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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 109 records · Page 6
All sourcesNASA NTRSDOE OSTI
NASA NTRS1983

High-speed machining of Space Shuttle External Tank (ET) panels

Potential production rates and project cost savings achieved by converting the conventional machining process in manufacturing shuttle external tank panels to high speed machining (HSM) techniques were studied. Savings were projected from the comparison of current production rates with HSM rates and with rates attainable on new conventional machines. The HSM estimates were also based on rates attainable by retrofitting existing conventional equipment with high speed spindle motors and rates attainable using new state of the art machines designed and built for HSM.

Miller, J. A.↗
NASA NTRS2016

Evaluation of the Effect of Surface Finish on High-Cycle Fatigue of SLM-IN718

The surface finish of parts produced by additive manufacturing processes is much rougher than the surface finish generated by machining processes, and a rougher surface can reduce the fatigue strength of a part. This paper discusses an effort to quantify that reduction of strength in high-cycle fatigue for selective laser melt (SLM) coupons. A high-cycle fatigue (HCF) knockdown factor was estimated for Inconel 718, manufactured with the SLM process. This factor is the percentage reduction from the maximum stress in fatigue for low-stress ground (LSG) specimens to the maximum stress of those left with the original surface condition at the same fatigue life. Specimens were provided by a number of vendors, free to use their "best practice"; only one heat treat condition was considered; and several test temperatures were characterized, including room temperature, 800F, 1000F, and 1200F. The 1000F data had a large variance, and was omitted from consideration in this document. A first method used linear approximations extracted from the graphs, and only where data was available for both. A recommended knockdown factor of the as-built surface condition (average roughness of approximately 245 micro-inches/inch) versus low-stress ground condition (roughness no more than 4 micro-inches/inch) was established at approximately 1/3 or 33%. This is to say that for the as-built surface condition, a maximum stress of 2/3 of the stress for LSG can be expected to produce a similar life in the as-built surface condition. In this first evaluation, the knockdown factor did not appear to be a function of temperature. A second approach, the "KP method", incorporated the surface finish measure into a new parameter termed the pseudo-stress intensity factor, Kp, which was formulated to be similar to the fracture mechanics stress intensity factor. Using Kp, the variance seemed to be reduced across all sources, and knockdown factors were estimated using Kp over the range where data occurred. A plot of the results suggests that the knockdown factor is a function of temperature, and that for low lives the knockdown might be lower than the knockdown observed above about one million cycles, where it tended to stabilize. This was not universal for all temperatures tested. The higher temperature tests are thought to be influenced by the test temperature, which perhaps continued the aging process. Further evaluation of the method is suggested.

Lambert, D. M.↗
NASA NTRS1971

Development of a plan for automating integrated circuit processing

The operations analysis and equipment evaluations pertinent to the design of an automated production facility capable of manufacturing beam-lead CMOS integrated circuits are reported. The overall plan shows approximate cost of major equipment, production rate and performance capability, flexibility, and special maintenance requirements. Direct computer control is compared with supervisory-mode operations. The plan is limited to wafer processing operations from the starting wafer to the finished beam-lead die after separation etching. The work already accomplished in implementing various automation schemes, and the type of equipment which can be found for instant automation are described. The plan is general, so that small shops or large production units can perhaps benefit. Examples of major types of automated processing machines are shown to illustrate the general concepts of automated wafer processing.

Source record↗
NASA NTRS2004

Using Ontologies to Formalize Services Specifications in Multi-Agent Systems

One key issue in multi-agent systems (MAS) is their ability to interact and exchange information autonomously across applications. To secure agent interoperability, designers must rely on a communication protocol that allows software agents to exchange meaningful information. In this paper we propose using ontologies as such communication protocol. Ontologies capture the semantics of the operations and services provided by agents, allowing interoperability and information exchange in a MAS. Ontologies are a formal, machine processable, representation that allows to capture the semantics of a domain and, to derive meaningful information by way of logical inference. In our proposal we use a formal knowledge representation language (OWL) that translates into Description Logics (a subset of first order logic), thus eliminating ambiguities and providing a solid base for machine based inference. The main contribution of this approach is to make the requirements explicit, centralize the specification in a single document (the ontology itself), at the same that it provides a formal, unambiguous representation that can be processed by automated inference machines.

Breitman, Karin Koogan↗
NASA NTRS1982

High-speed machining of space shuttle External Tank (ET) panels

The applicability to and advantages of the high-speed machining process for the production of Space Shuttle external tank panels by physically machining selected sample portions of an external tank panel were investigated. The panel sample configuration was selected, and potential high speed milling procedures identified. An 8 foot long panel was machined and the milling demonstration is described in detail.

