The materials processing research base of the Materials Processing Center
The investigation and evaluation of materials processing techniques in metals, alloys, polymers, and crystal growth are described.
Flemings, M. C.↗
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The materials processing research base of the Materials Processing Center. Report for FY 1982
The work described, while involving research in the broad field of materials processing, has two common features: the problems are closed related to space precessing of materials and have both practical and fundamental significance. An interesting and important feature of many of the projects is that the interdisciplinary nature of the problem mandates complementary analytical modeling/experimental approaches. An other important aspect of many of the projects is the increasing use of mathematical modeling techniques as one of the research tools. The predictive capability of these models, when tested against measurements, plays a very important role in both the planning of experimental programs and in the rational interpretation of the results. Many of the projects described have a space experiment as their ultimate objective. Mathematical models are proving to be extremely valuable in projecting the findings of ground - based experiments to microgravity conditions.
Flemings, M. C.↗
Methods for destriping Landsat Thematic Mapper images - A feasibility study for an online destriping process in the Thematic Mapper Image Processing System (TIPS)
Methods for destriping TM images and results of the application of these methods to selected TM scenes with sensor and scan striping, which was not removed by the radiometric correction during the TM Archive Generation Phase in TIPS, are presented. These methods correct only for gain and offset differences between detectors over many image lines and do not consider within-line effects. The feasibility of implementing a destriping process online in TIPS is also described.
Poros, D. J.↗
Flat-plate solar array project process development area: Process research of non-CZ silicon material
Several different techniques to simultaneously diffuse the front and back junctions in dendritic web silicon were investigated. A successful simultaneous diffusion reduces the cost of the solar cell by reducing the number of processing steps, the amount of capital equipment, and the labor cost. The three techniques studied were: (1) simultaneous diffusion at standard temperatures and times using a tube type diffusion furnace or a belt furnace; (2) diffusion using excimer laser drive-in; and (3) simultaneous diffusion at high temperature and short times using a pulse of high intensity light as the heat source. The use of an excimer laser and high temperature short time diffusion experiment were both more successful than the diffusion at standard temperature and times. The three techniques are described in detail and a cost analysis of the more successful techniques is provided.
Campbell, R. B.↗
The materials processing research base of the Materials Processing Center
An annual report of the research activities of the Materials Processing Center of the Massachusetts Institute of Technology is given. Research on dielectrophoresis in the microgravity environment, phase separation kinetics in immiscible liquids, transport properties of droplet clusters in gravity-free fields, probes and monitors for the study of solidification of molten semiconductors, fluid mechanics and mass transfer in melt crystal growth, and heat flow control and segregation in directional solidification are discussed.
Latanision, R. M.↗
Processing Overview: The Role of Processing in the Total Materials Cycle
This presentation starts off by overviewing the changing environment and introduces cross cutting themes in materials science. The applications to materials processing is covered before the final topic of conversation: the future.
Craig, Douglas F.↗
Cramer-Rao Bound for Gaussian Random Processes and Applications to Radar Processing of Atmospheric Signals
Calculations of the exact Cramer-Rao Bound (CRB) for unbiased estimates of the mean frequency, signal power, and spectral width of Doppler radar/lidar signals (a Gaussian random process) are presented. Approximate CRB's are derived using the Discrete Fourier Transform (DFT). These approximate results are equal to the exact CRB when the DFT coefficients are mutually uncorrelated. Previous high SNR limits for CRB's are shown to be inaccurate because the discrete summations cannot be approximated with integration. The performance of an approximate maximum likelihood estimator for mean frequency approaches the exact CRB for moderate signal to noise ratio and moderate spectral width.
Frehlich, Rod↗
Analyzing a Mature Software Inspection Process Using Statistical Process Control (SPC)
This paper presents a cooperative effort where the Software Engineering Institute and the Space Shuttle Onboard Software Project could experiment applying Statistical Process Control (SPC) analysis to inspection activities. The topics include: 1) SPC Collaboration Overview; 2) SPC Collaboration Approach and Results; and 3) Lessons Learned.
Barnard, Julie↗
Classifying Terrestrial Volcanic Alteration Processes and Defining Alteration Processes they Represent on Mars
Characterizing alteration of the rocks on Mars is difficult, but some guidelines can be made through comparison with terrestrial volcanic alteration. Subaerial volcanic activity on the Hawaiian islands and subglacial volcanic activity on Iceland have led to the formation of a variety of silicate and iron oxide-rich alteration products that may serve as models for chemical alteration on Mars. Multiple samples have been collected from palagonitized tuffs, altered pillow lavas, altered tephra, and S-rich vents for study in the lab. Variations in the kinds of alteration products have been observed depending on the sample environment. We are defining associations between the alteration products and formation conditions that can be used to provide information about environmental conditions on Mars. In particular, we are providing definitions for palagonitic, pedogenic and solfataric alteration that can be used to characterize these alteration processes.
Bishop, J. L.↗
Modeling of Unit-Cells With Z-Pins Using FLASH: Pre-Processing and Post Processing
Although the toughening properties of stitches, z-pins and similar structures have been studied extensively, investigations on the effect of z-pins on the in-plane properties of laminates are limited. A brief summary on the effect of z-pins on the in-plane tensile and compressive properties of composite laminates is presented together with a concise introduction into the finite element code FLASH. The remainder of the report illustrates the modeling aspect of unit cells with z-pins in FLASH and focuses on input and output data as well as post-processing of results.
