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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 397 records · Page 22
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Developing an Eco-Cooperative Automated Control System (Eco-CAC)

The goal of the project was to develop a novel Eco-Cooperative Automated Control (Eco-CAC) system that integrates vehicle dynamics (VD) control with connected and automated vehicle (CAV) applications. In particular, the team developed a novel integrated control system that (1) routes vehicles in a fuel/energy-efficient manner for internal combustion engine vehicles (ICEVs), battery-only electric vehicles (BEVs), and hybrid electric vehicles (HEVs); (2) selects vehicle speeds based on anticipated traffic network evolution; (3) minimizes vehicle fuel/energy consumption near signalized intersections; and (4) intelligently modulates the longitudinal motion of vehicles within a cooperative platoon to minimize its fuel/energy consumption.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2014

Tool coupling for the design and operation of building energy and control systems based on the Functional Mock-up Interface standard

This paper describes software tools developed at the Lawrence Berkeley National Laboratory (LBNL) that can be coupled through the Functional Mock-up Interface standard in support of the design and operation of building energy and control systems. These tools have been developed to address the gaps and limitations encountered in legacy simulation tools. These tools were originally designed for the analysis of individual domains of buildings, and have been difficult to integrate with other tools for runtime data exchange. The coupling has been realized by use of the Functional Mock-up Interface for co-simulation, which standardizes an application programming interface for simulator interoperability that has been adopted in a variety of industrial domains. As a variety of coupling scenarios are possible, this paper provides users with guidance on what coupling may be best suited for their application. Furthermore, the paper illustrates how tools can be integrated into a building management system to support the operation of buildings. These tools may be a design model that is used for real-time performance monitoring, a fault detection and diagnostics algorithm, or a control sequence, each of which may be exported as a Functional Mock-up Unit and made available in a building management system as an input/output block. We anticipate that this capability can contribute to bridging the observed performance gap between design and operational energy use of buildings.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2025

Optimizing Facility Operations by Applying Machine Learning to the Army Reserve Enterprise Building Control System (Final Report)

Thousands of U.S. Department of Defense (DoD) buildings have building automation systems (BASs) and/or advanced meters. Although these systems have a wealth of data, performance optimization requires time and expertise to review and act on that information. Machine learning (ML) can provide automated and actionable insights to controls operators. This demonstration implemented proven ML methods on the Army Reserve Enterprise Building Control System. ML refers to algorithms that “learn” from data and improve their performance on a given task over time. In the buildings domain these tasks range from predicting future energy consumption, to identifying operational issues before faults occur, to optimizing control decisions. To learn, ML requires input data, which – for buildings – typically consists of instrument data such as energy consumption data and subsystem controls information such as set-point temperatures, and context data consisting of information such as the physical location of the building, the area of the building, and the weather. ML models use the relationships learned from the input data to make predictions with new, previously unseen, data. The team was able to investigate and successfully implement the following ML use cases: labeling consumption data as anomalous or non-anomalous; baseline whole-building load prediction (unknown fault status); fault detection (validation not possible); and site prioritization for energy-related projects. Due to the constraints of the project, interventions were not able to be implemented during the demonstration; therefore, assessments of operational cost savings and maintenance avoided could not be performed. The project has been presented at two leading national building conferences and two additional publications to peer-reviewed journals are currently in preparation.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2022

First SELAP Algorithm Operational Experience of the New LLRF 3.0 RF Control System

The JLAB LLRF 3.0 system has been developed and is replacing the 30-year-old LLRF systems in the CEBAF accelerator. The LLRF system builds upon 25 years of design and operational RF control experience (digital and analog), and our recent collaboration in the design of the LCLSII LLRF system. The new system also incorporates a cavity control algorithm using a fully functional phase and amplitude locked Self Exciting Loop (SELAP). The first system (controlling 8 cavities) was installed and commissioned in August of 2021. Since then the new LLRF system has been operating with cavity gradients up to 20 MV/m, and electron beam currents up to 350 uA. This paper discusses the operational experience of the LLRF 3.0 SELAP algorithm along with other software and firmware tools like cavity and klystron characterization and quench detection.

