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At least 1,099 records · Page 61

Sensor selection and tool wear prediction with data‐driven models for precision machining

Abstract Estimation of tool wear in precision machining is vital in the traditional subtractive machining industry to reduce processing cost, improve manufacturing efficiency and product quality. In this vein, fusion of time and frequency‐domain features of commonly sensed signals can provide an early indication of tool wear and improve its prediction accuracy for prognostics and health management. This paper presents a data‐driven methodology and a complete tool chain for the inference of precision machining tool wear from fused machine measurements, such as cutting force, power, audio and vibration signals, and quantify the usefulness of each measurement. Indicators of tool wear are extracted from time‐domain signal statistics, frequency‐domain analysis, and time‐frequency domain analysis. Correlation coefficients between the extracted features (indicators) and the tool wear are used to select the most informative features. Principal Component Analysis and Partial Least‐Squares are used to reduce the dimensionality of the feature space. Regression models, including linear regression, support vector regression, Decision tree regression, neural network regression and Gaussian process regression, are used to predict the tool wear using data from a Haas milling machine performing spiral boss face milling. The performance of the regression models based on subsets of sensors validates the preliminary estimates about the saliency of the sensors. The experimental results show that the proposed methods can predict the machine tool wear precisely, with readily available sensor measurements. Neural network and Gaussian process regression were able to achieve good estimates of tool wear at different machine operating conditions. The most informative signal in predicting tool wear was shown to be the vibration signal. Time‐frequency domain features were the most informative features among the combination of features of three domains. In addition, using partial least squares components extracted from the original features of signals led to higher prediction accuracy.

Han, Seulki↗

An Approach for Preoperative Planning and Performance of MR-guided Interventions Demonstrated With a Manual Manipulator in a 1.5T MRI Scanner

Purpose: The aim of this work was to develop and test a general methodology for the planning and performance of robot-assisted, MR-guided interventions. This methodology also includes the employment of software tools with appropriately tailored routines to effectively exploit the capabilities of MRI and address the relevant spatial limitations. Methods: The described methodology consists of: (1) patient-customized feasibility study that focuses on the geometric limitations imposed by the gantry, the robotic hardware, and interventional tools, as well as the patient; (2) stereotactic preoperative planning for initial positioning of the manipulator and alignment of its end-effector with a selected target; and (3) real-time, intraoperative tool tracking and monitoring of the actual intervention execution. Testing was performed inside a standard 1.5T MRI scanner in which the MR-compatible manipulator is deployed to provide the required access. Results: A volunteer imaging study demonstrates the application of the feasibility stage. A phantom study on needle targeting is also presented, demonstrating the applicability and effectiveness of the proposed preoperative and intraoperative stages of the methodology. For this purpose, a manually actuated, MR-compatible robotic manipulation system was used to accurately acquire a prescribed target through alternative approaching paths. Conclusions: The methodology presented and experimentally examined allows the effective performance of MR-guided interventions. It is suitable for, but not restricted to, needle-targeting applications assisted by a robotic manipulation system, which can be deployed inside a cylindrical scanner to provide the required access to the patient facilitating real-time guidance and monitoring.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

The MicroBooNE Single-Photon Low-Energy Excess Search (Public Note 1087)

MicroBooNE is a short baseline neutrino experiment at Fermilab designed to address the low energy excess observed by the MiniBooNE experiment. This note describes and presents preliminary results for the MicroBooNE analysis developed to address this excess as a single photon plus one or zero protons in the final state. The analysis assumes neutrino neutral current Δ resonance production followed by Δ radiative decay on argon (NC Δ → Nγ ) as the "signal model"; event reconstruction and selection have been developed and optimized in order to maximize efficiency and reduce cosmogenic and other beam-related backgrounds to the NC Δ → Nγ signal. We present the analysis methodology and validation checks performed on limited-statistics open data sets, corresponding to 5 x10 19 protons on target (POT), following a blind analysis, as well as the projected sensitivities for testing the Standard Model (SM) predicted rate for the NC Δ → Nγ process and for testing the interpretation of the previously observed MiniBooNE low energy excess as NC Δ → Nγ events, using the full anticipated MicroBooNE data set of 12.25 x 10 20 POT.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Developing a Prototype Methodology to Rank CO2-EOR Wells and Assess Their Reuse Potential for Geologic Carbon Sequestration

