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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 37 records · Page 2

Life-Extending Control for Aircraft Engines Studied

Current aircraft engine controllers are designed and operated to provide both performance and stability margins. However, the standard method of operation results in significant wear and tear on the engine and negatively affects the on-wing life--the time between cycles when the engine must be physically removed from the aircraft for maintenance. The NASA Glenn Research Center and its industrial and academic partners have been working together toward a new control concept that will include engine life usage as part of the control function. The resulting controller will be able to significantly extend the engine's on-wing life with little or no impact on engine performance and operability. The new controller design will utilize damage models to estimate and mitigate the rate and overall accumulation of damage to critical engine parts. The control methods will also provide a means to assess tradeoffs between performance and structural durability on the basis of mission requirements and remaining engine life. Two life-extending control methodologies were studied to reduce the overall life-cycle cost of aircraft engines. The first methodology is to modify the baseline control logic to reduce the thermomechanical fatigue (TMF) damage of cooled stators during acceleration. To accomplish this, an innovative algorithm limits the low-speed rotor acceleration command when the engine has reached a threshold close to the requested thrust. This algorithm allows a significant reduction in TMF damage with only a very small increase in the rise time to reach the commanded rotor speed. The second methodology is to reduce stress rupture/creep damage to turbine blades and uncooled stators by incorporating an engine damage model into the flight mission. Overall operation cost is reduced by an optimization among the flight time, fuel consumption, and component damages. Recent efforts have focused on applying life-extending control technology to an existing commercial turbine engine, and doing so without modifying the hardware or adding sensors. This approach makes it possible to retrofit existing engines with life-extending control technology by changing only the control software in the full-authority digital engine controller (FADEC). The significant results include demonstrating a 20- to 30-percent reduction in TMF damage to the hot section by developing and implementing smart acceleration logic during takeoff. The tradeoff is an increase, from 5.0 to 5.2 sec, in the time required to reach maximum power from ground idle. On a typical flight profile of a cruise at Mach 0.8 at an altitude of 41,000 ft, and cruise time of 104 min, the optimized system showed that a reduction in cruise speed from Mach 0.8 to 0.79 can achieve an estimated 25-to 35-percent creep/rupture damage reduction in the engine's hot section and a fuel savings of 2.1 percent. The tradeoff is an increase in flight time of 1.3 percent (1.4 min).

Guo, Te-Huei↗

Evaluating and optimizing horticultural regimes in space plant growth facilities

In designing innovative space plant growth facilities (SPGF) for long duration space flight, various limitations must be addressed including onboard resources: volume, energy consumption, heat transfer and crew labor expenditure. The required accuracy in evaluating on board resources by using the equivalent mass methodology and applying it to the design of such facilities is not precise. This is due to the uncertainty of the structure and not completely understanding the properties of all associated hardware, including the technology in these systems. We present a simple criteria of optimization for horticultural regimes in SPGF: Qmax = max [M x (EBI)2/(V x E x T], where M is the crop harvest in terms of total dry biomass in the plant growth system; EBI is the edible biomass index (harvest index), V is volume occupied by the crop; E is the crop light energy supply during growth; T is the crop growth duration. The criterion reflects directly on the consumption of onboard resources for crop production. c2004 COSPAR. Published by Elsevier Ltd. All rights reserved.

NASA Discipline Life Support Systems↗

Venus High Temperature Atmospheric Dropsonde and Extreme-Environment Seismometer (HADES)

The atmospheric composition and geologic structure of Venus have been identified by the US National Research Council's Decadal Survey for Planetary Science as priority targets for scientific exploration, however the high temperature and pressure at the surface, along with the highly corrosive chemistry of the Venus atmosphere, present significant obstacles to spacecraft design that have severely limited past and proposed landed missions. Following the methodology of the NASA Innovative Advanced Concepts (NIAC) proposal regime and the Collaborative Modeling and Parametric Assessment of Space Systems (COMPASS) design protocol, this paper presents a conceptual study and initial feasibility analysis for a Discovery-class Venus lander capable of an extended-duration mission at ambient temperature and pressure, incorporating emerging technologies within the field of high temperature electronics in combination with novel configurations of proven, high Technology Readiness Level (TRL) systems. Radioisotope Thermal Power (RTG) systems and silicon carbide (SiC) communications and data handling are examined in detail, and various high-temperature instruments are proposed, including a seismometer and an advanced photodiode imager. The study combines this technological analysis with proposals for a descent instrument package and a relay orbiter to demonstrate the viability of an integrated atmospheric and in-situ geologic exploratory mission that differs from previous proposals by greatly reducing the mass, power requirements, and cost, while achieving important scientific goals.

