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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 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Transitioning from Simulation to Reality: Applying Chatter Detection Models to Real-World Machining Data

Chatter, a self-excited vibration phenomenon, is a critical challenge in high-speed machining operations, affecting tool life, product surface quality, and overall process efficiency. While machine learning models trained on simulated data have shown promise in detecting chatter, their real-world applicability remains uncertain due to discrepancies between simulated and actual machining environments. The primary goal of this study is to bridge the gap between simulation-based machine learning models and real-world applications by developing and validating a Random Forest-based chatter detection system. This research focuses on improving manufacturing efficiency through reliable chatter detection by integrating Operational Modal Analysis (OMA), Receptance Coupling Substructure Analysis (RCSA), and Transfer Learning (TL). The study applies a Random Forest classification model trained on over 140,000 simulated machining datasets, incorporating techniques like Operational Modal Analysis (OMA), Receptance Coupling Substructure Analysis (RCSA), and Transfer Learning (TL) to adapt the model for real-world operational data. The model is validated against 1600 real-world machining datasets, achieving an accuracy of 86.1%, with strong precision and recall scores. The results demonstrate the model’s robustness and potential for practical implementation in industrial settings, highlighting challenges such as sensor noise and variability in machining conditions. This work advances the use of predictive analytics in machining processes, offering a data-driven solution to improve manufacturing efficiency through more reliable chatter detection.

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DOE OSTI2024

Chatter detection in simulated machining data: a simple refined approach to vibration data

Vibration monitoring is a critical aspect of assessing the health and performance of machinery and industrial processes. This study explores the application of machine learning techniques, specifically the Random Forest (RF) classification model, to predict and classify chatter—a detrimental self-excited vibration phenomenon—during machining operations. While sophisticated methods have been employed to address chatter, this research investigates the efficacy of a novel approach to an RF model. The study leverages simulated vibration data, bypassing resource-intensive real-world data collection, to develop a versatile chatter detection model applicable across diverse machining configurations. The feature extraction process combines time-series features and Fast Fourier Transform (FFT) data features, streamlining the model while addressing challenges posed by feature selection. By focusing on the RF model’s simplicity and efficiency, this research advances chatter detection techniques, offering a practical tool with improved generalizability, computational efficiency, and ease of interpretation. The study demonstrates that innovation can reside in simplicity, opening avenues for wider applicability and accelerated progress in the machining industry.

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NASA NTRS1970

The use of the chatter mode in self-adaptive systems

Chatter mode is used advantageously if the ideal model dynamics is described by a switching function, the chatter mode is reached quickly and then sustained, the chatter frequency is reduced, and any zero in the plant transfer function is cancelled.

Yasui, S.↗
NASA NTRS1974

An investigation of chatter and tool wear when machining titanium

The low thermal conductivity of titanium, together with the low contact area between chip and tool and the unusually high chip velocities, gives rise to high tool tip temperatures and accelerated tool wear. Machining speeds have to be considerably reduced to avoid these high temperatures with a consequential loss of productivity. Restoring this lost productivity involves increasing other machining variables, such as feed and depth-of-cut, and can lead to another machining problem commonly known as chatter. This work is to acquaint users with these problems, to examine the variables that may be encountered when machining a material like titanium, and to advise the machine tool user on how to maximize the output from the machines and tooling available to him. Recommendations are made on ways of improving tolerances, reducing machine tool instability or chatter, and improving productivity. New tool materials, tool coatings, and coolants are reviewed and their relevance examined when machining titanium.

Sutherland, I. A.↗
NASA NTRS1991

Experimental investigations of the effects of cutting angle on chattering of a flexible manipulator

When a machine tool is mounted at the tip of a robotic manipulator, the manipulator becomes more flexible (the natural frequencies are lowered). Moreover, for a given flexible manipulator, its compliance will be different depending on feedback gains, configurations, and direction of interest. Here, the compliance of a manipulator is derived analytically, and its magnitude is represented as a compliance ellipsoid. Then, using a two-link flexible manipulator with an abrasive cut off saw, the experimental investigation shows that the chattering varies with the saw cutting angle due to different compliance. The main work is devoted to finding a desirable cutting angle which reduces the chattering.

Lew, J.↗
NASA NTRS1999

Chattering-Free Sliding Mode Control with Unmodeled Dynamics

Sliding mode control systems are valued for their robust accommodation of uncertainties and their ability to reject disturbances. In this paper, a design methodology is proposed to eliminate the chattering phenomenon affecting sliding mode controlled plants with input unmodeled actuator dynamics of second order or greater. The proposed controller design is based on the relative degrees of the plant and the unmodeled actuator dynamics and the ranges of the uncertainties of the plant and actuator. The controller utilizes the pass filter characteristics of the physical actuating device to provide a smoothing effect on the discontinuous control signal rather than introducing any artificial dynamics into the controller design thus eliminating chattering in the system's output response.

