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Intelligent sensor-model automated control of PMR-15 autoclave processing

An intelligent sensor model system has been built and used for automated control of the PMR-15 cure process in the autoclave. The system uses frequency-dependent FM sensing (FDEMS), the Loos processing model, and the Air Force QPAL intelligent software shell. The Loos model is used to predict and optimize the cure process including the time-temperature dependence of the extent of reaction, flow, and part consolidation. The FDEMS sensing system in turn monitors, in situ, the removal of solvent, changes in the viscosity, reaction advancement and cure completion in the mold continuously throughout the processing cycle. The sensor information is compared with the optimum processing conditions from the model. The QPAL composite cure control system allows comparison of the sensor monitoring with the model predictions to be broken down into a series of discrete steps and provides a language for making decisions on what to do next regarding time-temperature and pressure.

Hart, S.↗

Advanced Power Electronics and Electric Machines

The advanced power electronics and electric machines (APEEM) research group at the National Renewable Energy Laboratory (NREL) has developed world-class experimental and modeling capabilities for designing and evaluating efficient and reliable power electronics and electric machines thermal management systems. They also design, fabricate and characterize advanced power electronics packaging, and are developing state-of-health monitoring techniques. These researchers deliver safe, reliable, high performing, power-dense components that allow seamless integration between renewable energy sources, electric transportation, and the grid, helping to make widespread electric vehicle (EV) adoption and greenhouse gas emissions reduction more feasible. This document outlines the group's major capabilities in the areas of power electronics; module development and characterization; thermal modeling and management; thermomechanical reliability analysis of devices, modules, inverters/converters, and electric machines; physics-of-failure-based reliability analysis; and microelectronics. It also overviews the group's state-of-the-art equipment for fluid-based thermal management; thermal measurement & characterization; thermomechanical reliability analysis; micro- and power electronics measurement & characterization; and prototype fabrication, as well as the group's world-class modeling and simulation capabilities.

advanced gate drivers↗

Laboratory Instrument Software Controlled Spread Spectrum Time Domain Reflectometry for Electrical Cable Testing

This research discusses development of a software-controlled laboratory instrument based spread spectrum time domain reflectometry system (SSTDR). This constitutes one task within PNNL’s Light Water Sustainability Program (LWRS) whose mission includes advancing nondestructive examination (NDE) techniques for off-line and on-line in-situ cable condition monitoring. In 2022, PNNL evaluated SSTDR for detection and characterization of a number of cable anomalies (Glass et al. 2022). The review included comparison of SSTDR to Frequency Domain Reflectometry (FDR) techniques which have enjoyed encouraging feedback and are starting to be used in nuclear power plants for periodic cable condition monitoring of cable systems as part of the plant’s overall cable aging management program. The FDR test introduces a broad-band chirp onto the cable at the cable end then listens for any reflection from a change of impedance along the cable caused by a damaged conductor or insulation, splices, contact with moisture, or other cable anomalies. The signal is captured in the frequency domain then transformed back to the time domain using an inverse Fourier transform (IFT). Based on the velocity of propagation, the impedance response signal is plotted against distance along the cable. Peak locations along the X-axis indicate the distance along the cable where a portion of the signal has been reflected back to the instrument as a result of a cable anomaly. The FDR test is considered the gold standard of reflectometry however it does require the cable to be de-energized to perform the test. The LIVEWIRE commercial SSTDR produces a similar plot to the FDR however all processing is in the time domain. A pseudo-random noise code (PN code) is input onto the cable conductor and the instrument listens for any reflected response from cable anomalies. The SSTDR processes the signal as an autocorrelation comparing the input PN code to any reflected signal detected. The autocorrelation analysis for thermal aging, water and water ingress detection, ground fault and phase-to-phase fault detection at various locations along the cable and with the cable attached and detached from a motor load, and on both energized and un-energized conditions were performed. These results were contrasted to Frequency Domain Reflectometry (FDR) measurements of the un-energized cable. Results were encouraging but indicated more work was warranted – particularly with the SSTDR, it seemed that the insulation damage would likely be better evaluated with multiple bandwidth cable tests particularly including larger bandwidths than were possible with the current commercial instrument. The commercial instrument’s bandwidth was set at 6, 12, 24, and 48MHz but note that SSTDR and FDR definitions of bandwidth trend similarly but are not the same. The FDR response could be more broadly adjusted, and the bandwidth of 100 to 500 MHz produced the best responses. FDR responses to anomalies were clearer than SSTDR responses and indications were that a broader bandwidth SSTDR may lead to improved SSTDR detection capability. This project used a laboratory instrument based SSTDR (primarily using an Arbitrary Waveform Generator (AWG) and a digital oscilloscope plus Python in-house software) that allowed software adjustment of the SSTDR bandwidth, window functions applied to the exciting Pseudo-random Noise (PN) code plus and other aspects of the SSTDR signal processing. Hereafter, this will be referred to as the PNNL SSTDR. Evaluating specific performance of the PNNL SSTDR is left to a separate report. This report documents hardware and software development to produce the SSTDR cable test system.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Condition assessment of cable insulation materials in advanced reactor environments

