Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “VIBRATION TESTING MACHINE”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 91 records · Page 5
All sourcesNASA NTRSDOE OSTI
NASA NTRS1986

Ultrasonic level sensors for liquids under high pressure

An ultrasonic level sensor of novel design continuously measures the level of a liquid subjected to a high pressure (up to about 40 MPa), as is sometimes required for the effective transfer of the liquid. The sensor operates as a composite resonator fabricated from a standard high-pressure plug. A flat-bottom hole is machined into the plug along its center line. An ultrasonic transducer is bonded rigidly to the interior surface of the bottom wall, while the exterior surface is in contact with the liquid. Although the bottom wall is designed to satisfy the pressure code, it is still sufficiently thin to permit ready excitation of the axisymmetric plate modes of vibration. The liquid level is measured by a conventional pulse-echo technique. A prototype sensor was tested successfully in a 2300-l water vessel at pressures up to about 37 MPa. A spectral analysis of the transmitted pulse reveals that the flexural, extensional, thickness-shear, and radial plate modes are excited into vibration, but none of these appears to be significantly affected by the pressurization of the liquid.

Zuckerwar, A. J.↗
DOE OSTI2021

Characterization of Embedded Sensors in Stainless Steel Test Articles and Design/Planning for MAGNET Testing

The nuclear industry is pursuing microreactors that can be factory assembled and deployed to remote regions for reliable power generation. One class of microreactors uses a monolithic metal core block coupled to heat pipes for heat rejection, which results in significant thermal stresses in the monolithic structures. This work describes the initial characterization and test plan for evaluating stainless steel test articles fabricated with embedded sensors for measuring heat pipe performance limits, as well as spatially distributed temperatures and strains during electrically heated thermal testing. The electrically heated testing will be performed in the non-nuclear Microreactor Agile Non-Nuclear Testbed and Single Primary Heat Extraction and Removal Emulator facilities located at Idaho National Laboratory. The goals of these tests are to (1) accurately monitor temperature and strain distributions that result from differential thermal expansion in the test articles and (2) quantify heat rejection limits of heat pipes as a function of operating temperature and working fluid during steady-state and transient operations. More generally, the ability to monitor component and system health during microreactor operation is attractive for providing a high sensor density to inform a limited number of microreactor operators to ultimately reduce operation and maintenance costs and move toward semi-autonomous operation. This report discusses the characterization of embedded thermocouples and fiber optic sensors in relevant test articles, including cylindrical pipes and hexagonal monolithic test articles for heat pipe-based reactors. The sensors were embedded by placing them in machined channels and then building up additional material by using ultrasonic additive manufacturing (UAM). UAM is a solid-state welding process that uses downward pressure and a lateral scrubbing motion to bond thin metal foils to a base material layer by layer. The ultrasonic welding process relies on the plastic deformation of the metal—as opposed to typical melting and solidification—to break oxide scales and bond the metal layers. The characterization of these embedded sensors included evaluating fiber optic signal attenuation, observing residual strain in the fibers, investigating microstructural and mechanical aspects, and demonstrating the sensors under various thermal loads and acoustic vibrations. Post-embedding characterization showed a fine grain structure (<1 μm) near the interfaces of the bonded foils as a result of severe deformation from the welding process. A large increase in hardness was observed at the foil interfaces and the fiber/matrix interface compared with the bulk matrix. Even when compared with the SS304 interfaces, the higher hardness observed around the embedded fiber suggests a higher degree of deformation due to the soft metal coating around the silica fiber core. The distributed fiber-optic temperature sensors and embedded thermocouples reliably measured temperature distributions during steady-state and transient thermal testing. The embedded fiber-optic sensors reliably measured strain during both transient and steady-state testing and properly identified resonant frequencies during acoustic testing.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
NASA NTRS1973

Some questions of an optimum probability synthesis of dynamic metalworking machine systems

Attempts were made to develop a dynamic metal working machine tool system using probability information on external factors and independent disturbances of the parameters. The problem was optimized in two stages: (1) creation of mathematical models under conditions determined by input influences, and (2) processing the results of calculations obtained on such models. Data were obtained on the patterns of distribution of dynamic quality characteristics of the tool, vibration frequencies and amplitudes, attenuation coefficients, and duration of a transition process. These data were obtained using a digital computer, statistical test methods, or logical possibility trees.