This study presents a prototype methodology for evaluating the reuse potential of Class II CO₂-enhanced oil recovery (CO₂-EOR) wells as Class VI wells for geologic carbon sequestration. The approach focuses on assessing wellbore construction materials—casing, cement, tubing, and packers—based on U.S. Environmental Protection Agency (EPA) Class VI well conversion guidelines. Utilizing Python scripts and JSON representations, the methodology automates checks on digitized Texas Railroad Commission (TRRC) data to rank wells based on regulatory and integrity criteria. Key factors include casing integrity, cementing techniques, tubing compatibility, and packer selection. Due to limitations in digitized data, manual verification is required for certain sections. Future enhancements include incorporating non-digitized data via web scraping and machine learning. This research provides a practical framework for well owners and regulators, supporting informed decision-making for sustainable CO₂ storage.

carbon sequestration↗

Computational materials reliability assessment of hydrogen fueled gas turbine power generation engines

The use of blended fuel sources in land based gas turbine engines drives variations in the resulting operational profile (temperatures and pressures) which can impact engine reliability. Furthermore, variability in the manufacture of components affects the resulting microstructure which directly impacts material performance and reliability. Currently, data-driven models are typically used for maintaining and inspecting fleets of engines. Without explicitly capturing material and operational sources of variability conservatism must be used in developing component-level reliability models. Therefore, there exists an opportunity to use information from materials-scale physics models to better inform reliability modeling and reduce conservatism; the impact is more cost-efficient operation and maintenance of current and future fleets. Specifically, this work establishes a computational framework for evaluating the probabilistic high temperature creep performance of hot-section Ni-based superalloys where uncertainty comes from both microstructural and operational variability. A novel high-fidelity physics model which phenomenologically captures grain-boundary sensitive phenomena has been established. A probabilistic calibration procedure was used to calibrate the model and capture uncertainty in the parameterized model coefficients. A design of experiments methodology was established for identifying informative microstructural digital representations for suitable for forward model evaluation. Results show that training a machine-learning surrogate using this design criteria outperforms random selection of microstructural representations. Finally, two surrogate models were developed: (1) a deterministic surrogate model which predicts the local field response given microstructure, constitutive model parameters, and operating conditions (stress, temperature) and (2) a probabilistic model, where uncertainty comes from constitutive law uncertainty, built using denoising diffusion probabilistic models which samples responses given (1) microstructure and (2) operating conditions. These surrogate models enable partner Siemens Energy to rapidly perform UQ analysis specific to creep deformation across a range of microstructures and operating conditions. The impact is that these ML and physics codes can be used to establish more advanced reliability models for the inspection, servicing, and maintenance of land based gas turbine engines.

36 MATERIALS SCIENCE↗

WELDSMART: A vision-based expert system for quality control

This work was aimed at exploring means for utilizing computer technology in quality inspection and evaluation. Inspection of metallic welds was selected as the main application for this development and primary emphasis was placed on visual inspection, as opposed to other inspection methods, such as radiographic techniques. Emphasis was placed on methodologies with the potential for use in real-time quality control systems. Because quality evaluation is somewhat subjective, despite various efforts to classify discontinuities and standardize inspection methods, the task of using a computer for both inspection and evaluation was not trivial. The work started out with a review of the various inspection techniques that are used for quality control in welding. Among other observations from this review was the finding that most weld defects result in abnormalities that may be seen by visual inspection. This supports the approach of emphasizing visual inspection for this work. Quality control consists of two phases: (1) identification of weld discontinuities (some of which may be severe enough to be classified as defects), and (2) assessment or evaluation of the weld based on the observed discontinuities. Usually the latter phase results in a pass/fail judgement for the inspected piece. It is the conclusion of this work that the first of the above tasks, identification of discontinuities, is the most challenging one. It calls for sophisticated image processing and image analysis techniques, and frequently ad hoc methods have to be developed to identify specific features in the weld image. The difficulty of this task is generally not due to limited computing power. In most cases it was found that a modest personal computer or workstation could carry out most computations in a reasonably short time period. Rather, the algorithms and methods necessary for identifying weld discontinuities were in some cases limited. The fact that specific techniques were finally developed and successfully demosntrated to work illustrates that the general approach taken here appears to be promising for commercial development of computerized quality inspection systems. Inspection based on these techniques may be used to supplement or substitute more elaborate inspection methods, such as x-ray inspections.