While existing cable insulation materials are sufficient for use in the current reactor fleet, environmental conditions inside some advanced reactors, such as small modular reactors, will be substantially harsher. The work herein was conducted to assess the performance and overall survivability of several high-temperature, radiation resistant insulation polymers in a simulated small modular reactor environment. The materials evaluated under this research include polyether ether ketone, polyimide, and silicone rubber. These polymers were subjected to 1000 h of environmental stress exposure under two different conditions: 1) high temperature (i.e., 250 °C) in atmospheric pressure and 2) high temperature in a low-pressure vacuum (i.e., less than 2 psia). During the environmental exposure process, each insulation was periodically tested using several materials characterization techniques including Fourier transform infrared spectroscopy, oxidation induction time, and oxidation induction temperature. The objective of this testing was to assess and monitor changes that occurred in the thermal and chemical properties of the materials during the environmental exposures. The overall survivability of each insulation was assessed based on these property changes. The results of this research revealed that the polyimide and polyether ether ketone insulations had significantly better thermal and chemical stability than the silicone rubber during both the high-temperature atmospheric and vacuum exposures. Both polyimide and polyether ether ketone experienced minimal reductions in their chemical and thermal properties over the course of 1000 h in the simulated environments. Finally, based on this research, polyimide and polyether ether ketone show promise as potential base materials for small modular reactor cable insulation.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Monitoring and Modeling Astronaut Occupational Radiation Exposures in Space: Recent Advances

In 1982 astronauts were declared to be radiation workers by OSHA, and as such were subject to the rules and regulations applied to that group. NASA was already aware that space radiation was a hazard to crewmembers and had been studying and monitoring astronaut doses since 1962 at the Johnson Space Center. It was quickly realized NASA would not be able to accomplish all of its goals if the astronauts were subject to the ground based radiation worker limits, and thus received a waiver from OSHA to establish independent limits. As part of the stipulation attached to setting new limits, OSHA included a requirement to perform preflight dose projections for each crew and inform them of the associated risks. Additional requirements included measuring doses from various sources during the flight, making every effort to prevent a crewmember from exceeding the new limits, and keeping all exposures As Low As Reasonably Achievable (a.k.a. ALARA - a common health physics principle). The assembly of the International Space Station (ISS) and its initial manned operations will coincide with the 4-5 year period of high space weather activity at the next maximum in the solar cycle. For the first time in NASA's manned program, US astronauts will be in orbit continuously throughout a solar maximum period. During this period, crews are at risk of significantly increased radiation exposures due to solar particle events and trapped electron belt enhancements following geomagnetic storms. The problem of protecting crews is compounded by the difficulty of providing continuous real-time monitoring over a period of a decade in an era of tightly constrained budgets. In order to prepare for ISS radiological support needs, the NASA Space Radiation Analysis Group and the NOAA Space Environment Center have undertaken a multiyear effort to improve and automate ground-based space weather monitoring systems and real-time radiation analysis tools. These improvements include a coupled, automated space weather monitoring and alarm system--SPE exposure analysis system, an advanced space weather data distribution and display system, and a high-fidelity space weather simulation system. In addition, significant new real-time space weather data sets, which will enhance the forecasting and now-casting of near-Earth space environment conditions, are being made available through unique NASA-NOAA-USAF collaborations. These new data sets include coronal mass ejection monitoring by the Solar and Heliospheric Observatory (SOHO) and in-situ plasma and particle monitoring at the L1 libration point by the Solar Wind Monitor (SWIM) and Advanced Composition Explorer (ACE) spacecraft. Advanced real-time radiation monitoring data from charged particle telescopes and tissue equivalent proportional counters will also be available to assist crew and flight controllers in monitoring the external and intravehicular radiation environment.

