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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 73 records · Page 4

Process controls introduction of selected impurities into semiconductor wafers

Modified three-step process controls the concentration of lithium diffused as a dopant into the base region of a diffused n-on-p silicon solar cell wafer. Part of the surface layer of the base region of the p-type silicon containing the diffused dopant is removed, prior to redistributing the remaining portion of the dopant into the bulk of the wafer.

Bartholomay, W. C.↗

Methods of measurement for semiconductor materials, process control, and devices

The development of methods of measurement for semiconductor materials, process control, and devices is discussed. The following subjects are also presented: (1) demonstration of the high sensitivity of the infrared response technique by the identification of gold in a germanium diode, (2) verification that transient thermal response is significantly more sensitive to the presence of voids in die attachment than steady-state thermal resistance, and (3) development of equipment for determining susceptibility of transistors to hot spot formation by the current-gain technique.

Bullis, W. M.↗

Microstructural investigation of an extruded austenitic oxide dispersion strengthened steel containing a carbon-containing process control agent

The adhesion of austenitic oxide dispersion strengthened (ODS) steel during mechanical alloying and a decreased powder production yield can be overcome by the addition of a process control agent: stearic acid. Here, the influence of stearic acid and the introduction of carbon in an extruded and annealed austenitic ODS steel was investigated. In particular the impact of carbon on the precipitate formation, the stability of particle and grain sizes during a heat treatment of 2 h at temperatures in a range between 500 and 1100 °C and the resulting grain size were investigated. No direct influence of carbon on the formation of precipitates was detected in the as-extruded condition. The orientation relationship of oxide nano-particles and the austenitic matrix was found to be size dependent. Also, a surprising growth of oxide precipitates was recorded, which starts at annealing temperatures as low as 700 °C. Precipitates in other steels do not show a growth in this temperature regime at all. For that reason, a possible link between the unexpected growth and the formation of carbides was investigated. M 7 C 3 and M 23 C 6 carbides were found in every sample condition and we were able to show that their amount follows a trend suggested by thermodynamic simulations. The grain size of the extruded austenitic ODS steel was examined and a grain refinement was found after a heat treatment of 2 h at 700 °C or higher was performed. That is caused by the inhabitation of further grain growth after nucleation as part of the recrystallization process has happened. The dragging force exerted by precipitates is strong enough to pin grain boundaries. Furthermore, no direct impact of carbon on the oxide precipitate growth was found, an indirect impact of carbon on the growth of ODS precipitates is supposed but requires long-term annealing studies to be verified.

36 MATERIALS SCIENCE↗

Interoperability for Space Mission Monitor and Control: Applying Technologies from Manufacturing Automation and Process Control Industries

Various issues associated with interoperability for space mission monitor and control are presented in viewgraph form. Specific topics include: 1) Space Project Mission Operations Control Architecture (SuperMOCA) goals and methods for achieving them; 2) Specifics on the architecture: open standards ad layering, enhancing interoperability, and promoting commercialization; 3) An advertisement; 4) Status of the task - government/industry cooperation and architecture and technology demonstrations; and 5) Key features of messaging services and virtual devices.

Jones, Michael K.↗

SAFE-OCC: A novelty detection framework for Convolutional Neural Network sensors and its application in process control

Herein we present a novelty detection framework for Convolutional Neural Network (CNN) sensors that we call Sensor-Activated Feature Extraction One-Class Classification (SAFE-OCC). We show that this framework enables the safe use of computer vision sensors in process control architectures. Emergent control applications use CNN models to map visual data to a state signal that can be interpreted by the controller. Incorporating such sensors introduces a significant system operation vulnerability because CNN sensors can exhibit high prediction errors when exposed to novel (abnormal) visual data. Unfortunately, identifying such novelties in real-time is nontrivial. To address this issue, the SAFE-OCC framework leverages the convolutional blocks of the CNN to create an effective feature space to conduct novelty detection using a desired one-class classification technique. This approach engenders a feature space that directly corresponds to that used by the CNN sensor and avoids the need to derive an independent latent space. We demonstrate the effectiveness of SAFE-OCC via simulated control environments.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Statistical Process Control and Analysis on the Water Content Measurements in NASA Glenn’s Icing Research Tunnel

The Icing Research Tunnel at NASA Glenn follows the recommended practice for calibration outlined in SAE’s ARP5905. The calibration team has followed the schedule of a full calibration every five years with a check calibration done every six months following. The liquid water content of the IRT has maintained stability within the stated specifications of variation within +/- 10% of the curve fit equation generated from calibration data. Using past measurements and data trends, IRT characterization engineers wanted to develop methods for the ability to know when data were not within variation. Trends can be observed in the liquid water content measurement process by constructing statistical process control charts. This paper describes data processing procedures for the Multi-Element Sensor in the IRT, including collision efficiency corrections, canonical correlation analysis, process for rejection of data, and construction of control charts. Data are presented to display the control capability to meet defined liquid water content specifications of the IRT with the Multi-Element Sensor mounted in the center of the test section.