Plawski, T. E.↗
DOE OSTI2020

Trigger-DAQ and Slow Controls Systems in the Mu2e Experiment

The muon campus program at Fermilab includes the Mu2e experiment that will search for a charged-lepton flavor violating processes where a negative muon converts into an electron in the field of an aluminum nucleus, improving by four orders of magnitude the search sensitivity reached so far. Mu2e's Trigger and Data Acquisition System (TDAQ) uses otsdaq as its solution. Developed at Fermilab, otsdaq uses the artdaq DAQ framework and art analysis framework, under the-hood, for event transfer, filtering, and processing. otsdaq is an online DAQ software suite with a focus on flexibility and scalability, while providing a multi-user, web-based, interface accessible through the Chrome or Firefox web browser. The detector Read Out Controller (ROC), from the tracker and calorimeter, stream out zero-suppressed data continuously to the Data Transfer Controller (DTC). Data is then read over the PCIe bus to a software filter algorithm that selects events which are finally combined with the data flux that comes froma Cosmic Ray Ve to System (CRV). A Detector Control System (DCS) for monitoring, controlling, alarming, and archiving has been developed using the Experimental Physics and Industrial Control System (EPICS) Open Source Platform. The DCS System has also been itegrated into otsdaq. The installation of the TDAQ and the DCS systems in the Mu2e building is planned for 2021-2022, and a prototype has been built at Fermilab's Feynman Computing Center. We report here on the developments and achievements of the integration of Mu2e's DCS system into the online otsdaq software.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2023

Implementation of AI/DEEP learning disruption predictor into a plasma control system

Abstract This paper reports on advances in the state‐of‐the‐art deep learning disruption prediction models based on the Fusion Recurrent Neural Network (FRNN) originally introduced in a 2019 NATURE publication [ https://doi.org/10.1038/s41586‐019‐1116‐4 ]. In particular, the predictor now features not only the “disruption score,” as an indicator of the probability of an imminent disruption, but also a “sensitivity score” in real time to indicate the underlying reasons for the imminent disruption. This adds valuable physics interpretability for the deep learning model and can provide helpful guidance for control actuators now implemented into a modern plasma control system (PCS). The advance is a significant step forward in moving from modern deep learning disruption prediction to real‐time control and brings novel AI‐enabled capabilities relevant for application to the future burning plasma ITER system. Our analyses use large amounts of data from JET and DIII‐D vetted in the earlier NATURE publication. In addition to “when” a shot is predicted to disrupt, this paper addresses reasons “why” by carrying out sensitivity studies. FRNN is accordingly extended to use more channels of information, including measured DIII‐D signals such as (i) the “n1rms” signal that is correlated with the n = 1 modes with finite frequency, including neoclassical tearing mode and sawtooth dynamics; (ii) the bolometer data indicative of plasma impurity control; and (iii) “q‐min”—the minimum value of the safety factor relevant to the key physics of kink modes. The additional channels and interpretability features expand the ability of the deep learning FRNN software to provide information about disruption subcategories as well as more precise and direct guidance for the actuators in a PCS.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2015

Air pollution control systems in WtE units: An overview

Highlights: • The paper describes in brief terms the development of gas cleaning in waste incineration. • The main technologies for pollutant removal are described including their basic mechanisms. • Their respective efficiencies and their application are discussed. • A cautious outlook regarding future developments is made. - Abstract: All WtE (waste-to-energy) plants, based on combustion or other thermal processes, need an efficient gas cleaning for compliance with legislative air emission standards. The development of gas cleaning technologies started along with environment protection regulations in the late 1960s. Modern APC (air pollution control) systems comprise multiple stages for the removal of fly ashes, inorganic and organic gases, heavy metals, and dioxins from the flue gas. The main technologies and devices used for abatement of the various pollutants are described and their basic principles, their peculiarities, and their application are discussed. Few systems for cleaning of synthesis gas from waste gasification plants are included. Examples of APC designs in full scale plants are shown and cautious prospects for the future development of APC systems are made.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Solar tracker control system and method

A pneumatic control unit configured to inflate a first and second set of bellows with fluid from a pneumatic fluid source via a pneumatic circuit, the first and second set of bellows associated with one or more pneumatic actuators. The pneumatic control unit determines a target configuration of the actuators based on a determined current position of the sun; determines a current configuration of the actuators; determines a difference between the determined current configuration and target configuration of the actuators; determines that the difference between current configuration and the target configuration of the actuators is outside of a tolerance range; and actuates the actuators toward the determined target configuration by at least one of inflating the first or second set of bellows with fluid from the pneumatic fluid source via the pneumatic circuit.