Andersen, Kristinn↗

NASA Electronic Publishing System: Cost/benefit Methodology

The NASA Scientific and Technical Information Office was assigned the responsibility to examine the benefits of the utilization of electronic printing and duplicating systems throughout NASA Installations and Headquarters. The subject of this report is the documentation of the methodology used in justifying the acquisition of the most cost beneficial solution for the printing and duplicating requirements of a duplicating facility that is contemplating the acquisition of an electronic printing and duplicating system. Four alternatives are presented with each alternative costed out with its associated benefits. The methodology goes a step further than just a cost benefit analysis through its comparison of risks associated with each alternative, sensitivity to number of impressions and productivity gains on the selected alternative and finally the return on investment for the selected alternative. The report can be used in conjunction with the two earlier reports, NASA-TM-106242 and TM-106510 in guiding others in determining the cost effective duplicating alternative.

Tuey, Richard C.↗

Automated Finite Element Analysis of Elastically-Tailored Plates

A procedure for analyzing and designing elastically tailored composite laminates using the STAGS finite element solver has been presented. The methodology used to produce the elastic tailoring, namely computer-controlled steering of unidirectionally reinforced composite material tows, has been reduced to a handful of design parameters along with a selection of construction methods. The generality of the tow-steered ply definition provides the user a wide variety of options for laminate design, which can be automatically incorporated with any finite element model that is composed of STAGS shell elements. Furthermore, the variable stiffness parameterization is formulated so that manufacturability can be assessed during the design process, plus new ideas using tow steering concepts can be easily integrated within the general framework of the elastic tailoring definitions. Details for the necessary implementation of the tow-steering definitions within the STAGS hierarchy is provided, and the format of the ply definitions is discussed in detail to provide easy access to the elastic tailoring choices. Integration of the automated STAGS solver with laminate design software has been demonstrated, so that the large design space generated by the tow-steering options can be traversed effectively. Several design problems are presented which confirm the usefulness of the design tool as well as further establish the potential of tow-steered plies for laminate design.

Jegley, Dawn C.↗

Biospecimen Culling: Temporal RNA Integrity Analysis Across Spaceflight Missions Dating from 1985 to 2011

The Ames Life Science Data Archive (ALSDA) at NASA Ames Research Center is managed by the Space Biosciences Division and has been operational since 1993. The ALSDA is responsible for archiving information and biospecimens collected from life science spaceflight experiments and matching ground control experiments. They are stored in the Ames biobank, which is located in the Biospecimen Storage Facility (BSF). The ALSDA also manages a Biospecimen Sharing Program, performs curation and long-term storage operations, and makes biospecimens available to the scientific community for research purposes via the Life Science Data Archive public website (https:lsda.jsc.nasa.gov). The BSF maintains both fixed and frozen spaceflight and ground tissues, collected from recent and past spaceflight missions. Due to the ever increasing demand for space to preserve current and future flight biospecimens, the ALSDA has initiated the development of a culling plan for biospecimens currently stored in the BSF. Culling enables the ALSDA to assess the quality of archived samples, and supports the development of standardized culling procedures that improve the operational efficiency of the BSF. The culling plan focuses on generating disposition recommendations for samples in the BSF, and currently is based on measuring ribonucleic acid (RNA) integrity number (RIN). The culling process includes (1) sorting and identification of candidate samples for RIN analysis, (2) completion of RIN analysis on select samples, and (3) development of disposition recommendations for specimens based on the RIN values. Furthermore, our approach allows for unique scientific opportunities, including development of a RIN-based methodology for culling, and temporal assessment of the quality of the tissues that have been stored in BSF since the 1980s. Results of this work will also support NASA open science initiatives.

