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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 433 records · Page 24

Evaluation of an Active Clearance Control System Concept

Reducing blade tip clearances through active tip clearance control in the high pressure turbine can lead to significant reductions in emissions and specific fuel consumption as well as dramatic improvements in operating efficiency and increased service life. Current engines employ scheduled cooling of the outer case flanges to reduce high pressure turbine tip clearances during cruise conditions. These systems have relatively slow response and do not use clearance measurement, thereby forcing cold build clearances to set the minimum clearances at extreme operating conditions (e.g., takeoff, reburst) and not allowing cruise clearances to be minimized due to the possibility of throttle transients (e.g., step change in altitude). In an effort to improve upon current thermal methods, a first generation mechanically-actuated active clearance control (ACC) system has been designed and fabricated. The system utilizes independent actuators, a segmented shroud structure, and clearance measurement feedback to provide fast and precise active clearance control throughout engine operation. Ambient temperature performance tests of this first generation ACC system assessed individual seal component leakage rates and both static and dynamic overall system leakage rates. The ability of the nine electric stepper motors to control the position of the seal carriers in both open- and closed-loop control modes for single and multiple cycles was investigated. The ability of the system to follow simulated engine clearance transients in closed-loop mode showed the system was able to track clearances to within a tight tolerance ( 0.001 in. error).

Steinetz, Bruce M.↗

Ten questions concerning occupant-centric control and operations

Occupant-Centric Control and Operation (OCC) represents a transformative approach to building management, integrating sensing of indoor environmental quality, occupant presence, and occupant-building interactions. These data are then utilized to optimize both operational efficiency and occupant comfort. This paper summarizes the findings from the IEA-EBC Annex 79 research program's subtask on real world implementations of OCC during the past 5 years. First, in Q1 and Q2, we provide a definition and categorization of OCC. Q3 addresses the role of building operators for OCC, while Q4 describes the implications for designers. Then, Q5 and Q6 discuss the role and possibilities of OCC for load flexibility, and for pandemic induced paradigm shifts in the built environment, respectively. In Q7, we provide a taxonomy and selection process of OCC, while Q8 details real world implementation case studies. Finally, Q9 explains the limits of OCC, and Q10 provides a vision for future research opportunities. Furthermore, our findings offer valuable insights for researchers, practitioners, and policy makers, contributing to the ongoing discourse on the future of building operations management.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Stability Analysis of Parallel Connected Bidirectional WPT System

This paper presents a stability analysis of parallel-connected bi-directional series-series resonant network wireless power transfer (WPT), optimized for Electric Vehicle (EV) charging and vehicle-to-grid (V2G) applications. The study addresses critical stability challenges in systems integrated with diverse distributed energy resources (DERs), including photovoltaics, fuel cells, wind turbines, energy storage systems, and the AC grid. The stability of such integrated DC grid systems is paramount for ensuring reliable operation, particularly under varying power flow conditions and dynamic interactions between parallel WPT systems. The analysis included system impedance characterization, state-space modeling, and open and closed-loop stability evaluations. The results demonstrated that the integration of a robust control architecture effectively mitigates instability risks and supports scalable, efficient operation. This work underscores the converter's adaptability and its potential for large-scale deployment in wireless EV charging infrastructures and integrated DC grid systems.

Asa, Erdem [ORNL] (ORCID:0000000190884812)↗

Coupling of Transport and Chemical Processes in Catalytic Combustion

Catalytic combustors have demonstrated the ability to operate efficiently over a much wider range of fuel air ratios than are imposed by the flammability limits of conventional combustors. Extensive commercial use however needs the following: (1) the design of a catalyst with low ignition temperature and high temperature stability, (2) reducing fatigue due to thermal stresses during transient operation, and (3) the development of mathematical models that can be used as design optimization tools to isolate promising operating ranges for the numerous operating parameters. The current program of research involves the development of a two dimensional transient catalytic combustion model and the development of a new catalyst with low temperature light-off and high temperature stablity characteristics.

Bracco, F. V.↗

A Pre-Mixed Shock-Induced-Combustion Approach to Inlet and Combustor Design for Hypersonic Applications

The need for efficient access to space has created interest in airbreathing propulsion as a means of achieving that goal. The NASP program explored a single-stage-to-orbit approach which could require scramjet airbreathing propulsion out to Mach 16 to 20. Recent interest in global access could require hypersonic cruise engines operating efficiently in the Mach 10 to 12 speed range. A common requirement of both these types of propulsion systems is that they would have to be fully integrated with the aero configuration so that the forebody becomes a part of the external compression inlet and the nozzle expansion is completed on the vehicle aftbody.