Krupp, Don↗
NASA NTRS1971

Chatter-free check valve - A concept

Valve head moves in spiral motion away from seat. Motion is controlled by travel of pin along spiral groove in valve guide. Clearances between pin and groove permit free motion of valve, but effectively dampen vibration and chattering.

Dunbar, J. E.↗
NASA NTRS2016

Friction Pull Plug and Material Configuration for Anti-Chatter Friction Pull Plug Weld

A friction pull plug is provided for use in forming a plug weld in a hole in a material. The friction pull plug includes a shank and a series of three frustoconical sections. The relative sizes of the sections assure that a central one of the sections defines the initial contact point between the hole's sides. The angle defined by the central one of the sections reduces or eliminates chatter as the plug is pulled into the hole.

Littell, Justin Anderson↗
NASA NTRS1971

Improved relay chatter detector

Detector provides go/no-go sensing of momentary relay or contact opening during vibration testing. Device compares duration of unwanted openings to calibrated standard and lights indicator if standard is exceeded. Stability and reliability are higher than in any other comparable device.

Reynolds, R. K.↗
NASA NTRS1982

Wire-Wrap Chatter Detector

Monitoring circuit responds to changes in resistance as little as 0.1 ohm. Has been used to detect defective wire-wrap connections during thermal and vibration tests. Defect is indicated to operator by light-emitting diode and by increase in count on a two-digit display.

Fisch, G. Z.↗
DOE OSTI2024

A data-driven framework for predicting machining stability: employing simulated data, operational modal analysis, and enhanced transfer learning

Chatter, a self-excited vibration phenomenon, presents a significant challenge in machining operations, particularly in high-speed milling, where it can degrade tool life, reduce material removal efficiency, and compromise workpiece quality. Addressing this challenge requires a reliable predictive model that can accommodate the complex dynamics of various machining scenarios. This study introduces a novel, data-driven approach to predicting machining stability, leveraging over 140,000 simulated datasets and employing advanced techniques such as operational modal analysis (OMA), enhanced transfer learning (TL), and receptance coupling substructure analysis (RCSA). By integrating these methodologies, the framework effectively classifies and predicts chatter across diverse operational modes, achieving robust and accurate outcomes. Our model utilizes a Random Forest (RF) classifier trained with the comprehensive dataset, which demonstrates substantial improvements in both predictive accuracy and robustness. Specifically, the RF model achieved an accuracy rate of 85%, an area under the curve (AUC) of 0.90, and an F1 score of 0.88, underscoring its capability to adapt to varying machining configurations. These results highlight the framework’s potential to enhance operational efficiency and machining quality by providing reliable chatter predictions across a broad range of machining parameters. In conclusion, this research thus offers a significant advancement in predictive maintenance for machining processes, enabling more stable and efficient manufacturing operations.

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NASA NTRS1989

Feasibility of reduced gravity experiments involving quiescent, uniform particle cloud combustion

The study of combustible particle clouds is of fundamental scientific interest as well as a practical concern. The principal scientific interests are the characteristic combustion properties, especially flame structure, propagation rates, stability limits, and the effects of stoichiometry, particle type, transport phenomena, and nonadiabatic processes on these properties. The feasibility tests for the particle cloud combustion experiment (PCCE) were performed in reduced gravity in the following stages: (1) fuel particles were mixed into cloud form inside a flammability tube; (2) when the concentration of particles in the cloud was sufficiently uniform, the particle motion was allowed to decay toward quiescence; (3) an igniter was energized which both opened one end of the tube and ignited the suspended particle cloud; and (4) the flame proceeded down the tube length, with its position and characteristic features being photographed by high-speed cameras. Gravitational settling and buoyancy effects were minimized because of the reduced gravity enviroment in the NASA Lewis drop towers and aircraft. Feasibility was shown as quasi-steady flame propagation which was observed for fuel-rich mixtures. Of greatest scientific interest is the finding that for near-stoichiometric mixtures, a new mode of flame propagation was observed, now called a chattering flame. These flames did not propagate steadily through the tube. Chattering modes of flame propagation are not expected to display extinction limits that are the same as those for acoustically undisturbed, uniform, quiescent clouds. A low concentration of fuel particles, uniformly distributed in a volume, may not be flammable but may be made flammable, as was observed, through induced segregation processes. A theory was developed which showed that chattering flame propagation was controlled by radiation from combustion products which heated the successive discrete laminae sufficiently to cause autoignition.

Ross, Howard D.↗
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.

