOLAR ENERGY↗

Neuromorphic Photonics Based on Phase Change Materials

Neuromorphic photonics devices based on phase change materials (PCMs) and silicon photonics technology have emerged as promising solutions for addressing the limitations of traditional spiking neural networks in terms of scalability, response delay, and energy consumption. In this review, we provide a comprehensive analysis of various PCMs used in neuromorphic devices, comparing their optical properties and discussing their applications. We explore materials such as GST (Ge 2 Sb 2 Te 5 ), GeTe-Sb 2 Te 3 , GSST (Ge 2 Sb 2 Se 4 Te 1 ), Sb 2 S 3 /Sb 2 Se 3 , Sc 0.2 Sb 2 Te 3 (SST), and In 2 Se 3 , highlighting their advantages and challenges in terms of erasure power consumption, response rate, material lifetime, and on-chip insertion loss. By investigating the integration of different PCMs with silicon-based optoelectronics, this review aims to identify potential breakthroughs in computational performance and scalability of photonic spiking neural networks. Further research and development are essential to optimize these materials and overcome their limitations, paving the way for more efficient and high-performance photonic neuromorphic devices in artificial intelligence and high-performance computing applications.

36 MATERIALS SCIENCE↗

Plagioclase-melt equilibria

Results of experiments investigating the crystallization of plagioclase from natural and synthetic melts are presented and are analyzed in terms of empirical and semiquantitative mixing models for the melt. Elemental partition constants were determined from the results and from other published data. Activities of the melt components were modeled by assuming that the melt consists of two independent quasi-lattices of network-forming and network-modifying components, each of which is an ideal solution of its respective component. The semiquantitative analysis supports the suggestion that Na(+) is strongly associated with tetrahedrally-coordinated Al in the melt. It is shown that it is possible to predict the composition of plagioclase crystallizing under equilibrium conditions from a dry melt of known composition and known temperature at low total pressure.

Drake, M. J.↗

Navigating the International Cometary Explorer for encounter with Comet Giacobini-Zinner

The navigation of the International Cometary Explorer for its encounter with Comet Giacobini-Zinner, provided by orbit determination using radio metric data from the 64-m Deep Space Network antennas in California and Spain, is discussed. Orbital solutions providing predictions of 50-km geocentric delivery accuracy in the target plane were achieved using 6-12 week data arcs between periodic attitude change maneuvers. The one-sigma two-way range and range rate were found to be 40 m and 0.2 mm/s or better, respectively. Post-flight analysis shows tail centerline passage to be achieved within 10 s of the predicted time, and a geocentric position uncertainty at the encounter of better than 40 km is found.

Efron, L.↗

CONSOLE: A CAD tandem for optimization-based design interacting with user-supplied simulators

CONSOLE employs a recently developed design methodology (International Journal of Control 43:1693-1721) which provides the designer with a congenial environment to express his problem as a multiple ojective constrained optimization problem and allows him to refine his characterization of optimality when a suboptimal design is approached. To this end, in CONSOLE, the designed formulates the design problem using a high-level language and performs design task and explores tradeoff through a few short and clearly defined commands. The range of problems that can be solved efficiently using a CAD tools depends very much on the ability of this tool to be interfaced with user-supplied simulators. For instance, when designing a control system one makes use of the characteristics of the plant, and therefore, a model of the plant under study has to be made available to the CAD tool. CONSOLE allows for an easy interfacing of almost any simulator the user has available. To date CONSOLE has already been used successfully in many applications, including the design of controllers for a flexible arm and for a robotic manipulator and the solution of a parameter selection problem for a neural network.

Fan, Michael K. H.↗

Cascade Error Projection with Low Bit Weight Quantization for High Order Correlation Data

In this paper, we reinvestigate the solution for chaotic time series prediction problem using neural network approach. The nature of this problem is such that the data sequences are never repeated, but they are rather in chaotic region. However, these data sequences are correlated between past, present, and future data in high order. We use Cascade Error Projection (CEP) learning algorithm to capture the high order correlation between past and present data to predict a future data using limited weight quantization constraints. This will help to predict a future information that will provide us better estimation in time for intelligent control system. In our earlier work, it has been shown that CEP can sufficiently learn 5-8 bit parity problem with 4- or more bits, and color segmentation problem with 7- or more bits of weight quantization. In this paper, we demonstrate that chaotic time series can be learned and generalized well with as low as 4-bit weight quantization using round-off and truncation techniques. The results show that generalization feature will suffer less as more bit weight quantization is available and error surfaces with the round-off technique are more symmetric around zero than error surfaces with the truncation technique. This study suggests that CEP is an implementable learning technique for hardware consideration.

