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At least 937 records · Page 52
All sourcesNASA NTRSDOE OSTI
NASA NTRS2016

Characterization of Carbon Dioxide Washout Measurement Techniques in the Mark-III Space Suit

Providing adequate carbon dioxide (CO2) washout is essential to the reduction of risk in performing suited operations. Long term CO2 exposure can lead to symptoms such as headache, lethargy, dizziness, and in severe cases can lead to unconsciousness and death. Thus maintaining adequate CO2 washout in both ground testing and during in flight EVAs is a requirement of current and future suit designs. It is necessary to understand the inspired CO2 of suit wearers such that future requirements for space suits appropriately address the risk of inadequate washout. Testing conducted by the EVA Physiology Laboratory at the NASA Johnson Space Center aimed to characterize a method for noninvasively measuring inspired oronasal CO2 under pressurized suited conditions in order to better inform requirements definition and verification techniques for future CO2 washout limits in space suits. Prior work conducted by the EPL examined several different wearable, respirator style, masks that could be used to sample air from the vicinity surround the nose and mouth of a suited test subject. Previously published studies utilized these masks, some being commercial products and some novel designs, to monitor CO2 under various exercise and flow conditions with mixed results for repeatability and/or consistency between subjects. Based on a meta-analysis of those studies it was decided to test a nasal cannula as it is a commercially available device that is placed directly in the flow path of the user as they breathe. A nasal cannula was used to sample air inhaled by the test subjects during both rest and exercise conditions. Eight subjects were tasked with walking on a treadmill or operating an arm ergometer to reach target metabolic rates of 1000, 2000, and 3000 BTU/hr. Suit pressure was maintained at 4.3 psid for all tests, with supply flow rates of 6, 4, and 2 actual cubic feet per minute depending on the test condition. Each test configuration was conducted twice with subjects breathing either through their nose only, or however they felt comfortable. By restricting breathing through a single orifice, we are able to more accurately define exactly what flow stream the sampled CO2 is taken from. Oronasal CO2 was monitored using real time infrared gas analyzers fed via sample tubes connected to the nasal cannula within the suit. Two additional sampling tubes were placed at the head and chin of the test subject, in an effort to capture CO2 concentrations across the entire flow stream of the Mark-III vent system (flow path is head to neck). Metabolic rate was calculated via the exhaust CO2 concentration and used to adjust subject workload on either the treadmill or arm ergometer until the target was reached. Forward work will aim to characterize the historically accepted minimum ppCO2 in suit during EVA by repeating this study in the Extravehicular Mobility Unit (EMU) space suit. This will help to define washout requirements for future suits, be they NASA (e.g. Z-2) or Commercial Crew designed. Additionally it is important to determine the functional consequences of CO2 exposure during EVA. Severe CO2 symptoms are a result of very high concentration, acute exposures. While long term, low concentration exposures have been shown to result in slight cognitive decline, symptoms resolve upon quickly returning to nominal concentrations and it remains unknown the impact that minor deficits in cognitive performance can have on EVA performance.

Norcross, J.↗
NASA NTRS1993

Arterial gas emboli in altitude-induced decompression sickness

Exposure to high altitudes can result in the evolved-gas condition referred to as decompression sickness (DCS). Ultrasonic monitoring techniques have clearly demonstrated the presence of venous gas emboli (VGE) during decompression. Although important to DCS research and our understanding of the physiological mechanisms of this condition, Venus gas emboli have not been considered clinically hazardous, unless in extreme numbers. Arterial gas emboli (AGE), on the other hand, are generally viewed with great concern. Arterial gas emboli can enter the cerebral arterial circulation and arrest blood flow resulting in potentially serious injury. Left ventricular gas emboli were observed with echo imaging in five volunteer subjects during exposure to simulated altitude. These serendipitous findings occurred during altitude exposure under 3 separate research protocols involving 79 subject exposures. The voluntary, fully informed consent of the subjects used in this research was obtained as required by AFR 169-3. A Hewlett-Packard SONOS 1000 Echo Imaging System was used to monitor for precordial gas emboli. The improved resolution of the SONOS 1000 appears to account for these new findings. Four subjects had high incidence DCS and VGE during previous research flights. One subject only had one flight. The altitudes and AGE onset times for the five cases were: (1) 25,500 ft/2:23, (2) 29,000 ft/0:27, (3) 19,500 ft/3:49, (4) 29,500 ft/3:15, and (5) 29,500 ft/1:31. In all five cases, at the time of AGE onset, the VGE scores were high from all monitored locations. Four of the cases were symptomatic at the time of AGE onset (pain and skin mottling). No cerebral manifestations were observed. All subjects were immediately recompressed to ground level and successfully treated with 2 hours of post-breathing or with hyperbaric oxygen therapy. In conclusion, previously undetected AGE were demonstrated--with and without DCS symptoms--during exposure to altitude. It appears that this gas transferred from the venous side to the arterial side via either intracardiac defects or the pulmonary circulation. The clinical and operational implications of this finding are yet to be determined.