Betts, Kenneth H.↗
DOE OSTI2024

Using Generative AI to implement the discrepancy checker for a Nearly Autonomous Management and Control System for Advanced Reactors

Developments related to generative artificial intelligence (AI) have brought a major breakthrough in AI. These developments are rapidly accelerating developments in different science and engineering applications. Nearly Autonomous Management and Control (NAMAC) system provides recommendations to the operator for maintaining the safety and performance of the reactor. The discrepancy checker (DC) is an important component of the NAMAC) system, whose goal is to determine if the plant is moving towards the expected system state after the control actions are injected. In this work, we explore generative AI methods, particularly, a generative pretrained transformer (GPT) for implementing the DC function in NAMAC. The GPT-based DC aims to alert the operator in situations outside NAMAC’s scope and act as a chatbot the operator can use to retrieve relevant information. This study involves two versions of GPT developed by OpenAI: GPT-3.5 and GPT-4. These GPTs are trained on huge amounts of undisclosed general domain datasets. We explored two methods to adapt GPTs for DC implementation in NAMAC: fine-tuning and retrieval augmented generation. A small knowledge base (information file) that encompasses rules for DC implementation and some general information related to NAMAC has been created to support DC implementation using GPT. In this work, the GPT-based DC implementations have been tested for their reasoning abilities, comprehension, information retrieval, and extraction abilities. It should be noted that this paper only presents a preliminary study to test the feasibility of DC implementation using generative AI technology. Given the potential risks and severe consequences associated with nuclear reactor applications, combined with the black-box nature of AI, extensive offline and online testing and reliability analyses of GPT-based DCs are needed for further developing such capabilities.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2017

Spurious actuations in digital instrumentation and control systems - evaluation framework - 137

When a digital Instrumentation and Control (I and C) system or its associated components produce an unintended operation, it is known as a spurious actuation. Spurious actuations could lead to unnecessary challenges to safety equipment, challenge the ability of safety systems to provide their intended functions, or place the plant in an un-analyzed state. There is arguably a lack of clear and sufficient regulatory guidance for assessing spurious actuations. In an attempt to address this guidance gap, this paper provides a generic framework for evaluating spurious actuations in digital I and C systems, components, or supporting systems that are important to safety. The framework provides a methodology for: (1) defining the scope of the evaluation including supporting assumptions; (2) providing options for excluding a spurious actuation from the evaluation; (3) assessing the potential consequences from the assessed spurious actuations; and, (4) defining a high-level acceptance criteria. The methodology discussed by this paper is not to be construed as a requirement, regulation, or acceptable guidance by either domestic or international regulators; instead, it is intended to serve as a potential foundation or technical basis to be used for developing clear and sufficient regulatory guidance for assessing spurious actuations in digital I and C systems. (authors)

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2020

A Novel Architecture for Attack-Resilient Wide-Area Protection and Control System in Smart Grid

Wide-area protection and control (WAPAC) systems are widely applied in the energy management system (EMS) that rely on a wide-area communication network to maintain system stability, security, and reliability. As technology and grid infrastructure evolve to develop more advanced WAPAC applications, however, so do the attack surfaces in the grid infrastructure. This paper presents an attack-resilient system (ARS) for the WAPAC cybersecurity by seamlessly integrating the network intrusion detection system (NIDS) with intrusion mitigation and prevention system (IMPS). In particular, the proposed NIDS utilizes signature and behavior-based rules to detect attack reconnaissance, communication failure, and data integrity attacks. Further, the proposed IMPS applies state transition-based mitigation and prevention strategies to quickly restore the normal grid operation after cyberattacks. As a proof of concept, we validate the proposed generic architecture of ARS by performing experimental case study for wide-area protection scheme (WAPS), one of the critical WAPAC applications, and evaluate the proposed NIDS and IMPS components of ARS in a cyber-physical testbed environment. Our experimental results reveal a promising performance in detecting and mitigating different classes of cyberattacks while supporting an alert visualization dashboard to provide an accurate situational awareness in real-time.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2021

