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At least 1,459 records · Page 81

Evaluating the Global Water and Energy Cycles in Reanalyses Using Ensemble Spread

Reanalyses provide continuous observation based global data over weather and climate time scales through observational assimilation. Ensemble forecasts are a component of modern data assimilation systems, providing information to the analysis process. Storing this spread over the duration of a climate reanalysis will provide insight to the variations of the model that underlies the reanalysis data. Global water and energy cycles (WECs) are a critical aspect of both weather and climate, yet there are some large gaps in the observation of key components as well as their representation in models and reanalyses. NASA’s Water and Energy cycle Studies (NEWS) program is developing a corrected and balanced budget data set that is closed at monthly and regional scales during the 21st century, so far. In this paper, we will evaluate reanalysis WEC components against the initial NEWS collection of observation, but integrate the analysis spread from the reanalysis data assimilation as a new perspective on the evaluation. The initial evaluation will cover a few more recent years using ERA5 10 member spread. As the GMAO’s production of the Modern-Era Retrospective analysis for Research and Applications 21st Century (MERRA-21C) progresses, the effort will include the MERRA-21C 32 member spread. Ultimately, we will explore the potential of the ensemble spread as a measure of uncertainty in the reanalysis.

Michael Bosilovich↗

Irradiation Testing of Ultrasonic Transducers

Ultrasonic technologies offer the potential for high accuracy and resolution in-pile measurement of numerous parameters, including geometry changes, temperature, crack initiation and growth, gas pressure and composition, and microstructural changes. Many Department of Energy-Office of Nuclear Energy (DOE-NE) programs are exploring the use of ultrasonic technologies to provide enhanced sensors for in-pile instrumentation during irradiation testing. For example, the ability of single, small diameter ultrasonic thermometers (UTs) to provide a temperature profile in candidate metallic and oxide fuel would provide much needed data for validating new fuel performance models. Other efforts include an ultrasonic technique to detect morphology changes (such as crack initiation and growth) and acoustic techniques to evaluate fission gas composition and pressure. These efforts are limited by the lack of existing knowledge of ultrasonic transducer material survivability under irradiation conditions. To address this need, the Pennsylvania State University (PSU) was awarded an Advanced Test Reactor National Scientific User Facility (ATR NSUF) project to evaluate promising magnetostrictive and piezoelectric transducer performance in the Massachusetts Institute of Technology Research Reactor (MITR) up to a fast fluence of at least 1021 n/cm2 (E> 0.1 MeV). This test will be an instrumented lead test; and real-time transducer performance data will be collected along with temperature and neutron and gamma flux data. By characterizing magnetostrictive and piezoelectric transducer survivability during irradiation, test results will enable the development of novel radiation tolerant ultrasonic sensors for use in Material and Test Reactors (MTRs). The current work bridges the gap between proven out-of-pile ultrasonic techniques and in-pile deployment of ultrasonic sensors by acquiring the data necessary to demonstrate the performance of ultrasonic transducers

Daw, J.↗

A visual study of radial inward choked flow of liquid nitrogen

A visual study of the radial inward choked flow of liquid nitrogen was conducted. Data and high speed moving pictures were obtained. The study indicated the following: (1) steady radial inward choked flow seems equivalent to steady choked flow through axisymmetric nozzles, (2) transient choked flows through the radial gap are not uniform and the discharge pattern appears as nonuniform impinging jets, and (3) the critical mass flow rate data for the transient case appear different from those of the steady case.

Hendricks, R. C.↗

Multi-dimensional resilience: A quantitative exploration of disease outcomes and economic, political, and social resilience to the COVID-19 pandemic in six countries

