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At least 451 records · Page 25

Innovating the next generation of commercial smart building software

Nearly 30% of commercial building energy use is wasted due to equipment faults and HVAC controls problems. The result is increased emissions, compromised comfort and productivity, and less reliable coordination of building power needs with a clean grid. The energy impact alone represents $17 billion in potential savings. Today’s smart building software provides a robust solution to address these operational deficiencies. Energy management and information systems (EMIS) are saving up to 9% on average, with two-year paybacks. They are being incorporated into energy management processes, commissioning services, and utility programs. As effective as they are, two barriers prevent even deeper benefits; limited personnel to fix problems once they are identified, and the expense and time to manually implement changes in control systems. In partnership with the research community, the EMIS industry is developing new capabilities to overcome these barriers. Moving beyond siloed products for either fault detection and diagnostics, or optimal control, these new capabilities empower users to not only automatically identify faults, but also to push corrective action, and control improvements to their buildings. In this paper, several areas for enhancements are documented: ‘one-time’ correction of faults such as setpoints, schedules, and economizer lockouts; short-term active testing for automated proportional integral derivative (PID) loop tuning and functional testing; and continuous supervisory control for demand flexibility and year-round efficiency. Results are presented from a pair of partner implementations out of a dozen providers integrating these enhancements into their products, including field tests from across the country, and insights into operator acceptance and integration into operations and maintenance practices.

Casillas, Armando↗

Investigation of the Utilization of Modern Industrial Methods, Processes, Ergonomics, and the Internet in the Scientific Environment

On Oct. 1, 2001 Cleveland State University and NASA Glenn Research Center embarked on the above named cooperative agreement. Because NASA's research facilities often exhibit instances where the failure to use state-of-the-art technologies and methods to improve on outmoded systems of interface and control, and this runs contrary to the NASA philosophy of "faster, better, and cheaper", it was deemed an ideal opportunity for this collaboration. The main objectives of the proposed effort were to research and investigate the use of the latest technologies, methods, techniques, etc. which pertain to control and interface with industrial and research systems and facilities. The work was done in large part at NASA Glenn Research Center, using selected research facilities as real-world laboratories; such as certain Microgravity Science Division and Space Station projects. Microgravity Science Division at Glenn Research Center designs and builds experiments to be flown on the Space Shuttle and eventually on the International Space Station. Economy of space, weight, complexity, data storage, ergonomics, and many other factors present problems that also exist in industry. Many of the solutions can come from the same areas of study mentioned above.

Myer, Spencer S., Jr.↗

Organizational Influence on Supply Chain for Digital Energy Infrastructure: Business Models, and Policy Landscape

Significant investment is driving the essential modernization and digitization of U.S. energy infrastructure, but the United States faces a key challenge in this grid transformation: our renewable and clean energy supply chains have limited capacity to source necessary digital assets through U.S. or allied sources. Batteries and their associated power electronic interfaces are key components to delivering clean and more resilient energy delivery, providing much-needed fast ramping, emergency discharge, generation, and operations support to the electric grid. These services have grown to be invaluable over the past 10 years and will soon be an irreplaceable component of energy delivery. While there have been significant strides to move supply chains for raw and critical materials to U.S. and allied nations, the control and power electronic industry has lagged, in part because of lower cost margins. For example, the United States now has growing capacity to manufacture solar photovoltaic (PV) panels, but 90% of the inverters—which are essential to the conversion of DC to AC for grid connection and controls—are made in or source parts from the People’s Republic of China (PRC). While a global supply chain is beneficial for many economic and supply diversification reasons, presence of foreign entities of concern (FEOC) in a dominant role in this supply chain brings additional concerns for national security of infrastructure. The BESS relationship and new clean energy have features that warrant discussions and additional focus on impact for technology security, given their critical role. This review considers the impact and solutions for complex business and policy landscapes in clean energy supply chain, and the benefit trade-offs, focusing on the Battery Energy Storage System case study, and its complex organizational relationships across both the US, Allied countries and Foreign Entities of Concern. While many examples in this paper are presented on PRC focused manufacture, this could apply to any potentially adversarial relationship

25 - ENERGY STORAGE↗

Advanced communications technology satellite high burst rate link evaluation terminal power control and rain fade software test plan, version 1.0