Pilmanis, Andrew A.↗
NASA NTRS2005

Effects of temperature, CO2/O2 concentrations and light intensity on cellular multiplication of microalgae, Euglena gracilis

Microalgae culture is likely to play an important role in aquatic food production modules in bioregenerative systems for producing feeds for fish, converting CO2 to O2 and remedying water quality as well as aquatic higher plants. In the present study, the effects of culture conditions on the cellular multiplication of microalgae, Euglena gracilis, was investigated as a fundamental study to determine the optimum culture conditions for microalgae production in aquatic food production modules including both microalgae culture and fish culture systems. E. gracilis was cultured under conditions with five levels of temperatures (25-33 degrees C), three levels of CO2 concentrations (2-6%), five levels of O2 concentrations (10-30%), and six levels of photosynthetic photon flux (20-200 micromoles m-2 s-1). The number of Euglena cells in a certain volume of solution was monitored with a microscope under each environmental condition. The multiplication rate of the cells was highest at temperatures of 27-31 degrees C, CO2 concentration of 4%, O2 concentration of 20% and photosynthetic photon flux of about 100 micromoles m-2 s-1. The results demonstrate that E. gracilis could efficiently produce biomass and convert CO2 to O2 under relatively low light intensities in aquatic food production modules. c2005 Published by Elsevier Ltd on behalf of COSPAR.

Euglena gracilis/drug effects/growth & development↗
DOE OSTI2024

Emergent Trends Complicate the Interpretation of the United States Drought Monitor (USDM)

Abstract Effective drought management must be informed by an understanding of whether and how current drought monitoring and assessment practices represent underlying nonstationary climate conditions, either naturally occurring or forced by climate change. Here we investigate the emerging climatology and associated trends in drought classes defined by the United States Drought Monitor (USDM), a weekly product that, since 2000, has been used to inform drought management in the United States. The USDM classifies drought intensity based in part on threshold percentiles in key hydroclimate quantities. Here we assess how those USDM‐defined drought threshold percentiles have changed over the last 23 years, examining precipitation, runoff, soil moisture (SM), terrestrial water storage (TWS), vapor pressure deficit (VPD), and near‐surface air temperature. We also assess underlying trends in the frequency of drought classifications across the U.S. Our analysis suggests that the frequency of drought class occurrence is exceeding the threshold percentiles defined by the USDM in a number of regions in the United States, particularly in the American West, where the last 23 years have emerged as a prolonged dry period. These trends are also reflected in percentile‐based thresholds in precipitation, runoff, SM, TWS, VPD, and temperature. Our results emphasize that while the USDM appears to be accurately reflecting observed nonstationarity in the physical climate, such trends raise critical questions about whether and how drought diagnosis, classification, and monitoring should address long‐term intervals of wet and dry periods or trends.