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DOE OSTI2025

Optimization of an aerostructural machining process using physics-guided Bayesian stability modelling

Existing algorithms for predicting milling chatter have not been widely adopted in industry since they require specialized instruments to measure the stability inputs. This study describes how the machining process for a meter-scale aluminum aerostructure was optimized using a physics-guided Bayesian stability model. The study was performed in collaboration with an industrial partner on production machines to evaluate the practicality of the proposed method under real-world conditions. For each cutting tool, the Bayesian approach automatically selected a small number of cutting tests, which were monitored using a microphone to observe the chatter frequency. The algorithm learned the system dynamics, cutting forces, and stability map from these test results. A novel algorithm for predicting tool bending stress was incorporated into the test selection algorithm to avoid tool breakage. On average, each set of optimized cutting parameters required less than six tests to identify and were 97% more productive than baseline parameters from the cutting tool manufacturer. The machining program was then further optimized using commercial feedrate scheduling software to remove cutting force spikes and reduce air cutting time. Five components were machined using the optimized process. These results demonstrate the potential for physics-guided Bayesian models to improve productivity in industrial settings.

Cornelius, Aaron [UT Knoxville]↗
NASA NTRS1983

Application of tire dynamics to aircraft landing gear design analysis

The tire plays a key part in many analyses used for design of aircraft landing gear. Examples include structural design of wheels, landing gear shimmy, brake whirl, chatter and squeal, complex combination of chatter and shimmy on main landing gear (MLG) systems, anti-skid performance, gear walk, and rough terrain loads and performance. Tire parameters needed in the various analyses are discussed. Two tire models are discussed for shimmy analysis, the modified Moreland approach and the von Schlippe-Dietrich approach. It is shown that the Moreland model can be derived from the Von Schlippe-Dietrich model by certain approximations. The remaining analysis areas are discussed in general terms and the tire parameters needed for each are identified. Accurate tire data allows more accurate design analysis and the correct prediction of dynamic performance of aircraft landing gear.

Black, R. J.↗
NASA NTRS2003

Thruster Limitation Consideration for Formation Flight Control

Physical constraints of any real system can have a drastic effect on its performance. Some of the more recognized constraints are actuator and sensor saturation and bandwidth, power consumption, sampling rate (sensor and control-loop) and computation limits. These constraints can degrade system s performance, such as settling time, overshoot, rising time, and stability margins. In order to address these issues, researchers have investigated the use of robust and nonlinear controllers that can incorporate uncertainty and constraints into a controller design. For instance, uncertainties can be addressed in the synthesis model used in such algorithms as H(sub infinity), or mu. There is a significant amount of literature addressing this type of problem. However, there is one constraint that has not often been considered; that is, actuator authority resolution. In this work, thruster resolution and controller schemes to compensate for this effect are investigated for position and attitude control of a Low Earth Orbit formation flight system. In many academic problems, actuators are assumed to have infinite resolution. In real system applications, such as formation flight systems, the system actuators will not have infinite resolution. High-precision formation flying requires the relative position and the relative attitude to be controlled on the order of millimeters and arc-seconds, respectively. Therefore, the minimum force resolution is a significant concern in this application. Without the sufficient actuator resolution, the system may be unable to attain the required pointing and position precision control. Furthermore, fuel may be wasted due to high-frequency chattering phenomena when attempting to provide a fine control with inadequate actuators. To address this issue, a Sliding Mode Controller is developed along with the boundary Layer Control to provide the best control resolution constraints. A Genetic algorithm is used to optimize the controller parameters according to the states error and fuel consumption criterion. The tradeoffs and effects of the minimum force limitation on performance are studied and compared to the case without the limitation. Furthermore, two methods are proposed to reduce chattering and improve precision.

Yunjun Xu↗
DOE OSTI2024

Structure preserving and energy dissipative contact approaches for implicit dynamics

In this work, several structure preserving and energy dissipative contact approaches are proposed and evaluated. The time integration schemes considered are general with regard to the version of constraint type, but here the emphasis was on mortar contact. The proposed mortar contact approach conserves both linear and angular momentum for mortar contact in a novel way. The proposed time integration scheme can conserve energy or provide strict contact dissipation. In addition, the proposed scheme enforces both gap constraints and gap velocity constraints (i.e., persistency). Using a midstep time integrator often causes energy dissipation during initial impact, here this energy can be recovered in a novel way. Enforcing the gap velocity constraint mitigates the contact chatter of the contact pressure and nodes in many problems. Whereas some approaches enforce the persistency condition and gap constraints simultaneously during the solution of the equations of motion (EOM) requiring multipliers for both constraints included in the equation set, here the gap constraint is solved through the equations of motion and the persistency condition is satisfied in the time integration scheme by the velocity update after the equations of motion. It is shown that this approach is strictly dissipative in that a plastic contact condition can be achieved. Analogous to a coefficient of restitution for rigid bodies, any dissipated energy can then be returned upon release if energy conservation is desired. Structure preserving methods are good for long-time dynamics simulations and energy conserving and strictly dissipative methods can overcome stability issues associated with standard time integration algorithms such as the Newmark method.

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