Automated In-Process Cure Monitoring of Composite Laminates Using a Guided Wave-Based System With High-Temperature Piezoelectric Transducers
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Tyler B. Hudson↗
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Monitoring cleaning processes and procedures
Process and media for cleaning of corrosion resistant steel tubing for liquid oxygen and pneumatic service
Ellenburg, J. Y.↗
Comparison of simulation modeling and satellite techniques for monitoring ecological processes
In 1985 improvements were made in the world climatic data base for modeling and predictive mapping; in individual process models and the overall carbon-balance models; and in the interface software for mapping the simulation results. Statistical analysis of the data base was begun. In 1986 mapping was shifted to NASA-Goddard. The initial approach involving pattern comparisons was modified to a more statistical approach. A major accomplishment was the expansion and improvement of a global data base of measurements of biomass and primary production, to complement the simulation data. The main accomplishments during 1987 included: production of a master tape with all environmental and satellite data and model results for the 1600 sites; development of a complete mapping system used for the initial color maps comparing annual and monthly patterns of Normalized Difference Vegetation Index (NDVI), actual evapotranspiration, net primary productivity, gross primary productivity, and net ecosystem production; collection of more biosphere measurements for eventual improvement of the biological models; and development of some initial monthly models for primary productivity, based on satellite data.
Box, Elgene O.↗
Progress in the Multijunction Solar Cell Mantech Program
In September, 1995, the joint Wright Laboratory/Phillips Laboratory/NASA Lewis Multijunction Solar Cell Manufacturing Technology (ManTech) Program began to improve multijunction cell performance and scale them up to production size and quantity to support Air Force and commercial satellite programs. The first milestone of the program has been reached and the purpose of this paper is to present the results of the program so far. The objectives of the Multijunction Solar Cell ManTech Program are to increase the GaInP2/GaAs/Ge lot average cell efficiency to 24-26%, increase the cell size to > or equal to 16 sq cm while maintaining high efficiency, and limit the per cell costs to < or equal to 1.15X state of the art GaAs/Ge cells. Advanced manufacturing technology and process control techniques such as in-situ process monitoring and real time process feedback are being used to optimize multijunction solar cell growth processes to achieve these goals. This paper will discuss progress made in Phase I of the program and give an overview of Phase II but will focus on side-by-side testing results collected by Phillips Laboratory and NASA Lewis on Phase I deliverable cells from both vendors. Cell performance, pre- and post radiation, and temperature coefficient results on initial production multijunction solar cells will be presented and discussed. The data shows that this technology meets the objectives of the program, and that, in the interim before a new solar simulation standard becomes widely available, the measurement techniques being used by the major space solar cell manufacturers are providing adequate testing results for solar array design.
Keener, David N.↗
Breaking down barriers in cooperative fault management: Temporal and functional information displays
At the highest level, the fundamental question addressed by this research is how to aid human operators engaged in dynamic fault management. In dynamic fault management there is some underlying dynamic process (an engineered or physiological process referred to as the monitored process - MP) whose state changes over time and whose behavior must be monitored and controlled. In these types of applications (dynamic, real-time systems), a vast array of sensor data is available to provide information on the state of the MP. Faults disturb the MP and diagnosis must be performed in parallel with responses to maintain process integrity and to correct the underlying problem. These situations frequently involve time pressure, multiple interacting goals, high consequences of failure, and multiple interleaved tasks.
Potter, Scott S.↗
Monitoring installation of partially occluded subassemblies in modular construction factories using BIM, ray tracing, and computer vision
Modular and offsite construction methods are being increasingly adopted due to the advantages they offer in terms of project completion time, quality, and energy-efficiency. Despite these advantages, the current state of monitoring systems in modular construction factories highly relies on labor-intensive, subjective, and error-prone observational methods. A large body of research has aimed to automate the monitoring process using an array of sensors, such as IMUs and RFIDs, during the past two decades. Recently, computer vision-based methods have gained increasing interest as a non-intrusive technology to monitor the process inside modular construction factories. However, partial occlusion challenges have impeded their practical application on a large scale. This challenge is specifically important for monitoring the installation of subassemblies since they can obstruct the view of the monitoring camera, especially those that enable long-term monitoring like closed-circuit television (CCTV) fixed-view surveillance cameras. Here, this paper aims to address this challenge by proposing a novel computer vision-based method to monitor the installation of new subassemblies inside modular factories in highly occluded scenes. The proposed methodology identifies the subassemblies in the CCTV video footage using computer vision, analyzes the occlusions using BIM and ray casting techniques, and estimates the progress of assembly by comparing the BIM model with the detected subassemblies in the video. The proposed methodology was successfully validated on surveillance videos captured from a volumetric modular construction factory in the U.S., achieving 93% accuracy in identifying the installation of subassemblies. The results from this research show that the integration of BIM and computer vision is a promising method for monitoring the installation processes inside modular factories under severe occlusion.
