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This poster outlines several projects conducted on behalf of the construction EHS&Q staff at INL. Among the projects outlined is noise dosimetry conducted on numerous people working with the construction projects, chemical inventories gathered from several construction subcontractors, and secondary chemical container label creation.
It is important to control acoustic noise aboard the International Space Station (ISS) to provide a satisfactory environment for voice communications, crew productivity, and restful sleep, and to minimize the risk for temporary and permanent hearing loss. Acoustic monitoring is an important part of the noise control process on ISS, providing critical data for trend analysis, noise exposure analysis, validation of acoustic analysis and predictions, and to provide strong evidence for ensuring crew health and safety, thus allowing Flight Certification. To this purpose, sound level meter (SLM) measurements and acoustic noise dosimetry are routinely performed. And since the primary noise sources on ISS include the environmental control and life support system (fans and airflow) and active thermal control system (pumps and water flow), acoustic monitoring will indicate changes in hardware noise emissions that may indicate system degradation or performance issues. This paper provides the current acoustic levels in the ISS modules and sleep stations, and is an update to the status presented in 20031. Many new modules, and sleep stations have been added to the ISS since that time. In addition, noise mitigation efforts have reduced noise levels in some areas. As a result, the acoustic levels on the ISS have improved.
It is important to control acoustic noise aboard the International Space Station (ISS) to provide a satisfactory environment for voice communications, crew productivity, alarm audibility, and restful sleep, and to minimize the risk for temporary and permanent hearing loss. Acoustic monitoring is an important part of the noise control process on ISS, providing critical data for trend analysis, noise exposure analysis, validation of acoustic analyses and predictions, and to provide strong evidence for ensuring crew health and safety, thus allowing Flight Certification. To this purpose, sound level meter (SLM) measurements and acoustic noise dosimetry are routinely performed. And since the primary noise sources on ISS include the environmental control and life support system (fans and airflow) and active thermal control system (pumps and water flow), acoustic monitoring will reveal changes in hardware noise emissions that may indicate system degradation or performance issues. This paper provides the current acoustic levels in the ISS modules and sleep stations and is an update to the status presented in 2011. Since this last status report, many payloads (science experiment hardware) have been added and a significant number of quiet ventilation fans have replaced noisier fans in the Russian Segment. Also, noise mitigation efforts are planned to reduce the noise levels of the T2 treadmill and levels in Node 3, in general. As a result, the acoustic levels on the ISS continue to improve.
On July 4, 1982, the Space Shuttle Columbia landed at Edwards Air Force Base, CA, thus successfully completing the fourth and last in a series of Orbital Flight Tests (OFT) of the Space Transportation System (STS). The primary goal of medical operations support for the OFT was to assure the health and well-being of flight personnel during all phases of the mission. To this end, crew health status was evaluated preflight, inflight, and postflight. Biomedical flight test requirements were completed in the following areas: physiological adaptation to microgravity, cabin acoustical noise, cabin atmospheric evaluation, radiation dosimetry, crew exercise equipment evaluation, and a cardiovascular deconditioning countermeasure assessment.
Environmental noise in space vehicles, caused by onboard equipment and crew activities, has generated concerns for crew health and safety since early U.S. space missions. The International Space Station (ISS) provides a unique environment where acoustic conditions can be monitored while crewmembers from the U.S. and their international partners work and live for as long as 6 to 12 consecutive months. This review of acoustic dosimetry data collected to date reveals that the noise exposure limits of NASA’s stringent noise constraint flight rule have been exceeded in 41% of these dosimetry measurements since ISS Increment 17 (2008), with undefined impacts to crew. These measurements do not take into account the effects of hearing protection devices worn by the crew. The purpose of this paper is to provide an update on ISS noise exposure monitoring approaches and hearing conservation strategies that include acoustic dosimetry data collected since the ISS Increment 55 mission (April 2018). Future directions and recommendations for the ISS noise exposure monitoring program will also be presented, including research initiatives aimed at better defining the impact of ISS noise on crew health and performance.