biospecimen↗

Predicting Patterns of Solar Energy Buildout to Identify Opportunities for Biodiversity Conservation

The construction of solar energy facilities can have positive or negative impacts on biodiversity depending on siting and associated land use transitions. We identified drivers of solar siting and quantified patterns of buildout in states surrounding the Chesapeake Bay watershed – a biodiversity hotspot with numerous ecosystem services. Using a convolutional neural network, we mapped the footprints of ground-mounted solar arrays present in satellite imagery annually from 2017 to 2021 in Delaware, Maryland, Pennsylvania, New York, Virginia, and West Virginia. As of 2021, we identified 958 solar arrays covering 52.3 km2 built primarily on previously cultivated land, while avoiding natural landcover. We fit a binomial-Weibull model to these solar timeseries data in a hierarchical, Bayesian framework to quantify the relationship between geospatial covariates and rate of solar development. Solar array construction rate increased in cultivated areas, areas of lower agricultural suitability, lower slope, lower forest cover, lower biodiversity protection, and greater distances from roads. We also estimated changes in the rate of solar construction over time and found differences among states: acceleration in Virginia and deceleration in New York. We used parameter estimates to map the relative likelihood of future solar development across the study area. This methodology can be used to anticipate where solar is likely to be built in different landscapes and how these patterns align with conservation goals. Around the Chesapeake Bay watershed, the selection of lower quality agricultural areas for solar energy minimizes removal of important habitat and provides opportunities for native plant and pollinator restoration.

Artificial Intelligence↗

Analytical Methods for Measuring Mercury in Water, Sediment and Biota

Mercury (Hg) exists in a large number of physical and chemical forms with a wide range of properties. Conversion between these different forms provides the basis for mercury's complex distribution pattern in local and global cycles and for its biological enrichment and effects. Since the 1960’s, the growing awareness of environmental mercury pollution has stimulated the development of more accurate, precise and efficient methods of determining mercury and its compounds in a wide variety of matrices. During recent years new analytical techniques have become available that have contributed significantly to the understanding of mercury chemistry in natural systems. In particular, these include ultra sensitive and specific analytical equipment and contamination-free methodologies. These improvements allow for the determination of total mercury as well as major species of mercury to be made in water, sediments and soils, and biota. Analytical methods are selected depending on the nature of the sample, the concentration levels of mercury, and what species or fraction is to be quantified. The terms “speciation” and “fractionation” in analytical chemistry were addressed by the International Union for Pure and Applied Chemistry (IUPAC) which published guidelines (Templeton et al., 2000) or recommendations for the definition of speciation analysis. "Speciation analysis is the analytical activity of identifying and/or measuring the quantities of one or more individual chemical species in a sample. The chemical species are specific forms of an element defined as to isotopic composition, electronic or oxidation state, and/or complex or molecular structure. The speciation of an element is the distribution of an element amongst defined chemical species in a system. In case that it is not possible to determine the concentration of the different individual chemical species that sum up the total concentration of an element in a given matrix, meaning it is impossible to determine the speciation, it is a useful practice to do fractionation instead. Fractionation is the process of classification of an analyte or a group of analytes from a certain sample according to physical (e.g. size, solubility) or chemical (e.g. bonding, reactivity) properties."

