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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 1,639 records · Page 91

AI-Enabled Robots for Automated Nondestructive Evaluation and Repair of Power Plant Boilers. Final Report

Boiler failure could cause loss of life and safety issues, cost hundreds of thousands of dollars in equipment repairs, property damage and production losses, and drive up the cost of electric power. Boiler maintenance is challenging and risky for inspectors working on scaffolding in confined hazardous spaces inside of a boiler and sometimes the space is hard to access. The operation is also time-consuming due to the large area of vertical structures for inspection and the tremendous effort needed for scaffolding. Recently, the use of robotics (e.g., drones and crawlers) in power plants for maintenance is growing rapidly. However, the existing robotics solutions show two notable technological gaps: no live repair capability, and no Artificial Intelligence (AI) for smart autonomy. The objective of this project is to develop an integrated autonomous robotic platform that is equipped with compact non-destructive evaluation (NDE) sensors to perform live inspection, operates onboard repair devices to perform live repair, and uses AI for intelligent data fusion and predictive analysis for automated and smart spatiotemporal inspection, analysis and repair of the furnace walls in coal-fired boilers. The approach to achieve the objective includes developing NDE sensors with signal processing techniques, designing and evaluating repair devices for robots based on fusion and solid-state technologies, and an autonomous robotic platform that can attach to and navigate on boiler furnace walls using magnetic drive tracks. The robot is also powered by AI to automate data gathering (e.g., 3D mapping and damage localization) and predictive analysis. This project has advanced the state-of-the-art by providing technological breakthroughs including compact NDE and repair tools for robots, AI capabilities for smart autonomy, and a robotic platform for automated boiler maintenance. This project has great potential to result in significant benefits including limiting or eliminating the need to send operators to assess difficult-to-access or hazardous areas, enabling automated live inspection and repair, avoiding time consuming scaffolding (especially for partial maintenance during unplanned outage), collecting comprehensive and well-organized data smartly, and avoiding or limiting the need for onsite or remote piloting technicians. The impacts can be tremendous in terms of the time and cost savings, reducing the risk for human operators, and increasing boiler reliability, usability, and efficiency. In addition, by developing the new technologies on the autonomous inspection and repair robot, by involving multiple undergraduate and graduate students working together with the faculty members on this project, and by generating knowledge and building up collaborations with industrial partners, this effort will significantly update the education capabilities, support long-term fundamental research, and maintain the leadership of Colorado School of Mines and Michigan State University in energy fields.

20 FOSSIL-FUELED POWER PLANTS↗

Application of a Prize Mechanism to Address Data Utilization Challenges at Utilities

The electric industry sector is facing an “explosion” of data from a variety of sources. Electric sector stakeholders need to define how to capitalize on large datasets, both those they create and those from other sources (like data on weather, buildings, electric vehicles, etc.), to improve reliability and resilience and meet the changing system dynamics from renewable integration. For the electricity sector to fully utilize these vast new datasets, it must undergo a transformation in how it manages data quality, storage, and processing. The U.S. Department of Energy (DOE) Office of Electricity (OE) is committed to accelerating research, development, and demonstration of new technologies and tools within the electricity sector to advance reliability, resilience, and affordable operation of the power system. Through the prize mechanism, OE identified two widespread data-related challenges for utilities—load modeling and data analysis automation—and offered an opportunity for utilities and teams of software engineers to identify additional challenges faced by utilities. After completing one round of the American-Made Digitizing Utilities Prize, OE, the National Renewable Energy Laboratory (NREL) as the prize administrator, and Pacific Northwest National Laboratory (PNNL) as the domain experts have compiled the results and lessons learned to feed into the second round of the prize.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Laboratory Evaluation and Field Demonstration of High Rotor Switched Reluctance Motor (HRSRM) Technology

In this project, a new motor technology based on a novel design called a High Rotor Pole Switched Reluctance Motor (HRSRM) was demonstrated and evaluated. The HRSRM system combines an innovative electric motor design with a programmable variable-speed drive and a controller that provides real time monitoring and cloud-based connectivity. Unlike induction or permanent-magnet motor designs, this motor uses a switched reluctance (SR) design that purports to be simpler to manufacture and more reliable and efficient to operate. Several of the stated benefits of the HRSRM system were evaluated as part of this project. First, the technology is claimed to offer greater energy efficiency than any motor currently on the market. Second, according to the manufacturer, the motor can be dropped into an existing pump or heating, ventilation, and air-conditioning application in less than 30 minutes, and has controls that can be pre-programmed to interact with the application’s existing control structure. Third, the control system allows the HRSRM to replace a constant-speed motor with one that provides variable-speed capabilities without requiring the installation of a variable-speed drive. The evaluation of a 10 hp HRSRM system was conducted in two parts. One portion of the evaluation consisted of performance tests conducted in a tightly controlled laboratory environment in which the performance of the HRSRM system was compared with that of a premium efficiency induction motor with a variable-frequency drive. The other portion of the evaluation was conducted at a field location within a General Services Administration facility in which the HRSRM system replaced an existing motor system in a 10 hp chilled water pump. The performance of the HRSRM system was compared with that of the incumbent motor system that was supplied with the pump from the manufacturer. The overall project and performance objectives for this motor evaluation are defined in Table ES.1.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Klickitat Valley Health Central Utility Plant Modernization