Statistical Process Control↗

Statistical Process Control and Analysis on the Water Content Measurements in NASA Glenn’s Icing Research Tunnel

The Icing Research Tunnel at NASA Glenn follows the recommended practice for calibration outlined in SAE’s ARP5905. The calibration team has followed the schedule of a full calibration every five years with a check calibration done every six months following. The liquid water content of the IRT has maintained stability within the stated specifications of variation within +/- 10% of the curve fit equation generated from calibration data. Using past measurements and data trends, IRT characterization engineers wanted to develop methods for the ability to know when data were not within variation. Trends can be observed in the liquid water content measurement process by constructing statistical process control charts. This paper describes data processing procedures for the Multi-Element Sensor in the IRT, including collision efficiency corrections, canonical correlation analysis, process for rejection of data, and construction of control charts. Data are presented to display the control capability to meet defined liquid water content specifications of the IRT with the Multi-Element Sensor mounted in the center of the test section.

Statistical Process Control↗

SU-E-CAMPUS-T-04: Statistical Process Control for Patient-Specific QA in Proton Beams

Purpose: To evaluate and improve the reliability of proton QA process, to provide an optimal customized level using the statistical process control (SPC) methodology. The aim is then to suggest the suitable guidelines for patient-specific QA process. Methods: We investigated the constancy of the dose output and range to see whether it was within the tolerance level of daily QA process. This study analyzed the difference between the measured and calculated ranges along the central axis to suggest the suitable guidelines for patient-specific QA in proton beam by using process capability indices. In this study, patient QA plans were classified into 6 treatment sites: head and neck (41 cases), spinal cord (29 cases), lung (28 cases), liver (30 cases), pancreas (26 cases), and prostate (24 cases). Results: The deviations for the dose output and range of daily QA process were ±0.84% and ±019%, respectively. Our results show that the patient-specific range measurements are capable at a specification limit of ±2% in all treatment sites except spinal cord cases. In spinal cord cases, comparison of process capability indices (Cp, Cpm, Cpk ≥1, but Cpmk ≤1) indicated that the process is capable, but not centered, the process mean deviates from its target value. The UCL (upper control limit), CL (center line) and LCL (lower control limit) for spinal cord cases were 1.37%, −0.27% and −1.89%, respectively. On the other hands, the range differences in prostate cases were good agreement between calculated and measured values. The UCL, CL and LCL for prostate cases were 0.57%, −0.11% and −0.78%, respectively. Conclusion: SPC methodology has potential as a useful tool to customize an optimal tolerance levels and to suggest the suitable guidelines for patient-specific QA in clinical proton beam.

60 APPLIED LIFE SCIENCES↗

Status of the nuclear measurement stations for the process control of spent fuel reprocessing at AREVA NC/La Hague

Nuclear measurements are used at AREVA NC/La Hague for the monitoring of spent fuel reprocessing. The process control is based on gamma-ray spectroscopy, passive neutron counting and active neutron interrogation, and gamma transmission measurements. The main objectives are criticality and safety, online process monitoring, and the determination of the residual fissile mass and activities in the metallic waste remained after fuel shearing and dissolution (empty hulls, grids, end pieces), which are put in radioactive waste drums before compaction. The whole monitoring system is composed of eight measurement stations which will be described in this paper. The main measurement stations no. 1, 3 and 7 are needed for criticality control. Before fuel element shearing for dissolution, station no. 1 allows determining the burn-up of the irradiated fuel by gamma-ray spectroscopy with HP Ge (high purity germanium) detectors. The burn-up is correlated to the {sup 137}Cs and {sup 134}Cs gamma emission rates. The fuel maximal mass which can be loaded in one bucket of the dissolver is estimated from the lowest burn-up fraction of the fuel element. Station no. 3 is dedicated to the control of the correct fuel dissolution, which is performed with a {sup 137}Cs gamma ray measurement with a HP Ge detector. Station no. 7 allows estimating the residual fissile mass in the drums filled with the metallic residues, especially in the hulls, from passive neutron counting (spontaneous fission and alpha-n reactions) and active interrogation (fission prompt neutrons induced by a pulsed neutron generator) with proportional {sup 3}He detectors. The measurement stations have been validated for the reprocessing of Uranium Oxide (UOX) fuels with a burn-up rate up to 60 GWd/t. This paper presents a brief overview of the current status of the nuclear measurement stations. (authors)