Miller, J. A.↗
NASA NTRS1969

Cold machining of high density tungsten and other materials

Cold machining process, which uses a sub-zero refrigerated cutting fluid, is used for machining refractory or reactive metals and alloys. Special carbide tools for turning and drilling these alloys further improve the cutting performance.

Ziegelmeier, P.↗
DOE OSTI2024

Recycling of CF-ABS machining waste for large format additive manufacturing

Large format additive manufacturing (LFAM) necessitates the use of short fiber thermoplastic composites, such as carbon fiber filled acrylonitrile butadiene styrene, to enable printing. Currently, when LFAM parts are machined into their final shape, the machining scrap (i.e., small flake like particles and offcuts) is landfilled. Previous studies have demonstrated the viability of recycling end-of-life LFAM parts by shredding and optionally re-compounding the material back into pellets. However, there is little understanding of the value and performance of recycled material made from LFAM machining scrap, which if pursued could motivate more broad recycling of this waste stream. In this study, recycled in-process machining scrap is explored as an LFAM feedstock source. Herein, it is found that the primary degradation mechanism of the recycled material is significant fiber length attrition during surface machining. While this fiber attrition negatively impacts the mechanical performance of the material in the print direction, it seems that the changes in processing behaviors and print quality, namely the surface roughness of the printed structure associated with shorter fiber lengths, is beneficial to interlayer adhesion. The tensile strength and elastic modulus of the recycled material, in the print direction, decreased 11% and 31% respectively compared to the pristine material. However, in the layer-wise direction it was found that the recycled material exhibited no significant change in elastic modulus and a significant 21% increase in tensile strength – a surprising result. In conclusion, this work indicates that machining waste could be a viable material stream for recycled LFAM feedstock materials.

42 ENGINEERING↗
DOE OSTI2021

A Novel Laser-Aided Machining and Polishing Process for Additive Manufacturing Materials with Multiple Endmill Emulating Scan Patterns

In additive manufacturing (AM), the surface roughness of the deposited parts remains significantly higher than the admissible range for most applications. Additionally, the surface topography of AM parts exhibits waviness profiles between tracks and layers. Therefore, post-processing is indispensable to improve surface quality. Laser-aided machining and polishing can be effective surface improvement processes that can be used due to their availability as the primary energy sources in many metal AM processes. While the initial roughness and waviness of the surface of most AM parts are very high, to achieve dimensional accuracy and minimize roughness, a high input energy density is required during machining and polishing processes although such high energy density may induce process defects and escalate the phenomenon of wavelength asperities. In this paper, we propose a systematic approach to eliminate waviness and reduce surface roughness with the combination of laser-aided machining, macro-polishing, and micro-polishing processes. While machining reduces the initial waviness, low energy density during polishing can minimize this further. The average roughness (Ra=1.11μm) achieved in this study with optimized process parameters for both machining and polishing demonstrates a greater than 97% reduction in roughness when compared to the as-built part.

42 ENGINEERING↗
NASA NTRS1994

Feasibility study, software design, layout and simulation of a two-dimensional Fast Fourier Transform machine for use in optical array interferometry

The goal of this project was the feasibility study of a particular architecture of a digital signal processing machine operating in real time which could do in a pipeline fashion the computation of the fast Fourier transform (FFT) of a time-domain sampled complex digital data stream. The particular architecture makes use of simple identical processors (called inner product processors) in a linear organization called a systolic array. Through computer simulation the new architecture to compute the FFT with systolic arrays was proved to be viable, and computed the FFT correctly and with the predicted particulars of operation. Integrated circuits to compute the operations expected of the vital node of the systolic architecture were proven feasible, and even with a 2 micron VLSI technology can execute the required operations in the required time. Actual construction of the integrated circuits was successful in one variant (fixed point) and unsuccessful in the other (floating point).

Boriakoff, Valentin↗
NASA NTRS1967

Dual photochemical replenisher system reduces chemical losses

Dual replenisher system reduces chemical losses and maintains optimum solution concentration during long nonprocessing cycles of photo processing machines. Using a single 3-position switch and solenoid control valves, the system provides instantaneous flow control to each processing tank.

Kolber, J. M.↗
NASA NTRS1989

Parallel eigenanalysis of finite element models in a completely connected architecture

A parallel algorithm is presented for the solution of the generalized eigenproblem in linear elastic finite element analysis, (K)(phi) = (M)(phi)(omega), where (K) and (M) are of order N, and (omega) is order of q. The concurrent solution of the eigenproblem is based on the multifrontal/modified subspace method and is achieved in a completely connected parallel architecture in which each processor is allowed to communicate with all other processors. The algorithm was successfully implemented on a tightly coupled multiple-instruction multiple-data parallel processing machine, Cray X-MP. A finite element model is divided into m domains each of which is assumed to process n elements. Each domain is then assigned to a processor or to a logical processor (task) if the number of domains exceeds the number of physical processors. The macrotasking library routines are used in mapping each domain to a user task. Computational speed-up and efficiency are used to determine the effectiveness of the algorithm. The effect of the number of domains, the number of degrees-of-freedom located along the global fronts and the dimension of the subspace on the performance of the algorithm are investigated. A parallel finite element dynamic analysis program, p-feda, is documented and the performance of its subroutines in parallel environment is analyzed.