Co-Optimization Scheme for Hybrid Electric Vehicles Powertrain and Exhaust Emission Control System Using Future Speed Prediction

Hybrid electric vehicles (HEVs) have been an effective solution for improved vehicle fuel efficiency and reduced emission pollution. In this paper, a co-optimization scheme is proposed to optimize fuel efficiency for HEVs. Here, the proposed optimization scheme uses obtainable future speed prediction as the basis to optimally tune control parameters for the existing powertrain control system. The ramp-up time of the catalyst temperature to reach its light-off level in the exhaust emission system is also considered as an additional optimization constraint to reduce emission. The Toyota Prius Hybrid Simulink model which is an integrated model for a powertrain and exhaust emission system is validated using real data from several real driving cycle scenarios. Then, to simplify the formulation of the proposed algorithm, the model for the optimization for powertrain and exhaust emission systems is represented by a set of equivalent neural network (NN) models learned using the data generated from the well-validated Toyota Prius Hybrid Simulink model. Using NN models, a co-optimization algorithm is established that provides an optimal tuning of some fuel-sensitive powertrain control parameters using future speed prediction, leading to a novel co-optimization algorithm, achieving on average a further 9.22% fuel savings for the Toyota Prius Hybrid Simulink model.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2020

Attack Scenarios Relating to Army Facility-Related Control Systems: Quantifying the Cost to Secure and Cost Savings of the Army’s FRCS Program

Pacific Northwest National Laboratory (PNNL) analyzed the cyber-threat environment to U.S. Army facilities. This report describes three key factors in securing Army-owned facility-related control systems (FRCS). First, Section 1.0 provides background information about the project. Section 2.0 describes the various types of cyber-attacks. Section 3.0 provides a series of attack scenarios from real-world use cases are described in Section 3. These examples are relevant to the Army because the targeted systems or operating environments are like those used at Army installations. An estimated range for the cost to secure these systems is described in Section 4.0. Finally, the cost savings of preventing these kinds of attacks are described in Section 5.0.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗
DOE OSTI2020

Development of Control System Functional Capabilities within the IES Plug-and-Play Simulation Environment

The concept of an Integrated Energy System (IES) is meant to combine different energy technologies in synergistic ways to achieve a more secure and economical energy supply. The RAVEN-based HYBRID framework is used to find the optimal installed capacity and the optimal economical dispatch of each component of the IES. A new RAVEN (Risk Analysis Virtual ENvironment) plugin for grid and capacity optimization (HERON) has been developed for optimizing the production variables of the IES given the demand profile. Currently, only the limits that affect the production variables and their corresponding time rates of change are considered (explicit constraints). However, other variables are additionally subject to constraints, but the associated limits are not accounted for (implicit constraints). In particular, for the power dispatch problem, the optimization algorithm takes into account the limits on the electrical power output and the corresponding hourly power variations but does not consider other constraints on process variables whose response effects the service life of the IES. This report describes a scheme that allows accounting for implicit constraints without increasing the size of the optimization problem. The Reference Governor (RG) algorithm is traditionally used for enforcing state and control constraints by modifying the set-point trajectories supplied to the feedback regulators. In our application, the RG is coupled within an iterative loop with the HERON-power dispatcher to generate optimal trajectories that ensure the operational constraints are met. A data-driven procedure to derive a representation of the dynamics of the controlled system was developed. First, the variables that represented the state of the system are selected (PCA-based approach), and then state-space representation matrices are derived from the collected measurements (DMDc algorithm). A preliminary version of the developed workflow based on Linear Time Invariant matrices was assessed by adopting a two-unit test case. More sophisticated versions of this workflow foreseeing the on-line derivation of system matrices will be deployed in FY 2021. Finally, a “plug-and-play” library of controllers and state observers was developed in Dymola. Some aspects of the current configuration of the IES unit components, e.g., the encapsulation of the control schemes into dedicated blocks, are consistent with the “plug-and-play” philosophy. Other features, e.g., the system buses collecting the input and the output variables, are not. For this reason, once listed and described the limits of the current configuration, necessary modifications to the plant model interface are presented. As a test-case, the interfaces of the SES model in the RAVEN-based HYBRID framework were reworked accordingly, and two different control schemes were applied to the same plant model.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2021

Qubit Control System (QubiC) v1.0

We design a modular FPGA (field-programmable gate array) based system called QubiC to control and measure a superconducting quantum processing unit. The system includes room temperature electronics hardware, FPGA gateware, and engineering software.