Environmental noise in space vehicles caused by onboard equipment and noisy activities has generated concerns for crew health and safety since early U.S. space missions. The International Space Station (ISS) provides a unique environment where acoustic conditions can be monitored while crewmembers from the U.S. and their international partners work and live for as long as 6 to 12 consecutive months. This review of acoustic dosimetry data collected to date reveals that the noise exposure limits of NASA’s stringent noise constraint flight rule have been exceeded in 41% of these dosimetry measurements since ISS Increment 17 (2008), with undefined impacts to crew. These measurements do not take into account the effects of hearing protection devices worn by the crew. The purpose of this paper is to provide an update on ISS noise exposure monitoring approaches and hearing conservation strategies that include acoustic dosimetry data collected since the ISS Increment 55 mission (April 2018). Future directions and recommendations for the ISS noise exposure monitoring program will also be presented, including research initiatives aimed at better defining the impact of ISS noise on crew health and performance.
The International Space Station (ISS) is a unique workplace environment for U.S. astronauts and Russian cosmonauts to conduct research and live for a period of six months or more. Noise has been an enduring environmental physical hazard that has been a challenge for the U.S. space program since before the Apollo era. Noise exposure in ISS poses significant risks to the crewmembers, such as; hearing loss (temporary or permanent), possible disruptions of crew sleep, interference with speech intelligibility and communication, possible interference with crew task performance, and possible reduction in alarm audibility. Acoustic measurements are made aboard ISS and compared to requirements in order to assess the acoustic environment to which the crewmembers are exposed. The purpose of this paper is to describe in detail the noise exposure monitoring program as well as an assessment of the acoustic dosimeter data collected to date. The hardware currently being used for monitoring the noise exposure onboard ISS will be discussed. Acoustic data onboard ISS has been collected since the beginning of ISS (Increment 1, November 2000). Noise exposure data analysis will include acoustic dosimetry logged data from crew-worn during work and sleep periods and also fixed-location measurements from Increment 1 to present day. Noise exposure levels (8-, 16- and 24-hr), LEQ, will also be provided and discussed in this paper. Discussions related to hearing protection will also be included. Future directions and recommendations for the noise exposure monitoring program will be highlighted. This acoustic data is used to ensure a safe and healthy working and living environment for the crewmembers aboard the ISS.
The International Space Station (ISS) is a unique workplace environment for U.S. astronauts and Russian cosmonauts to conduct research and live for a period of six months or more. Noise has been an enduring environmental physical hazard that has been a challenge for the U.S. space program since before the Apollo era. Noise exposure in ISS poses significant risks to the crewmembers, such as; hearing loss (temporary or permanent), possible disruptions of crew sleep, interference with speech intelligibility and communication, possible interference with crew task performance, and possible reduction in alarm audibility. Acoustic measurements were made onboard ISS and compared to requirements in order to assess the acoustic environment to which the crewmembers are exposed. The purpose of this paper is to describe in detail the noise exposure monitoring program as well as an assessment of the acoustic dosimeter data collected to date. The hardware currently being used for monitoring the noise exposure onboard ISS will be discussed. Acoustic data onboard ISS has been collected since the beginning of ISS (Increment 1, November 2001). Noise exposure data analysis will include acoustic dosimetry logged data from crew-worn dosimeters during work and sleep periods and also fixed-location measurements from Increment 1 to present day. Noise exposure levels (8-, 16- and 24-hr), LEQ, will also be provided and discussed in this paper. Future directions and recommendations for the noise exposure monitoring program will be highlighted. This acoustic data is used to ensure a safe and healthy working and living environment for the crewmembers onboard the ISS.
Single event upset phenomena are discussed, taking into account cosmic ray induced errors in IIL microprocessors and logic devices, single event upsets in NMOS microprocessors, a prediction model for bipolar RAMs in a high energy ion/proton environment, the search for neutron-induced hard errors in VLSI structures, soft errors due to protons in the radiation belt, and the use of an ion microbeam to study single event upsets in microcircuits. Basic mechanisms in materials and devices are examined, giving attention to gamma induced noise in CCD's, the annealing of MOS capacitors, an analysis of photobleaching techniques for the radiation hardening of fiber optic data links, a hardened field insulator, the simulation of radiation damage in solids, and the manufacturing of radiation resistant optical fibers. Energy deposition and dosimetry is considered along with SGEMP/IEMP, radiation effects in devices, space radiation effects and spacecraft charging, EMP/SREMP, and aspects of fabrication, testing, and hardness assurance.