97 MATHEMATICS AND COMPUTING↗
Quantifying Temperature Dependence of Pu(IV) Absorbance Spectra for Advanced Online Monitoring of Nuclear Processes
This article presents a systematic study of Pu(IV) absorbance spectral features as a function of temperature to develop an understanding of this parameter’s effect on chemometric models that can be used as online monitoring tools to support nuclear processing. The descriptive and predictive models that provide real-time feedback of these processes are usually constructed with data collected in conditions typical of a laboratory environment, which can differ drastically from a processing environment. To assess the impact of temperature on Pu(IV) absorbance spectra, 11 samples of Pu(IV) were synthesized with varying HNO 3 concentrations ranging from 0.6 to 9.5 M and heated between 15 and 45 °C. Ultraviolet (UV)–visible (vis)–near-infrared (NIR) absorption spectra collected at different HNO 3 concentrations and temperatures revealed that features associated with Pu(IV) are sensitive to temperature at all HNO 3 concentrations and that changes in features depend on HNO 3 concentration. The contributions of temperature and HNO 3 concentration to variation in Pu(IV) spectral features were evaluated using the principal component analysis of spectra that were baseline-corrected with an asymmetric least-squares method. Furthermore, predictive modeling for HNO 3 concentration with partial least-squares regression of UV–vis–NIR spectra highlighted the importance of accounting for temperature in the calibration set to optimize model performance. This methodology constitutes a new, systematic approach to account for the effect of temperature on the absorption spectra of metal ions and is useful for process monitoring applications in many industries.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Effect of threshold parameters on infrared segmentation methods for porosity detection in electron beam powder bed fusion
In-situ process monitoring has seen significant interest in additive manufacturing to address qualification and certification goals. This is especially prevalent in metal powder bed fusion processes such as electron beam powder bed fusion (PBF-EB), with layer-wise infrared imaging being commonly used to detect defects. Here, this work compares two different segmentation methods (static thresholding and statistical thresholding) used for detecting porosity from in-situ infrared imaging data for PBF-EB. Samples were manufactured at a variety of focus offset values to induce porosity. Then, the segmented infrared images were compared to ex-situ X-ray computed tomography scans, which served as a ground-truth reference for objective evaluation. Through this analysis framework, the influential parameters, static threshold and N-value (number of standard deviations above the mean pixel value), respectively, for both image segmentation methods were analyzed and compared for their effects on porosity detection. With optimal parameter settings, the two methods had similar porosity detection performance, but the statistical method performed better under a larger variety of parameter settings.
Infrared imaging↗
A representation for error detection and recovery in robot task plans
A general definition is given of the problem of error detection and recovery in robot assembly systems, and a general representation is developed for dealing with the problem. This invariant representation involves a monitoring process which is concurrent, with one monitor per task plan. A plan hierarchy is discussed, showing how diagnosis and recovery can be handled using the representation.
Lyons, D. M.↗
Correlations Between Porosity, Spatter, and Process Metrics for Powder Bed Fusion Laser Beam Metallic Additive Manufacturing
Components fabricated using the powder bed fusion laser beam metallic (PBF-LB/M)additive manufacturing process are the result of a multitude of weld passes conducted sequentially. Qualifying components for aerospace applications requires a thorough understanding of the process-structure-properties relationships. Porosity defects are known to have a strong adverse effect on the mechanical properties of a component. In particular, porosity defects created by lack of fusion have high aspect ratio morphologies leading to stress concentrations that become crack initiation sites. In the present work, the occurrence of spatter induced lack of fusion porosity was studied using synchronized in-situ process monitoring, additive manufacturing model-based process metrics, and high-resolution X-ray computed tomography. The results show that lack of fusion porosity is statistically correlated with unremoved welding spatter ejecta of the PBF-LB/M process and process metrics related to the hatching strategy.
