Search NASA⌕ Search

SEARCH · Search NASA

Results for “Command and Control”

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 145 records · Page 8
All sourcesNASA NTRSDOE OSTI
DOE OSTI2017

Development of the Delphi display concept for alternative explanations decision making support - 120

Human operators of advanced technology systems, such as nuclear power, command and control, and deepwater oil drilling, must be able to evaluate and respond to a wide array of operational anomalies. Unfortunately, these circumstances are often complex and ambiguous, complicating decision making tasks. One common decision making error, called confirmation bias, occurs when decision makers prematurely focus on one explanation instead of systematically considering all plausible alternative explanations that could equally well account for an operational anomaly (Nickerson, 1998). The Delphi display is designed to counteract decision makers' tendencies towards confirmation bias and to encourage them to consider all plausible explanations, including high risk explanations, they might otherwise overlook. An initial Delphi display prototype was designed to help identify the underlying cause of operational anomalies in the complex, high-consequence technology of deepwater drilling. This prototype decision aid incorporates major indicators related to operational anomalies and presents corresponding plausible explanations for each indicator, ranging from high-risk system-critical explanations to lower-risk but still significant events. The Delphi display incorporates several innovative features to help decision makers detect and monitor operational anomalies and view the relationships among indicators and their associated plausible explanations. Preliminary evaluations of an early prototype Delphi display for detecting kicks in deepwater oil drilling operations have been promising. Moreover, the methodology used to design and develop the Delphi display can be readily generalized to numerous other operational contexts that require humans to make system-critical decisions. To illustrate, an initial Delphi display design for nuclear power plant control is described. (authors)

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2024

Supervisory genset control in range-extended electric vehicle

A controls system for a range-extended electric vehicle comprising an overall system control unit, an engine control module configured to control a range extender of the range-extended electric vehicle, power electronics configured to control a generator of the range-extended electric vehicle, and a supervisory control module coupled between the overall system control unit and the engine control module and the power electronics, the supervisory control module configured to receive information from the overall system control unit and provide commands to the engine control module and the power electronics.

Li, Ke↗
DOE OSTI2025

Improving Cyber Situational Understanding

Effective cybersecurity operations require the ability to analyze large amounts of information to assess security risks and formulate defensive strategies against adversaries. This has become more complex in recent years as the sprawl and interconnectivity of devices grows through implementation of virtualization, cloud computing, and Internet of Things (IoT). The amount of data and analysis required for effective cybersecurity command and control decisions far exceeds humans’ capacity to perform manually. We characterize the analysis problem as cyber situational understanding. The research presented to improve cyber situational understanding focuses on vulnerability analysis and threat intelligence. Regarding vulnerabilities, entities must analyze and plan work for between thousands and tens of thousands of software vulnerabilities annually. Entities heavily use network firewalls to limit vulnerability exposure. As a result, some of these vulnerabilities permit exposure to adversarial exploitation, whereas others are inaccessible and therefore present negligible risk of exploitation. Distinguishing between high and low risk software vulnerabilities requires a deep understanding of the vulnerability, network firewall protection, and characteristics of the targeted device. This problem is solved by extracting network service features from vulnerability data features using both machine-learning and natural language processing. Then, the network firewall topology is parsed to determine which vulnerabilities are reachable by adversaries. Ultimately, a state-based safety analysis ascertains which vulnerabilities are unsafe. A related vulnerability analysis problem occurs in cybersecurity operations when associating an entity’s hardware and software assets to public vulnerability databases. Assets often reveal hardware and software through installation artifacts and network service identification, and entities store these artifacts in inventory databases. However, software and hardware vendors apply a standard Common Platform Enumeration (CPE) naming convention when publicly reporting vulnerabilities. Associating these two datasets often requires many hours to days of manual inspection. The proposed solution automates the mapping approach of human analysts using fuzzy matching techniques, natural language processing, and, ultimately, machine learning to present a small set of recommendations for mapping the two datasets. The result significantly reduces human analysis time and reduces the occurrence of false positives in vulnerability notifications. Finally, cyber threat intelligence (CTI) requires associating cyber observable artifacts, such as IP addresses, URIs, and file hashes, with cyber threat tactics, techniques, and procedures. Unfortunately, most CTI data is compartmentalized across multiple organizations and cannot be shared due to the legal and reputational risk with cyber threat being associated with the entity. The approach to solving this problem inovlves using a distributed ledger with anonymous token spending and authentication. This allows a consortium of semi-trusted entities to share the workload of curating CTI for a threat sharing community’s cooperative benefit.