The COVID-19 pandemic has highlighted a need for better understanding of countries’ vulnerability and resilience to not only pandemics but also disasters, climate change, and other systemic shocks. A comprehensive characterization of vulnerability can inform efforts to improve infrastructure and guide disaster response in the future. In this paper, we propose a data-driven framework for studying countries’ vulnerability and resilience to incident disasters across multiple dimensions of society. To illustrate this methodology, we leverage the rich data landscape surrounding the COVID-19 pandemic to characterize observed resilience for several countries (USA, Brazil, India, Sweden, New Zealand, and Israel) as measured by pandemic impacts across a variety of social, economic, and political domains. We also assess how observed responses and outcomes (i.e., resilience) of the COVID-19 pandemic are associated with pre-pandemic characteristics or vulnerabilities, including (1) prior risk for adverse pandemic outcomes due to population density and age and (2) the systems in place prior to the pandemic that may impact the ability to respond to the crisis, including health infrastructure and economic capacity. Our work demonstrates the importance of viewing vulnerability and resilience in a multi-dimensional way, where a country’s resources and outcomes related to vulnerability and resilience can differ dramatically across economic, political, and social domains. This work also highlights key gaps in our current understanding about vulnerability and resilience and a need for data-driven, context-specific assessments of disaster vulnerability in the future.

59 BASIC BIOLOGICAL SCIENCES↗

Modelling urban-scale occupant behaviour, mobility, and energy in buildings: A survey

The proliferation of urban sensing, IoT, and big data in cities provides unprecedented opportunities for a deeper understanding of occupant behaviour and energy usage patterns at the urban scale. This enables data-driven building and energy models to capture the urban dynamics, specifically the intrinsic occupant and energy use behavioural profiles that are not usually considered in traditional models. Although there are related reviews, none have investigated urban data for use in modelling occupant behaviour and energy use at multiple scales, from buildings to neighbourhood to city. This survey paper aims to fill this gap by providing a critical summary and analysis of the works reported in the literature. We present the different sources of occupant-centric urban data that are useful for data-driven modelling and categorise the range of applications and recent data-driven modelling techniques for urban behaviour and energy modelling, along with the traditional stochastic and simulation-based approaches. Finally, we present a set of recommendations for future directions in data-driven modelling of occupant behaviour and energy in buildings at the urban scale.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

CHESS 2025: Leaf Area Index (LAI) for meadow, shrub, tree, and understory vegetation