Akl, F. A.↗
NASA NTRS2016

Floating Ultrasonic Transducer Inspection System and Method for Nondestructive Evaluation

A method for inspecting a structural sample using ultrasonic energy includes positioning an ultrasonic transducer adjacent to a surface of the sample, and then transmitting ultrasonic energy into the sample. Force pulses are applied to the transducer concurrently with transmission of the ultrasonic energy. A host machine processes ultrasonic return pulses from an ultrasonic pulser/receiver to quantify attenuation of the ultrasonic energy within the sample. The host machine detects a defect in the sample using the quantified level of attenuation. The method may include positioning a dry couplant between an ultrasonic transducer and the surface. A system includes an actuator, an ultrasonic transducer, a dry couplant between the transducer the sample, a scanning device that moves the actuator and transducer, and a measurement system having a pulsed actuator power supply, an ultrasonic pulser/receiver, and a host machine that executes the above method.

Zalameda, Joseph N.↗
NASA NTRS1972

Data processing 2: Advancements in large scale data processing systems for remote sensing

The development of large scale data processing systems for remote sensing is studied by evaluating: (1) the suitability of several sensor types with regard to producing data required for multispectral machine analysis; (2) various types of data preprocessing necessary to prepare such data for analysis; and (3) transfer of machine processing techniques for earth resources data to user community.

Landgrebe, D. A.↗
NASA NTRS2011

Forming Mandrels for X-Ray Mirror Substrates

Future x-ray astronomical missions, like the International X-ray Observatory (IXO), will likely require replicated mirrors to reduce both mass and production costs. Accurately figured and measured mandrels - upon which the mirror substrates are thermally formed - are essential to enable these missions. The challenge of making these mandrels within reasonable costs and schedule has led the Goddard and Marshall Space Flight Centers to develop in-house processes and to encourage small businesses to attack parts of the problem. Both Goddard and Marshall have developed full-aperture polishing processes and metrologies that yield high-precision axial traces of the finished mandrels. Outside technologists have been addressing challenges presented by subaperture CNC machining processes: particularly difficult is the challenge of reducing mid-spatial frequency errors below 2 nm rms. The end-product of this approach is a realistic plan for the economically feasible production of mandrels that meet program requirements in both figure and quantity.

Blake, Peter N.↗
DOE OSTI2020

Development of neural network force fields for corrosion studies

To fully understand the chemistry and physics of corrosion, novel methods of simulation must be developed. One approach is designing machine learning (ML) algorithms integrated with density functional theory to develop adaptive force fields to gain insight into corrosion behavior namely at the surface of metal oxides. Current methods of modeling corrosion are slow due to the computational cost of resolving both reaction mechanics and mass transport processes. Machine learning methods can be implemented to obtain structure-activity relationships at both the molecular and bulk scale while still retaining the accuracy of density functional theory (DFT) and significantly decreasing the time needed for simulations of complex chemical processes in the various environments of corrosion. Multiscale models are needed for corrosion studies to fully understand its processes not only at the atomic length scale (chemical bonding, energies, and forces), but also at the nano and meso length scales (solid-state physics and material science processes). Current methods of study include DFT, molecular dynamics, and Monte Carlo. The limitation of DFT is that only a small number of atoms or molecules can be simulated at that level of theory. Density functional theory is used to study the electronic structure of atoms and molecules, and calculate the force component of each atom. However, these calculations are limited to about 1000 atoms. Custom periodic boundary conditions (PBC) can be used to describe the various environments and defects that affect the atomic forces to produce a large data set from which a training set can be derived. Machine learning can be utilized to overcome the barrier of modeling macroscopic and multi-scale processes from ab initio calculations through the development of adaptive force fields. Local environments determine the atomic forces of a given system, therefore adaptive force fields must be created to produce reliable quantum mechanical calculations. This can be achieved by developing a learning algorithm that uses the mapped atomic forces or fingerprint as an input to produce energies and magnetic moments as output. A systematic approach was used to begin to build a data set in order to accurately describe the atomic forces in various environments. In Figure 4 below, a simple PBC cell of Fe{sub 2}O{sub 3} was first optimized. A surface optimization was performed next, followed by a hydroxylated surface optimization. Once this calculation has converged, the adsorption of halide species to the hydroxylated surface will be investigated. TensorFlow is an open source platform for machine learning developed by Google. Using a high level application program interface (API) such as Keras allows for building and training ML models easily in a number of different environments and languages. For this project, a neural network was developed within Anaconda in Python. Future Work: Further development of reference data set; Refining neural network and learning algorithm; Fingerprinting atomic environment to enable mapping of atomic force components; Choosing appropriate training set from reference data; Learning from training set and enabling non-linear mapping of training set fingerprints and the atomic forces; Estimation of uncertainty to identify ranges of outside applicability; Testing and analysis of molecular dynamic simulations.