Dobrynin, S. A.↗
DOE OSTI2022

A Feasibility Study on Use of an Accelerometer to Measure the Dynamic Forces in Turning

Metal cutting is a highly dynamic process that generates continuously varying forces. Measurement of these forces is essential to characterizing a cutting process and to fully utilize the machine tool. A force dynamometer is often used to measure these varying forces; however, it is limited by the natural frequency of the sensor and can sometimes be hard to set up on a machine. Therefore, this study aims to estimate the dynamic component of the cutting force using an accelerometer placed directly below the cutting edge. The placement of the sensor helps achieving better signal to noise ratio (S/N). The cutting tool is modelled as a single degree of freedom (SDOF) system relative to the workpiece and dynamic loads are experimentally simulated on it. The measured acceleration is numerically integrated to obtain velocity and deflection, which along with the natural frequency (ω n ) and damping ratio (ζ), is used to predict the dynamic load using the system equation. The dynamic forces tested over a wide range of frequencies, show good agreement with the data from simultaneous dynamometer measurement and the force estimated using the proposed method. The study shows the feasibility of this method in a real cutting scenario and the capability to apply it to a multi DOF system. One major limitation is the inability to capture the static or quasi-static component of the cutting force.

Cutting vibrations↗
NASA NTRS1983

A magnetically suspended linearly driven cryogenic refrigerator

This paper described a novel Stirling cycle cryogenic refrigerator which was designed, fabricated and successfully tested at Philips Laboratories. The prominent features of the machine are an electro-magnetic bearing system, a pair of moving magnet linear motors, and clearance seals with a 25 mu m radial gap. The all-metal and ceramic construction eliminates long-term organic contamination of the helium working fluid. The axial positions of the piston and displacer are electronically controlled, permitting independent adjustment of the amplitude of each and their relative phase relationship during operation. A simple passive counterbalance reduces axial vibrations. The design of the refrigerator system components is discussed and a comparison is made between performance estimates and measured results.

Stolfi, F.↗
NASA NTRS1983

Evaluation of human exposure to the noise from large wind turbine generators

The human perception of a nuisance level of noise was quantified in tests and attempts were made to define criteria for acceptable sound levels from wind turbines. Comparisons were made between the sound necessary to cause building vibration, which occurred near the Mod-1 wind turbine, and human perception thresholds for building noise and building vibration. Thresholds were measured for both broadband and impulsive noise, with the finding that noise in the 500-2000 Hz region, and impulses with a 1 Hz fundamental, were most noticeable. Curves were developed for matching a receiver location with expected acoustic output from a machine to determine if the sound levels were offensive. In any case, further data from operating machines are required before definitive criteria can be established.

Shepherd, K. P.↗
DOE OSTI2023

Explainable AI (XAI)-driven vibration sensing scheme for surface quality monitoring in a smart surface grinding process

Local Interpretable and Model-agnostic Explanation (LIME), an explainable artificial intelligence (XAI) approach is adapted to identify the globally important time-frequency bands for predicting average surface roughness (Ra) in a smart grinding process. The smart grinding setup consisted of a Supertech CNC precision surface grinding machine, instrumented with a Dytran piezoelectric accelerometer attached to the tailstock quill along the tangential direction (Y-axis). For every grinding pass, vibration signatures were captured, and the ground truth surface roughness values were recorded using a Mahr Marsurf M300C portable surface roughness profilometer. The roughness values ranged from 0.06 to 0.14 microns over the complete set of experiments. Time-frequency domain spectrogram frames were extracted for each of the vibration signals collected during the grinding process. Convolutional Neural Networks (CNNs) were modeled to predict the surface roughness based on these spectrogram frames and their image augmentations. The best CNN model was able to predict the roughness values with an overall R2-score of 0.95, training R2-score of 0.99, and testing R2-score of 0.81 with only 80 sets of vibration signals corresponding to 4 experiments with 20 trials each. Although the data size is not large enough to guarantee such performance metrics in real-world scenarios, one can extract statistically consistent explanations underlying the relationships these complex deep learning models capture. Further, the LIME methodology was implemented on the developed surface roughness CNN model to identify the important time-frequency bands (i.e., the superpixels of a spectrogram) influencing the predictions. Based on the identified important regions on the spectrogram frames, the corresponding frequency characteristics were determined that influence the surface roughness predictions. The important frequency range based on LIME results was approximately 11.7 to 19.1 kHz. The power of XAI was demonstrated by cutting down the sampling rate from 160 kHz to 30, 20, 10, and 5 kHz based on the important frequency range and considering Nyquist criteria. Separate CNN models were developed for these ranges by only extracting time-frequency contents below their corresponding Nyquist cut-offs. A proper data acquisition strategy is proposed by comparing the model performances to argue the selection of a sufficient sampling rate to capture the grinding process successfully and robustly.