HADES↗

A Strip-Yield Model for Predicting the Growth of Part-Through Cracks Under Cyclic Loading

Flaws exist in aircraft structures due to manufacturing operations and material defects. Under variable amplitude cyclic loading, these flaws grow as part-through cracks reducing the residual strength of structural components. To meet damage tolerant design requirements, accurate flaw growth predictions are needed which account for continual changes in crack shape as well as crack growth retardation and acceleration. Predicting the growth of part-through cracks under cyclic loading using an innovative and computationally efficient model is the focus of the research summarized in this report. In this research effort, a slice synthesis methodology was developed and used to construct a modified strip-yield model for the part-through semi-elliptical surface flaw, enabling prediction of plasticity-induced closure along the crack front and subsequent fatigue crack growth under constant amplitude and variable amplitude loading. While modeling the plasticity-induced closure in a part-through flaw may be performed using three dimensional elastic-plastic finite element analysis, this type of effort is impractical from an engineering perspective. A modified strip-yield model similar to that used in FASTRAN for part-through flaws is a much needed engineering design tool, particularly when computational resources are limited.

Daniewicz, S. R.↗

Overview of the ACT program

NASA's Advanced Composites Program (ACT) was initiated in 1988. A National Research Announcement was issued to solicit innovative ideas that could significantly contribute to development and demonstration of an integrated technology data base and confidence level that permits cost-effective use of composite primary structures in transport aircraft. Fifteen contracts were awarded by the Spring of 1989 and the participants include commercial and military airframe manufacturers, materials developers and suppliers, universities, and government laboratories. The program approach is to develop materials, structural mechanics methodology, design concepts, and fabrication procedures that offer the potential to make composite structures cost-effective compared to aluminum structure. Goals for the ACT program included 30-50 percent weight reduction, 20-25 percent acquisition cost reduction, and provided the scientific basis for predicting materials and structures performance. This paper provides an overview of the ACT program status, plans, and selected technical accomplishments. Sixteen additional papers, which provide more detailed information on the research and development accomplishments, are contained in this publication.

Davis, John G., Jr.↗

Assessment of Soft Vane and Metal Foam Engine Noise Reduction Concepts

Two innovative fan-noise reduction concepts developed by NASA are presented - soft vanes and over-the-rotor metal foam liners. Design methodologies are described for each concept. Soft vanes are outlet guide vanes with internal, resonant chambers that communicate with the exterior aeroacoustic environment via a porous surface. They provide acoustic absorption via viscous losses generated by interaction of unsteady flows with the internal solid structure. Over-the-rotor metal foam liners installed at or near the fan rotor axial plane provide rotor noise absorption. Both concepts also provide pressure-release surfaces that potentially inhibit noise generation. Several configurations for both concepts are evaluated with a normal incidence tube, and the results are used to guide designs for implementation in two NASA fan rigs. For soft vanes, approximately 1 to 2 dB of broadband inlet and aft-radiated fan noise reduction is achieved. For over-the-rotor metal foam liners, up to 3 dB of fan noise reduction is measured in the low-speed fan rig, but minimal reduction is measured in the high-speed fan rig. These metal foam liner results are compared with a static engine test, in which inlet sound power level reductions up to 5 dB were measured. Brief plans for further development are also provided.

Jones, Michael G.↗

Lightning protection technology for small general aviation composite material aircraft

An on going NASA (Small Business Innovative Research) SBIR Phase II design and development program will produce the first lightning protected, fiberglass, General Aviation aircraft that is available as a kit. The results obtained so far in development testing of typical components of the aircraft kit, such as the wing and fuselage panels indicate that the lightning protection design methodology and materials chosen are capable of protecting such small composite airframes from lightning puncture and structural damage associated with severe threat lightning strikes. The primary objective of the program has been to develop a lightening protection design for full scale test airframe and verify its adequacy with full scale laboratory testing, thus enabling production and sale of owner-built, lightning-protected, Stoddard-Hamilton Aircraft, Inc. Glasair II airplanes. A second objective has been to provide lightning protection design guidelines for the General Aviation industry, and to enable these airplanes to meet lightening protection requirements for certification of small airplanes. This paper describes the protection design approaches and development testing results obtained thus far in the program, together with design methodology which can achieve the design goals listed above. The presentation of this paper will also include results of some of the full scale verification tests, which will have been completed by the time of this conference.