The Power Control and Rain Fade Software was developed at the NASA Lewis Research Center to support the Advanced Communications Technology Satellite High Burst Rate Link Evaluation Terminal (ACTS HBR-LET). The HBR-LET is an experimenters terminal to communicate with the ACTS for various experiments by government, university, and industry agencies. The Power Control and Rain Fade Software is one segment of the Control and Performance Monitor (C&PM) Software system of the HBR-LET. The Power Control and Rain Fade Software automatically controls the LET uplink power to compensate for signal fades. Besides power augmentation, the C&PM Software system is also responsible for instrument control during HBR-LET experiments, control of the Intermediate Frequency Switch Matrix on board the ACTS to yield a desired path through the spacecraft payload, and data display. The Power Control and Rain Fade Software User's Guide, Version 1.0 outlines the commands and procedures to install and operate the Power Control and Rain Fade Software. The Power Control and Rain Fade Software Maintenance Manual, Version 1.0 is a programmer's guide to the Power Control and Rain Fade Software. This manual details the current implementation of the software from a technical perspective. Included is an overview of the Power Control and Rain Fade Software, computer algorithms, format representations, and computer hardware configuration. The Power Control and Rain Fade Test Plan provides a step-by-step procedure to verify the operation of the software using a predetermined signal fade event. The Test Plan also provides a means to demonstrate the capability of the software.

Reinhart, Richard C.↗

Subjective Assessment of Initial and Mid-Term UAM Operations and the Impact on Air Traffic Controllers' Workload

The emergence of Urban Air Mobility (UAM) marks a new era of aviation that will be characterized by a shift in transportation dynamics marked by safe, efficient, and sustainable air travel within urban areas. Although UAM will provide significant advantages, increased air travel demand has the potential to impact air traffic controllers (ATCo) workload. Therefore, industry, government, and academia in the UAM ecosystem are actively working to overcome potential implementation challenges that include airspace integration and air traffic management. As part of this effort, researchers from the National Aeronautics and Space Administration (NASA) are studying the challenges associated with UAM operations’ interactions with air traffic control (ATC). The present research paper presents an analysis of subjective assessments to determine the usability and acceptability of airspace procedures under two different operating conditions – Initial and Mid-Term – and two different levels of UAM traffic. The completion of these investigations will be a steppingstone in supporting the successful implementation of UAM operations into the National Airspace System.

Urban Air Mobility, Air Traffic Control, Workload↗

Subjective Assessment of Initial and Mid-Term UAM Operations and the Impact on Air Traffic Controllers' Workload

The emergence of Urban Air Mobility (UAM) marks a new era of aviation that will be characterized by a shift in transportation dynamics marked by safe, efficient, and sustainable air travel within urban areas. Although UAM will provide significant advantages, increased air travel demand has the potential to impact air traffic controllers (ATCo) workload. Therefore, industry, government, and academia in the UAM ecosystem are actively working to overcome potential implementation challenges that include airspace integration and air traffic management. As part of this effort, researchers from the National Aeronautics and Space Administration (NASA) are studying the challenges associated with UAM operations’ interactions with air traffic control (ATC). The present research paper presents an analysis of subjective assessments to determine the usability and acceptability of airspace procedures under two different operating conditions – Initial and Mid-Term – and two different levels of UAM traffic. The completion of these investigations will be a steppingstone in supporting the successful implementation of UAM operations into the National Airspace System.

Urban Air Mobility↗

Techniques and potential capabilities of multi-resolutional information (knowledge) processing

A concept of nested hierarchical (multi-resolutional, pyramidal) information (knowledge) processing is introduced for a variety of systems including data and/or knowledge bases, vision, control, and manufacturing systems, industrial automated robots, and (self-programmed) autonomous intelligent machines. A set of practical recommendations is presented using a case study of a multiresolutional object representation. It is demonstrated here that any intelligent module transforms (sometimes, irreversibly) the knowledge it deals with, and this tranformation affects the subsequent computation processes, e.g., those of decision and control. Several types of knowledge transformation are reviewed. Definite conditions are analyzed, satisfaction of which is required for organization and processing of redundant information (knowledge) in the multi-resolutional systems. Providing a definite degree of redundancy is one of these conditions.