Geology↗
DOE OSTI2020

Calibration and Uncertainty Estimation Using the Ensemble Kalman Filter with a Large Subsurface Flow and Transport Model - 20321

At routinely monitored groundwater contamination sites, periodically measured environmental conditions such as groundwater levels and contaminant concentrations are used to inform and confirm a conceptual site model (CSM) and guide the development and calibration of a numerical groundwater flow and transport model. The calibration of groundwater flow and transport models after each measurement (sampling) event can illuminate deficiencies in a CSM, identify areas where additional monitoring is warranted, and predict the behavior of the system to guide decision making. However, manual and automated (e.g. PEST) model calibration tools can be time-consuming and computationally expensive to implement after each sampling event. Perhaps as a result, such calibration tools generally utilize all available monitoring data simultaneously rather than sequentially assimilating monitoring data one sampling event at a time as the results from sampling become available. A more real-time data assimilation approach may reduce parameter uncertainty, quantify the value of additional monitoring data, and produce a usable model more quickly and with less effort. To mitigate the potential time-consuming aspects of manual and widely applied automated calibration techniques, a data assimilation algorithm called the ensemble Kalman filter (EnKF) was evaluated as a relatively efficient method of model calibration and uncertainty assessment via the sequential integration of monitoring data into a model. The EnKF was able to successfully and efficiently assimilate monitoring and modeling data to calibrate a complex flow and transport model at a real-world site with significant subsurface heterogeneity, uncertainty, and 12 years of monitoring data (over 4,000 individual measurements of groundwater levels and over 2,500 measurements of contaminant concentrations). Starting with an uncalibrated model data from annual sampling events were sequentially assimilated, and the resultant predication errors and estimated parameter uncertainties were tracked. After all monitoring data were assimilated, both flow and transport residuals at the end of the EnKF process were comparable to those produced via a concurrent PEST calibration effort but required fewer model simulations. Both uncertainty and prediction errors decreased over time. In a real-time application, the adequacy of the model could be assessed after each sampling event. The benefits of such a real-time approach to utilizing monitoring data include reduced costs (in the form of model updates or site characterization efforts), early flagging of possible errors in the CSM, and a reduced risk of overfitting and corresponding increased confidence in model predictions. This tool may be particularly useful compared to other calibration techniques (e.g. manual, PEST) when model runtimes are long, calibration parameters are many, or parameter uncertainty is large. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
NASA NTRS2009

Complex Event Recognition Architecture

Complex Event Recognition Architecture (CERA) is the name of a computational architecture, and software that implements the architecture, for recognizing complex event patterns that may be spread across multiple streams of input data. One of the main components of CERA is an intuitive event pattern language that simplifies what would otherwise be the complex, difficult tasks of creating logical descriptions of combinations of temporal events and defining rules for combining information from different sources over time. In this language, recognition patterns are defined in simple, declarative statements that combine point events from given input streams with those from other streams, using conjunction, disjunction, and negation. Patterns can be built on one another recursively to describe very rich, temporally extended combinations of events. Thereafter, a run-time matching algorithm in CERA efficiently matches these patterns against input data and signals when patterns are recognized. CERA can be used to monitor complex systems and to signal operators or initiate corrective actions when anomalous conditions are recognized. CERA can be run as a stand-alone monitoring system, or it can be integrated into a larger system to automatically trigger responses to changing environments or problematic situations.

Fitzgerald, William A.↗
NASA NTRS2011

Utilizing Non-Contact Stress Measurement System (NSMS) as a Health Monitor

Continuously monitor all 156 blades throughout the entire operating envelope without adversely affecting tunnel conditions or compromise compressor shell integrity, Calculate dynamic response and identify the frequency/mode to determine individual blade deflection amplitudes, natural frequencies, phase, and damping (Q), Log static deflection to build a database of deflection values at certain compressor conditions to use as basis for real-time online Blade Stack monitor, Monitor for stall, surge, flutter, and blade damage, Operate with limited user input, low maintenance cost, safe illumination of probes, easy probe replacement, and require little or no access to compressor.