Weidner, John P.↗

A fresh perspective on the role of band bending, and related contributors, in light-driven production of electricity and chemicals

It is widely known that semiconductor-based solar energy conversion could power our planet. This is in part because high-quality semiconductor structures are unrivalled in their ability to separate photogenerated electrons and holes. One effective approach to achieving this photoinduced charge separation relies on a phenomenon known as “band bending”. But details to justify why band bending results in photoinduced charge separation are more complex than often appreciated. This underappreciation is an impediment to the rational, hypothesis-driven design of next-generation approaches to solar energy conversion. Herein we show, by means of derivations rooted in physical chemistry, that several phenomena – not just band bending – can facilitate photoinduced charge separation, and that each is influenced by nonequilibrium species concentration and a parameter, such as diffusion coefficient or rate coefficient, that introduces dynamics. To help visualize the impact of each phenomenon, we introduce plots that depict their contributions as free energy, force, flux, force constant, and rate. We reveal that spatial dopant distributions that define band bending are predictors of initial photogenerated species transport rates. But charge separation alone does not guarantee high-efficiency operation. A photogenerated change in energy that is freely available to do useful work is also essential, and is strongly dependent on semiconductor optical properties and reaction kinetics. Notably, this information reveals that specificity of interfacial chemical reactions – even when they are not preceded by charge separation elsewhere – can result in efficient solar energy conversion. We expect that this tutorial will guide researchers in their pursuit to uncover new mechanisms for light to perform useful work.

14 SOLAR ENERGY↗

Survey of methods for calculating sensitivity of general eigenproblems

A survey of methods for sensitivity analysis of the algebraic eigenvalue problem for non-Hermitian matrices is presented. In addition, a modification of one method based on a better normalizing condition is proposed. Methods are classified as Direct or Adjoint and are evaluated for efficiency. Operation counts are presented in terms of matrix size, number of design variables and number of eigenvalues and eigenvectors of interest. The effect of the sparsity of the matrix and its derivatives is also considered, and typical solution times are given. General guidelines are established for the selection of the most efficient method.

Murthy, Durbha V.↗

Derivatives of eigenvalues and eigenvectors of a general complex matrix

A survey of methods for sensitivity analysis of the algebraic eigenvalue problem for non-Hermitian matrices is presented. In addition, a modification of one method based on a better normalizing condition is proposed. Methods are classified as Direct or Adjoint and are evaluated for efficiency. Operation counts are presented in terms of matrix size, number of design variables and number of eigenvalues and eigenvectors of interest. The effect of the sparsity of the matrix and its derivatives is also considered, and typical solution times are given. General guidelines are established for the selection of the most efficient method.

Murthy, Durbha V.↗

Developing An Autonomy Infusion Infrastructure for Robotic Exploration

Future robotic exploration missions will require autonomy in order to accomplish mission goals for operational efficiency and science return. For example, it will require three communication cycles for the Mars Exploration Rovers, Spirit and Opportunity, to place an instrument on a science target. Reducing this time necessitates highly accurate navigation, obstacle avoidance, target tracking, target analysis, manipulation, and fault diagnosis. Technologies to address these and other operational elements are currently being developed at NASA and within academia. However, infusion into missions has always been a difficult task for researchers. In order to keep risk down, mission managers are reluctant to include new technologies unless they have undergone extensive testing and verification under flight-realistic conditions. Furthermore, infusion of new technologies into missions is made more difficult by the variety of software frameworks under which these technologies are developed. Missions would like to see competing solutions demonstrated on a common platform so that they can compare performance and choose the solution best suited to their application.

