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Results for “Quality control”

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 793 records · Page 44
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Stress-dominated growth of two-dimensional materials on nonplanar substrates

Curved features are ubiquitous on solid surfaces, but the effect of surface curvatures on growth of two-dimensional (2D) materials has not yet been established. Using a newly developed method based on the Metropolis algorithm and taking graphene as a prototype, we find that a curved feature on substrates can result in a variety of topological defects in 2D materials. As the feature's size increases by just nanometers, the defects can vary from adatoms, dislocation pairs, and grain boundary scars to long-range grain boundaries, in contrast to previously reported defect-free modes of rigid colloidal crystals growing on spheres. We identify an important role of curvature-induced lattice stress in lowering the growth rate over the curved features and driving a plastic instability in the materials. When the feature's size increases to several nanometers, the stress effect is compromised by an enhanced effect of geodesic curvature, yielding long-range grain boundaries as a result of increased local growth rate on the feature with respect to that on flat regions. Here we further provide a ‘phase diagram’ of defects that helps to guide a rational choice of geometrical parameters of features towards the growth of high-quality 2D materials as well as controllable creation of topological defects.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Wildland Urban Interface (WUI) Emissions: Laboratory Measurement of Aerosol and Trace Gas from Combustion of Manufactured Building Materials

Wildfires are increasing in intensity and more often threatening the wildland urban interface (WUI) where buildings and homes coexist with the natural environment. WUI emissions have not been as well-studied as emissions from vegetation. Thus, there is a need to quantify the emissions of building materials used in home construction under flaming and smoldering conditions to study their impacts to human health, visibility, air quality, and climate. Here, in a controlled laboratory setting, we quantify emissions of aerosols and trace gases including formaldehyde, particulate matter, and black carbon. We focus on the combustion of traditional single-source wood-based construction fuels. Our results indicate that, similar to natural fuels, the aerosol optical properties were more related to combustion conditions than the fuel type. Overall, we observed significant variability in the gas and particle emissions. Consistent trends include high formaldehyde (HCHO) and carbon monoxide (CO) emissions for smoldering conditions and higher carbon dioxide (CO 2 ), nitrogen oxides (NO x ), and black carbon for flaming conditions. Finally, these observations highlight the need to better characterize emissions for materials in the built environment to assess large-scale climate and human health impacts of fires at the WUI.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Bound States in the Continuum on a Silicon Chip with Dynamic Tuning

Expanding bound states in the continuum (BIC) beyond photonic crystal systems may enable broader applications benefiting from the unique properties of BIC states. We use photonic integrated circuit to realize a Fabry-Pérot BIC on a silicon chip. The devices consist of cascaded ring resonators with tunable resonance frequencies and phase delays. As a result, the BIC state is dynamically tuned with electrical I/O. We analyze the mechanism of the formation of BIC states in this waveguide system and point out the fundamental differences between the BIC states and electromagnetically induced transparency states in integrated photonics. The high transmission protected by the BIC state enables versatile optical filters, which are capable of independent control over switching, peak position, and quality factor. We also demonstrate the scalability of this platform. As a result, this integrated silicon photonic platform brings opportunities for practical BIC applications.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2023

Active Q-Switched X-Ray Regenerative Amplifier Free-Electron Laser

Despite tremendous progress in x-ray free-electron laser (FEL) science over the last decade, future applications still demand fully coherent, stable x-rays that have not been demonstrated in existing X-ray FEL facilities. Here in this Letter, we describe an active Q-switched x-ray regenerative amplifier FEL scheme to produce fully coherent, high-brightness, hard x rays at a high-repetition rate. By using simple electron-beam phase space manipulation, we show this scheme is flexible in controlling the x-ray cavity quality factor Q and hence the output radiation. We report both theoretical and numerical studies on this scheme with a wide range of accelerator, x-ray cavity, and undulator parameters.