Huff, Philip↗
DOE OSTI2017

A novel priority selection system for nuclear power plant - 287

The priority selection system is an important component of security level instrument control platform for nuclear power plant, the main function of which is priority processing the manual or automatic command with various security levels and driving engineering safety features and field devices, such as pump and valve. Its stability and safety plays a crucial role in the operation of the power plant. The main objective of the present paper is to describe the new nuclear power plant-oriented priority selection system, which is developed independently by China Nuclear Control System Engineering Company. In this system, the control commands from 1E DCS, ECP and DAS systems are transmitted via hardwire, while those from NC DCS are transmitted by field-bus. The control commands experience priority output to control the field actuators. Meanwhile, in order to control key field devices when failure of the instrument control systems occurs, the issuing interface for native instructions with permissions setting is also offered. The whole system provides collection-feedback functions for field devices, high coverage self-diagnostic functions and periodic test functions for safety systems. Moreover, the feedback information of field devices, the results of self-diagnosis and periodic test will be submitted to DCS of nuclear power plant. In addition, the core part of priority selection system, namely priority selection module, is obtained by pure FPGA technology, which is different from DCS systems and could avoid common cause failure of software effectively. (authors)

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2016

Evaluation of Electromechanical Systems Dynamically Emulating a Candidate Hydrokinetic Turbine

The use of controllable motor-generator sets to emulate the dynamics of a hydrokinetic turbine is evaluated as an alternative to field testing a prototype. The emulator control dynamic equations are presented, methods for scaling turbine parameters are examined, and experimental results are presented from three electromechanical emulation machines (EEMs) programmed to emulate the same vertical-axis fixed-pitch turbine. Although hardware platforms and control implementations varied, results show that each EEM is successful in emulating the turbine model, thus demonstrating the general feasibility of the approach. However, performance of motor control under torque command, current command or speed command differed. In one of the EEMs evaluated, the power take off controller tracks the maximum power-point of the turbine in response to turbulence. Utilizing realistic inflow conditions and control laws, the emulator dynamic speed response is shown to agree well at low frequencies with numerical simulation but to deviate at high frequencies.

13 HYDRO ENERGY↗
DOE OSTI2021

Monte Carlo Hauser-Feshbach computer code system to model nuclear reactions: YAHFC

A computer program framework, YAHFC, to model low-energy nuclear reactions is presented. The framework allows for reactions with incident particles ranging from protons/neutrons to alphas and is designed to address reactions that ultimately lead to the formation of compound nuclear systems that then decay statistically as outlined in concepts of Hauser and Feshbach. Additionally, instead of a reaction, it is also possible to model the decay of a nuclear system with an initial excitation and population. The code models nuclear decays with a Monte Carlo process that tracks the decay of each state. This allows for an exact representation of the spectra for all emitted particles in each of the final exit channels and the possibility of generating reaction data for simulation purposes. The program is interfaced with the optical model code system FRESCOX to calculate transmission coefficients as well as the effects of coupled channels and other direct excitations via the distorted wave Born approximation (DWBA). Modules are included to account for nuclear processes such as width corrections, pre-equilibrium emission, and fission. The program is controlled by a series of input commands and while a set of input parameters exists for each projectile and target, the input commands allow for complete control over each input parameter. Extensive data files are produced and a program is provided that converts YAHFC data files into nuclear data library entries in the generalized nuclear data structure (GNDS).

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2012

XBox Input -Version 1.0

Contains class for connecting to the Xbox 360 controller, displaying the user inputs {buttons, triggers, analog sticks), and controlling the rumble motors. Also contains classes for converting the raw Xbox 360 controller inputs into meaningful commands for the following objects: • Robot arms - Provides joint control and several tool control schemes • UGV's - Provides translational and rotational commands for "skid-steer" vehicles • Pan-tilt units - Provides several modes of control including velocity, position, and point-tracking • Head-mounted displays (HMO)- Controls the viewpoint of a HMO • Umbra frames - Controls the position andorientation of an Umbra posrot object • Umbra graphics window - Provides several modes of control for the Umbra OSG window viewpoint including free-fly, cursor-focused, and object following.