Meystel, A.↗

Reinforcement learning for online adaptation of model predictive controllers: Application to a selective catalytic reduction unit

Here we present a novel application of reinforcement learning (RL) for online dynamic tuning of model predictive controllers (MPC). Applying a state-action-reward-state-action (SARSA) algorithm for temporal difference learning with a control-specific reward function improves the error tracking performance of a standard MPC formulation. The proposed RL approach is also readily adaptable to other MPCs, or entirely different control approaches. Practical details for the implementation of the RL-MPC algorithm are also presented. The proposed algorithm is applied to a case study of controlling nitrogen oxide (NO x ) emissions in an industrial selective catalytic reduction (SCR) unit, a control problem characterized by significant nonlinearity and time delay. Along with an RL-MPC formulation for NOx control, another MPC is proposed to mitigate ammonia slip and decrease ammonia consumption in the SCR. Results showing the efficacy of the RL-MPC for NO x control through learning and implementation on the nonlinear SCR dynamic model are presented.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Mathematical model for adaptive control system of ASEA robot at Kennedy Space Center

The dynamic properties and the mathematical model for the adaptive control of the robotic system presently under investigation at Robotic Application and Development Laboratory at Kennedy Space Center are discussed. NASA is currently investigating the use of robotic manipulators for mating and demating of fuel lines to the Space Shuttle Vehicle prior to launch. The Robotic system used as a testbed for this purpose is an ASEA IRB-90 industrial robot with adaptive control capabilities. The system was tested and it's performance with respect to stability was improved by using an analogue force controller. The objective of this research project is to determine the mathematical model of the system operating under force feedback control with varying dynamic internal perturbation in order to provide continuous stable operation under variable load conditions. A series of lumped parameter models are developed. The models include some effects of robot structural dynamics, sensor compliance, and workpiece dynamics.

Zia, Omar↗

Instrumentation and Control Digital Modernization Research Plan for Long-Term Sustainability in the Nuclear Industry

This report, developed by Idaho National Laboratory (INL) in collaboration with Oak Ridge National Laboratory (ORNL), outlines a comprehensive research plan to support the digital modernization of safety-related instrumentation and control (I&C) systems in the U.S. nuclear industry. The modernization effort is critical to ensuring the long-term safety, reliability, and economic viability of both existing and future nuclear power plants (NPPs), particularly as aging analog systems become increasingly obsolete and difficult to maintain.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

New Insertion Device Control System for the APS Upgrade

New Hybrid Permanent Magnet Undulators (HPMUs) have been designed and manufactured using servo motors for precise and reliable gap motion control for the Advanced Photon Source Upgrade (APS-U) project. Meanwhile, existing HPMUs equipped with legacy stepper motors are systematically replaced with servo motors. In parallel with mechanical modifications of the undulators, a comprehensive upgrade has been implemented for the control of the devices. This upgrade includes integration of standardized industrial components for replacement of motor controllers and motor drives using the Kollmorgen Programmable Controller Multi-axis Master (PCMM) controllers and the AKD2G series servo drives. Soft Input Output Controllers (IOCs) are developed and deployed to replace the legacy VME-based IOCs for both single-period undulators and Revolver undulators. In this paper, we will present the architecture of the new insertion device control system, including control mechanisms, interlock protocols, and tools for diagnostics and troubleshooting.

Li, W.↗

Piloted Simulation Investigation of a Supersonic Transport Configuration (LaRC.4)

This report contains a description of the test facilities and software utilized during a joint NASA/aerospace industry study of improved control laws and desired inceptor characteristics for a candidate supersonic transport air-craft design. Details concerning the characteristics of the simulation cockpit, image generator and display systems, and motion platform are described. Depictions of the various display formats are included. The test schedule, session log, and flight cards describing the maneuvers performed is included. A brief summary of high-lights of the study is given. Modifications made to the industry-provided simulation model are described. This report is intended to serve as a reference document for industry researchers.