mercury↗

Development of Remote Cutting Tools for use at ATR - 20438

As a result of years of operations of the Advanced Test Reactor (ATR) at the Idaho National Lab (INL), the ATR canal has become congested due to the storage of materials including waste consisting of highly irradiated remote handled (RH) metals. In order to support its continuing nuclear mission the ATR requires canal space to support fuel storage and future core internal change out (CIC) components. INL staff determined that the canal must be cleaned out and waste removed to efficiently utilize the valuable canal floor space. It was determined that a methodology for processing, packaging, characterizing, and removing current and future irradiated hardware from the ATR canal is needed. Orano Federal Services (OFS) and its subcontractor Babcock Services Inc. (BSI) were selected to provide remote tooling in order to safely and efficiently size reduce the material currently stored in the ATR canal. INL developed detailed requirements that established the design and performance requirements for the tooling. Orano TN and BSI had recently successfully completed similar tasks in clearing highly activated materials from spent fuel pools and canals at commercial nuclear plants. That experience directly translated into a proven approach that could be used at the ATR thereby saving time and money and lowering risks. Based on BSI's demonstrated proficiency in the design and deployment of remote size reduction specialty tooling at comparable commercial facilities, Orano Federal Services was confident that a solution to INL's requirements could be delivered. The tooling had to be designed to be compatible with the operational requirements of the ATR canal as well as the functionality needed by the facility operators that will use the equipment. Some of the major design requirements and functions of the equipment included remote operations, capability to shear highly irradiated sections of aluminum and steel tubing, pipe, and components ranging in size from 0.6 cm to 16.5 cm diameter into 1.5 m -1.8 m lengths, utilizing buoyancy compensation to assist with underwater operations, and use commercially available existing technology and components as much as practical. The design team evaluated and selected commercially available equipment that could be modified to meet the design and performance specifications. In addition, a waste sizing table (WST) was designed and fabricated to further ensure the size reduction equipment would perform as expected and give the facility operators a stable and usable remote, underwater work platform. After successful development of the tooling, a mock up test and operator training was conducted to ensure the tooling performed as expected and met the requirements of INL. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

An Overview of the Quality Function Deployment (QFD) Technique

QFD is a product planning tool and a process methodology that enables all organizations, departments, and individuals in a business or a project to systematically focus on the critical performance, functions, and/or characteristics of a product that are the most important to the customer. It is part of the Total Quality Management (TQM) concept.. This presentation describes the objectives of QFD, the process for implementing the technique, the benefits derived from proper implementation, the kinds of systems where QFD is best utilized, what the success factors are, how QFD works, some guidelines for selection of a QFD team, and the functional roles of key team members.

Quality Function Deployment QFD customer focus cus↗

THE BOSS EMISSION-LINE LENS SURVEY (BELLS). I. A LARGE SPECTROSCOPICALLY SELECTED SAMPLE OF LENS GALAXIES AT REDSHIFT {approx}0.5

We present a catalog of 25 definite and 11 probable strong galaxy-galaxy gravitational lens systems with lens redshifts 0.4 {approx}< z {approx}< 0.7, discovered spectroscopically by the presence of higher-redshift emission lines within the Baryon Oscillation Spectroscopic Survey (BOSS) of luminous galaxies, and confirmed with high-resolution Hubble Space Telescope (HST) images of 44 candidates. Our survey extends the methodology of the Sloan Lens Advanced Camera for Surveys survey (SLACS) to higher redshift. We describe the details of the BOSS spectroscopic candidate detections, our HST ACS image processing and analysis methods, and our strong gravitational lens modeling procedure. We report BOSS spectroscopic parameters and ACS photometric parameters for all candidates, and mass-distribution parameters for the best-fit singular isothermal ellipsoid models of definite lenses. Our sample to date was selected using only the first six months of BOSS survey-quality spectroscopic data. The full five-year BOSS database should produce a sample of several hundred strong galaxy-galaxy lenses and in combination with SLACS lenses at lower redshift, strongly constrain the redshift evolution of the structure of elliptical, bulge-dominated galaxies as a function of luminosity, stellar mass, and rest-frame color, thereby providing a powerful test for competing theories of galaxy formation and evolution.