47 OTHER INSTRUMENTATION↗
DOE OSTI2024

Dual-Band Polarization Control with Pairwise Positioning of Polarization Singularities in Metasurfaces

Emerging applications of metasurfaces in classical and quantum optics are driving the need for precise polarization control of nearly-degenerate, high quality (𝑄)-factor modes. However, current approaches to creating specifically polarized pairs of modes force a trade-off between maintaining high 𝑄 factors and robustness. Here, we solve this challenge by employing pairwise generation, annihilation, and positioning of polarization singularities, derived from symmetry-guaranteed pairs of symmetry-protected bound states in the continuum. We experimentally demonstrate this design paradigm in silicon metasurfaces with mode splittings of ≈ 20 nm, mode splitting deviations as low as 1 nm, and 𝑄 factors up to 200. Furthermore, this approach opens new avenues for enhancing metasurface performance across a diverse range of applications, including sensing, modulating, nonlinear mixing, and generating quantum light.

Metasurfaces↗
DOE OSTI2024

Growth and characterization of α-Sn thin films on In- and Sb-rich reconstructions of InSb(001)

α-Sn thin films can exhibit a variety of topologically nontrivial phases. Both studying the transitions between these phases and making use of these phases in eventual applications requires good control over the electronic and structural quality of α-Sn thin films. α-Sn growth on InSb often results in out-diffusion of indium, a p-type dopant. By growing α-Sn via molecular beam epitaxy on the Sb-rich c(4×4) surface reconstruction of InSb(001) rather than the In-rich c(8×2), we demonstrate a route to substantially decrease and minimize this indium incorporation. The reduction in indium concentration allows for the study of the surface and bulk Dirac nodes in α-Sn via angle-resolved photoelectron spectroscopy without the common approaches of bulk doping or surface dosing, simplifying topological phase identification. In this study, the lack of indium incorporation is verified in angle-resolved and angle-integrated ultraviolet photoelectron spectroscopy as well as in clear changes in the Hall response.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Automatic Drift Correction through Nonlinear Sensing

For successful design and operation of advanced monitoring and control systems, engineers rely on high quality sensor signals that are simultaneously accurate, representative, voluminous, and timely. Unfortunately, sensor faults are common and lead to short-lived symptoms, such as outliers and spikes as well as long-lived symptoms, such as sensor drift. Sensor drift belongs to the category of incipient faults. These are particularly challenging to detect, diagnose, and correct as the time scales of these faults are typically longer than the time scales of the system dynamics that are of interest. Moreover, if sensor drift occurs as a result of exposure to measured medium, then it is likely that multiple sensors will exhibit similar drift rates, thus challenging fault management strategies based on redundancy. In this contribution, we present a first method that can handle this unique challenge.

Chowdhury, Dhruba↗
DOE OSTI2021

Scale Up of High-Performance REBCO Tapes in a Pilot-Scale Advanced MOCVD Tool With In-Line 2D-XRD System

We have reported the development of an Advanced Metal-Organic Chemical Vapor Deposition (AMOCVD) method featuring ohmic heating of the substrate for REBCO film growth, direct tape temperature monitoring, and laminar precursor flow. This A-MOCVD method has been used to fabricate 4 – 5 m thick film REBCO tapes with record high performance: critical currents exceeding 8700 A/12 mm at 30 K, 3 T; and engineering current density of 5200 A/mm 2 at 4.2 K, 15 T. Recently, we constructed a pilot-scale reel-to-reel A-MOCVD system to scale up the technology to long tapes. Preliminary batches of tapes exhibit consistent performance and good uniformity along the length. An in-line 2D X-ray Diffraction (XRD) system has been integrated into the pilot A-MOCVD tool to monitor the REBCO texture and composition, RE 2 O 3 content, and the dimensions of BaMO 3 (BMO, M=Zr,Hf) nanorods that act as artificial pinning centers. Specifically, the streaking angle between REBCO (103) and BZO (101) has been found to correlate well with (Ba+M)/Cu of the film, lift factor in critical current over a range of temperatures and magnetic fields, and the size of the BMO nanorods. Furthermore, the in-line 2D-XRD is expected to serve as a valuable quality measuring tool supporting realtime feedback control for the process to yield uniform and consistent manufacturing of high performance REBCO tapes by Advanced MOCVD.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2020