Data illustrating the radiation response of emerging high gain, low noise detectors are presented. Ionizing dose testing of silicon internal discrete avalanche photodiodes, and 51-MeV proton testing of InGaAs/InAlAs avalanche photodiodes operated in Geiger mode are discussed.
Topics covered include: Video Mosaicking for Inspection of Gas Pipelines; Shuttle-Data-Tape XML Translator; Highly Reliable, High-Speed, Unidirectional Serial Data Links; Data-Analysis System for Entry, Descent, and Landing; Hybrid UV Imager Containing Face-Up AlGaN/GaN Photodiodes; Multiple Embedded Processors for Fault-Tolerant Computing; Hybrid Power Management; Magnetometer Based on Optoelectronic Microwave Oscillator; Program Predicts Time Courses of Human/ Computer Interactions; Chimera Grid Tools; Astronomer's Proposal Tool; Conservative Patch Algorithm and Mesh Sequencing for PAB3D; Fitting Nonlinear Curves by Use of Optimization Techniques; Tool for Viewing Faults Under Terrain; Automated Synthesis of Long Communication Delays for Testing; Solving Nonlinear Euler Equations With Arbitrary Accuracy; Self-Organizing-Map Program for Analyzing Multivariate Data; Tool for Sizing Analysis of the Advanced Life Support System; Control Software for a High-Performance Telerobot; Java Radar Analysis Tool; Architecture for Verifiable Software; Tool for Ranking Research Options; Enhanced, Partially Redundant Emergency Notification System; Close-Call Action Log Form; Task Description Language; Improved Small-Particle Powders for Plasma Spraying; Bonding-Compatible Corrosion Inhibitor for Rinsing Metals; Wipes, Coatings, and Patches for Detecting Hydrazines; Rotating Vessels for Growing Protein Crystals; Oscillating-Linear-Drive Vacuum Compressor for CO2; Mechanically Biased, Hinged Pairs of Piezoelectric Benders; Apparatus for Precise Indium-Bump Bonding of Microchips; Radiation Dosimetry via Automated Fluorescence Microscopy; Multistage Magnetic Separator of Cells and Proteins; Elastic-Tether Suits for Artificial Gravity and Exercise; Multichannel Brain-Signal-Amplifying and Digitizing System; Ester-Based Electrolytes for Low-Temperature Li-Ion Cells; Hygrometer for Detecting Water in Partially Enclosed Volumes; Radio-Frequency Plasma Cleaning of a Penning Malmberg Trap; Reduction of Flap Side Edge Noise - the Blowing Flap; and Preventing Accidental Ignition of Upper-Stage Rocket Motors.
In this work, we provide an analytical model for the total ionizing dose (TID) effects on the bit error statistics of commercial flash memory chips. We have validated the model with experimental data collected by irradiating several commercial NAND flash memory chips from different technology nodes. We find that our analytical model can project bit errors at higher TID values (~ 20 krad(Si)) from measured data at lower TID values (<1 krad(Si)). Based on our model and the measured data, we have formulated basic design rules for using a commercial flash memory chip as a dosimeter. We discuss the impact of NAND chip-to-chip variability, noise margin and the intrinsic errors on the dosimeter design using detailed experimentation.
Environmental screening of gamma radiation consists of detecting weak nuisance and anomaly signal in the presence of strong and highly varying background. In a typical scenario, a mobile detector-spectrometer continuously measures gamma radiation spectra in short, e.g., one-second, signal acquisition intervals. The measurement data is a 2D matrix, where one dimension is gamma ray energy, and the other dimension is the number of measurements or total time. In principle, gamma radiation sources can be detected and identified from the measured data by their unique spectral lines. Detecting sources from data measured in a search scenario is difficult due to the highly varying background because of naturally occurring radioactive material (NORM), and low signal-to-noise ratio (S/N) of spectral signal measured during one-second acquisition intervals. The objective of this work is to explore supervised machine learning (ML) algorithms for development of a Hopfield Neural Network (HNN) in conjunction with an image processing algorithm for detection and identification of weak nuisances and anomalies events in the presence of a highly fluctuating background.