Qualification↗
Ultrasonic Inspection During Autoclave Cure of Reflowable-Interface Composite Joints
In structural bonds, the interface between adherend and adhesive is nearly two-dimensional making the interface susceptible to minute quantities of contamination, which can cause weak bonds. Regulatory organizations such as the Federal Aviation Administration (FAA) often require redundant load paths in secondary-bonded primary-structures due to uncertainty in bond performance. To address this issue, the NASA Convergent Aeronautics Solutions (CAS): Adhesive Free Bonding of Composites (AERoBOND) project is investigating reformulated aerospace epoxy-matrix resins to enable reflow and diffusion of the resin at the joint interface during a secondary bonding and cure process that can eliminate the material discontinuity at the interface. Implementing in-situ process monitoring enables assessing the bond quality during processing rather than waiting for post-fabrication mechanical testing to be completed. In this paper, an in-situ ultrasonic inspection system is used to monitor the joining of three composite laminates assembled using the AERoBOND technique. For each panel, the amplitude of the wave reflection at the joint was measured throughout the cure cycle. The results indicate the timing and extent of reflow and cure of the epoxy resin at the joint. Factors indicating end of cure were ascertained and a metric was developed to qualitatively predict acceptable mode-II fracture toughness based on the ultrasonic amplitude at the joint line during cure. In addition, since the inspection system scans an area of the joint, high-resolution localized results can be obtained across the joint.
Tyler B Hudson↗
Demonstrating Advanced Sensors for In-Situ Monitoring Towards Qualification of Nuclear Relevant Components
The U.S. Department of Energy’s Office of Nuclear Energy Advanced Materials and Manufacturing Technologies (AMMT) program is pursuing qualification of laser powder bed fusion (LPBF) components for nuclear applications. A major focus of this effort is the use of in situ process monitoring and machine learning–based tools to establish real-time quality assurance. The primary objective of this report is to identify and evaluate the most relevant in situ sensor systems for LPBF, and to document the deployment of these systems across platforms critical to the AMMT program. This work demonstrates how in situ monitoring can detect process anomalies, track geometry-dependent flaws, and identify limiting combinations of processing parameters—particularly those related to energy density and complex geometries (e.g., overhanging structures). To support this goal, a diverse suite of sensor modalities was evaluated across LPBF platforms, including visible and near-infrared (NIR) imaging, fringe projection profilometry, long-wavelength infrared (LWIR) thermography, and high-speed photodiode/pyrometry systems. These sensor streams were integrated with Peregrine, a machine-agnostic software platform that, among other capabilities, can generate real-time process anomaly classification. This report documents sensor deployments on multiple AMMT flagship platforms, including the Concept Laser M2 and Renishaw AM400/AM250 systems. Calibration builds with complex, flaw-prone geometries such as unsupported overhangs, stepped features, and thin walls, were used to evaluate how well Peregrine and its associated sensors could detect process anomalies and other instabilities under varied energy densities. It will be shown how Peregrine reliably identifies common process anomalies such as recoater streaking, superelevation, etc., and can be used in post-build analysis for anomaly spatial distributions throughout the build height to better understand the impact of geometry and processing parameter choice on the build. This work demonstrates measurable progress toward the vision that components can be born-qualified by establishing a real-time monitoring framework, identifying limiting process conditions, and laying the foundation for sensor fusion–enabled prediction pipelines that are scalable across platforms and applicable to nuclear-relevant components.
22 GENERAL STUDIES OF NUCLEAR REACTORS↗
On the formation of swelling and related flaws in laser powder bed fusion
Process monitoring in laser powder bed fusion additive manufacturing can provide insights into stochastic anomalies, melt pool and plume dynamics, and part quality. Swelling, a build anomaly where overbuilt material protrudes through the powder layer after recoating, is readily detectable in post-recoat visible light images of the powder bed. Here, this work identifies several of the underlying mechanisms driving swelling formation by analyzing the influence of processing parameters, laser scan paths, and build plate locations on the presence of swelling detected in situ. Swelling near the edge of the part and swelling in the internal region of the part are shown to correlate with different process conditions. Edge and internal swelling may be driven by different phenomena, with edge swelling predominately occurring on the edge of a part facing the laser module and correlated to clusters of near-surface voids (detected with X-ray computed tomography). A larger spot size, higher laser power, and lower scan velocity also increased the presence of edge swelling. Laser spot size and scan path influenced internal swelling, which occurred preferentially with a larger spot size and in regions with large melt pools, caused by localized heat accumulation due to non-optimal processing parameters or scan path strategies. For coupons processed with a slicer-defined maximum scan vector length, swelling seldom occurred at internal vector-stripe boundaries. These results provide a mechanistic understanding of how swelling can be linked to material flaws, insight into how some instances of swelling can be avoided, and evidence supporting the use of swelling as an in situ indicator for quality assurance and part qualification.