Hayes, Terry↗
DOE OSTI2020

A Flux Detection Probe to Quantify Dynamic Groundwater-Surface Water Exchange in the Hyporheic Zone

A new probe was designed to quantify groundwater-surface water exchange in the hyporheic zone under dynamic stage condition. Current methods focus on either vertical pore water velocity or Darcy flux measurements. Both parameters must be understood to evaluate residence time and mass flux of constituents. Furthermore, most instruments are not well suited for monitoring instantaneous velocity or flux under dynamic exchange conditions. For this reason, the flux detection probe (FDP) was designed that employs electrogeophysical measurements to estimate in situ sediment porosity, which can be used to convert pore water velocity to Darcy flux. Dynamic pore water velocity is obtained by monitoring fluid conductivity and temperature along the FDP probe. Pressure sensors deployed at the top and bottom of the probe provide the additional information necessary to estimate vertical permeability. This study focuses on the use of a geophysical method to estimate pore water velocity, porosity, and permeability within a controlled soil column where simulated river water displaces simulated groundwater. The difference between probe derived and theoretical pore water velocity using natural tracers such as electrical conductivity and temperature was -4.9 and 3.9% for downward flow and 1.1 and 12.8% for upward flow, respectively. The difference in porosity calculated from mass and volume packed in the soil column and probe measure porosity ranged between -3.2% and 1.5%. Also, the calculated hydraulic conductivity differed from probe derived values by -8.9%.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2013

Validation of Helicopter Gear Condition Indicators Using Seeded Fault Tests

A "seeded fault test" in support of a rotorcraft condition based maintenance program (CBM), is an experiment in which a component is tested with a known fault while health monitoring data is collected. These tests are performed at operating conditions comparable to operating conditions the component would be exposed to while installed on the aircraft. Performance of seeded fault tests is one method used to provide evidence that a Health Usage Monitoring System (HUMS) can replace current maintenance practices required for aircraft airworthiness. Actual in-service experience of the HUMS detecting a component fault is another validation method. This paper will discuss a hybrid validation approach that combines in service-data with seeded fault tests. For this approach, existing in-service HUMS flight data from a naturally occurring component fault will be used to define a component seeded fault test. An example, using spiral bevel gears as the targeted component, will be presented. Since the U.S. Army has begun to develop standards for using seeded fault tests for HUMS validation, the hybrid approach will be mapped to the steps defined within their Aeronautical Design Standard Handbook for CBM. This paper will step through their defined processes, and identify additional steps that may be required when using component test rig fault tests to demonstrate helicopter CI performance. The discussion within this paper will provide the reader with a better appreciation for the challenges faced when defining a seeded fault test for HUMS validation.

Dempsey, Paula↗
DOE OSTI2021

Measurement of internal dark current in a 17 GHz accelerator structure with an elliptical sidewall

A 17 GHz single cell, standing wave, copper accelerator structure with an axisymmetric elliptical central cell sidewall was tested for internal and downstream dark current as a function of gradient up to 93 MV/m. The elliptical sidewall was predicted to suppress the internal dark current and the lower order multipactor modes as compared with a previously tested structure having a straight sidewall. During the conditioning phase of the elliptical sidewall structure, strong internal dark current generated by an N = 1 multipactor mode was observed at gradients in the 10 to 20 MV/m range. After conditioning with 2.2x10^5 pulses to 93 MV/m, the N = 1 mode was completely suppressed and no multipactor resonances were observed. The internal dark current was reduced to a comparatively low level, much smaller than in the previously studied, straight sidewall structure, in good agreement with simulations. The energy spectrum of the electrons colliding with the sidewall was measured using an isolated side dark current monitor and a bias voltage. As the conditioning progressed, the electron energy spectrum showed an increase in the concentration of lower energy electrons, also in good agreement with simulations. Studies of internal dark current may help to understand the rf conditioning and ultimate performance of high gradient accelerator structures.

43 PARTICLE ACCELERATORS↗
NASA NTRS2003

The cumulative cost of additional wakefulness: dose-response effects on neurobehavioral functions and sleep physiology from chronic sleep restriction and total sleep deprivation