42 ENGINEERING↗
DOE OSTI2023

Reprint of: Explainable AI (XAI)-driven vibration sensing scheme for surface quality monitoring in a smart surface grinding process

Local Interpretable and Model-agnostic Explanation (LIME), an explainable artificial intelligence (XAI) approach is adapted to identify the globally important time-frequency bands for predicting average surface roughness (Ra) in a smart grinding process. The smart grinding setup consisted of a Supertech CNC precision surface grinding machine, instrumented with a Dytran piezoelectric accelerometer attached to the tailstock quill along the tangential direction (Y-axis). For every grinding pass, vibration signatures were captured, and the ground truth surface roughness values were recorded using a Mahr Marsurf M300C portable surface roughness profilometer. The roughness values ranged from 0.06 to 0.14 microns over the complete set of experiments. Time-frequency domain spectrogram frames were extracted for each of the vibration signals collected during the grinding process. Convolutional Neural Networks (CNNs) were modeled to predict the surface roughness based on these spectrogram frames and their image augmentations. The best CNN model was able to predict the roughness values with an overall R2-score of 0.95, training R2-score of 0.99, and testing R2-score of 0.81 with only 80 sets of vibration signals corresponding to 4 experiments with 20 trials each. Although the data size is not large enough to guarantee such performance metrics in real-world scenarios, one can extract statistically consistent explanations underlying the relationships these complex deep learning models capture. Further, the LIME methodology was implemented on the developed surface roughness CNN model to identify the important time-frequency bands (i.e., the superpixels of a spectrogram) influencing the predictions. Based on the identified important regions on the spectrogram frames, the corresponding frequency characteristics were determined that influence the surface roughness predictions. The important frequency range based on LIME results was approximately 11.7 to 19.1 kHz. The power of XAI was demonstrated by cutting down the sampling rate from 160 kHz to 30, 20, 10, and 5 kHz based on the important frequency range and considering Nyquist criteria. Separate CNN models were developed for these ranges by only extracting time-frequency contents below their corresponding Nyquist cut-offs. A proper data acquisition strategy is proposed by comparing the model performances to argue the selection of a sufficient sampling rate to capture the grinding process successfully and robustly.

47 OTHER INSTRUMENTATION↗
DOE OSTI2024

Coupled Aero-Hydro-Mechanical Hybrid Simulation Testing of Offshore Wind Turbines Subjected to Operational and Extreme Loading Conditions

Understanding the response of the Offshore Wind Turbine (OWT) subjected to realistic applied loads requires modeling the whole structure including its soil-foundation system. This requires unique and innovative testing facilities. OWT systems experience cyclic and dynamic loading due to wind, wave, current, rotor vibrations (i.e., 1P load) and vibrations caused by the blade shadowing effects (2P/3P loads). These loads are complicated in nature and have varying amplitudes, frequencies, and directions. Investigating the response of the entire OWT system including the soil-foundation system under these complex loading conditions, requires: (1) full understanding of the loading characteristics including: the power take-off mechanical load (1P and 3P), and areo- and hydrodynamic loads that the OWT system is subjected to; (2) testing facility with unique multidirectional loading capabilities that allows for simultaneous application of realistic wind, wave and machine loads, axial gravity loads, and induced overturning moments; and (3) unique and cost-effective testing techniques that allow for accurate analysis of the overall response of the OWT system under realistic conditions such as: Real-Time Hybrid Simulation (RTHS).