Radiation dosimetry aboard LDEF, as well as post-flight measurements of the radioactivity induced in numerous LDEF spacecraft components, provide unique data for evaluating the accuracy of current models for predicting both the space radiation environments (trapped proton intensity, spectra, and directionality; cosmic ray fluence) and the radiation environments induced in spacecraft components (fluence, energy spectra, secondary particle, linear energy transfer, etc.). By determining the accuracy of such models using LDEF data, and with model updates where required, improved radiation environment predictions can be made for future missions, which in turn allows improved predictions for specific radiation effects for future spacecraft components (single event upsets of microelectronics, radiation damage to focal plane arrays, noise in sensitive instrumentation, etc.). Herein, the status and results from radiation model predictions and comparisons with LDEF data is given. The calculations are made using radiation transport codes coupled with a 3-D geometry/mass model of LDEF, together with current models of the space radiation environment.
Environmental screening of gamma radiation consists of detecting weak nuisance and anomaly signal in the presence of strong and highly varying background. In a typical scenario, a mobile detector-spectrometer continuously measures gamma radiation spectra in short, e.g., one-second, signal acquisition intervals. In principle, gamma radiation sources can be detected and identified by their unique spectral lines. However, detecting sources from data measured in a search scenario is difficult due to the highly varying background because of naturally occurring radioactive material (NORM), and low signal-to-noise ratio (S/N) of spectral signal measured during one-second acquisition intervals. In recent prior work, we have developed a Hopfield Neural Network (HNN) in conjunction with an image processing algorithm to detect a weak signal anomaly hidden among the highly fluctuating background spectra. The objective of this work is to explore quantum computing methods to increase the speed of HNN. The approach is based on the Grover’s search algorithm in conjunction with a 3-SAT problem formalism. The Grover’s algorithm is implemented on a quantum computing simulator using Qiskit software. Performance of HNN algorithm is benchmarked using search data from an environmental screening campaign, where the anomaly is a subset of measurements containing a 137 Cs source. Results indicate that using Grover’s algorithm on a quantum simulator reduces runtime of HNN by two orders of magnitude.
Environmental screening of gamma radiation consists of detecting weak nuisance and anomaly signal in the presence of strong and highly varying background. In a typical scenario, a mobile detector-spectrometer continuously measures gamma radiation spectra in short, e.g., one-second, signal acquisition intervals. The measurement data is a 2D matrix, where one dimension is gamma ray energy, and the other dimension is the number of measurements or total time. In principle, gamma radiation sources can be detected and identified from the measured data by their unique spectral lines. Detecting sources from data measured in a search scenario is difficult due to the highly varying background because of naturally occurring radioactive material (NORM), and low signal-to-noise ratio (S/N) of spectral signal measured during one-second acquisition intervals. The objective of this work is to explore unsupervised machine learning (ML) algorithms for detection and identification of weak nuisances and anomalies events in the presence of highly fluctuating background. The challenge is that spectral lines of isotopes are difficult to observe in one-second measurements. Averaging over the entire measurement campaign data set reveals spectral lines of most common background isotopes. Spectral lines of orphan sources, which might appear only in a few measurements during the campaign, will be washed out if averaging is performed over the entire measurement data set. The approach we have explored consists of extracting one-second measurements containing weak spectral features through data clustering. Averaging one-second spectra in a cluster should reveal the presence of anomaly sources. We created two ML models using K-means clustering and Neural Network Self-organizing Map (SOM). Performance of these ML models was benchmarked using search data. One data set contained 137 Cs source, and another dataset contained 131 I source.