Bualat, Maria G.↗

Operational Lessons Learned from NASA Analog Missions

National Aeronautics and Space Administration s (NASA) efforts in human space flight are currently focused on the Space Shuttle and International Space Station (ISS) programs, with efforts beginning on the future exploration opportunities. Both the Space Shuttle and ISS programs are important to the development of a capability for human exploration beyond Low Earth Orbit (LEO). The ISS provides extensive research capabilities to determine how the human body reacts to long duration stays in space. Also, the ISS and Shuttle can serve as a limited testbed for equipment or entire systems that may be used on missions to the Moon, Mars, or to a near-Earth asteroid. It has been nearly 35 years since the Apollo astronauts visited the Moon. Future space explorers will have to re-learn how to work and live on planetary surfaces, and how to do that for extended periods of time. Exploration crews will perform a wide assortment of scientific tasks, including material sampling and emplacement of automated instruments. Surface mission operations include the activities of the crew living and working, mission support from the Earth, and the operation of robotic and other remotely commanded equipment on the surface and in planetary orbit. Other surface activities will include the following: exploring areas surrounding a habitat; using rovers to collect rock and soil samples; setting up experiments on the surface to monitor the radiation environment and any seismic or thermal activity; and conducting scientific analyses and experiments inside a habitat laboratory. Of course, the astronauts will also have to spend some of their surface time "doing chores" and maintaining their habitat and other systems. In preparation for future planetary exploration, NASA must design the answers to many operational questions. What will the astronauts do on the surface? How will they accomplish this? What tools will they require for their tasks? How will robots and astronauts work together? What vehicle and system capabilities are required to support the activities? How will the crew and the Earth-based mission control team interact? During the initial phases of manned planetary exploration, one challenge in particular is virtually the same as during the Apollo program: How can scientific return be maximized during a relatively short surface mission? Today, NASA is investigating solutions to these challenges by conducting analog missions. These Earth-based missions possess characteristics that are analogous to missions on the Moon or Mars. These missions are excellent for testing operational concepts, and the design, configuration, and functionality of spacesuits, robots, rovers, and habitats. Analog mission crews test specific techniques and procedures for surface field geology, biological sample collection, and planetary protection. The process of actually working an analog mission reveals a myriad of small details, which either contribute to or impede efficient operations, many of which would never have been thought about otherwise. It also helps to define the suite of tools, containers, and other small equipment that surface explorers will use. This paper focuses on how analog missions have addressed selected operational considerations for future planetary missions.

Arnold, Larissa S.↗

A hardware-in-the-loop (HIL) testbed for cyber-physical energy systems in smart commercial buildings

In recent years, there has been a growing trend toward the development of smart buildings that rely on cyber-physical systems (CPS) to optimize occupant comfort, safety, and energy efficiency. To ensure the reliable and efficient operation of CPS with designed control strategies, it is important to evaluate their performance under various scenarios before deploying them in the real world. This is where a Hardware-in-the-loop (HIL) testbed designed for studying sensor and control-related studies in smart buildings can be highly valuable. With the growing threat of cyber-attacks and physical faults targeting smart buildings, it is essential to ensure the security of building operations. A HIL testbed can emulate cyber-attack and physical fault scenarios, allowing researchers to develop and test threat detection and mitigation algorithms. This enables researchers to identify potential issues and optimize the algorithms in a safe and controlled environment before they are deployed in real-world settings, reducing the risk of failures that can negatively impact occupant comfort, safety, and energy efficiency. Therefore, this paper developed a HIL testbed designed for cyber-physical energy systems (e.g. buildings automation system (BAS)) in smart commercial buildings. The HIL testbed is comprised of a real-time building and Heating, Ventilation, and Air-Conditioning (HVAC) emulator using Modelica-based dynamic models, a set of BAS controllers, and a BAS computer server. The data generation capability of the HIL testbed is demonstrated by tracking normal and faulty operating data in the BAS, as well as monitoring detailed network traffic in the local BAS network. Here, this study further demonstrates the HIL testbed’s capability by conducting case studies on real-time physical fault and cyber-attack experiments using a Department of Energy (DOE) prototype commercial building. It is anticipated that the fully functional HIL testbed will be utilized for a variety of sensor and control-related studies, including but not limited to testing, developing, validating of different HVAC control strategies, fault detection & diagnosis, energy monitoring and analysis, cyber security study, etc.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Prediction of Silicon Content in a Blast Furnace via Machine Learning: A Comprehensive Processing and Modeling Pipeline

Silicon content plays an important role in determining the operational efficiency of blast furnaces (BFs) and their downstream processes in integrated steelmaking; however, existing sampling methods and first-principles models are somewhat limited in their capability and flexibility. Current data-based prediction models primarily rely on a limited set of manually selected furnace parameters. Additionally, different BFs present a diverse set of operating parameters and state variables that are known to directly influence the hot metal’s silicon content, such as fuel injection, blast temperature, and raw material charge composition, among other process variables that have their own impacts. The expansiveness of the parameter set adds complexity to parameter selection and processing. This highlights the need for a comprehensive methodology to integrate and select from all relevant parameters for accurate silicon content prediction. Providing accurate silicon content predictions would enable operators to adjust furnace conditions dynamically, improving safety and reducing economic risk. To address these issues, a two-stage approach is proposed. First, a generalized data processing scheme is proposed to accommodate diverse furnace parameters. Second, a robust modeling pipeline is used to establish a machine learning (ML) model capable of predicting hot metal silicon content with reasonable accuracy. The method employed herein predicted the average Si content of the upcoming furnace cast with an accuracy of 91% among 200 target predictions for a specific furnace provisioned by the XGBoost model. This prediction is achieved using only the past shift’s operating conditions, which should be available in real time. This performance provides a strong baseline for the modeling approach with potential for further improvement through provision of real-time features.