17 WIND ENERGY↗
DOE OSTI2025

A Multi-Sensor Approach for Measuring Bird and Bat Collisions with Offshore Wind Turbines (Final Technical Report)

Collision of birds and bats with wind turbines is a conservation concern for both land-based and offshore wind projects. The fatality rates of birds and bats at land-based turbines are well documented. The measurement strategies on land focus on finding carcasses following collision, estimating the number of carcasses missed through searcher efficiency, carcass persistence trials and carcass fall distributions, and modeling statistically robust fatality rates. Few technologies have been developed to monitor offshore bird and bat collisions, and many that have been developed focused on detecting collisions with large birds. The few studies that have attempted to document collisions at offshore turbines do not account for smaller bodied animals or for collisions that might be missed, which prevents the calculation of statistically robust fatality rates. The overall goal of this report, A Multi-Sensor Approach for Measuring Bird and Bat Collisions with Offshore Wind Turbines (Project), was to develop an effective multi-sensor system for quantifying bird and bat collision rates, specifically for offshore wind facilities. The Project goal and resulting automated collision detection system was achieved through two major technological advancements: 1) refining The Netherlands Organisation for Applied Scientific Research’s (TNO’s) existing WT-Bird® vibration sensing system, that had successfully detected large bird collisions during daytime, to allow for improved detection of smaller birds and bats during both daytime and nighttime hours and 2) improving image processing systems and developing and integrating machine learning algorithms to automatically detect and classify small and large bird and bat collisions with offshore turbines. This final technical report (FTR) summarizes Methods , Results , Conclusions , and Lessons Learned during each of the five Tasks identified for this research and development effort. This FTR includes summaries of the following: Task 1. Initial Engineering Tests to Improve WT-Bird® Task 2. Installation of WT‐Bird® on a Utility-scale Turbine at the National Wind Technology Center – National Renewable Energy Laboratory Task 3. Field Tests and Refinement of the Object Detection System Task 4. Validation of WT-Bird® on a Land-based Turbine Task 5. Preparation for the Implementation of WT-Bird® on an Offshore Turbine. This research and development effort documented successful improvement of the WT Bird® collision detection system to detect small birds and bats, and WT-Bird® is the first collision detection system to validate results compared to land-based post-construction monitoring. The collision trials provide estimates of missed targets that can be used to estimate fatality rates, a significant improvement relative to other offshore collision monitoring systems. Advances were made in developing an edge-processing solution to reduce data storage requirements, which is important if the system is deployed for long periods of time at offshore turbines. The improved WT-Bird® system also provides an important option for wind operators on land or offshore who need to document specific details about when collisions occur, particularly efforts to further research on bat impact minimization, or when standard fatality searches are impractical (e.g. offshore) or inadequate (e.g. challenging locations on land).

17 WIND ENERGY↗
NASA NTRS2003

TF41 Engine Fan Disk Seeded Fault Crack Propagation Test

Uncontained engine failures, although rare in occurrence, can have a catastrophic effect on aircraft performance and safety. Engine disk cracks can eventually lead to these type of failures. A number of techniques to detect engine disk cracks have been developed in recent years. However, these technologies have only been validated by disk spin pit tests, not actual engine tests. Due to this, a project was established to perform seeded fault engine tests on a TF41 engine disk fan. A defect was machined in the first stage fan disk of a TF41 engine. The disk was run in a spin pit to initiate a crack. Once initiated, the disk was run in an actual engine test facility. The engine was cycled by a number of start and stops with the goal of propagating the crack to disk burst through low cycle fatigue. Various crack detection techniques were installed on the engine and run real-time during the test to validate their abilities to detect disk cracks. These techniques were based on methods such as change in mass imbalance using vibration or shaft displacement, change in blade position, acoustic emission, and torsional resonance. At the completion of 4474 test cycles, the crack in the TF41 disk was determined to have grown approximately 0.025 inches. This was far less the predicted crack growth based on a fracture mechanics analysis and finite element stress analysis.