Source record↗
DOE OSTI2018

Synchronous generator modeling and frequency control using unscented Kalman filter

Various examples are related to synchronous generator modeling with frequency control, which can be achieved using unscented Kalman filtering. In one example, a method includes obtaining operational parameters associated with a generator of a power system; determining parameters of a synchronous generator model with frequency control based at least in part upon the operational parameters associated with the generator; and providing a command to a frequency control of the generator, the command updating one or more parameters of the frequency control. In another example, a system includes a generator controller for a generator of a power system; and a computing device in communication with the generator controller, where the computing device is configured to determine parameters of the synchronous generator model using operational parameters associated with the generator and provide a command updating one or more parameters of a frequency control of the generator controller.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2014

HC-NIDS: signatures and simulations for detecting cyber-attacks aiming to cause damage against cyber-physical energy systems

Physical device safety is typically implemented locally using embedded controllers, while operations safety is primarily performed in control centers. Safe operations can be enhanced by correct design of device-level control algorithms, and protocols, procedures and operator training at the control-room level, but all can fail. Moreover, these elements exchange data and issue commands via vulnerable communication layers. In order to secure these gaps and enhance operational safety, we believe monitoring of command sequences must be combined with an awareness of physical device limitations and automata models that capture safety mechanisms. One way of doing this is by leveraging specification-based intrusion detection to monitor for physical constraint violations. The method can also verify that physical infrastructure state is consistent with monitoring information and control commands exchanged between field devices and control centers. This additional security layer enhances protection from both outsider attacks and insider mistakes. We implemented specification-based SCADA command analyzers using physical constraint algorithms directly in the Bro framework and Broccoli APIs for three separate scenarios: a water heater, an automated distribution system, and an over-current protection scheme. To accomplish this, we added low-level analyzers capable of examining control system-specific protocol packets for both Modbus TCP and DNP3, and also higher-level analyzers able to interpret device command and data streams within the context of each device's physical capabilities and present operational state. Thus the software that we are making available includes the Bro/Broccoli scripts for these three scenarios, as well as simulators, written in C, of those scenarios that generate sample traffic that is monitored by the Bro/Broccoli scripts. In addition, we have also implemented systems to directly pull cyber-physical information from the OSIsoft PI historian system. We have included the Python scripts used to perform that monitoring.

Source record↗
DOE OSTI2014

HC-NIDS: signatures and simulations for detecting cyber-attacks aiming to cause damage against cyber-physical energy systems

Physical device safety is typically implemented locally using embedded controllers, while operations safety is primarily performed in control centers. Safe operations can be enhanced by correct design of device-level control algorithms, and protocols, procedures and operator training at the control-room level, but all can fail. Moreover, these elements exchange data and issue commands via vulnerable communication layers. In order to secure these gaps and enhance operational safety, we believe monitoring of command sequences must be combined with an awareness of physical device limitations and automata models that capture safety mechanisms. One way of doing this is by leveraging specification-based intrusion detection to monitor for physical constraint violations. The method can also verify that physical infrastructure state is consistent with monitoring information and control commands exchanged between field devices and control centers. This additional security layer enhances protection from both outsider attacks and insider mistakes. We implemented specification-based SCADA command analyzers using physical constraint algorithms directly in the Bro framework and Broccoli APIs for three separate scenarios: a water heater, an automated distribution system, and an over-current protection scheme. To accomplish this, we added low-level analyzers capable of examining control system-specific protocol packets for both Modbus TCP and DNP3, and also higher-level analyzers able to interpret device command and data streams within the context of each device's physical capabilities and present operational state. Thus the software that we are making available includes the Bro/Broccoli scripts for these three scenarios, as well as simulators, written in C, of those scenarios that generate sample traffic that is monitored by the Bro/Broccoli scripts. In addition, we have also implemented systems to directly pull cyber-physical information from the OSIsoft PI historian system. We have included the Python scripts used to perform that monitoring.

Source record↗
DOE OSTI2013

System and method for determining stator winding resistance in an AC motor using motor drives

A system and method for determining the stator winding resistance of AC motors is provided. The system includes an AC motor drive having an input connectable to an AC source and an output connectable to an input terminal of an AC motor, a pulse width modulation (PWM) converter having switches therein to control current flow and terminal voltages in the AC motor, and a control system connected to the PWM converter. The control system generates a command signal to cause the PWM converter to control an output of the AC motor drive corresponding to an input to the AC motor, selectively generates a modified command signal to cause the PWM converter to inject a DC signal into the output of the AC motor drive, and determines a stator winding resistance of the AC motor based on the DC signal of at least one of the voltage and current.