Huang, Gang↗
DOE OSTI2016

Evaluating the Maturity of Cybersecurity Programs for Building Control Systems

The cyber-physical security threat to buildings is complex, non-linear, and rapidly evolving as operational and information technologies converge and connect buildings to cyberspace. Cyberattacks on buildings can exploit smart building controls and breach corporate networks, causing financial and reputational damage. This may result in the loss of sensitive building information or the disruption of, or damage to, the systems necessary for the safe and efficient operation of buildings. For the buildings and facility infrastructure, there is a need for a robust national cybersecurity strategy for buildings, guidance on the selection and implementation of appropriate cybersecurity controls for buildings, an approach to evaluate the maturity and adequacy of the cybersecurity programs. To provide an approach for evaluating the maturity of the cybersecurity programs for building control systems, the US Department of Energy’s widely used Cybersecurity Capability and Maturity Model (C2M2) has been adapted into a building control systems version. The revised model, the Buildings-C2M2 (B-C2M2) provides maturity level indicators for cybersecurity programmatic domains. A “B-C2M2 Lite” version allows facility managers and building control system engineers, or information technology personnel to perform rapid self-assessments of their cybersecurity program. Both tools have been pilot tested on several facilities. This paper outlines the concept of a maturity model, describes the B-C2M2 tools, presents results and observations from the pilot assessments, and lays out plans for future work.

Glantz, Clifford S.↗
DOE OSTI2020

Cyber-Physical Smart Light Control System Integration with Smart Grid using Zigbee

This paper presents a hardware-in-the-loop cyber-physical system architecture design to monitor and control smart lights connected to the active distribution grid. The architecture uses Zigbee-based (IEEE 802.15.4) wireless sensor networks and publish-subscribe architecture to exchange monitoring and control signals between smart-light actuators (SLAs) and a smart-light central controller (SLCC). Each SLA integrated into a smart light consists of a Zigbee-based endpoint module to send and receive signals to and from the SLCC. The SLCC consists of a Zigbee-based coordinator module, which further exchanges the monitoring and control signals with the active distribution management system over the TCP/IP communication network. The monitoring signals from the SLAs include light status, brightness level, voltage, current, and power data, whereas, the control signals to the SLAs include light intensity, turn ON, turn OFF, standby, and default settings. We have used our existing hardware-in-the-loop (HIL) cyber-physical system (CPS) security SCADA testbed to process signals received from the SLCC and respond suitable control signals based on the smart light schedule requirements, system operation, and active distribution grid dynamic characteristics. We have integrated the proposed cyber-physical smart light control system (CPSLCS) testbed to our existing HIL CPS SCADA testbed. We use the integrated testbed to demonstrate the efficacy of the proposed algorithm by real-time performance and latency between the SLCC and SLAs. The experiments demonstrated significant results by 100% realtime performance and low latency while exchanging data between the SLCC and SLAs.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2013

Development of a new type of high pressure calorimetric cell, mechanically agitated and equipped with a dynamic pressure control system: Application to the characterization of gas hydrates

A novel prototype of calorimetric cell has been developed allowing experiments under pressure with an in situ agitation system and a dynamic control of the pressure inside the cell. The use of such a system opens a wide range of potential practical applications for determining properties of complex fluids in both pressurized and agitated conditions. The technical details of this prototype and its calibration procedure are described, and an application devoted to the determination of phase equilibrium and phase change enthalpy of gas hydrates is presented. Our results, obtained with a good precision and reproducibility, were found in fairly good agreement with those found in literature, illustrate the various interests to use this novel apparatus.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