Plumer, J. A.↗

NASA Workshop on Technology for Human Robotic Exploration and Development of Space

Continued constrained budgets and growing interests in the industrialization and development of space requires NASA to seize every opportunity for assuring the maximum return on space infrastructure investments. This workshop provided an excellent forum for reviewing, evaluating, and updating pertinent strategic planning, identifying advanced concepts and high-risk/high-leverage research and technology requirements, developing strategies and roadmaps, and establishing approaches, methodologies, modeling, and tools for facilitating the commercial development of space and supporting diverse exploration and scientific missions. Also, the workshop addressed important topic areas including revolutionary space systems requiring investments in innovative advanced technologies; achieving transformational space operations through the insertion of new technologies; revolutionary science in space through advanced systems and new technologies enabling experiments to go anytime to any location; and, innovative and ambitious concepts and approaches essential for promoting advancements in space transportation. Details concerning the workshop process, structure, and results are contained in the ensuing report.

Mankins, J. C.↗

A Hierarchical Approach to Fracture Mechanics

Recent research conducted under NASA LaRC's Creativity and Innovation Program has led to the development of an initial approach for a hierarchical fracture mechanics. This methodology unites failure mechanisms occurring at different length scales and provides a framework for a physics-based theory of fracture. At the nanoscale, parametric molecular dynamic simulations are used to compute the energy associated with atomic level failure mechanisms. This information is used in a mesoscale percolation model of defect coalescence to obtain statistics of fracture paths and energies through Monte Carlo simulations. The mathematical structure of predicted crack paths is described using concepts of fractal geometry. The non-integer fractal dimension relates geometric and energy measures between meso- and macroscales. For illustration, a fractal-based continuum strain energy release rate is derived for inter- and transgranular fracture in polycrystalline metals.

Saether, Erik↗

Wildfire Segmentation From Remotely Sensed Data Using Quantum-Compatible Conditional Vector Quantized-Variational Autoencoders

Wildfires represent a critical environmental hazard with multifaceted implications for ecosystems, communities, and public health [1]. The escalating frequency and intensity of wildfires globally have intensified the urgency for robust segmentation methodologies to facilitate effective mitigation, response, and recovery strategies [2]. Accurate wildfire segmentation is pivotal for delineating fire boundaries, assessing progression patterns, and prioritizing resource allocation during emergency scenarios. Furthermore, precise segmentation enables stakeholders, including policymakers, environmental scientists, and emergency responders, to formulate evidence-based strategies, thereby minimizing socio-economic disruptions and ecological degradation. Consequently, advancing wildfire segmentation techniques through innovative technological interventions remains a paramount research imperative. Although foundational in wildfire segmentation, traditional deterministic models exhibit inherent limitations that compromise their efficacy in dynamic and uncertain environments. These models often operate on rigid algorithms prioritizing deterministic classifications, thereby overlooking the inherent complexities and uncertainties associated with wildfire behavior and satellite data variability. Such deterministic frameworks tend to produce oversimplified representations that fail to capture the intricate nuances of evolving fire dynamics, spatial heterogeneity, and environmental interactions [1]. Consequently, the deterministic approach’s propensity for uncertainty collapsing [1, 3] hampers the accuracy, reliability, and applicability of segmentation outcomes in real-world scenarios. Contrastingly, stochastic models offer a more nuanced and adaptable framework for wildfire segmentation. By integrating probabilistic elements into the modeling paradigm, stochastic approaches, particularly probabilistic approaches such as variational auto encoders (VAEs) [4], facilitate comprehensive uncertainty assessment, enabling researchers to quantify and incorporate uncertainties into segmentation outcomes effectively. This probabilistic nature empowers stochastic models to encapsulate variability, account for data inconsistencies, and adapt to evolving environmental conditions, enhancing segmentation accuracy, reliability, and robustness. Embracing stochastic methodologies thus catalyzes advancements in wildfire science by fostering a more holistic, adaptive, and resilient segmentation framework. Despite VAEs demonstrating significant promise in various applications, they come with inherent limitations that have garnered attention within the machine learning community. One of the primary drawbacks lies in their reliance on static priors, which essentially assume a fixed distribution for latent variables, thereby limiting the model’s flexibility to capture complex data structures effectively [5]. This static nature leads to suboptimal representations, especially when dealing with complex and high-dimensional data. Additionally, VAEs often struggle with generating sharp and realistic samples, a phenomenon commonly referred to as mode collapse [5, 7, 6]. Furthermore, the optimization process in VAEs, which involves balancing the reconstruction loss and the regularization term, can sometimes be challenging to fine-tune [7]. In recent efforts to address these shortcomings, alternative approaches like Vector Quantized Variational Auto encoders(VQ-VAEs) [7], address the challenges by incorporating discrete latent variables and leveraging techniques that enhance the quality and diversity of generated samples while maintaining efficient training dynamics. VQ-VAEs propose a dynamic prior distribution generation mechanism that diverges from the static priors commonly associated with traditional VAEs. This dynamic approach allows for more adaptive and context-aware latent variable representations, thereby potentially capturing complex data structures more effectively. Unlike autoregressive prior models such as PixelCNN, which, despite their ability to model dependencies across data dimensions, suffer from significant computational inefficiencies and lack flexibility in handling diverse datasets. In our work, we propose to use a generative quantum-compatible approach to help alleviate the shortcomings of autoregressive prior model in VQ-VAEs. Restricted Boltzmann Machines (RBMs) are a viable alternative prior model that can learn prior distributions in a faster and more flexible manner. In this research endeavor, we meticulously curate a state-of-the-art dataset leveraging satellite MODIS data in conjunction with VIIRS fire masks, derived from Fire Radiative Power (FRP), thereby encapsulating diverse wildfire scenarios and environmental contexts. We developed a conditional VQ-VAE architecture with the RBM prior model that is trained in a supervised manner for segmenting wildfire masks. This innovative approach synergistically harnesses deep learning capabilities, enabling the generation of segmentation maps characterized by heightened precision, granularity, and contextual relevance. Furthermore, replacing the autoregressive prior learning method proposed by the original VQ-VAE with a prior density approximation via quantum-compatible RBM facilitates expedited inference processes, augments flexibility in prior sampling, optimizes computational efficiency and establishes a groundbreaking benchmark in wildfire segmentation methodologies.