OBJECTIVES: To inform the debate over whether human sleep can be chronically reduced without consequences, we conducted a dose-response chronic sleep restriction experiment in which waking neurobehavioral and sleep physiological functions were monitored and compared to those for total sleep deprivation. DESIGN: The chronic sleep restriction experiment involved randomization to one of three sleep doses (4 h, 6 h, or 8 h time in bed per night), which were maintained for 14 consecutive days. The total sleep deprivation experiment involved 3 nights without sleep (0 h time in bed). Each study also involved 3 baseline (pre-deprivation) days and 3 recovery days. SETTING: Both experiments were conducted under standardized laboratory conditions with continuous behavioral, physiological and medical monitoring. PARTICIPANTS: A total of n = 48 healthy adults (ages 21-38) participated in the experiments. INTERVENTIONS: Noctumal sleep periods were restricted to 8 h, 6 h or 4 h per day for 14 days, or to 0 h for 3 days. All other sleep was prohibited. RESULTS: Chronic restriction of sleep periods to 4 h or 6 h per night over 14 consecutive days resulted in significant cumulative, dose-dependent deficits in cognitive performance on all tasks. Subjective sleepiness ratings showed an acute response to sleep restriction but only small further increases on subsequent days, and did not significantly differentiate the 6 h and 4 h conditions. Polysomnographic variables and delta power in the non-REM sleep EEG-a putative marker of sleep homeostasis--displayed an acute response to sleep restriction with negligible further changes across the 14 restricted nights. Comparison of chronic sleep restriction to total sleep deprivation showed that the latter resulted in disproportionately large waking neurobehavioral and sleep delta power responses relative to how much sleep was lost. A statistical model revealed that, regardless of the mode of sleep deprivation, lapses in behavioral alertness were near-linearly related to the cumulative duration of wakefulness in excess of 15.84 h (s.e. 0.73 h). CONCLUSIONS: Since chronic restriction of sleep to 6 h or less per night produced cognitive performance deficits equivalent to up to 2 nights of total sleep deprivation, it appears that even relatively moderate sleep restriction can seriously impair waking neurobehavioral functions in healthy adults. Sleepiness ratings suggest that subjects were largely unaware of these increasing cognitive deficits, which may explain why the impact of chronic sleep restriction on waking cognitive functions is often assumed to be benign. Physiological sleep responses to chronic restriction did not mirror waking neurobehavioral responses, but cumulative wakefulness in excess of a 15.84 h predicted performance lapses across all four experimental conditions. This suggests that sleep debt is perhaps best understood as resulting in additional wakefulness that has a neurobiological "cost" which accumulates over time.

NASA Discipline Regulatory Physiology↗
DOE OSTI2021

A Comprehensive Urine Proteome Database Generated From Patients With Various Renal Conditions and Prostate Cancer

Urine proteins can serve as viable biomarkers for diagnosing and monitoring various diseases. A comprehensive urine proteome database, generated from a variety of urine samples with different disease conditions, can serve as a reference resource for facilitating discovery of potential urine protein biomarkers. Herein, we present a urine proteome database generated from multiple datasets using 2D LC-MS/MS proteome profiling of urine samples from healthy individuals (HI), renal transplant patients with acute rejection (AR) and stable graft (STA), patients with non-specific proteinuria (NS), and patients with prostate cancer (PC). A total of ~28,000 unique peptides spanning ~2,200 unique proteins were identified with a false discovery rate of <0.5% at the protein level. Over one third of the annotated proteins were plasma membrane proteins and another one third were extracellular proteins according to gene ontology analysis. Ingenuity Pathway Analysis of these proteins revealed 349 potential biomarkers in the literature-curated database. Forty-three percentage of all known cluster of differentiation (CD) proteins were identified in the various human urine samples. Interestingly, following comparisons with five recently published urine proteome profiling studies, which applied similar approaches, there are still ~400 proteins which are unique to this current study. These may represent potential disease-associated proteins. Among them, several proteins such as serpin B3, renin receptor, and periostin have been reported as pathological markers for renal failure and prostate cancer, respectively. Taken together, our data should provide valuable information for future discovery and validation studies of urine protein biomarkers for various diseases.

60 APPLIED LIFE SCIENCES↗
NASA NTRS1980

Applications of HCMM data to soil moisture snow and estuarine current studies

The author has identified the following significant results. The HCMM thermal data are useful for monitoring estuarine surface thermal patterns. Estuarine thermal patterns, are, under certain conditions, indicative of the surface tidal current circulation patterns. Under optimum conditions, estuaries as small as the Cooper River (i.e., approximately 100 sq km) can be monitored for tidal/thermal circulation patterns by HCMM-type IR sensors.