Abstract for CRADA between the National Energy Technology Laboratory and General Motors (AGMT-0876)

Lightweight aluminum shape castings have widespread applications for structural components in the automotive, aerospace, and general engineering industries because of their excellent castability, corrosion resistance, and particularly high strength-to-weight ratio in the heat-treated condition. In the automotive industry, cast aluminum alloys have been increasingly used to replace cast iron and steel in vehicle applications such as engine blocks, cylinder heads, intake manifolds, brackets, housings, chassis, transmission parts, and suspension systems to reduce mass. As many of the aluminum shape castings used in automobiles involve cyclic loading, fatigue properties of the castings are critical to their success. The increasing use of lightweight aluminum cast components in critical structures thus requires improved integrity, with more reliable and quantifiable performance. The objective of this project is to demonstrate and further develop GM’s patent-pending, novel casting process, “Pressure-Assistant Precision Sand Casting (PAPSC) for producing flawless cast aluminum cylinder heads with minimum manufacturing and energy costs”. The approach is to leverage NETL’s experience in producing high-quality metal castings through various microstructure control and defect elimination technologies as well as comprehensive quantification of microstructure characteristics and mechanical properties. A baseline (production) alloy together with the melt treatment will be initially evaluated with the new PAPSC process to develop and validate the process window for producing flawless cast aluminum heads.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Phase-field predictions of the influence of cooling rates during AM on the Evolution of Microstructures in Nickel-Based Single Crystal Superalloys

Additive manufacturing of single crystals made of Ni-based superalloys offers major cost savings for gas turbine engines with the inclusion of internal cooling channels. However, the lack of understanding of the effect of transient thermal conditions on solidification grain structure during additive manufacturing hinders the potential for process control to maintain the single crystal quality. The use of high-fidelity simulations through high performance computing to predict the evolution of the solidification microstructure will enhance the abilities to tailor the microstructures through process optimization. Phase field simulations are used to determine the effect local thermal conditions and defects on the stability of the solidification morphology, specifically with respect to the onset of columnar-to-equiaxed transition that results in the loss of the single crystal. The results are expected to be instrumental for developing future surrogate models to speed up the integration of design and manufacturing of turbine blades under the harsh in-service conditions.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Shunt-Connected FACTS and Synchronous Condensers

In recent years, the electric-transmission system has undergone a significant transformation marked by a greater integration of renewable-energy sources like wind and solar, the phasing out of thermal generation plants, and a concerted effort towards electrifying energy consumption. To keep pace with the integration of renewable-energy sources and the escalating demands of industries and households, it is imperative to expand and modernize the existing power infrastructure. These upgrades are essential to maintain grid stability, enhance power delivery, and boost overall efficiency of the system. However, challenges have emerged with the growing complexity of power grids, particularly in the realms of voltage control, transient stability, and power-quality management.

24 - POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2025

Machine Learning-Based Process Control for Injection Molding of Recycled Polypropylene