quantum machine learning↗

WARP: Weight Associative Rule Processor. A dedicated VLSI fuzzy logic megacell

During the last five years Fuzzy Logic has gained enormous popularity in the academic and industrial worlds. The success of this new methodology has led the microelectronics industry to create a new class of machines, called Fuzzy Machines, to overcome the limitations of traditional computing systems when utilized as Fuzzy Systems. This paper gives an overview of the methods by which Fuzzy Logic data structures are represented in the machines (each with its own advantages and inefficiencies). Next, the paper introduces WARP (Weight Associative Rule Processor) which is a dedicated VLSI megacell allowing the realization of a fuzzy controller suitable for a wide range of applications. WARP represents an innovative approach to VLSI Fuzzy controllers by utilizing different types of data structures for characterizing the membership functions during the various stages of the Fuzzy processing. WARP dedicated architecture has been designed in order to achieve high performance by exploiting the computational advantages offered by the different data representations.

Pagni, A.↗

Pressure Ratio to Thermal Environments

A pressure ratio to thermal environments (PRatTlE.pl) program is a Perl language code that estimates heating at requested body point locations by scaling the heating at a reference location times a pressure ratio factor. The pressure ratio factor is the ratio of the local pressure at the reference point and the requested point from CFD (computational fluid dynamics) solutions. This innovation provides pressure ratio-based thermal environments in an automated and traceable method. Previously, the pressure ratio methodology was implemented via a Microsoft Excel spreadsheet and macro scripts. PRatTlE is able to calculate heating environments for 150 body points in less than two minutes. PRatTlE is coded in Perl programming language, is command-line-driven, and has been successfully executed on both the HP and Linux platforms. It supports multiple concurrent runs. PRatTlE contains error trapping and input file format verification, which allows clear visibility into the input data structure and intermediate calculations.