Weyland, Mark↗

Advancing ocean monitoring and knowledge for societal benefit: the urgency to expand Argo to OneArgo by 2030

The ocean plays an essential role in regulating Earth’s climate, influencing weather conditions, providing sustenance for large populations, moderating anthropogenic climate change, encompassing massive biodiversity, and sustaining the global economy. Human activities are changing the oceans, stressing ocean health, threatening the critical services the ocean provides to society, with significant consequences for human well-being and safety, and economic prosperity. Effective and sustainable monitoring of the physical, biogeochemical state and ecosystem structure of the ocean, to enable climate adaptation, carbon management and sustainable marine resource management is urgently needed. The Argo program, a cornerstone of the Global Ocean Observing System (GOOS), has revolutionized ocean observation by providing real-time, freely accessible global temperature and salinity data of the upper 2,000m of the ocean (Core Argo) using cost-effective simple robotics. For the past 25 years, Argo data have underpinned many ocean, climate and weather forecasting services, playing a fundamental role in safeguarding goods and lives. Argo data have enabled clearer assessments of ocean warming, sea level change and underlying driving processes, as well as scientific breakthroughs while supporting public awareness and education. Building on Argo’s success, OneArgo aims to greatly expand Argo’s capabilities by 2030, expanding to full-ocean depth, collecting biogeochemical parameters, and observing the rapidly changing polar regions. Providing a synergistic subsurface and global extension to several key space-based Earth Observation missions and GOOS components, OneArgo will enable biogeochemical and ecosystem forecasting and new long-term climate predictions for which the deep ocean is a key component. Driving forward a revolution in our understanding of marine ecosystems and the poorly-measured polar and deep oceans, OneArgo will be instrumental to assess sea level change, ocean carbon fluxes, acidification and deoxygenation. Emerging OneArgo applications include new views of ocean mixing, ocean bathymetry and sediment transport, and ecosystem resilience assessment. Implementing OneArgo requires about $100 million annually, a significant increase compared to present Argo funding. OneArgo is a strategic and cost-effective investment which will provide decision-makers, in both government and industry, with the critical knowledge needed to navigate the present and future environmental challenges, and safeguard both the ocean and human wellbeing for generations to come.

ARGO↗

Microbial Monitoring and the Risk of Infectious Disease Aboard the International Space Station

The International Space Station (ISS) is a semi-closed habitat in low Earth orbit with environmental conditions provided by an advanced life support system that controls temperature and recycles air and most of the potable water. The crew's activities, such as eating, sleeping, hygiene, and laboratory research, are performed in relatively close proximity. Research in the laboratory includes a myriad of experiments, including those with rodents, plants, and pathogenic microorganisms. Despite these conditions, in-flight monitoring of ISS indicates that the microbial diversity is similar to homes on earth. Accordingly, the crew is generally very healthy, however infectious disease does occur and potential routes of infection by obligate and opportunistic pathogens cannot be completely prevented. Determining the extent of this risk is further complicated, as microorganisms can alter their characteristics in response to spaceflight culture, as exemplified by the increase in virulence of the enteric pathogen Salmonella enterica Typhimurium during spaceflight compared to otherwise identical cultures grown on Earth. Taken together, these factors suggest a need for continued microbiological monitoring and research to understand and mitigate the risk of infectious disease during long duration missions.