Wiesnet, D. R.↗
DOE OSTI2025

Summary of Graphite Data Stored within NDMAS

The Graphite Technology Development Project provides data to support the design of graphite core components within specific reactor service conditions of the next generation of high-temperature, gas-cooled nuclear reactors. Physical, mechanical, and thermal properties of nuclear grade graphite were characterized for specimens that were unirradiated, irradiated, and irradiated under various stress conditions. The material properties include diameter, length, mass, density, compressive strength, tensile strength, flexural strength, modulus, resistivity, thermal diffusivity, and thermal expansion coefficient. Baseline graphite specimens are unirradiated from different grades (2114, IG-110, NBG-17, NBG-18, and PCEA) and different types used in different characterization tests (compressive, flexural, tensile, one-inch cylinder, and quarter-inch cylinder). The Advanced Graphite Creep (AGC) irradiation specimens are from a much larger number of grades and cylinder types (creep, piggyback, and pencil). For baseline graphite, characterization data for 7,756 specimens extracted from thirteen graphite billets were captured to the NDMAS database. For AGC experiments, four irradiation campaigns have been completed: AGC-1, AGC-2, AGC-3, and AGC-4. The ongoing HDG-1 (High-Dose Graphite) experiment, which began irradiation with Cycle 168B on August 26, 2020, includes specimens previously irradiated in AGC-2 in addition to the specimens originally destined for AGC-5.. Besides the characterization data, the AGC data includes irradiation monitoring and physics data representing the irradiation conditions of AGC specimens. Currently, all data for AGC-1, AGC-2, and AGC-3 have been captured to the NDMAS database. Only AGC-4 pre-irradiation and irradiation monitoring data have been captured, and HDG-1 pre-irradiation data are in process of being captured for unirradiated specimens. To date, a total of 38,149 material property records have been captured into NDMAS database for baseline and AGC specimens. All characterization data are qualified for use according to their perspective data verification reports. For the AGC irradiation campaigns, a total of 41,502 qualified physics calculation records were added for AGC-1, AGC-2, and AGC-3. Finally, a total of 173,698,505 AGC irradiation monitoring data records (thermocouple temperature, gas flow rate, gas pressure, gas moisture, applied load, and specimen displacement) have been captured to NDMAS; the majority of those records (~94%) are qualified data records.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2023

The variable influence of anthropogenic noise on summer season coastal underwater soundscapes near a port and marine reserve

Monitoring soundscapes is essential for assessing environmental conditions for soniferous species, yet little is known about sound levels and contributors in Oregon coastal regions. From 2017-2021, during June-September, two hydrophones were deployed near Newport, Oregon to sample 10-13,000Hz underwater sound. One hydrophone was deployed near the Port of Newport in a high vessel activity area, and another 17km north within a protected Marine Reserve. Vessel noise and whale vocalizations were detected at both sites, but whales were recorded on more days at the Marine Reserve. Median sound levels in frequencies related to noise from various vessel types and sizes (50-4,000Hz) were up to 6dB higher at the Port of Newport, with greater diel variability compared to the Marine Reserve. In addition to documenting summer season conditions in Oregon waters, these results exemplify how underwater soundscapes can differ over short distances depending on anthropogenic activity.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Assessing the design of integrated methane sensing networks

Abstract While methane is the second largest contributor to global warming after carbon dioxide, it has a larger warming effect over a much shorter lifetime. Despite accelerated technological efforts to radically reduce global carbon dioxide emissions, rapid reductions in methane emissions are needed to limit near-term warming. Being primarily emitted as a byproduct from agricultural activities and energy extraction, methane is currently monitored via bottom–up (i.e. activity level) or top–down (via airborne or satellite retrievals) approaches. However, significant methane leaks remain undetected and emission rates are challenging to characterize with current monitoring frameworks. In this paper, we study the design of a layered monitoring approach that combines bottom–up and top–down approaches as an integrated sensing network. By recognizing that varying meteorological conditions and emission rates impact the efficacy of bottom–up monitoring, we develop a probabilistic approach to optimal sensor placement in its bottom–up network. Subsequently, we derive an inverse Bayesian framework to quantify the improvement that a design-optimized integrated framework has on emission-rate quantifications and their uncertainties. We find that under realistic meteorological conditions, the overall error in estimating the true emission rates is approximately 1.3 times higher, with their uncertainties being approximately 2.4 times higher, when using a randomized network over an optimized network, highlighting the importance of optimizing the design of integrated methane sensing networks. Further, we find that optimized networks can improve scenario coverage fractions by more than a factor of 2 over experimentally-studied networks, and identify a budget threshold beyond which the rate of optimized-network coverage improvement exhibits diminishing returns, suggesting that strategic sensor placement is also crucial for maximizing network efficiency.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Advanced Laboratory and Field Arrays (ALFA)/Lab Collaboration Project (LCP) for Marine Energy (Final Scientific/Technical Report)