Lopez, Pedro↗

NASA's Aeronautics Vision

Six long-term technology focus areas are: 1. Environmentally Friendly, Clean Burning Engines. Focus: Develop innovative technologies to enable intelligent turbine engines that significantly reduce harmful emissions while maintaining high performance and increasing reliability. 2. New Aircraft Energy Sources and Management. Focus: Discover new energy sources and intelligent management techniques directed towards zero emissions and enable new vehicle concepts for public mobility and new science missions. 3. Quiet Aircraft for Community Friendly Service. Focus: Develop and integrate noise reduction technology to enable unrestricted air transportation service to all communities. 4. Aerodynamic Performance for Fuel Efficiency. Focus: Improve aerodynamic efficiency,structures and materials technologies, and design tools and methodologies to reduce fuel burn and minimize environmental impact and enable new vehicle concepts and capabilities for public mobility and new science missions. 5. Aircraft Weight Reduction and Community Access. Focus: Develop ultralight smart materials and structures, aerodynamic concepts, and lightweight subsystems to increase vehicle efficiency, leading to high altitude long endurance vehicles, planetary aircraft, advanced vertical and short takeoff and landing vehicles and beyond. 6. Smart Aircraft and Autonomous Control. Focus: Enable aircraft to fly with reduced or no human intervention, to optimize flight over multiple regimes, and to provide maintenance on demand towards the goal of a feeling, seeing, sensing, sentient air vehicle.

Tenney, Darrel R.↗

Sustainable Crop Cultivation in Space Analogs: A BRIDGES Methodology Perspective Through SpaCEA

Sustainable crop cultivation in space holds paramount significance for the support of life in future long-duration missions. This research explores the development and integration of innovative low-cost proof-of-concept (LC-POC) plant growth cabinets tailored for use in space analog missions. By outlining past and current efforts in space farming, this study introduces the SpaCEA Cabinet using BRIDGES framework, establishing a context for reproducible experiments and innovation in plant growth systems. The SpaCEA cabinets can either be delivered in flat packs or assembled on-site, employing cutting-edge methods like 3-D printing and laser cutting. The main objective is to assess how effectively these structures foster crop growth within analog environments while replicating conditions crucial for space exploration. Employing a multi-faceted approach encompassing technical and qualitative dimensions, this project integrates a qualitative investigation where representatives managing analog stations and analog astronauts will partake in interviews and questionnaires to discern specific requirements and challenges within these environments. Insights gained from these engagements will significantly define the final design parameters of updated SpaCEA plant growth cabinets. The practical applicability of these cabinets emphasizes ease of assembly and transportation, addressing the inherent spatial and logistical constraints associated with space missions. Furthermore, the BRIDGES framework ensures the standardization of hardware, software, and data-gathering elements within a unified structure, which utilizes cutting-edge manufacturing technologies for the prototyping and deployment of these cabinets. The anticipated outcomes of this research include the identification of key design considerations and technical specifications for plant growth cabinets tailored to space farming analog systems. This research is poised to contribute valuable knowledge to sustainable space exploration through the development of interoperable plant growth systems for analog environments, advancing research in space crop cultivation which will make up part of a larger bioregenerative life support system.

Advanced Life Support↗

Sustainable Crop Cultivation in Space Analogs: A BRIDGES Methodology Perspective Through SpaCEA

Sustainable crop cultivation in space holds paramount significance for the support of life in future long-duration missions. This research explores the development and integration of innovative low-cost proof-of-concept (LC-POC) plant growth cabinets tailored for use in space analog missions. By outlining past and current efforts in space farming, this study introduces the SpaCEA Cabinet using BRIDGES framework, establishing a context for reproducible experiments and innovation in plant growth systems. The SpaCEA cabinets can either be delivered in flat packs or assembled on-site, employing cutting-edge methods like 3-D printing and laser cutting. The main objective is to assess how effectively these structures foster crop growth within analog environments while replicating conditions crucial for space exploration. Employing a multi-faceted approach encompassing technical and qualitative dimensions, this project integrates a qualitative investigation where representatives managing analog stations and analog astronauts will partake in interviews and questionnaires to discern specific requirements and challenges within these environments. Insights gained from these engagements will significantly define the final design parameters of updated SpaCEA plant growth cabinets. The practical applicability of these cabinets emphasizes ease of assembly and transportation, addressing the inherent spatial and logistical constraints associated with space missions. Furthermore, the BRIDGES framework ensures the standardization of hardware, software, and data-gathering elements within a unified structure, which utilizes cutting-edge manufacturing technologies for the prototyping and deployment of these cabinets. The anticipated outcomes of this research include the identification of key design considerations and technical specifications for plant growth cabinets tailored to space farming analog systems. This research is poised to contribute valuable knowledge to sustainable space exploration through the development of interoperable plant growth systems for analog environments, advancing research in space crop cultivation which will make up part of a larger bioregenerative life support system.