Ott, C. Mark↗

Improved Prediction of Quasi-Global Vegetation Conditions Using Remotely-Sensed Surface Soil Moisture

The added value of satellite-based surface soil moisture retrievals for agricultural drought monitoring is assessed by calculating the lagged rank correlation between remotely-sensed vegetation indices (VI) and soil moisture estimates obtained both before and after the assimilation of surface soil moisture retrievals derived from the Advanced Microwave Scanning Radiometer-EOS (AMSR-E) into a soil water balance model. Higher soil moisture/VI lag correlations imply an enhanced ability to predict future vegetation conditions using estimates of current soil moisture. Results demonstrate that the assimilation of AMSR-E surface soil moisture retrievals substantially improve the performance of a global drought monitoring system - particularly in sparsely-instrumented areas of the world where high-quality rainfall observations are unavailable.

Bolten, John↗

Development of RGB Composite Imagery for Operational Weather Forecasting Applications

The NASA Short-term Prediction Research and Transition (SPoRT) Center, in collaboration with the Cooperative Institute for Research in the Atmosphere (CIRA), is providing red-green-blue (RGB) color composite imagery to several of NOAA s National Centers and National Weather Service forecast offices as a demonstration of future capabilities of the Advanced Baseline Imager (ABI) to be implemented aboard GOES-R. Forecasters rely upon geostationary satellite imagery to monitor conditions over their regions of responsibility. Since the ABI will provide nearly three times as many channels as the current GOES imager, the volume of data available for analysis will increase. RGB composite imagery can aid in the compression of large data volumes by combining information from multiple channels or paired channel differences into single products that communicate more information than provided by a single channel image. A standard suite of RGB imagery has been developed by the European Organization for the Exploitation of Meteorological Satellites (EUMETSAT), based upon the Spinning Enhanced Visible and Infrared Imager (SEVIRI). The SEVIRI instrument currently provides visible and infrared wavelengths comparable to the future GOES-R ABI. In addition, the Moderate Resolution Imaging Spectroradiometer (MODIS) instruments aboard the NASA Terra and Aqua satellites can be used to demonstrate future capabilities of GOES-R. This presentation will demonstrate an overview of the products currently disseminated to SPoRT partners within the GOES-R Proving Ground, and other National Weather Service forecast offices, along with examples of their application. For example, CIRA has used the channels of the current GOES sounder to produce an "air mass" RGB originally designed for SEVIRI. This provides hourly imagery over CONUS for looping applications while demonstrating capabilities similar to the future ABI instrument. SPoRT has developed similar "air mass" RGB imagery from MODIS, and through a case study example, synoptic-scale features evident in single-channel water vapor imagery are shown in the context of the air mass product. Other products, such as the "nighttime microphysics" RGB, are useful in the detection of low clouds and fog. Nighttime microphysics products from MODIS offer some advantages over single-channel or spectral difference techniques and will be discussed in the context of a case study. Finally, other RGB products from SEVIRI are being demonstrated as precursors to GOES-R within the GOES-R Proving Ground. Examples of "natural color" and "dust" imagery will be shown with relevant applications.

Molthan, Andrew L.↗

Development of Advanced Low Conductivity Thermal Barrier Coatings

Advanced multi-component, low conductivity oxide thermal barrier coatings have been developed using an approach that emphasizes real-time monitoring of thermal conductivity under conditions that are engine-like in terms of temperatures and heat fluxes. This is in contrast to the traditional approach where coatings are initially optimized in terms of furnace and burner rig durability with subsequent measurement in the as-processed or furnace-sintered condition. The present work establishes a laser high-heat-flux test as the basis for evaluating advanced plasma-sprayed and electron beam-physical vapor deposited (EB-PVD) thermal barrier coatings under the NASA Ultra-Efficient Engine Technology (UEET) Program. The candidate coating materials for this program are novel thermal barrier coatings that are found to have significantly reduced thermal conductivities and improved thermal stability due to an oxide-defect-cluster design. Critical issues for designing advanced low conductivity coatings with improved coating durability are also discussed.

