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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
All sourcesNASA NTRSDOE OSTI
NASA NTRS1994

A fuzzy classifier system for process control

A fuzzy classifier system that discovers rules for controlling a mathematical model of a pH titration system was developed by researchers at the U.S. Bureau of Mines (USBM). Fuzzy classifier systems successfully combine the strengths of learning classifier systems and fuzzy logic controllers. Learning classifier systems resemble familiar production rule-based systems, but they represent their IF-THEN rules by strings of characters rather than in the traditional linguistic terms. Fuzzy logic is a tool that allows for the incorporation of abstract concepts into rule based-systems, thereby allowing the rules to resemble the familiar 'rules-of-thumb' commonly used by humans when solving difficult process control and reasoning problems. Like learning classifier systems, fuzzy classifier systems employ a genetic algorithm to explore and sample new rules for manipulating the problem environment. Like fuzzy logic controllers, fuzzy classifier systems encapsulate knowledge in the form of production rules. The results presented in this paper demonstrate the ability of fuzzy classifier systems to generate a fuzzy logic-based process control system.

Karr, C. L.↗
DOE OSTI2019

Effects of Process Control Agents on Characteristics of Cu-Ta Nanocomposite during Milling and Subsequent Sintering

Effects of type and concentration of process control agent on characteristics of the nanocrystalline Cu-1Ta nanocomposite during milling and subsequent sintering were investigated. Microstructural analyses showed that addition of stearic acid (SA) into Cu-1Ta mixture was more effective compared to toluene. The results revealed that application of 2% SA provided a significant dissolution of Ta in Cu lattice after milling for 32 h; however, the extended milling encouraged Ta rejection and increased the crystallite size. Reduction of SA to 1% resulted in a narrower crystallite size distribution with mean size of 18.5 nm. The mechanical and physical tests also indicated that addition of 1% SA rather than 2% toluene caused an increase of 33% in electrical conductivity with nearly no change in micro-hardness.

36 MATERIALS SCIENCE↗
DOE OSTI2013

Spectroscopic online monitoring for process control and safeguarding of radiochemical streams

This paper summarizes application of the absorption and vibrational spectroscopic techniques supplemented by physicochemical measurements for radiochemical process monitoring. In this context, our team experimentally assessed the potential of Raman and spectrophotometric techniques for online real-time monitoring of the U(VI)/nitrate ion/nitric acid and Pu(IV)/Np(V)/Nd(III), respectively, in solutions relevant to spent fuel reprocessing. These techniques demonstrate robust performance in the repetitive batch measurements of each analyte in a wide concentration range using simulant and commercial dissolved spent fuel solutions. Spectroscopic measurements served as training sets for the multivariate data analysis to obtain partial least squares predictive models, which were validated using on-line centrifugal contactor extraction tests. Satisfactory prediction of the analytes concentrations in these preliminary experiments warrants further development of the spectroscopy-based methods for radiochemical process control and safeguarding. Additionally, the ability to identify material intentionally diverted from a liquid-liquid extraction contactor system was successfully tested using on-line process monitoring as a means to detect the amount of material diverted. (authors)

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2025

Crossing the Finish Line: Integration of Data-Driven Process Control for Maximization of Energy and Resource Efficiency in Advanced Water Resource Recovery Facilities

Improvements in process monitoring and control at water resource recovery facilities (WRRFs) could result in reductions in electricity consumption, chemical inputs, and greenhouse gas emissions, as well as improved energy recovery. Many current WRRF data collection, monitoring, and control approaches use 20th century process monitoring and control systems, which require large design safety factors to ensure reliability in the absence of more advanced, precise controls. Implementation of more modern data-driven control tools could lead to more efficient operations that provide intrinsic reliability with better overall process performance at full-scale. This project (1) developed and demonstrated data-driven process controls at full-scale facilities for five promising WRRF process technologies that provide whole-plant approaches and offer substantial energy and resource recovery benefits, and (2) created a Machine Learning (ML) Toolkit and an implementation guide of new process control approaches that walks users through each step of the ML workflow and illustrates the steps through case study examples.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1967

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.↗
NASA NTRS1971

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.↗
DOE OSTI2013

Spectroscopic Online Monitoring for Process Control and Safeguarding of Radiochemical Fuel Reprocessing Streams - 13553

There is a renewed interest worldwide to promote the use of nuclear power and close the nuclear fuel cycle. The long term successful use of nuclear power is critically dependent upon adequate and safe processing and disposition of the used nuclear fuel. Liquid-liquid extraction is a separation technique commonly employed for the processing of the dissolved spent nuclear fuel. The instrumentation used to monitor these processes must be robust, require little or no maintenance, and be able to withstand harsh environments such as high radiation fields and aggressive chemical matrices. This paper discusses application of absorption and vibrational spectroscopic techniques supplemented by physicochemical measurements for radiochemical process monitoring. In this context, our team experimentally assessed the potential of Raman and spectrophotometric techniques for on-line real-time monitoring of the U(VI)/nitrate ion/nitric acid and Pu(IV)/Np(V)/Nd(III), respectively, in solutions relevant to spent fuel reprocessing. Both techniques demonstrated robust performance in the repetitive batch measurements of each analyte in a wide concentration range using simulant and commercial dissolved spent fuel solutions. Static spectroscopic measurements served as training sets for the multivariate data analysis to obtain partial least squares predictive models, which were validated using on-line centrifugal contactor extraction tests. Satisfactory prediction of the analytes concentrations in these preliminary experiments warrants further development of the spectroscopy-based methods for radiochemical safeguards and process control. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2019

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↗
NASA NTRS1998

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.↗
DOE OSTI2022

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↗
NASA NTRSDate not supplied

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↗
NASA NTRSDate not supplied

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↗
DOE OSTI2014

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↗
DOE OSTI2015

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↗