Advanced Life Support↗

Expert Seeker

Expert Seeker is a computer program of the knowledge-management-system (KMS) type that falls within the category of expertise-locator systems. The main goal of the KMS system implemented by Expert Seeker is to organize and distribute knowledge of who are the domain experts within and without a given institution, company, or other organization. The intent in developing this KMS was to enable the re-use of organizational knowledge and provide a methodology for querying existing information (including structured, semistructured, and unstructured information) in a way that could help identify organizational experts. More specifically, Expert Seeker was developed to make it possible, by use of an intranet, to do any or all of the following: Assist an employee in identifying who has the skills needed for specific projects and to determine whether the experts so identified are available. Assist managers in identifying employees who may need training opportunities. Assist managers in determining what expertise is lost when employees retire or otherwise leave. Facilitate the development of new ways of identifying opportunities for innovation and minimization of duplicated efforts. Assist employees in achieving competitive advantages through the application of knowledge-management concepts and related systems. Assist external organizations in requesting speakers for specific engagements or determining from whom they might be able to request help via electronic mail. Help foster an environment of collaboration for rapid development in today's environment, in which it is increasingly necessary to assemble teams of experts from government, universities, research laboratories, and industries, to quickly solve problems anytime, anywhere. Make experts more visible. Provide a central repository of information about employees, including information that, heretofore, has typically not been captured by the human-resources systems (e.g., information about past projects, patents, or hobbies). Unify myriad collections of data into Web-enabled repository that could easily be searched for relevant data.

Fernandez, Becerra↗

Show Me the Money! Evaluating A Graduated Incentive Structure to Keep Respondents Engaged Through 101 Surveys in 28 Days

We report the results of a survey test conducted in advance of a series of community response tests (CRTs) to evaluate response to noise from NASA’s X-59 aircraft. The CRTs will require a substantial number of observations to generate a dose response curve for noise exposure and related annoyance levels and the timeframe is limited due to resource and scheduling constraints with an experimental aircraft. Within each CRT area, we will recruit a sample of residents in advance and ask them to fill out a brief survey each time the aircraft passes over. Respondents will be asked to fill out the survey either on the web or as part of an application they are able to download onto their mobile phones. Respondents will be notified each time the plane flies over, asking for their reactions. On many days, respondents will be asked to fill out the survey for multiple flights. Typical incentives are used during the recruitment phase (pre-incentive for a household screener and post-paid for a background survey completed by the selected respondent) and post-paid for an end of study survey. To improve response rates over such a demanding survey schedule (101 surveys in 28 days) we will implement a weekly incentive based upon participation rates, with higher incentives for greater participation and increasing rates each week. The survey test will follow the proposed methodology of the CRTs. We will report on the participation rates by incentive amount and the effectiveness of the incentive structure in obtaining and maintaining response rates over the 4 weeks. We will examine how quickly participation fades over the 4-week period and consider whether the incentive schedule could be improved by altering the distribution of payments. Finally, we will compare how these rates varied across web and app respondents. We will use the results of this work to confirm or improve the design of the CRTs, ensuring the collection of data needed by NASA to evaluate the impact of this innovative technology.

incentives↗

Integration of magnetic bearings in the design of advanced gas turbine engines

Active magnetic bearings provide revolutionary advantages for gas turbine engine rotor support. These advantages include tremendously improved vibration and stability characteristics, reduced power loss, improved reliability, fault-tolerance, and greatly extended bearing service life. The marriage of these advantages with innovative structural network design and advanced materials utilization will permit major increases in thrust to weight performance and structural efficiency for future gas turbine engines. However, obtaining the maximum payoff requires two key ingredients. The first key ingredient is the use of modern magnetic bearing technologies such as innovative digital control techniques, high-density power electronics, high-density magnetic actuators, fault-tolerant system architecture, and electronic (sensorless) position estimation. This paper describes these technologies. The second key ingredient is to go beyond the simple replacement of rolling element bearings with magnetic bearings by incorporating magnetic bearings as an integral part of the overall engine design. This is analogous to the proper approach to designing with composites, whereby the designer tailors the geometry and load carrying function of the structural system or component for the composite instead of simply substituting composites in a design originally intended for metal material. This paper describes methodologies for the design integration of magnetic bearings in gas turbine engines.

Storace, Albert F.↗