Zhu, Dong-Ming↗

Physics-Guided Deep Learning for Complex System Health Management and Decision Making

The landscape of complex engineered systems is rapidly evolving, from smart manufacturing facilities to next-generation transportation vehicles. As these systems become increasingly sophisticated and interconnected, the need for advanced health management systems grows ever more critical. These systems must go beyond simple monitoring, actively predicting potential failures before they occur. This paradigm shift from fixed maintenance schedules to condition-based predictions is key to optimizing system performance, enhancing safety, and paving the way for autonomous decision-making across various industries. Whether in industrial processes, energy systems, or advanced transportation, the ability to anticipate and prevent failures is becoming a cornerstone of operational excellence. To accurately predict the future health of any complex system, knowledge of its current health state and future operational conditions is essential. Recent advancements in data-driven algorithms have generated growing interest in artificial intelligence for industrial applications. However, the limitations of pure data-driven methods, particularly in industries where data acquisition is costly and limited, have become apparent. This has led to a focus on blending physics with data-driven algorithms, mitigating the drawbacks of both approaches while emphasizing their respective advantages. This research proposes a novel framework for integrating physics-based performance models with deep learning algorithms for the prognostics of complex safety-critical systems. In this approach, physics-based models serve as a blueprint, capturing fundamental system behaviors, while deep learning algorithms, leveraging real-world sensor data, fill in gaps and identify subtle patterns indicative of potential problems. This hybrid methodology, utilizing techniques such as Physics-Informed Neural Networks (PINNs), offers a powerful solution for predicting system health. By fusing domain knowledge with data-driven insights, this approach promises more accurate, adaptable, and reliable models for health prediction. The resulting framework is versatile, applicable across various sectors including aerospace, manufacturing, and energy systems, ultimately contributing to safer, more efficient operations in our increasingly complex technological landscape.

Diagnostics↗

Development of an In-Situ Method for Cable Condition Monitoring in Nuclear Power Plants (SBIR Phase IIB Final Report)

This is the final report of a Small Business Innovation Research (SBIR) project that Analysis and Measurement Services Corporation (AMS) has conducted for the U.S. Department of Energy (DOE) over a seven-and-a-half year period (February 2013 through April 2020 with the awards of Phase I, Phase II and Phase IIB projects). The goal of the project was to design, develop, validate, and demonstrate a technique for in-situ testing of cable insulation polymers that will identify, locate, and provide the degree of aging for cables commonly used in nuclear power plants. During the Phase I project, AMS established that the frequency domain reflectometry (FDR) technique can successfully identify and measure cable insulation degradation that can be trended with aging. In Phase II, AMS performed extensive cable aging studies to correlate FDR measurements with other laboratory condition monitoring techniques and developed aging condition categories to quantify the severity of insulation degradation. In Phase IIB, the project expanded the research to include a wider variety of cable polymers that are used in the commercial nuclear power industry. This work also involved developing acceptance criteria to objectively assess age-related cable degradation while sharing the results of this research with industry, academia, and national laboratories to advance the state of the art in cable aging management technologies. The products developed under this research project provide the nuclear industry with an effective condition monitoring tool to support safe and long-term plant operation. Throughout the project, collaborations and support were received from a variety of industry organizations and individuals including DOE National Laboratories as well as nuclear plant utilities and several other industry experts and cable manufacturers. Contributions from these organizations included the donation of new cables, naturally aged cables, and research collaboration. The validation and commercialization of the products of this project were achieved through opportunities to test and demonstrate the technologies’ capabilities on-site at nuclear power generation and research facilities as well as in the laboratory alongside industry peers and cable testing service companies. The research resulted in a technology that can be used to identify, locate, and quantify age-related degradation in several types of cable polymers. This included developing software and hardware as well as the methodology for using the FDR technique to assess age-related degradation of installed cables. The technology developed under this project can provide nuclear plant management, engineers, and technicians with an in-situ electrical test method to determine if in-service cables need to be replaced, monitored on a periodic basis, or show no evidence of significant age-related degradation that may require action. Near the end of this Phase IIB project, the FDR product was sold to a nuclear power utility in South Korea. This sale of a dedicated aging assessment tool is the beginning of a comprehensive contract with the expectation of twelve (12) units sold to that country. Additionally, the FDR technology has been sold to several industry organizations including a nuclear research institute and the Diablo Canyon nuclear power plant. This technology is also being leased by other nuclear industry service companies for incorporation into aging management programs. The cable testing technology that was developed under this project was also integrated into a comprehensive cable aging assessment service that is being offered to the nuclear industry at the request of U.S. nuclear utilities and is currently part of onsite testing services provided by AMS.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