Lewicki, David G.↗
NASA NTRS2012

Hybrid Gear Preliminary Results-Application of Composites to Dynamic Mechanical Components

Composite spur gears were fabricated and then tested at NASA Glenn Research Center. The composite material served as the web of the gear between the gear teeth and a metallic hub for mounting to the torque-applying shaft. The composite web was bonded only to the inner and outer hexagonal features that were machined from an initially all-metallic aerospace quality spur gear. The Hybrid Gear was tested against an all-steel gear and against a mating Hybrid Gear. As a result of the composite to metal fabrication process used, the concentricity of the gears were reduced from their initial high-precision value. Regardless of the concentricity error, the hybrid gears operated successfully for over 300 million cycles at 10000 rpm and 490 in.*lbs torque. Although the design was not optimized for weight, the composite gears were found to be 20% lighter than the all-steel gears. Free vibration modes and vibration/noise tests were also conduct to compare the vibration and damping characteristic of the Hybrid Gear to all-steel gears. The initial results indicate that this type of hybrid design may have a dramatic effect on drive system weight without sacrificing strength.

Handschuh, Robert F.↗
NASA NTRS1990

Vibration analyzer

The invention relates to monitoring circuitry for the real time detection of vibrations of a predetermined frequency and which are greater than a predetermined magnitude. The circuitry produces an instability signal in response to such detection. The circuitry is particularly adapted for detecting instabilities in rocket thrusters, but may find application with other machines such as expensive rotating machinery, or turbines. The monitoring circuitry identifies when vibration signals are present having a predetermined frequency of a multi-frequency vibration signal which has an RMS energy level greater than a predetermined magnitude. It generates an instability signal only if such a vibration signal is identified. The circuitry includes a delay circuit which responds with an alarm signal only if the instability signal continues for a predetermined time period. When used with a rocket thruster, the alarm signal may be used to cut off the thruster if such thruster is being used in flight. If the circuitry is monitoring tests of the thruster, it generates signals to change the thruster operation, for example, from pulse mode to continuous firing to determine if the instability of the thruster is sustained once it is detected.

Bozeman, Richard J., Jr.↗
DOE OSTI2021

A Heterogeneous System for Eagle Detection, Deterrent, and Wildlife Collision Detection for Wind Turbines (Final Technical Report)

This report summarizes the design, implementation, and test of an integrated system for automated detection and deterrence of eagles, with included wind turbine blade strike detection and imaging functionality. A machine learning approach was used in conjunction with a 360° camera system for automated detection and classification of golden eagles. This was developed using footage obtained from trained golden eagles and other raptors, in collaboration with wildlife biologists and professional bird handlers. Oregon State University developed a visual deterrent system, which uses inflatable anthropomorphic sculptures with random, kinetic motion to deter eagles, and conducted limited field testing on live eagles; the deterrent can be triggered by the visual detection of eagles using the vision system. Finally, a multi-sensor module was developed that is mounted at the turbine blade root. This module measures vibration and other motions to detect blade strikes, and an integrated on-blade camera captures an image of any impacting objects. Long-term, this blade strike detection system is intended to support an automatic monitoring and certification system for the eagle detection and deterent system. Independent field testing of each system component is described. Testing of the integrated system on an operational wind turbine was conducted across three separate field tests. This includes multi-day fields tests on a General Electric 1.5MW wind turbine at the National Renewable Energy Laboratory (NREL) National Wind Technology Center (NWTC) in Boulder, CO in October 2018 and July 2019; installation procedures, test procedures, and a summary of collected data are presented. A third multi-day on-turbine field test is also presented, which was performed using a General Electric 1.5MW wind turbine at the North American Wind Research and Training Center (NAWRTC) at Mesalands Community College, Tucumcari, NM in April 2019. Across these field tests, the vision system was demonstrated using unmanned aerial vehicles (UAV), and the eagle classification algorithm was not tested; the visual deterrent system was demonstrated, including automatic, remote deployment following surrogate visual detections; and, multi-sensor on-blade data was recorded across multiple wind turbine operational conditions and through more than 100 surrogate blade strikes using soft projectiles, including the successful demonstration of automatic image capture of striking objects. This data set was also used for offline development and validation of enhanced collision detection algorithms. As summarized in this report, the development and field validation of an integrated detection, deterrent, and blade collision detection system represents a critical proof of concept for future technology development of related detection and deterrent technologies, where both deterrent as well as collision detection recording devices are needed for future siting, monitoring, and operation of wind turbine installations, both onshore and offshore.