79 ASTRONOMY AND ASTROPHYSICS↗

Fatigue life and crack growth prediction methodology

The capabilities of a plasticity-induced crack-closure model and life-prediction code to predict fatigue crack growth and fatigue lives of metallic materials are reviewed. Crack-tip constraint factors, to account for three-dimensional effects, were selected to correlate large-crack growth rate data as a function of the effective-stress-intensity factor range (delta(K(sub eff))) under constant-amplitude loading. Some modifications to the delta(K(sub eff))-rate relations were needed in the near threshold regime to fit small-crack growth rate behavior and endurance limits. The model was then used to calculate small- and large-crack growth rates, and in some cases total fatigue lives, for several aluminum and titanium alloys under constant-amplitude, variable-amplitude, and spectrum loading. Fatigue lives were calculated using the crack growth relations and microstructural features like those that initiated cracks. Results from the tests and analyses agreed well.

Newman, J. C., Jr.↗

Impact of soiling on Si and CdTe PV modules: Case study in different Brazil climate zones

Soiling, particulate accumulation on photovoltaic (PV) module surfaces, reduces the available solar resource and the resulting generated device power. This case-study summarizes initial results of 5-year research on the contrasting soiling conditions in the tropical, subtropical, and semi-arid climates in Brazil. A major objective is to present a case study of the effects of soiling on PV module performance in different Brazil climate zones that represent the primary areas for the current and expanding Brazil solar installations. For this, the paper presents methodologies to quantify the soiling ratio (SRatio) and soiling rate (SRate) for two representative commercial technologies, polycrystalline or multicrystalline silicon (mc-Si) and thin-film cadmium telluride (CdTe) modules, through soiling monitoring stations deployed in the selected climate regions. An aim is to add to the growing soiling-research knowledge base through addressing these key factors and their relationships to critical electrical, solar resource, thermal, and local meteorological and environmental parameters. This paper presents, evaluates, and compares soiling rates and losses in Belo Horizonte, Minas Gerais (Equatorial Tropical: 19.92° S, 43.99° W), Porto Alegre, Rio Grande do Sul (Humid-Subtropical: 30.05° S, 51.17° W), and Brotas de Macaúbas, Bahia (Semi-Arid: 12.00° S, 42.63° W). The results show that soiling is moderate in all 3-regions, for example with 0.1%/day < SRate < 0.2%/day for Belo Horizonte. Precipitation dominates the cleaning of the modules in the summertime in this climate zone, while it is the major factor year-round in Rio Grande do Sul. Wind is the major issue mitigating the soiling accumulation for the Bahia installation. The methodology incorporates several key refinements, including the normalization and adjustment for the meteorological parameters (temperature, irradiance, wind, precipitation). The evaluations include the region-specific differing effects of non-uniform soiling, natural cleaning, and ambient temperatures.

14 SOLAR ENERGY↗

Theoretical calculating the thermodynamic properties of solid sorbents for CO 2 capture applications

Since current technologies for capturing CO 2 to fight global climate change are still too energy intensive, there is a critical need for development of new materials that can capture CO 2 reversibly with acceptable energy costs. Accordingly, solid sorbents have been proposed to be used for CO 2 capture applications through a reversible chemical transformation. By combining thermodynamic database mining with first principles density functional theory and phonon lattice dynamics calculations, a theoretical screening methodology to identify the most promising CO 2 sorbent candidates from the vast array of possible solid materials has been proposed and validated. The calculated thermodynamic properties of different classes of solid materials versus temperature and pressure changes were further used to evaluate the equilibrium properties for the CO 2 adsorption/desorption cycles. According to the requirements imposed by the pre- and post- combustion technologies and based on our calculated thermodynamic properties for the CO 2 capture reactions by the solids of interest, we were able to screen only those solid materials for which lower capture energy costs are expected at the desired pressure and temperature conditions. Only those selected CO 2 sorbent candidates were further considered for experimental validations. The ab initio thermodynamic technique has the advantage of identifying thermodynamic properties of CO 2 capture reactions without any experimental input beyond crystallographic structural information of the solid phases involved. Such methodology not only can be used to search for good candidates from existing database of solid materials, but also can provide some guidelines for synthesis new materials. In this presentation, we first introduce our screening methodology and the results on a testing set of solids with known thermodynamic properties to validate our methodology. Then, by applying our computational method to several different kinds of solid systems, we demonstrate that our methodology can predict the useful information to help developing CO 2 capture Technologies.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