An Experimental Global Monitoring System for Rainfall-triggered Landslides using Satellite Remote Sensing Information

Landslides triggered by rainfall can possibly be foreseen in real time by jointly using rainfall intensity-duration thresholds and information related to land surface susceptibility. However, no system exists at either a national or a global scale to monitor or detect rainfall conditions that may trigger landslides due to the lack of extensive ground-based observing network in many parts of the world. Recent advances in satellite remote sensing technology and increasing availability of high-resolution geospatial products around the globe have provided an unprecedented opportunity for such a study. In this paper, a framework for developing an experimental real-time monitoring system to detect rainfall-triggered landslides is proposed by combining two necessary components: surface landslide susceptibility and a real-time space-based rainfall analysis system (http://trmm.gsfc.nasa.aov). First, a global landslide susceptibility map is derived from a combination of semi-static global surface characteristics (digital elevation topography, slope, soil types, soil texture, and land cover classification etc.) using a GIs weighted linear combination approach. Second, an adjusted empirical relationship between rainfall intensity-duration and landslide occurrence is used to assess landslide risks at areas with high susceptibility. A major outcome of this work is the availability of a first-time global assessment of landslide risk, which is only possible because of the utilization of global satellite remote sensing products. This experimental system can be updated continuously due to the availability of new satellite remote sensing products. This proposed system, if pursued through wide interdisciplinary efforts as recommended herein, bears the promise to grow many local landslide hazard analyses into a global decision-making support system for landslide disaster preparedness and risk mitigation activities across the world.

Hong, Yang↗

Rotorcraft Diagnostics

Health management (HM) in any engineering systems requires adequate understanding about the system s functioning; a sufficient amount of monitored data; the capability to extract, analyze, and collate information; and the capability to combine understanding and information for HM-related estimation and decision-making. Rotorcraft systems are, in general, highly complex. Obtaining adequate understanding about functioning of such systems is quite difficult, because of the proprietary (restricted access) nature of their designs and dynamic models. Development of an EIM (exact inverse map) solution for rotorcraft requires a process that can overcome the abovementioned difficulties and maximally utilize monitored information for HM facilitation via employing advanced analytic techniques. The goal was to develop a versatile HM solution for rotorcraft for facilitation of the Condition Based Maintenance Plus (CBM+) capabilities. The effort was geared towards developing analytic and reasoning techniques, and proving the ability to embed the required capabilities on a rotorcraft platform, paving the way for implementing the solution on an aircraft-level system for consolidation and reporting. The solution for rotorcraft can he used offboard or embedded directly onto a rotorcraft system. The envisioned solution utilizes available monitored and archived data for real-time fault detection and identification, failure precursor identification, and offline fault detection and diagnostics, health condition forecasting, optimal guided troubleshooting, and maintenance decision support. A variant of the onboard version is a self-contained hardware and software (HW+SW) package that can be embedded on rotorcraft systems. The HM solution comprises components that gather/ingest data and information, perform information/feature extraction, analyze information in conjunction with the dependency/diagnostic model of the target system, facilitate optimal guided troubleshooting, and offer decision support for optimal maintenance.