This project replaced legacy heating and cooling equipment at Klickitat Valley Health (KVH), a rural hospital in Goldendale, Washington. Work included constructing a new chiller building, installing modern hydronic piping systems, replacing the main Emergency Department air handler (Air Handlining Unit (AHU-1)), upgrading electrical systems, and converting the Emergency Department wing from electric reheat to hydronic heating and cooling. Commissioning, testing, adjusting, and balancing were completed under this grant. These upgrades improve energy efficiency, operational resilience, and system reliability while preparing the campus for future electrification and renewable energy integration. They also support growth in healthcare services for a rural population. The project directly reduces energy costs and provides a foundation for future decarbonization measures, including a FEMA-funded microgrid and a large-scale ground source heat pump (GSHP) project. These follow-on initiatives would not have been possible without the hydronic backbone built through this project.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

AI-Ready Control System for the Fermilab Accelerator Complex

Reliable, high-intensity operation of the Fermilab Accelerator Complex is critical to the success of the Long-Baseline Neutrino Facility and Deep Underground Neutrino Experiment. We describe the requirements and infrastructure necessary to support routine use of artificial intelligence and machine learning (AI/ML) in the accelerator control system. Three capabilities are identified: a machine learning operations (MLOps) framework standardizing the lifecycle of AI/ML automation from data management through deployment and monitoring; a data quality framework defining and enforcing standards required to build trustworthy AI/ML applications; and workflow integration with large language models to assist physicists, engineers, and operators with information retrieval, code development, and routine analysis. Use cases spanning beam diagnostics, beam control, and support system automation illustrate the technical requirements across the complex.

43 PARTICLE ACCELERATORS↗

Restoring Worn Components in Automobile Timing Mechanisms

In operation, the end of the valve tappet in an automobile’s timing mechanism undergoes not only wear but also fatigue crumbling. Several methods of removing the worn cast-iron layer are proposed to restore the gas-distributor components.

42 ENGINEERING↗

Optimal Siting of EV Fleet Charging Station Considering EV Mobility and Microgrid Formation for Enhanced Grid Resilience

Coordinating infrastructure planning for transportation and the power grid is essential for enhanced reliability and resilience during operation and disaster management. This paper presents a two-stage stochastic model to optimize the location of electric vehicle fleet charging stations (FEVCSs) to enhance the resilience of a distribution network. The first stage of this model deals with the decision to place an FEVCS at the most favorable and optimized location, whereas the second stage aims to minimize the weighted sum of the value of lost load in multiple potential scenarios with different faults. Indeed, the second stage is a joint grid restoration scheme with network reconfiguration and microgrid formation using available distributed generators and fleet electric vehicles. The proposed model is tested on a modified IEEE-33 node distribution network and a four-node transportation network. Case studies demonstrate the effectiveness of the proposed model.

25 ENERGY STORAGE↗

Unsupervised Detection of SOC Spoofing in OCPP 2.0.1 EV Charging Communication Protocol Using One-Class SVM

The electric vehicles (EVs) market keeps growing globally; thus, it is critical to secure the EV charging communication protocols in order to guarantee reliable and fair charging operations among the customers. The Open Charge Point Protocol (OCPP) 2.0.1 supports the communication between the Electric Vehicle Supply Equipment (EVSE) and Charging Station Management Systems (CSMSs); therefore, it becomes vulnerable to several types of attacks, which aim to jeopardize smart charging, billing, and energy management. Specifically, OCPP 2.0.1 allows the self-reporting of the State of Charge (SOC) values, which makes it vulnerable to spoofing-based cyberattacks, which target manipulating the scheduling priorities, distorting the load forecasts, and extending the charging sessions in an unfair manner. In this paper, we try to address this type of attack by providing a comprehensive analysis of the SOC spoofing attacks and introducing a novel unsupervised detection framework based on the One-Class Support Vector Machine (OCSVM) algorithm. Specifically, two types of attack scenarios are analyzed (i.e., priority manipulation and session extension) by deriving engineered features that capture the nonlinear relationships under normal charging behavior. Detailed simulation-based results are derived by utilizing the DESL-EPFL Level 3 EV charging dataset. Our results demonstrate high F1-score and recall in identifying spoofed SOC values and that the proposed OCSVM model demonstrates superior performance compared to alternative clustering and deep-learning based detectors.