We report the effect of EH 6/7 electron trap centers alone on the performance of high-resolution radiation detectors fabricated on n-type 4H–SiC epitaxial layers. A Schottky barrier detector (SBD) and a metal-oxide-semiconductor (MOS) capacitor detector fabricated using two sister samples derived from the same 50 μm 4H–SiC parent wafer exhibited widely different energy resolutions of 0.4% and 0.9% for 5486 keV alpha particles. An equivalent noise charge model analysis ruled out the effect of the detector capacitance and the leakage current on the resolution of the detectors. Deep level transient spectroscopic studies revealed the presence of two trapping centers in each detector within the temperature scan range 240–800 K. The Z 1/2 center, a potential electron trap, was detected in both the detectors in equal concentration, which suggested that the observed difference in the energy resolution is due to the presence of the other defect, the EH 6/7 center, in the SBD. The capture cross section of the EH 6/7 center was calculated to be three orders of magnitude higher than the second defect [a carbon antisite vacancy (CAV) center] observed in the MOS detector with an activation energy of 1.10 eV, which accounted for the enhanced electronic trapping in the SBD leading to its poor energy resolution. It has been proposed that the EH 6/7 centers in the SBD have likely been reconfigured to CAV pairs during the thermal growth of the silicon dioxide layer in the MOS detector. The proposed formation mechanism of CAV, a stable qubit state for quantum information processing, addresses the outstanding questions related to the role of defect dynamics in their formation.
Nuclear Safety is a review journal that covers significant developments in the field of nuclear safety. Its scope includes the analysis and control of hazards associated with nuclear energy, operations involving fissionable materials, and the products of nuclear fission and their effects on the environment. Primary emphasis is on safety in reactor design, construction, and operation; however, the safety aspects of the entire fuel cycle, including fuel fabrication, spent-fuel processing, nuclear waste disposal, handling of radioisotopes, and environmental effects of these operations, are also treated. Table of Contents for this issue follows. GENERAL SAFETY CONSIDERATIONS: 1 Technical Note: A New Approach to Fission Reactor Safety, Yu. V. Petrov; 5 Erratum; ACCIDENT ANALYSIS: 6 Analysis and Modeling of Fission Product Release from Various Uranium-Aluminum Plate-Type Reactor Fuels, R. P. Taleyarkhan; CONTROL AND INSTRUMENTATION: 23 Applications of a Surveillance and Diagnostics Methodology Using Neutron Noise From a Pressurized-Water Reactor, R. T. Wood, L. F. Miller, and R. B. Perez; DESIGN FEATURES: 36 Westinghouse Advanced Passive 600 Plant, B. A. McIntyre and R. K. Beck; 47 System 80+™ PWR Safety Design, C. W. Bagnal, R. A. Matzie, and R. S. Turk; ENVIRONMENTAL EFFECTS: 58 The MATS Experiments—Mesoscale Atmospheric Transport Studies at the Savannah River Site, A. H. Weber, S. Berman, R. J. Kurzeja, and R. P. Addis; 75 Book Review: Environmental Radioactivity in the European Community 1984-1985-1986, C. A. Little; WASTE AND SPENT FUEL MANAGEMENT: 76 Activities Related to Waste and Spent Fuel Management, M. D. Muhlheim and E. G. Silver; OPERATING EXPERIENCES: 87 Aging Assessment of BWR Control Rod Drive Systems, R. H. Greene; 100 Reactor Shutdown Experience, Compiled by J. W. Cletcher; 103 Selected Safety-Related Events, Compiled by G. A. Murphy; 110 Operating U.S. Power Reactors, Compiled by M. D. Muhlheim and E. G. Silver; RECENT DEVELOPMENTS: 129 General Administrative Activities, Compiled by M. D. Muhlheim and E. G. Silver; 139 Reports, Standards, and Safety Guides, D. S. Queener; 143 Proposed Rule Changes as of Sept. 30 1991; ANNOUNCEMENTS: 128 Harvard School of Public Health Announces Short Courses; 128 16th Biennial ANS Topical Meeting on Reactor Operating Experience: Present and Future Technologies—Applying Lessons Learned (Call for Papers); 147 The Authors; 150 Indexes to Nuclear Safety, Volume 32; 154 Errata.