Chemistry↗

Using Machine Learning Tools to Predict Compressor Stall

Clean energy has become an increasingly important consideration in today’s power systems. As the push for clean energy continues, many coal-fired power plants are being decommissioned in favor of renewable power sources such as wind and solar. However, the intermittent nature of renewables means that dynamic load following traditional power systems is crucial to grid stability. With high flexibility and fast response at a wide range of operating conditions, gas turbine systems are poised to become the main load following component in the power grid. Yet, rapid changes in load can lead to fluid flow instabilities in gas turbine power systems. These instabilities often lead to compressor surge and stall, which are some of the most critical problems facing the safe and efficient operation of compressors in turbomachinery today. Although the topic of compressor surge and stall has been extensively researched, no methods for early prediction have been proven effective. This study explores the utilization of machine learning tools to predict compressor stall. The long short-term memory (LSTM) model, a form of recurrent neural network (RNN), was trained using real compressor stall datasets from a 100 kW recuperated gas turbine power system designed for hybrid configuration. Two variations of the LSTM model, classification and regression, were tested to determine optimal performance. The regression scheme was determined to be the most accurate approach, and a tool for predicting compressor stall was developed using this configuration. Overall, results show that the tool is capable of predicting stalls 5–20 ms before they occur. With a high-speed controller capable of 5 ms time-steps, mitigating action could be taken to prevent compressor stall before it occurs.

42 ENGINEERING↗

A European mobile satellite system concept exploiting CDMA and OBP

This paper describes a novel Land Mobile Satellite System (LMSS) concept applicable to networks allowing access to a large number of gateway stations ('Hubs'), utilizing low-cost Very Small Aperture Terminals (VSAT's). Efficient operation of the Forward-Link (FL) repeater can be achieved by adopting a synchronous Code Division Multiple Access (CDMA) technique, whereby inter-code interference (self-noise) is virtually eliminated by synchronizing orthogonal codes. However, with a transparent FL repeater, the requirements imposed by the highly decentralized ground segment can lead to significant efficiency losses. The adoption of a FL On-Board Processing (OBP) repeater is proposed as a means of largely recovering this efficiency impairment. The paper describes the network architecture, the system design and performance, the OBP functions and impact on implementation. The proposed concept, applicable to a future generation of the European LMSS, was developed in the context of a European Space Agency (ESA) study contract.

Vernucci, A.↗

Airborne Management of Traffic Conflicts in Descent With Arrival Constraints

NASA is studying far-term air traffic management concepts that may increase operational efficiency through a redistribution of decisionmaking authority among airborne and ground-based elements of the air transportation system. One component of this research, En Route Free Maneuvering, allows trained pilots of equipped autonomous aircraft to assume responsibility for traffic separation. Ground-based air traffic controllers would continue to separate traffic unequipped for autonomous operations and would issue flow management constraints to all aircraft. To evaluate En Route Free Maneuvering operations, a human-in-the-loop experiment was jointly conducted by the NASA Ames and Langley Research Centers. In this experiment, test subject pilots used desktop flight simulators to resolve conflicts in cruise and descent, and to adhere to air traffic flow constraints issued by test subject controllers. Simulators at NASA Langley were equipped with a prototype Autonomous Operations Planner (AOP) flight deck toolset to assist pilots with conflict management and constraint compliance tasks. Results from the experiment are presented, focusing specifically on operations during the initial descent into the terminal area. Airborne conflict resolution performance in descent, conformance to traffic flow management constraints, and the effects of conflicting traffic on constraint conformance are all presented. Subjective data from subject pilots are also presented, showing perceived levels of workload, safety, and acceptability of autonomous arrival operations. Finally, potential AOP functionality enhancements are discussed along with suggestions to improve arrival procedures.

Doble, Nathan A.↗

Regenerable Liquid Desiccants for High Efficiency Humidity Control in Microgravity

The NASA X-Hab project aims to design, manufacture, test, and prove functionality of an air humidity control subsystem to dehumidify and re-humidify air from a space cabin. The method of regulating cabin air humidity utilizes vortex phase separation, which uses an ionic liquid (IL) desiccant for air-water phase separation. This subsystem is intended to be integrated with a CO 2 removal system requiring de-humidified air to operate efficiently. The air humidity control subsystem is composed of a cold-desiccant or cold-side Vortex Phase Separator (VPS) that dehumidifies the cabin air. The dehumidified air exits the cold-side (CS) VPS chamber to flow into the CO 2 removal module, and the cold, water-laden liquid desiccant flows to a regenerative heat exchanger. From the heat exchanger the liquid desiccant continues to the heater. After heating, the desiccant flows into a hot-desiccant or hot-side (HS) VPS as the dehumidified air from CO 2 removal module enters through the HS VPS air inlet. The rehumidified air exits the HS VPS into the space cabin. One pump installed at the liquid exit of the CS VPS and one pump installed at the liquid exit of the HS VPS transport the fluid through the system. To evaluate the system’s efficiency and effectiveness, the temperature, pressure, flow rate and relative humidity are read, recorded, and analyzed at critical points along the module.