EV charging↗

An Investigation into the Effects of Swirl on the Performance and Emissions of an Opposed-Piston Two-Stroke Engine using Large Eddy Simulations

Opposed-piston two-stroke (OP-2S) engines have the potential to achieve higher thermal efficiency than a conventional four-stroke diesel engine. However, the uniflow scavenging process is difficult to control over a wider range of speed and loads due to its sensitivity to pressure dynamics, port timings, and port design. Specifically, the angle of the intake ports can be used to generate swirl which has implications for open and closed cycle effects. This study proposes an analysis of the effects of port angle on the in-cylinder flow distribution and combustion performance of an OP-2S using computational fluid dynamics engine. Large Eddy Simulation (LES) was used to model turbulence given its ability to predict in-cylinder mixing and cyclic variability. A three-cylinder model was validated to experimental data collected by Achates Power and the grid was verified using an LES quality approach from the literature. The model was used to simulate port angles from 12 to 29 degrees at constant pressure and temperature boundary conditions. Results indicated that the higher bulk swirl ratio generated by larger port angles tends to trap more internal residuals. This effect on the scavenging performance, combined with the larger trapped swirl ratio, also has a significant impact on the combustion performance in a two-stroke engine. It was concluded that there exists a tradeoff of efficiency and emissions that must be considered when increasing the port angle in a uniflow two-stroke engine. 1. Introduction Two-stroke engines were developed in the 1800s and are commonly used in practice today for lightweight power applications such as motorcycles or handheld power tools, as well as large-bore low speed engines for stationary power and marine applications. Two-stroke engines provide the distinct advantage of higher torque/power output but present challenges due to its coupled intake and exhaust process. Four-stroke engines have the benefit of using two full piston strokes to induct intake charge and to expel exhaust gases. Controlling the trapped charge composition in a twostroke engine via a scavenging process is crucial for reliable and efficient engine operation.

33 ADVANCED PROPULSION SYSTEMS↗

Nuclear rocket know-how.

Nuclear rockets operating efficiency and flexibility, reliability, safety, hot high stress structures, nozzle cooling, etc

Gabriel, D.↗

Precision calibration and reference voltage source for data acquisition systems

Hybrid integrated circuit operational amplifiers, which have inherent characteristics of low quiescent power dissipation and extended operational lifetime with high reliability, are source for digital systems. Amplifiers are coupled to Zener reference diode in current control and buffer configuration.

Source record↗

A traverse gravimeter for the lunar surface

A semi-automatic, self-levelling lunar gravimeter was designed for the purpose of measuring gravity at predetermined stops along the route of a lunar rover vehicle to obtain a gravity profile. The traverse gravimeter is completely self-contained and is powered by an internal battery. The gravity sensor is a vibrating string accelerometer (VSA) which is enclosed in a precision oven. Gravity data are obtained by initiating a measurement. After the gravimeter has levelled, the VSA difference frequency is counted down and a gate is generated to enable a crystal-controlled clock to a BCD counter. The BCD counter stores the data which are a measurement of gravity. These data, displayed upon command by the astronaut, are transmitted by voice back to earth. It is expected that the accuracy of the gravimeter will be better than one milligal. Low power, light weight, reliability, and simplicity of operation are major considerations in the design of the gravimeter.

Mamon, G.↗

A simple, accurate depth check guage

Easily made, pen-light battery operated production check gauge has probe-activated switch with fail-safe features to insure proper operation. Parts can be reliably and quickly checked. Gauge is equipped with tolerance band adjustment and can use interchangeable probes for different applications. Accompanying tester permits frequent check of calibration.

Rauch, E. P.↗

Single-channel digital command-detection system

System, fabricated of highly-reliable digital logic elements, operates on binary pulse-code-modulated signals and derives internal synchronization from data signal. All-digital implementation of detector develops synchronization from data signal by computer cross-correlation of command modulation signal with its expected forms in sequence and adjusts detector phases in accordance with correlation peaks.

Carl, C. C.↗

Monitoring physical and chemical parameters of Delaware Bay waters with an ERTS-1 data collection platform

The author has identified the following significant results. Evaluation of the probe performances during the initial phase indicates that the dissolved oxygen sensor available as part of the package is not sufficiently reliable for long term operation. The turbidity probe requires frequent visits to the site to maintain it in proper operating condition. The cost of these visits would have to be weighed against the information obtained. The conductivity/salinity, temperature, pH, and depth indicators have worked extremely well over the course of the study. Monthly cleanings would maintain all these probes in top operating condition. Currently the accuracy of each measurement returned via satellite is being compared to the accuracy of the probe reading and water samples analyzed in the laboratory.

Klemas, V.↗

Discussion and theoretical summarization of the experimental data

A summary of research on psychological factors that cause substantial changes in the reliability indicators of an operators work is followed by a conclusion that strong moral-volitional qualities are the basic factors that make the human behavior under conditions of stress effective; emotional subcortical subdominants affect a person's conscious organization and self control in a man machine environment.

Mileryan, Y. A.↗