42 ENGINEERING↗
DOE OSTI2014

Methods, systems and apparatus for controlling third harmonic voltage when operating a multi-space machine in an overmodulation region

Methods, system and apparatus are provided for controlling third harmonic voltages when operating a multi-phase machine in an overmodulation region. The multi-phase machine can be, for example, a five-phase machine in a vector controlled motor drive system that includes a five-phase PWM controlled inverter module that drives the five-phase machine. Techniques for overmodulating a reference voltage vector are provided. For example, when the reference voltage vector is determined to be within the overmodulation region, an angle of the reference voltage vector can be modified to generate a reference voltage overmodulation control angle, and a magnitude of the reference voltage vector can be modified, based on the reference voltage overmodulation control angle, to generate a modified magnitude of the reference voltage vector. By modifying the reference voltage vector, voltage command signals that control a five-phase inverter module can be optimized to increase output voltages generated by the five-phase inverter module.

42 ENGINEERING↗
DOE OSTI2012

Methods, systems and apparatus for overmodulation of a five-phase machine

Methods, system and apparatus are provided for overmodulation of a five-phase machine in a vector controlled motor drive system that includes a five-phase PWM controlled inverter module that drives the five-phase machine. Techniques for overmodulating a reference voltage vector are provided to optimize voltage command signals that control a five-phase inverter module to increase output voltages generated by the five-phase inverter module.

Perisic, Milun↗
DOE OSTI2019

Enabling a Decentralized Smart Grid Using Autonomous Edge Control Devices

As a large number of distributed devices are connected to the modern smart grid, the traditional centralized connectivity models fail to provide economic value. These models have relied on sending data to the cloud for processing and receiving commands to exert control actions, resulting in an ‘on-demand system’ with high bandwidth, low latency and an overload of data on the cloud. For realizing a decentralized system, there is a strong need to embed intelligence at the ‘edge of the network’. These intelligent devices, capable of sensing, local data processing and exerting control actions, report only actionable information to the cloud, acting as an edge control node. The system can then function autonomously, without constant cloud inputs, tolerating longer delays in communication, making the overall system ultra-low cost. The Global Asset Monitoring, Management and Analytics (GAMMA) Platform is a novel ultralow- cost, secure platform that operates through a Bluetooth based delay tolerant network. It relies on so-called ‘data mules’ to bridge the last mile connectivity gap in an inherently secure way. Due to this model, the platform requires no in-country certifications, does not rely on a dedicated backhaul technology and is immune to technology migration. This architecture also addresses some gaps identified in traditional IoT-based solutions in remote areas and sparse connectivity. A functional unit of the edge computing node has been built, taking into account various constraints like costs, customizations, data storage, cybersecurity and power management. Here, the platform has been built, deployed and has demonstrated distributed smart grid applications like power quality sensing, automated metering infrastructure and utility asset monitoring.

42 ENGINEERING↗
DOE OSTI2021

Hierarchical Power Flow Control in Smart Grids: Enhancing Rotor Angle and Frequency Stability with Demand-Side Flexibility

Large-scale integration of renewables in power systems gives rise to new challenges for keeping synchronization and frequency stability in volatile and uncertain power flow states. To ensure the safety of operation, the system must maintain adequate disturbance rejection capability at the time scales of both rotor angle and system frequency dynamics. This calls for flexibility to be exploited on both the generation and demand sides, compensating volatility and ensuring stability at the two separate time scales. This article proposes a hierarchical power flow control architecture that involves both transmission and distribution networks as well as individual buildings to enhance both small-signal rotor angle stability and frequency stability of the transmission network. The proposed architecture consists of a transmission-level optimizer enhancing system damping ratios, a distribution-level controller following transmission commands and providing frequency support, and a building-level scheduler accounting for quality of service and following the distribution-level targets. Furthermore, we validate the feasibility and performance of the whole control architecture through real-time hardware-in-loop tests involving real-world transmission and distribution network models along with real devices at the Stone Edge Farm Microgrid.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2017

Multi-protocol header generation system

A communication device includes a data source that generates data for transmission over a bus, and a data encoder that receives and encodes outgoing data. An encoder system receives outgoing data from a data source and stores the outgoing data in a first queue. An encoder encodes outgoing data with a header type that is based upon a header type indication from a controller and stores the encoded data that may be a packet or a data word with at least one layered header in a second queue for transmission. The device is configured to receive at a payload extractor, a packet protocol change command from the controller and to remove the encoded data and to re-encode the data to create a re-encoded data packet and placing the re-encoded data packet in the second queue for transmission.

97 MATHEMATICS AND COMPUTING↗