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Derivation of sequential, real-time, process-control programs

The use of weakest-precondition predicate transformers in the derivation of sequential, process-control software is discussed. Only one extension to Dijkstra's calculus for deriving ordinary sequential programs was found to be necessary: function-valued auxiliary variables. These auxiliary variables are needed for reasoning about states of a physical process that exists during program transitions.

Marzullo, Keith↗

Methods of measurement for semiconductor materials, process control, and devices

Activities directed toward the development of methods of measurement for semiconductor materials, process control, and devices are described. Topics investigated include: measurements of transistor delay time; application of the infrared response technique to the study of radiation-damaged, lithium-drifted silicon detectors; and identification of a condition that minimizes wire flexure and reduces the failure rate of wire bonds in transistors and integrated circuits under slow thermal cycling conditions. Supplementary data concerning staff, standards committee activities, technical services, and publications are included as appendixes.

Bullis, W. M.↗

Methods of measurement for semiconductor materials, process control, and devices

Activities directed toward the development of methods of measurement for semiconductor materials, process control, and devices are described. Accomplishments include the determination of the reasons for differences in measurements of transistor delay time, identification of an energy level model for gold-doped silicon, and the finding of evidence that it does not appear to be necessary for an ultrasonic bonding tool to grip the wire and move it across the substrate metallization to make the bond. Work is continuing on measurement of resistivity of semiconductor crystals; study of gold-doped silicon; development of the infrared response technique; evaluation of wire bonds and die attachment; measurement of thermal properties of semiconductor devices, delay time, and related carrier transport properties in junction devices, and noise properties of microwave diodes; and characterization of silicon nuclear radiation detectors.

Bullis, W. M.↗

SU-F-T-294: The Analysis of Gamma Criteria for Delta4 Dosimetry Using Statistical Process Control

Purpose: To evaluate the sensitivity of gamma criteria for patient-specific volumetric modulated arc therapy(VMAT) quality assurance of the Delta{sup 4} dosimetry program using the statistical process control(SPC) methodology. Methods: The authors selected 20 patient-specific VMAT QA cases which were undertaken MapCHECK and ArcCHECK with gamma pass rate better than 97%. The QAs data were collected Delta4 Phantom+ and Elekta Agility six megavolts without using an angle incrementer. The gamma index(GI) were calculated in 2D planes with normalizing deviation to local dose(local gamma). The sensitivity of the GI methodology using criterion of 3%/3mm, 3%/2mm and 2%/3mm was analyzed with using process acceptability indices. We used local confidence(LC) level, the upper control limit(UCL) and lower control limit(LCL) of I-MR chart for process capability index(Cp) and a process acceptability index (Cpk). Results: The lower local confidence levels of 3%/3mm, 3%/2mm and 2%/3mm were 92.0%, 83.6% and 78.8% respectively. All of the calculated Cp and Cpk values that used LC level were under 1.0 in this study. The calculated LCLs of I-MR charts were 89.5%, 79.0% and 70.5% respectively. These values were higher than 1.0 which means good quality of QA. For the generally used lower limit of 90%, we acquired over 1.3 of Cp value for the gamma index of 3%/3mm and lower than 1.0 in the rest of GI. Conclusion: We applied SPC methodology to evaluate the sensitivity of gamma criteria and could see the lower control limits of VMAT QA for the Delta 4 dosimetry and could see that Delta 4 phantom+ dosimetry more affected by the position error and the I-MR chart derived values are more suitable for establishing lower limits. Acknowledgement: This research was supported by Basic Science Research Program through the National Research Foundation of Korea(NRF) funded by the Ministry of Education (No. 2015R1D1A1A01060463)

60 APPLIED LIFE SCIENCES↗

TRA Warm Waste Treatment Facility Process Controller Replacement

This poster details the work I did to replace the TRA Warm Waste Treatment System Process Controller. Additionally, my poster explains what Warm waste is, how the warm waste treatment system functions, and the next steps moving forward in the engineering process.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