Gerardo Castro↗

Getting NuSTAR on Target: Predicting Mast Motion

The Nuclear Spectroscopic Telescope Array (NuSTAR) is the first focusing high energy (3-79 keV) X-ray observatory operating for four years from low Earth orbit. The X-ray detector arrays are located on the spacecraft bus with the optics modules mounted on a flexible mast of 10.14m length. The motion of the telescope optical axis on the detectors during each observation is measured by a laser metrology system and matches the pre-launch predictions of the thermal flexing of the mast as the spacecraft enters and exits the Earths shadow each orbit. However, an additional motion of the telescope field of view was discovered during observatory commissioning that is associated with the spacecraft attitude control system and an additional flexing of the mast correlated with the Solar aspect angle for the observation. We present the methodology developed to predict where any particular target coordinate will fall on the NuSTAR detectors based on the Solar aspect angle at the scheduled time of an observation. This may be applicable to future observatories that employ optics deployed on extendable masts. The automation of the prediction system has greatly improved observatory operations efficiency and the reliability of observation planning.

NASA small explorer↗

Energy Intensity Baselining and Tracking Guidance

Each company joining the U.S. Department of Energy’s (DOE’s) Better Buildings, Better Plants Program (Better Plants) commits to establishing an energy consumption and energy intensity (EI) baseline and to tracking its energy performance over a 10-year period against that baseline. The baseline must reflect a company’s energy consumption over a 12-month period, covering all its U.S.-based operations. Energy consumption is calculated by fuel type in terms of primary energy (also known as source energy). EI is broadly defined as the amount of energy consumed per unit of output produced. For this guidance document and for the program, the term energy performance represents an evaluation of a facility’s capacity to use energy efficiently. Metrics used to assess a facility’s energy performance can include EI, energy consumption, improvements in EI, etc. Establishing an energy baseline and tracking system is a critical first step in effectively managing energy use. Developing a baseline can help a company understand energy use within the corporation and give it a point of comparison to evaluate future efforts to improve energy performance. It can also support efforts to validate a company’s energy management activities, improve comparative analyses when using benchmarks, and help in predicting future energy needs. In addition, a company that normalizes its performance data can determine highly defensible measures of energy savings generated through implemented energy efficiency projects. Establishing a baseline and tracking energy performance is also a requirement for ISO 50001 certification. Although basic energy data can be collected through utility bills, most manufacturers will have to perform additional analyses to develop accurate and robust energy baselines and tracking systems. Energy is consumed in many ways within the manufacturing sector and can come from multiple sources. Energy is sometimes generated and sold to other parties or captured and reused on-site. External events can exert a significant impact on a facility or company’s energy use independent of any purposeful efforts to improve energy efficiency. Operational changes, such as production shifts—which may be inevitable for some companies over the 10-year period covered by the program—can also make a big difference in energy use. Since Better Plants asks companies to account for all their U.S.-based operations, mergers, acquisitions, and divestitures can also have significant implications for a company’s energy metrics. This document aims to demystify the sometimes complex baselining process. It devotes special attention to the task of normalizing and adjusting energy consumption to account for external factors, such as weather and production changes. A key recommendation is that companies use regression analysis to normalize their energy consumption data whenever possible. Regression analysis is a statistical technique that estimates the dependence of a variable (i.e., energy use in the context of Better Plants) on one or more independent variables such as ambient temperature, while controlling for the influence of other variables at the same time. A properly developed regression analysis can provide a reliable estimate of energy savings resulting from energy improvement strategies and projects by accounting for the effects of variables such as annual production levels and weather. DOE has developed a companion Energy Performance Indicator software tool (EnPI) to simplify the baselining process. This tool can run regression models, calculate changes in EI at the facility level, and automatically compile facility-level data into a corporate-wide metric. Note that although the relevant equations used to calculate EI are provided in this document, the EnPI tool will automatically perform most calculations for the user. Additionally, Better Plants Partners (Partners) can call on their Technical Account Manager (TAM) to help them establish a baseline and assist with the necessary calculations to track progress.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