Jackson, E. Bruce↗

Overview of Active Flow Control at NASA Langley Research Center

The paper summarizes Active Flow Control projects currently underway at the NASA Langley Research Center. Technology development is being pursued within a multidisciplinary, cooperative approach, involving the classical disciplines of fluid mechanics, structural mechanics, material science, acoustics, and stability and control theory. Complementing the companion papers in this session, the present paper will focus on projects that have the goal of extending the state-of-the-art in the measurement, prediction, and control of unsteady, nonlinear aerodynamics. Toward this goal, innovative actuators, micro and macro sensors, and control strategies are considered for high payoff flow control applications. The target payoffs are outlined within each section below. Validation of the approaches range from bench-top experiments to wind-tunnel experiments to flight tests. Obtaining correlations for future actuator and sensor designs are implicit in the discussion. The products of the demonstration projects and design tool development from the fundamental NASA R&D level technology will then be transferred to the Applied Research components within NASA, DOD, and US Industry. Keywords: active flow control, separation control, MEMS, review

Pack, L. G.↗

Black carbon emissions and reduction potential in China: 2015–2050

Black carbon is a product of the incomplete combustion of carbonaceous fuels and has significant adverse effects on climate change, air quality, and human health. China has been a major contributor to global anthropogenic black carbon emissions. This study develops a black carbon inventory in China, using 2015 as the base year, and projects annual black carbon emissions in China for the period 2016–2050, under two scenarios: a Reference scenario and an Accelerated Reduction scenario. The study estimates that the total black carbon emissions in China in 2015 were 1100 thousand tons (kt), with residential use being the biggest contributor, accounting for more than half of the total black carbon emissions, followed by coke production, industry, agricultural waste burning, and transportation. This study then projects the total black carbon emissions in China in 2050 to be 278 kt in the Reference scenario and 86 kt in the Accelerated Reduction Scenario. Compared to the Reference scenario, the Accelerated Reduction scenario will achieve much faster and deeper black carbon reductions in all the sectors. The dramatic reductions can be attributed to the fuel switching in the residential sector, faster implementation of high-efficiency emission control measures in the industry, transportation, and coke production sectors, and faster phase-out of agricultural waste open burning. This analysis reveals the high potential of black carbon emission reductions across multiple sectors in China through the next thirty years.

54 ENVIRONMENTAL SCIENCES↗

National Ignition Facility. Facility and Infrastructure Systems Maintenance Plan

Ensuring the reliability of the NIF, including its support systems, laser systems, target diagnostic systems, and utilities, is essential to the availability of the NIF in its support of NNSA missions. NIF is a key capability in the DOE Stockpile Stewardship Program and supports high energy physics experiments for nuclear weapons, energy, and astrophysics applications. High system reliability provides opportunities for shots and scientific discoveries with opportunities to enhance and upgrade capabilities. This Maintenance Plan (MP) identifies the policies and procedures used to perform and support asset management of the NIF Facility and Infrastructure Systems (FInS), NIF Lasers & Alignment (LASE), NIF Target Experimental Operations (TOPS), NIF Target Area Science and Engineering (TASE), and NIF&PS Control Systems (NCS). The FInS systems include the facility, HVAC, contamination control, beampath, and Line Replaceable Units (LRUs) as well as utilities which create the beampath environments, such as vacuum, argon, or clean dry air. The LASE systems are Programmatic systems which include laser diagnostics, alignment, power conditioning, pulsed power, and input laser systems. The TOPS and TASE systems are also Programmatic systems which include target and diagnostic delivery systems and positioners, many different insertable and fixed target diagnostics, and cryogenic and target gas fill systems. Finally, the NCS systems include both software and hardware for industrial and shot operation control systems. Policies governing administrative and operational practices related to maintenance of FInS, LASE, TOPS, TASE, and NCS systems are described in this plan. In addition, the plan provides processes and procedures for managing, tracking, and documenting the work. This document, the NIF Operations Management Plan, NIF-5020544 (Ref. 1), and NIF Shot Operations Plan, NIF-5018506 (Ref. 2), together satisfy the requirements of the Conduct of Operations. Duties, responsibilities, and reporting requirements of the various positions associated with FInS, LASE, and TOPS maintenance are detailed in this plan. The FInS systems include both Real Property systems with asset management requirements specified in DOE Order 430.1C (Ref. 3) and Programmatic systems. In addition, for FInS, there is a list of the System Level Maintenance Plans (SLMPs) in NIF-1007419198 (Ref. 4) which provide the system descriptions and maintenance plan and schedule. In addition, the list includes the Reliability Centered Maintenance (RCM) and Experience Centered Maintenance (ECM) evaluations that have been performed for applicable FInS systems as well as reliability criticality per Section 3.5. The -AM version of the NIF Maintenance Plan focuses on the reliability program for FInS, LASE, TOPS, TASE, and NCS within the context of the overall NIF Reliability, Availability, and Maintainability (RAM) program and incorporates changes since the -AL version from August 2011 and has been updated to be fully consistent with the updates to Ref. 1. It also includes asset management considerations, updates to the Work Order (WO) process within the NIF Computerized Maintenance Management System (CMMS) which is EAM infor® System Maintenance and Reliability Tracking (SMaRT) (Ref. 5), and updates to metrics and key performance indicators (KPIs).