The increased interest in artificial intelligence in manufacturing has driven the adoption of machine learning to optimize processes and improve efficiency. A key challenge in injection molding is the variability of recycled materials, which affects part quality and processing stability. This study presents a novel closed-loop process control approach for injection molding, leveraging machine learning to adaptively predict processing inputs and quality outcomes. The methodology was tested on five blends of recycled polypropylene (rPP), using artificial neural networks (ANNs), linear regression, and polynomial regression to model the relationships between material properties and process parameters. The dataset was split 80/20 into training and testing sets. The ANN model was implemented using TensorFlow and Keras, with six hidden layers of 32 neurons per layer, ReLU activation, and an Adam optimizer. Empirical tuning and early stopping were used to optimize performance and prevent overfitting. Predictions were evaluated based on mean absolute error (MAE), mean squared error (MSE), and percentage error. The results showed that yield stress, ultimate elongation, and part weight were accurately predicted within a 5% error for linear and polynomial regression models and within a 10% error for the ANN. However, modulus predictions were less reliable, with errors of ~11% for ANN and linear regression and ~40% for polynomial regression, reflecting the inherent variability of this property in rPP blends. Predictions of processing inputs had errors ranging from 3% to 25%, depending on the model and response variable. No single modeling approach was consistently superior across all responses, highlighting the complexity of the relationship between material properties, process parameters, and quality metrics. Overall, the work demonstrates that closed-loop process control, powered by machine learning, can effectively predict key quality parameters in injection molding of recycled materials. The proposed approach can improve process stability and material utilization, facilitating increased adoption of sustainable materials.

Krantz, Joshua↗
DOE OSTI2024

E-PVT: enhanced position-velocity-time scheduler for computer-controlled optical finishing with comprehensive considerations of dynamics constraints, continuity and efficiency

Deterministic computer-controlled optical finishing is an essential approach for achieving high-quality optical surfaces. Its determinism and convergence rely heavily on precise and smooth motion control to guide the machine tool over an optical surface to correct residual errors. One widely supported and smooth motion control model is position-velocity-time (PVT), which employs piecewise cubic polynomials to describe positions. Our prior research introduced a PVT-based velocity scheduling method, demonstrating sub-nanometer level convergence in ion beam figuring (IBF) processes. However, three challenges remained. Firstly, this method relies on quadratic programming, resulting in computational intensiveness for dense tool paths. Secondly, the dynamics constraints and velocity and acceleration continuities are not comprehensively considered, limiting the full potential of PVT-based control. Thirdly, no compensation mechanism existed when dynamics constraints are exceeded. In this study, in response to these challenges, we proposed the Enhanced PVT (E-PVT) method, reducing the time complexity from O ( n 3 ) to O ( n ) while fully addressing dynamics constraints and continuities. A novel compensation method utilizing particle swarm optimization was proposed to address situations where dynamics constraints might be exceeded while maintaining the overall processing efficiency. Validation through simulation and experimentation confirmed the improved performance of E-PVT.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Modeling the Effects of Microwave Heating on Densification in Chemical Vapor Infiltration

Microwave heating has great potential to accelerate the synthesis of ceramic matrix composites (CMCs) by a process called Chemical Vapor Infiltration (CVI). In CVI, reactive gases ingress a porous preform and undergo chemical transformation to deposit solid ceramic phase within the pores at high temperature thus, densifying the preform. However, the competing effects of chemical kinetics and gas transport are known to result in non-uniform densification as the outer surfaces of the preform experience faster depositions compared to the core. Achieving spatial temperature control plays a key role improving the densification quality. Microwave heating can potentially create temperature inversion such that the core of the preform is hotter than the outer surface and subsequently, lead to improved densification while keeping the manufacturing times and costs low. In the present work, a computational modeling strategy has been developed that accounts for the key physical phenomena responsible for densification of porous preforms using microwave heating. Specifically, a chemical kinetics model has been formulated for Silicon Carbide (SiC) deposition from MTS/H2 precursor. The model is implemented in a pore-resolved reactive transport solver, Quilt. The CVI simulations are performed for several conditions. Initially, parameterized temperature control is imposed to identify optimum conditions for good densification quality at a fraction of processing time. Further, simulations of microwave heating of porous SiC preforms are performed using OpenFOAM. A strategy to achieve and enhance temperature inversion is identified. The resulting temperature profiles are used in the pore-resolved densification simulations to analyze the densification behavior. It is observed that the temperature inversion achieved by microwave heating leads to significant improvements in densification quality and at the same time, keeps the manufacturing time low.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Simulation and power quality analysis of a Loose-Coupled bipolar DC microgrid in an office building