Krueger, Ronald↗
Film/Adhesive Processing Module for Fiber-Placement Processing of Composites
An automated apparatus has been designed and constructed that enables the automated lay-up of composite structures incorporating films, foils, and adhesives during the automated fiber-placement process. This apparatus, denoted a film module, could be used to deposit materials in film or thin sheet form either simultaneously when laying down the fiber composite article or in an independent step.
Hulcher, A. Bruce↗
Modified metal-organic framework (MOF) compositions, process of making and process of use thereof
This invention relates to modified MOF materials, methods of preparing them and processes using them. A modified MOF of the invention is modified by impregnating a MOF with an inorganic metal salt. The starting MOF contains at least one linker or ligand which contains an aryl amino group as part of its structure. These modified MOFs are able to adsorb either basic or acidic toxic industrial compounds (TIC). The modified MOFs can be used to remove TICs from various gaseous streams such as air.
Weston, Mitchell Hugh↗
Comparing the Economics of Metal Additive Manufacturing Processes for Micro-scale Plate Reactors in the Chemical Process Industry
Not Available
36 MATERIALS SCIENCE↗
Analyzing Case Histories of Process Plant Disasters to Understand Chemical Process Cybersecurity
This presentation reviews worst case plant disasters and map a cyberattack scenario that would have a similar outcome.
42 ENGINEERING↗
Process Control Across the Board: Supplier Process Control Training Program
No abstract available
process quality↗
Control of Shell Morphology in p-n Heterostructured Water-Processable Semiconductor Colloids: Toward Extremely Efficient Charge Separation
This article describes p-n heterostructured water-borne semiconductor naonoparticles (NPs) with unique surface structures via control of shell morphology. The shell particles, comprising PC60-PC61BM composite, having n-type semiconductor characteristic, notably influence the charge carrier behavior in the core-shell NPs. A one- or two-phase methodology based on a PC60 surfactant-water phase and PC61BM n-type semiconductor-organic phase provided highly specific control over the shell structure of the NPs, which promoted their superior charge separation ability when combined with poly-3-hexyl-thiophene (P3HT). Moreover, the resulting water-borne NPs exhibit shell morphology-dependent carrier quenching and stability, which was characterized via luminescence studies paired with structural analysis. Corresponding to the results, outstanding performances of photovoltaic cells with over 5 % efficiency were achieved. The results suggest that the surrounding shell environments, such as the shell structure, and its electronic charge density, were crucial in determining the overall activity of the core-shell p-n heterostructured NPs. Thus, this work provides a new protocol in the current fields of water-based organic semiconductor colloids.
charge separation↗
Oxidation Resistance in 1200°C Steam of a FeCrAl Alloy Fabricated by Three Metallurgical Processes
Abstract FeCrAl alloys are a leading candidate material for accident tolerant fuel cladding due to their good performance in both normal light-water reactor operating conditions as well as their resilience to high-temperature accident scenarios. For commercial-scale production, new fabrication techniques need to be investigated. In this study, the effects of fabrication methods on the high-temperature steam oxidation performance of C26M (Fe12Cr6Al2Mo in wt.%) were investigated. Three variants of C26M were manufactured: wrought (cast and forged) (WC26M), powder metallurgy hot isostatic pressing (PMC26M), and laser powder bed fusion additive manufacturing (AMC26M). All three variants were exposed to steam at 1200°C for 2 h. Results showed no significant variation in mass change between the variants after steam exposure. All three variants effectively formed stable protective alumina films with ~0.6–1.3 µ m thickness. This study suggests FeCrAl alloys have excellent resilience to high-temperature steam in nuclear reactor accident scenarios regardless of the fabrication method.
Materials Science↗
Enhanced Data Efficiency Using Deep Neural Networks and Gaussian Processes for Aerodynamic Design Optimization
Adjoint-based optimization methods are attractive for aerodynamic shape design primarily due to their computational costs being independent of the dimensionality of the input space and their ability to generate high-fidelity gradients that can then be used in a gradient-based optimizer. This makes them very well suited for high-fidelity simulation based aerodynamic shape optimization of highly parametrized geometries such as aircraft wings. However, the development of adjoint-based solvers involve careful mathematical treatment and their implementation require detailed software development. Furthermore, they can become prohibitively expensive when multiple optimization problems are being solved, each requiring multiple restarts to circumvent local optima. In this work, we propose a machine learning enabled, surrogate-based framework that replaces the expensive adjoint solver, without compromising on predicting predictive accuracy. Specifically, we first train a deep neural network (DNN) from training data generated from evaluating the high-fidelity simulation model on a model-agnostic design of experiments on the geometry shape parameters. The optimum shape may then be computed by using a gradient-based optimizer coupled with the trained DNN. Subsequently, we also perform a gradient-free Bayesian optimization, where the trained DNN is used as the prior mean. We observe that the latter framework (DNN-BO) improves upon the DNN-only based optimization strategy for the same computational cost. Overall, this framework predicts the true optimum with very high accuracy, while requiring far fewer high-fidelity function calls compared to the adjoint-based method. Furthermore, we show that multiple optimization problems can be solved with the same machine learning model with high accuracy, to amortize the offline costs associated with constructing our models. Our methodology finds applications in the early stages of aerospace design. (C) 2021 Published by Elsevier Masson SAS.
Renganathan, S. Ashwin↗