17 WIND ENERGY↗
NASA NTRS2003

Novel Engineering and Fabrication Techniques Tested in Low-Noise- Research Fan Blades

A major source of fan noise in commercial turbofan engines is the interaction of the wake from the fan blades with the stationary vanes (stators) directly behind them. The Trailing Edge Blowing (TEB) project team at the NASA Glenn Research Center designed and fabricated new fan blades to study the effects of fan trailing edge blowing as a potential noise-reduction concept. The intent is to fill the rotor wake by supplying air to the rotor blade trailing edge at the proper conditions to minimize the wake deficit, and thus generate less noise. The TEB hardware is designed for the Active Noise Control Fan (ANCF) test rig in Glenn's Aeroacoustic Propulsion Laboratory. For this test, the air is fed from an external supply through the shaft of the rig. It is distributed to the base of each blade through an impeller, where it is forced into a plenum at the core of each blade. In actual engine configuration, air would most likely be bled from the compressor, but only at times when noise is an issue, such as takeoffs and landings. Glenn researchers designed and manufactured the blades in-house, using new techniques and concepts. The skins, which were designed for maximum strength in the directions of highest stress, were molded from multiple layers of carbon fiber. Considerable use was made of rapid prototyping techniques, such as laser sintering. The core was sintered from a lightweight polymer, and the retainer was CNC-machined (computer numerical control machined) from aluminum. All the components were joined with a cold-cure aerospace adhesive. These techniques and processes reduced the overall cost and allowed the new concept to be studied much sooner than would be possible using traditional fabrication methods. Since this test rig did not support the use of blade-monitoring techniques such as strain gauges, extensive bench testing was required to qualify the design. The blades were examined using a variety of methods including holography, pull tests (cyclic and failure), shake tests, rap tests, and nondestructive inspection. Acoustic testing of the ANCF fan using TEB has been ongoing since January of 2001. The fan has completed about 100 hr of testing with no structural, vibrational, or fatigue problems. Far-field acoustic measurements, in-duct mode measurements, precise hot wire surveys, and detailed performance measurements are providing data for evaluating the concept. The far-field noise data show that tone noise was reduced significantly with the initial ANCF TEB fan design. In addition, a significant reduction in unsteady stator loading has been measured, indicating the potential for stator broadband noise reduction. The acoustic benefits will be assessed and important design parameters identified to improve the ability to fully exploit any benefit provided by this technique. On the basis of the success of trailing edge blowing, Glenn plans to continue this research with a higher speed, higher pressure ratio fan operating in an acoustic wind tunnel to simulate flight conditions.