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Interface design in the process industries

Every operator runs his plant in accord with his own mental model of the process. In this sense, one characteristic of an ideal man-machine interface is that it be in harmony with that model. With this theme in mind, the paper first reviews the functions of the process operator and compares them with human operators involved in control situations previously studied outside the industrial environment (pilots, air traffic controllers, helmsmen, etc.). A brief history of the operator interface in the process industry and the traditional methodology employed in its design is then presented. Finally, a much more fundamental approach utilizing a model definition of the human operator's behavior is presented.

Beaverstock, M. C.↗

Machine Learning for Automated Weld Quality Monitoring and Control

Resistance Spot Welding (RSW) is a critical process in the automotive industry, valued for its cost-effectiveness, short cycle time, and robustness. However, achieving consistent high-quality joints remains challenging due to the complex interplay of various factors, like materials, processes, and manufacturing uncertainties, etc. Under the collaborative project between Oak Ridge National Laboratory (ORNL) and General Motors (GM), we have developed a robust and expansible machine learning (ML) framework aimed at enhancing quality control in RSW. By harnessing the power of machine learning, we have developed the ability to ensure every aspect of the welding process, from the initial process design stage to the final weld joint quality. The framework operates by analyzing a variety of data streams, including in-line process signals, process parameters, materials, and postprocessed weld joint data. Through this analysis, the models have been trained to detect deviations from optimal quality standards, leveraging their ability to identify signature data patterns and anomalies within in-line signals and construct complex correlations between these signals and weld quality parameters. Meanwhile, the machine learning framework is designed to adapt to a variety of materials, including high strength steels and aluminum alloys, etc. Its flexible architecture facilitates the incorporation of diverse data sources and features, enabling precise modeling and prediction across a broad range of material properties and weld quality variables. The expansible ML frameworks represent a promising transformation in weld quality monitoring and control, empowering industry to achieve high levels of efficiency, consistency, and reliability in manufacturing.

99 GENERAL AND MISCELLANEOUS↗

Machine Learning for Automated Weld Quality Monitoring and Control

Resistance Spot Welding (RSW) is a critical process in the automotive industry, valued for its cost-effectiveness, short cycle time, and robustness. However, achieving consistent high-quality joints remains challenging due to the complex interplay of various factors, like materials, processes, and manufacturing uncertainties, etc. Under the collaborative project between Oak Ridge National Laboratory (ORNL) and General Motors (GM), we have developed a robust and expansible machine learning (ML) framework aimed at enhancing quality control in RSW. By harnessing the power of machine learning, we have developed the ability to ensure every aspect of the welding process, from the initial process design stage to the final weld joint quality. The framework operates by analyzing a variety of data streams, including in-line process signals, process parameters, materials, and postprocessed weld joint data. Through this analysis, the models have been trained to detect deviations from optimal quality standards, leveraging their ability to identify signature data patterns and anomalies within in-line signals and construct complex correlations between these signals and weld quality parameters. Meanwhile, the machine learning framework is designed to adapt to a variety of materials, including high strength steels and aluminum alloys, etc. Its flexible architecture facilitates the incorporation of diverse data sources and features, enabling precise modeling and prediction across a broad range of material properties and weld quality variables. The expansible ML frameworks represent a promising transformation in weld quality monitoring and control, empowering industry to achieve high levels of efficiency, consistency, and reliability in manufacturing.

42 ENGINEERING↗