36 MATERIALS SCIENCE↗
NASA NTRS2019

Understanding Machine Learning in Earth Science: A Natural Language Processing Approach

Machine learning (ML) is being increasingly utilized in Earth science research. Benefits of ML include efficiency, reduction of human error, and ability to extract hidden patterns within data. However, the mutual lack of each other’s domain knowledge by ML and Earth science stands as a barrier to timely and effective implementation. Earth science, in particular, faces challenges in generating sample data, compared to those of traditional ML problems such as face recognition or stock predictions, where data is abundant and not lacking in ground truth, which is necessary for labeling. Earth science data are more varying in formats, such as HDF5 and image resolutions, and are not standardized across instruments, even within a given Earth science discipline. Previous studies have been done to outline the specific challenges that Earth science faces with ML, while others have focused on using existing publications to mine information efficiently. Other resources such as Scikit-Learn have developed decision trees for choosing appropriate machine learning algorithms, but application within Earth science subjects becomes much more complex. For the current study, we propose a methodology and tool that aids in implementation of ML in Earth science using natural language processing (NLP). Our work comprises three main parts: (1) analyzing existing publications related to ML and Earth science, using natural language processing: (2) extracting from the publications information on ML models subjects in Earth Science: and (3) visualizing the extracted relationships as a network graph. The resulting network graph should aid the Earth science communities in applying optimal ML algorithms and guiding data preparation through visualization of similar studies. The network graph and analysis of document similarity will be the basis of our next step, which is to develop a decision tree for selecting optimal machine learning methodologies for specified Earth science applications.

Zheng, Laura↗
DOE OSTI2020

Pitting behavior of friction stir repair-welded 304L stainless steel in 3.5% NaCl solution at room temperature: role of grain and defect structures

Stainless steel (SS) canisters used for storing spent nuclear waste are prone to chloride-induced stress corrosion cracking. Friction stir welding (FSW), being a low heat input process, can be used for repair welding of these canisters. In this study, an artificial crack was introduced on the 304L SS coupons by an electric discharge machining process. The artificial crack was repair-welded by FSW by maintaining the tool temperature a constant at two levels (725 and 825 °C). Friction stirring significantly reduced the grain size of the stirred zone (SZ) from about 47 to 2–4 μm. The fraction of low-angle grain boundaries increased in the SZ from 2 to 37–43%. Here, on the other hand, the fraction of special grain boundaries (Σ3 and Σ9) that was ~ 50% in the base metal reduced to < 10% in the SZ. During friction stirring, the oxide layer of artificial crack was broken and aligned to form a spiral defect called lazy-S structure. All these microstructural changes affected the corrosion behavior of the FSW specimens when tested in 3.5% NaCl at room temperature using cyclic polarization, chronoamperometry, and electrochemical impedance spectroscopy. The FSW specimens showed lower polarization resistance and lower transpassive potential than those of the base metal specimens. However, the pitting protection potentials of the FSW specimens were higher than that of the base metal. The pitting behavior of the FSW specimens was influenced more by the preferential attack on the lazy-S region than by passive film breakdown. The flat band potentials of the passive film formed on the FSW specimens were more positive than that of base metal. The charge carrier density of passive film formed on the FSW specimens was higher than that of the base metal. The higher fraction of low-angle grain boundaries present in the FSW specimens could supply more number of misorientation dislocations at the metal/film interface which could form anion vacancies by a climb process leading to formation of oxide at these locations without stressing the substrate. Therefore, low-angle boundaries are considered helpful for formation of stress-free passive films that will be highly stable and enhance both pitting and stress corrosion cracking resistance.

Dry storage canister↗
NASA NTRS1987

On acquisition of programming knowledge

For the evolving discipline of programming, acquisition of programming knowledge is a difficult issue. Common knowledge results from the acceptance of proven techniques based on results of formal inquiries into the nature of the programming process. This is a rather slow process. In addition, the vast body of common knowledge needs to be explicated to a low enough level of details for it to be represented in the machine processable form. It is felt that this is an impediment to the progress of automatic programming. The importance of formal approaches cannot be overstated since their contributions lead to quantum leaps in the state of the art.

Amin, Ashok T.↗