Cunningham, Cameron C.↗
DOE OSTI2022

Magnetic Gears: The Key to Robust, Cost-Effective Hydropower Drivetrains

Based on previous demonstrated success at fabricating 5 and 10 kW scale magnetic gearbox (MGB) prototypes, Emrgy and its partners (the project team) proposed to design and construct a 100 kW scale MGB with a 30:1 gear ratio for the low-head hydro applications. The Statement of Project Objectives included tasks covering: 1) Market Applicability; 2) Technical Metrics; 3) Design (initial); 4) Electromagnetic (EM) Load and Structural Analysis; 5) Modal Analysis; 6) Sealing Design and 7) Final Design during Budget Period 1. Budget Period 2 included tasks covering: 1) Materials Procurement and Test Plan Development; 2) Assembly; and 3) Testing. The Market Applicability study (Task 1) led to a clear conclusion and recommendation toward “Low Head” technologies for maximum market share of both New Stream Reach development as well as powering Non-Powered Dams. The findings of this study also identified the opportunity for a larger scale magnetic gearbox-based drive train as a function of increased torque, as opposed to increased speed. The Technical Metrics Study (Task 2) concluded a horizontal orientation was preferred, examined potential loss mechanisms, concluded that a Halbach Array magnetic design was preferred, established a 30:1 gear ratio as optimal, and established a power rating of 100 kW as optimal. The subsequent initial and final detailed design process included electro-magnetic (EM) load and structural analysis (Task 4), a Modal analysis (for vibration) (Task 5), and a sealing design (Task 6) to assure water impermeability. The final design package (Task 7) included 729 individual parts, 117 unique part numbers, and 15 assemblies. In order to facilitate procurement, the full bill of materials was broken down into several sub-components: 1) custom magnetic parts; 2) custom machined parts; 3) custom casted parts; and 4) commercial off the shelf (COTS) parts. The casted parts were fabricated by Oak Ridge National Laboratory (ORNL) via a Cooperative Research and Development Agreement (CRADA) with Emrgy and funded by the Advanced Manufacturing Office (AMO). The procurement effort (Task 8) ultimately covered three time periods based on challenges encountered in meeting the budgeted cost for the prototype. Following the first effort in the early stages of Budget Period 2 in 2017, a no-cost time extension was granted to seek alternative fabrication and procurement options. The project was re-booted in 2020 based on the new ORNL CRADA that would focus on five (5) of the more difficult and expensive parts using their advanced manufacturing expertise. Procurement efforts for the other custom machined parts resulted in quotations that still exceeded the budget by more than $\$$100k. This was, in part, also due to the concurrent COVID-19 pandemic that caused both supply chain disruptions and labor shortages. As the project continued, pricing and availability degraded further. In Q2 FY’22, it was decided to not proceed with the fabrication of the prototype (Task 9) based on budgetary limitations. Outcomes included a full and detailed design of a 100 kW magnetic gearbox and associated indented bill of materials (BOM) and CAD drawings, a full assembly instruction manual with an associated BOM for materials necessary to support assembly, the fabrication of the double Halbach magnetic array for the rotor/stator system, fabrication of five (5) sand-casted/machined parts (via CRADA with ORNL) and an initial draft of a comprehensive testing plan. The most significant non-outcome was the actual fabrication and testing of the prototype gearbox based on budget limitations. Lessons learned included the need for an Application / Design / Cost trade analysis to better elucidate the cost potential of the MGB in the projected volumes anticipated for future demand. This would better establish the efficacy of the original cost target ($\$$0.80/Watt) and/or the need for reconsideration of designs and applications. Likewise, additional consideration of the prototype nature of the gearbox – single use, short lifetime, etc. - either as a separate exercise or in place of the design process completed, to reduce the cost of the demonstration prototype device. Additionally, project continuity was cited as a significant risk based on the loss of the primary design engineering firm after Budget Period 1. A design analysis exercise was conducted at the conclusion of the project to identify potential areas for cost reduction. One concept considered was the removal of the inner ring of magnets (with associated changes in the outer ring magnets) to enable a horizontal collapse of the design. It was estimated this could reduce cost by 10-25% without impacting performance.

13 HYDRO ENERGY↗
NASA NTRS1996

Quantification of Gear Tooth Damage by Optimal Tracking of Vibration Signatures

This paper presents a technique for quantifying the wear or damage of gear teeth in a transmission system. The procedure developed in this study can be applied as a part of either an onboard machine health-monitoring system or a health diagnostic system used during regular maintenance. As the developed methodology is based on analysis of gearbox vibration under normal operating conditions, no shutdown or special modification of operating parameters is required during the diagnostic process. The process of quantifying the wear or damage of gear teeth requires a set of measured vibration data and a model of the gear mesh dynamics. An optimization problem is formulated to determine the profile of a time-varying mesh stiffness parameter for which the model output approximates the measured data. The resulting stiffness profile is then related to the level of gear tooth wear or damage. The procedure was applied to a data set generated artificially and to another obtained experimentally from a spiral bevel gear test rig. The results demonstrate the utility of the procedure as part of an overall health-monitoring system.

Choy, F. K.↗
DOE OSTI2024

Using GANs to predict milling stability from limited data

Milling is a key manufacturing process that requires the selection of operating parameters that provide efficient performance. However, the presence of chatter, a self-excited vibration causing poor surface finish and potential damage to the machine and cutting tool, makes it challenging to select the appropriate parameters. To predict chatter, stability maps are commonly used, but their generation requires expensive data, making it difficult to employ these maps in industry. Therefore, there is a pressing need for an approach that can accurately predict stability maps using limited experimental data. This study introduces the new Encoder GAN (EGAN) approach based on Generative Adversarial Networks (GANs) that predicts stability maps using limited experimental data. The approach consists of the encoder, generator, and discriminator subnetworks and uses the trained encoder and generator to predict the target stability map. This versatile method can be applied to various tool setups and can accurately predict stability maps with limited experimental data (five to 10 cutting tests) even when there is little information available for unknown parameters. In conclusion, the study evaluates the proposed approach using both numerical data and experiments and demonstrates its superior performance compared to state-of-the-art benchmarks.

42 ENGINEERING↗