The objective of the Advanced Laboratory and Field Arrays (ALFA) project was to reduce the Levelized Cost of Energy (LCOE) of Marine and Hydrokinetic (MHK) energy by leveraging research, development, and testing capabilities at Oregon State University, University of Washington, and the University of Alaska, Fairbanks. ALFA is a project within the Pacific Marine Energy Center (PMEC; formerly NNMREC), a multi-institution entity with a diverse funding base that focuses on research and development for marine renewables. The ALFA project aimed to accelerate the development of next-generation arrays of wave energy conversion (WEC) and tidal energy conversion (TEC) devices through a suite of field-focused R&D activities spanning a broad range of strategic opportunity areas identified in the Funding Opportunity Announcement: • Device and/or array operation and maintenance (O&M) logistics development; • High-fidelity resource characterization and/or modeling technique development and validation; • Array-specific component technology development (e.g. moorings and foundations, transmission, and other offshore grid components); • Array performance testing and evaluation; and • Novel cost-effective environmental monitoring techniques and instrumentation testing and evaluation. The objective of the Lab Collaboration Project (LCP) was to accelerate the development of next-generation marine energy conversion systems. The LCP aimed to achieve these project objectives in collaboration with the national laboratories by: • Developing concept generation and assessment tools; • Improving access to existing testing resources; • Validating collision risk models between fish and turbines; and • Advancing analysis and simulation capabilities for wave-WEC interactions and PTO analysis in nonlinear ocean waves. The ALFA portion of the project was comprised of six overarching technical tasks: • Task 1: Debris Modeling, Detection and Mitigation; • Task 2: Autonomous Monitoring & Intervention; • Task 3: Resource Characterization for Extreme Conditions; • Task 4: Robust Models for Design of Offshore Anchoring and Mooring Systems; • Task 5: Performance Enhancement for Marine Energy Converter (MEC) Arrays; and • Task 6: Evaluating Sampling Techniques for MHK Biological Monitoring. The LCP was divided into four overarching technical tasks: • Task 7: Project Management and Reporting • Task 8: Novel Design and Assessment Methodologies for Wave Energy Converter Design (Wave- SPARC) • Task 9: Testing Access for Commercial Marine Renewable Energy Technology Developers • Task 10: Quantifying Collision Risk for Fish and Turbines • Task 11: Nonlinear Ocean Waves and PTO Control Strategy Each ALFA/LCP task listed above functioned as a separate and discreet project. A final Technical Report was written for each individual task and these reports were uploaded to OSTI, after receiving DOE approval. The following document is a compilation of each of these final, approved reports arranged as individual chapters.

13 HYDRO ENERGY↗
NASA NTRS2001

Design for Vibration Monitoring: A Methodology for Reliable and Cost-Effective Vibration Monitoring

The purpose of health monitoring systems is to detect failures or defects for increased safety and performance and to provide on-condition maintenance with reduced costs. The problems associated with health monitoring systems include high rates of false alarms and missed failures, which make monitoring an unreliable and costly task. The reason for this is that unaccounted variations invalidate signal modeling assumptions. Our approach was to focus on vibration monitoring of rotating components. We analyzed baseline signals to determine statistical variations, identify and model factors that influence vibrations (pre-production vs. post-production variations), determine hit and false alarm rates with baseline flight data, model and predict effects of defects and variations on vibrations, and develop algorithms and metrics for failure and anomaly detection in the presence of variations.

Tumer, Irem Y.↗