Haste, Deepak↗

Reusable rocket engine turbopump condition monitoring

Significant improvements in engine readiness with attendant reductions in maintenance costs and turnaround times can be achieved with an engine condition monitoring system (CMS). The CMS provides real time health status of critical engine components, without disassembly, through component monitoring with advanced sensor technologies. Three technologies were selected to monitor the rotor bearings and turbine blades: the isotope wear detector and fiber optic deflectometer (bearings), and the fiber optic pyrometer (blades). Signal processing algorithms were evaluated and ranked for their utility in providing useful component health data to unskilled maintenance personnel. Design modifications to current configuration Space Shuttle Main Engine (SSME) high pressure turbopumps and the MK48-F turbopump were developed to incorporate the sensors.

Hampson, M. E.↗

High pressure turbomachinery ground test facility

Turbomachinery test facilities are at present scarce to non-existent world-wide. The turbomachinery test facility at Stennis Space Center will provide for advanced development and research and development capabilities for liquid hydrogen/liquid oxygen propellant rocket engine components. The facility will provide ultra-high pressure via gas generators to deliver the needed turbine drive on various turbomachinery. State of the art process control systems will provide the vital pressure, temperature and flow requirements during tests. These systems will better control adverse transient conditions during start-up and shutdown, and by using advanced control theory, as well as incorporate test article health monitoring. Also, digital data acquisition systems will obtain high frequency (up to 20 KHz) and low frequency (up to 1 KHz) data during the test. Pressures of up to 15,000 psi will be generated to pressurize high pressure tanks supplying cryogens to various test article inlets thus pushing turbopump materials and manufacturing processes to their limits. By planning for future projects the test facility will be easily adaptable to multi-program test configurations over a range of thermodynamic positions.

Scheuermann, Patrick E.↗

Random Vibration Testing of Advanced Wet Tantalum Capacitors

Advanced wet tantalum capacitors allow for improved performance of power supply systems along with substantial reduction of size and weight of the systems that is especially beneficial for space electronics. Due to launch-related stresses, acceptance testing of all space systems includes random vibration test (RVT). However, many types of advanced wet tantalum capacitors cannot pass consistently RVT at conditions specified in MIL-PRF-39006, which impedes their use in space projects. This requires a closer look at the existing requirements, modes and mechanisms of failures, specifics of test conditions, and acceptance criteria. In this work, different lots of advanced wet tantalum capacitors from four manufacturers have been tested at step stress random vibration conditions while their currents were monitored before, during, and after the testing. It has been shown that the robustness of the parts and their reliability are mostly due to effective self-healing processes and limited current spiking or minor scintillations caused by RVT do not increase the risk of failures during operation. A simple model for scintillations events has been used to simulate current spiking during RVT and optimize test conditions. The significance of scintillations and possible effects of gas generation have been discussed and test acceptance criteria for limited current spiking have been suggested.

cracking↗

Random Vibration Testing of Advanced Wet Tantalum Capacitors

Advanced wet tantalum capacitors allow for improved performance of power supply systems along with substantial reduction of size and weight of the systems that is especially beneficial for space electronics. Due to launch-related stresses, acceptance testing of all space systems includes random vibration test (RVT). However, many types of advanced wet tantalum capacitors cannot pass consistently RVT at conditions specified in MIL-PRF-39006, which impedes their use in space projects. This requires a closer look at the existing requirements, modes and mechanisms of failures, specifics of test conditions, and acceptance criteria. In this work, different lots of advanced wet tantalum capacitors from four manufacturers have been tested at step stress random vibration conditions while their currents were monitored before, during, and after the testing. It has been shown that the robustness of the parts and their reliability are mostly due to effective self-healing processes and limited current spiking or minor scintillations caused by RVT do not increase the risk of failures during operation. A simple model for scintillations events has been used to simulate current spiking during RVT and optimize test conditions. The significance of scintillations and possible effects of gas generation have been discussed and test acceptance criteria for limited current spiking have been suggested.

cracking↗