Anomaly↗
Spacelab Data Processing Facility
The capabilities of the Spacelab Data Processing Facility (SPDPF) are highlighted. The capturing, quality monitoring, processing, accounting, and forwarding of vital Spacelab data to various user facilities around the world are described.
Source record↗
Toward memory-efficient melt pool monitoring: a classification framework using event-based imaging and sparse sensing technique
Vision sensors like CMOS and CCD cameras are often used for in-process monitoring of melt pools in laser-based additive and welding processes, but they require transferring large amounts of data and computational processing resources. Event-based neuromorphic imagery, on the other hand, detects only the change in pixel intensity, thus potentially reducing the data amount and latency. With an event imager, this study develops a framework for melt pool condition classification, including image construction, time scale selection, optimal pixel selection, and sparse classification, to achieve a highly memory-efficient scheme. These are based on sparse sensing techniques with singular value decomposition (SVD) and QR pivoting, the two fundamental matrix transformations for linear dimensionality reduction. The framework is then validated by classifying a controlled experiment by exciting various mode shapes of liquid gallium pools of varying depths (3, 6, and 8 mm). At 200 pixels, the classifier can reach overall accuracy of 75%, while at 2000 pixels (0.013% of the total possible pixels), the accuracy is nearly 90% (89.86%). At the same number of pixels, random selection can only achieve 46% and 67%, respectively. The memory savings of the sparsely sampled event data compared to a conventional imager is about 500 times. In addition to performance, implementation and limitations of the framework are also discussed.
42 ENGINEERING↗
Spacelab Data Processing Facility (SLDPF) quality assurance expert systems development
Spacelab Data Processing Facility (SLDPF) expert system prototypes have been developed to assist in the quality assurance of Spacelab and/or Attached Shuttle Payload (ASP) processed telemetry data. SLDPF functions include the capturing, quality monitoring, processing, accounting, and forwarding of mission data to various user facilities. Prototypes for the two SLDPF functional elements, the Spacelab Output Processing System and the Spacelab Input Processing Element, are described. The prototypes have produced beneficial results including an increase in analyst productivity, a decrease in the burden of tedious analyses, the consistent evaluation of data, and the providing of concise historical records.
Kelly, Angelita C.↗
Accelerating Ground-Test Cycle Time: The Six-Minute Model Change and Other Visions for the 21st Century
The advantage of managing organizations to minimize product development cycle time has been well established. This paper provides an overview of the wind tunnel testing cycle time reduction activities at Langley Research Center (LaRC) and gives the status of several improvements in the wind tunnel productivity and cost reductions that have resulted from these activities. Processes have been examined and optimized. Metric data from monitoring processes provides guidance for investments in advanced technologies. The most promising technologies under implementation today include the use of formally designed experiments, a diverse array of quick disconnect technology and the judicious use of advanced electronic and information technologies.
Kegelman, Jerome T.↗
Monitoring system and methods for a distributed and recoverable digital control system
A monitoring system and methods are provided for a distributed and recoverable digital control system. The monitoring system generally comprises two independent monitoring planes within the control system. The first monitoring plane is internal to the computing units in the control system, and the second monitoring plane is external to the computing units. The internal first monitoring plane includes two in-line monitors. The first internal monitor is a self-checking, lock-step-processing monitor with integrated rapid recovery capability. The second internal monitor includes one or more reasonableness monitors, which compare actual effector position with commanded effector position. The external second monitor plane includes two monitors. The first external monitor includes a pre-recovery computing monitor, and the second external monitor includes a post recovery computing monitor. Various methods for implementing the monitoring functions are also disclosed.
Stange, Kent↗