Duong, Tuan A.↗

Did I Say Terabyte? I Meant Petabyte: Data Archiving in the Era of SDO

Two years ago (Gurman 1999, Bull, AAS, 31, 955), we discussed the treatment of archives of the order of 10 Tbyte per year from solar physics missions in the period 2004 - 2006 (e.g. Solar-B and STEREO). By early 2007, we expect that the Sun-Earth Connections community will have to deal with data sets from the Solar Dynamics Observatory (SDO) of order I Tbyte per day. As in the previous work, we examine several alternatives for dealing with data flow and service on a fire-hose scale, and show that off-the shelf, network-attached storage can provide an inexpensive and scaleable solution. We discuss some of the differences between an SDO data archive, as well as the range of requirements for data integrity, disaster recovery, &c. in various scenarios for archive concentration or distribution.

Gurman, Joseph B.↗

Multi-Body Analysis of the 1/5 Scale Wind Tunnel Model of the V-22 Tiltrotor

The paper presents a multi-body analysis of the 1/5 scale wind tunnel model of the V-22 tiltrotor, the Wing and Rotor Aeroelastic Testing System (WRATS), currently tested at NASA Langley Research Center. An original multi-body formulation has been developed at the Dipartimento di Ingegneria Aerospaziale of the Politecnico di Milano, Italy. It is based on the direct writing of the equilibrium equations of independent rigid bodies, connected by kinematic constraints that result in the addition of algebraic constraint equations, and by dynamic constraints, that directly contribute to the equilibrium equations. The formulation has been extended to the simultaneous solution of interdisciplinary problems by modeling electric and hydraulic networks, for aeroservoelastic problems. The code has been tailored to the modeling of rotorcrafts while preserving a complete generality. A family of aerodynamic elements has been introduced to model high aspect aerodynamic surfaces, based on the strip theory, with quasi-steady aerodynamic coefficients, compressibility, post-stall interpolation of experimental data, dynamic stall modeling, and radial flow drag. Different models for the induced velocity of the rotor can be used, from uniform velocity to dynamic in flow. A complete dynamic and aeroelastic analysis of the model of the V-22 tiltrotor has been performed, to assess the validity of the formulation and to exploit the unique features of multi-body analysis with respect to conventional comprehensive rotorcraft codes; These are the ability to model the exact kinematics of mechanical systems, and the possibility to simulate unusual maneuvers and unusual flight conditions, that are particular to the tiltrotor, e.g. the conversion maneuver. A complete modal validation of the analytical model has been performed, to assess the ability to reproduce the correct dynamics of the system with a relatively coarse beam model of the semispan wing, pylon and rotor. Particular care has been used to model the kinematics of the gimbal joint, that characterizes the rotor hub, and of the control system, consisting in the entire swashplate mechanism. The kinematics of the fixed and the rotating plates have been modeled, with variable length control links used to input the controls, the rotating flexible links, the pitch horns and the pitch bearings. The investigations took advantage of concurring wind tunnel test runs, that were performed in August 1998, and allowed the acquisition of data specific to the multi-body analysis.

Ghiringhelli, G. L.↗

Strategies for Information Retrieval and Virtual Teaming to Mitigate Risk on NASA's Missions

Following the loss of NASA's Space Shuttle Columbia in 2003, it was determined that problems in the agency's organization created an environment that led to the accident. One component of the proposed solution resulted in the formation of the NASA Engineering Network (NEN), a suite of information retrieval and knowledge sharing tools. This paper describes the implementation of this set of search, portal, content management, and semantic technologies, including a unique meta search capability for data from distributed engineering resources. NEN's communities of practice are formed along engineering disciplines where users leverage their knowledge and best practices to collaborate and take informal learning back to their personal jobs and embed it into the procedures of the agency. These results offer insight into using traditional engineering disciplines for virtual teaming and problem solving.

communities of practices↗

Chemical Sharpening, Shortening, and Unzipping of Boron Nitride Nanotubes

Boron nitride nanotubes (BNNTs), the one-dimensional member of the boron nitride nanostructure family, are generally accepted to be highly inert to oxidative treatments and can only be covalently modifi ed by highly reactive species. Conversely, it is discovered that the BNNTs can be chemically dispersed and their morphology modifi ed by a relatively mild method: simply sonicating the nanotubes in aqueous ammonia solution. The dispersed nanotubes are significantly corroded, with end-caps removed, tips sharpened, and walls thinned. The sonication treatment in aqueous ammonia solution also removes amorphous BN impurities and shortened BNNTs, resembling various oxidative treatments of carbon nanotubes. Importantly, the majority of BNNTs are at least partially longitudinally cut, or "unzipped". Entangled and freestanding BN nanoribbons (BNNRs), resulting from the unzipping, are found to be approximately 5-20 nm in width and up to a few hundred nanometers in length. This is the fi rst chemical method to obtain BNNRs from BNNT unzipping. This method is not derived from known carbon nanotube unzipping strategies, but is unique to BNNTs because the use of aqueous ammonia solutions specifi cally targets the B-N bond network. This study may pave the way for convenient processing of BNNTs, previously thought to be highly inert, toward controlling their dispersion, purity, lengths, and electronic properties.