With distributed generation and battery storage technologies thriving in microgrids, the use of direct current (DC) microgrids in the building sector offers multiple advantages in energy efficiency and power quality compared with alternating current (AC) systems. This study developed a new concept of a loose-coupled bipolar DC building power system. In this work, the concept was used to design a real-world office building in Shenzhen, China. A power system model was developed to study the stability and control of the DC power system and to verify DC power quality. The design and modeling of the DC power control system is discussed in detail. The study developed a few common fault scenarios in DC building microgrids that were simulated in the MATLAB-Simulink environment to validate the design of a loose-coupled bipolar DC system. The results indicate that the proposed loose-coupled bipolar DC system schema, when implemented with proper control algorithms, can achieve good fault-tolerant performance with reliable power quality, even during disruptive system events.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2020

A signal compensation based cascaded PI control for an industrial heat exchange system

Since the characteristics of the industrial heat exchange system (HES) are drastically affected by variations of the steam pressure, ambient temperature and water quality, it is difficult for the classical cascade PI control system to meet the desirable control objectives. Therefore, in this paper, a deterministic linear model with unmodeled dynamics is used to describe the dynamic characteristics of the HES. It should be noted that the unmodeled dynamics at the previously sampled instant can be calculated using actual measurements and that the tracking error, which includes effects of the rate of changes of unmodeled dynamics on the controlled model, can be accurately determined. An additional compensating signal is obtained with the feedforward control together with a one-step optimal control law. Consequently, the cascade PI control strategy with the signal compensation is established. Furthermore, the simulation and industrial application show that the proposed method can effectively improve the performance of the cascade PI control system, especially when the unmodeled dynamics is subjected to unknown variations.

42 ENGINEERING↗
DOE OSTI2023

Robotic Systems integration for cleanroom SRF assembly at Fermilab

Superconducting Radio Frequency (SRF) cryomodule assembly is a critical process that demands the highest levels of contamination control in a cleanroom to ensure product quality and reliability. Within the cleanroom environment, human-driven activities remain the major source of uncontrolled particulate. Moreover, the precise manual alignment of components often exceeds expected timeframes, increasing the risk of particulate migration into the critical inner space of the SRF resonant cavity, and causing extended discomfort for workers. Automation comes as a natural solution to address these challenges. The goal of this activity is to set up and integrate a robotic system to support cavity coupler installation in the cleanroom environment. Initially, remote control of a 6-axis collaborative robot arm will be implemented as an introductory step towards automation in the cleanroom. Subsequently, the system will be further enhanced by integrating manipulation capabilities through an appropriate end-effector, and computer vision technology to enable accurate pose estimation. This comprehensive approach aims to achieve a fully automated and adaptable assembly process in the partially structured cleanroom environment, thereby enhancing efficiency and mitigating existing challenges for better product quality and workers safety.

42 ENGINEERING↗
DOE OSTI2021

SMART Perovskite Growth: Enabling a Larger Range of Process Conditions

Cost-effective, high-throughput industrial applications of metal-halide perovskites require a highly tolerant method (i.e., wide process window) that produces high-quality materials with a short annealing time. Here, we introduce a Seed Modulation for ARTificially controlled nucleation (SMART) process that enables rapid fabrication of high-quality perovskite films under a wide set of initial input parameters. Additionally, we characterized the thin-film evolution from the perspective of crystallinity, surface potential, diffusivity, surface carrier dynamics, and interfacial recombination. We find that surface and subsurface defects primarily determine the performance of materials and devices. By modulating the seeds for perovskite nucleation, we were able to improve the overall crystallization. We achieved a >20% power conversion efficiency using only a 5 min annealing step, and we found that the annealing window is widened such that differing initial conditions achieve similar quality. Furthermore, we demonstrated reproducibility and performance improvement in larger-area perovskite cells by incorporating the SMART process.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