Liao, Yunlong↗

Airborne Trajectory Management (ABTM): A Blueprint for Greater Autonomy in Air Traffic Management

The aviation users of the National Airspace System (NAS) - the airlines, General Aviation (GA), the military and, most recently, operators of Unmanned Aircraft Systems (UAS) - are constrained in their operations by the design of the current paradigm for air traffic control (ATC). Some of these constraints include ATC preferred routes, departure fix restrictions and airspace ground delay programs. As a result, most flights cannot operate on their most efficient business trajectories and a great many flights are delayed even getting into the air, which imposes a significant challenge to maintaining efficient flight and network operations. Rather than accepting ever more sophisticated scheduling solutions to accommodate the existing constraints in the airspace, a series of increasingly capable airborne technologies, integrated with planned improvements in the ground system through the Federal Aviation Administration (FAA) Next Generation Air Traffic Management System (NextGen) programs, could produce much greater operational flexibility for flight path optimization by the aviation system users. These capabilities, described in research coming out of NASA's Aeronautics Research Mission Directorate, can maintain or improve operational safety while taking advantage of air and ground NextGen technologies in novel ways. The underlying premise is that the nation's physical airspace is still abundant and underused, and that the delays and inefficient flight operations resulting from artificial structure in airspace use and procedural constraints on those operations may not be necessary for safe and efficient flight. This article is not an indictment of today's NAS or the people who run it. Indeed, it is an exceptional achievement that Air Traffic Management (ATM) - the complex human/machine conglomeration of communications, navigation and surveillance equipment and the rules and procedures for controlling traffic in the airspace - has both the capacity and enables the degree of efficiency in air travel that it does. But it is also true that sixty years of the "radar religion" (i.e., reliance on radar-based command and control) has produced several generations of ATM system operators and researchers who believe that introducing automation within the existing functional structure of ATM is the only way to "modernize" the system. Even NextGen, which began as a proposal for "transformational" change in the way ATC is performed, has morphed over the last decade and a half to become just the inclusion of Global Positioning System (GPS) for navigation, Automatic Dependent Surveillance Broadcast (ADS-B) for surveillance, and Data Communications (Data Comm) for communications, while still operating in rigidly structured airspace with human controllers being responsible for separation and traffic flow management (TFM) within defined sectors of airspace, using the same horizontal separation standards that have been in use since raw primary radar was introduced in the 1950s. No system as massive as the current NAS ATM can be replaced with a better system while simultaneously meeting the transportation and other aviation needs of the nation. A new generation of more flexible operations must emerge and yet coexist in harmony with the current operation (i.e., share the same airspace without segregation), thereby enabling a long-term transformation to take place in the way increasing numbers of flights are handled. Market forces will be the ultimate driver of this transformation, and investment realities mandate that real benefits must accrue to the first operators to adopt these new capabilities. In fact, the kinds of missions envisioned in the emerging world of UAS operations, unachievable under conventional ATM, demand that this transformation take place. Airborne Trajectory Management (ABTM) is proposed as a series of transformational steps leading to vastly increased flexibility in flight operations and capacity in the airspace to accommodate many varied airspace uses while improving safety. As will be described, ABTM enables the gradual emergence of a new paradigm for user-based trajectory management in ATM that brings tangible benefits to equipped operators at every step while leveraging the air and ground investments of NextGen. There are five steps in this ABTM transformation.1 NASA has extensively studied the first and last of these steps, and a roadmap of increasing capabilities and benefits is proposed for bridging between these operational concepts.

Cotton, William B.↗

Harmony: Bringing Data Together by Bringing Services Together

As Earth observation data volume, velocity, and variety continues to accelerate, so do the challenges of working with those data. The computation, storage, and network transfer requirements for multi-petabyte datasets demand solutions that allow users to process, store, and move fewer bytes while still finding the valuable insights they seek. Our cloud-based data transformation framework, Harmony, tackles these challenges by providing consistent, standards-based interface to multiple disparate backend processors collocated with NASA EOSDIS data. It allows data scientists to perform data processing and harmonization activities across many datasets through familiar tooling. Simultaneously, it provides a clear, consistent interface for data providers to expose new or customized backend services for their data. This talk will discuss Harmony, its architecture and interface, and the path forward for cloud-based NASA EOSDIS data harmonization services.

Quinn, Patrick↗

TAOS Orbit Determination Results Using Global Positioning Satellites

Orbit determination results for the Air Force Phillips Laboratory's Technology for Autonomous Operational Survivability (TAOS) satellite using a Rockwell AST V Global Positioning System (GPS) receiver are presented in this paper. Under a cooperative effort, GPS orbit determination technology developed at Jet Propulsion Laboratory (JPL) has been transferred to the U.S. Air Force. JPL's post processing differential GPS software MIRAGE [1] was modified to perform precise orbit determination for the TAOS satellite. Reconstructed TAOS position accuracies of 10 meters (3 sigma) are the objective. With four days of data, three-dimensional positions of less than 3 meters (1 sigma) have been achieved with overlapping orbit determination spans. Orbit determination results are also compared with those of the on-board GPS receiver's navigation solutions and with the Air Force's Satellite Control Network SGLS processing.

TAOS↗