This dataset contains Leaf Area Index (LAI) measurements made as part of the Colorado Headwaters Ecological Spectroscopy Study (CHESS) during June and July of 2025. Data were collected in the Upper Gunnison Basin, Colorado, across three study domains: the Upper East River (CRBU), Almont Triangle (ALMO), and the Upper Taylor Basin (UPTA). Field observations of LAI were collected within 72 hours of airborne data collection by the National Ecological Observatory Network’s Aerial Observation Platform (NEON AOP). The NEON AOP collected waveform LiDAR (Light Detection and Ranging) and imaging spectrometer data in 426 spectral bands from the visible to shortwave infrared. LAI measurements were collected using the LICOR LAI-2200C Plant Canopy Analyzer following protocols outlined in the instrument manual (LI-COR 2019). Sampling targeted four distinct vegetation types: meadows, shrubs, trees, and aspen forest understory. We have archived data separately by site type because different field methods were used for each. At meadow sites, measurements were made at the four corners of 1m x 1m plots, with the instrument moving inward toward the center of the plot. At shrub sites, we measured the canopies of individual shrubs. At tree sites, we made measurements within a 10m x 10m subplot centered around a focal tree, with 30 observations taken on a regular grid. At aspen understory sites, we measured overstory trees following the tree protocol and understory herbaceous vegetation following the meadow protocol. All measurements included above-canopy (A) and below-canopy (B) readings, with specific protocols for scattering correction measurements in direct-sun conditions. Data were processed using the R package `rlai` (Worsham 2025). This package includes functions to calculate LAI, gap fraction, apparent clumping factor (Ω), scattering correction, and other canopy metrics. Package contents: Full file descriptions appear in ‘flmd.csv’. Files named according to the convention ‘lai_*_summary_data_cleaned.csv’ contain summary values of LAI, apparent clumping factor (Ωapp), and scattering correction factors for each site. These are the analysis-ready products that most data users will work with. Files named ‘lai_*_metadata_cleaned.csv’ contain additional site-level observations made during field collection. We have also archived intermediate and supplementary data for users who wish to check our processing approach or apply alternative methods. ‘raw_lai_2200C.zip’ contains the raw files as read from the LI-COR instrument, with no processing applied, in TXT format. The zip archive contains subdirectories by site type, which are further subdivided by sampling area. Filenames correspond to the sampling site number. ‘intermediate_results.zip’ contains detailed output from the processing routines, in JSON format. The zip archive contains subdirectories by site type; filenames correspond to the sampling site number. ‘scattering_correction_logs.zip’ contains logfiles from the implementation of Kobayashi et al.'s (2013) scattering correction algorithm. The logfiles report values of several parameters at each iteration of the algorithm, as the model converges toward a stable solution. They are intended for users who want to verify scattering correction performance. The zip archive contains subdirectories by site type; filenames correspond to the sampling site number. ‘spot_checks.csv’ reports LAI and other values for a small number of files processed with LI-COR FV2200 software (LI-COR 2013) using the same control parameters as in our R-based approach. Additional metadata are provided in a data dictionary describing column names and definitions (dd.csv), and in a file-level metadata file (flmd.csv). All zip files can be expanded with common archive utilities. TXT, CSV, and JSON files can be ingested into R or Python computing environments or read in common text editor utilities. Geospatial information: Geospatial data for mapping measurement site locations are in the files CHESS_polygons_lai_UTM.geojson, CHESS_polygons_shrub_UTM.geojson, and CHESS_polygons_meadow_UTM.geojson in the companion geospatial package for the 2025 CHESS campaign, ‘CHESS 2025: Location data for field observations and sampling’ (Henderson et al., 2026). CHESS Project Description: The Colorado Headwaters Ecological Spectroscopy Study (CHESS) comprised a multi-week airborne remote sensing and field observation campaign in the Upper Gunnison Basin, Colorado, conducted in June and July of 2025. Airborne remote sensing was conducted by the National Ecological Observatory Network Airborne Observation Platform (NEON AOP), concurrent with a field campaign run by the Rocky Mountain Biological Laboratory (RMBL), the Lawrence Berkeley National Laboratory (LBNL) and SLAC National Accelerator Laboratory Watershed Function Science Focus Area (SFA), and NASA-JPL (Jet Propulsion Laboratory) Earth Surface Mineral Dust Source Investigation (EMIT) program. Between June 10 and July 18, 2025, the NEON AOP flight team collected high-resolution aerial imaging spectroscopy and Light Detection and Ranging (LiDAR) data over three domains: the Upper East River (CRBU), Almont Triangle (ALMO), and the Upper Taylor Basin (UPTA). In coordination with the flights, a field campaign acquired ground-truth observations, including observations of vegetation composition, foliar traits, forest demography, and subsurface properties in 18 core sampling areas within the domains. Additional surface water observations were taken at over 380 point locations. All CHESS campaign datasets can be found within the CHESS ESS-DIVE data portal: https://data.ess-dive.lbl.gov/portals/chess. Funding Acknowledgement: Field and remote-sensing data acquisition was performed under a grant from the National Aeronautics and Space Administration (80NSSC24K1005). This work was also supported by the Watershed Function Science Focus Area at Lawrence Berkeley National Laboratory funded by the US Department of Energy, Office of Science, Biological and Environmental Research under Contract No. DE-AC02-05CH11231. * Todorov and Worsham are co–first authors.

2018 NEON and 2025 CHESS Campaigns↗

Simulated imaging properties of a series of magnetic electron lenses

The paraxial lens data were determined for a series of symmetrical magnetic lenses of equal lens diameter but variable air gap width for a wide range of lens excitations using the three-dimensional electrodynamic computer code MAFIA. The results are compared with a similar study done by Liebman and Grad wherein the field distributions within the lenses were measured experimentally with a resistance network analogue. Using these fields the lens data were obtained through numerical trajectory tracing. The utility of using MAFIA, instead of experimental methods for lens design is shown by the excellent agreement of the simulated results compared to experiment. Also demonstrated is the capability of using MAFIA to investigate aberration sources such as higher order off-axis magnetic field and space-charge effects.

Kory, Carol L.↗

Light-Curve Modelling Constraints on the Obliquities and Aspect Angles of the Young Fermi Pulsars

In more than four years of observation the Large Area Telescope on board the Fermi satellite has identified pulsed gamma-ray emission from more than 80 young or middle-aged pulsars, in most cases providing light curves with high statistics. Fitting the observed profiles with geometrical models can provide estimates of the magnetic obliquity alpha and of the line of sight angle zeta, yielding estimates of the radiation beaming factor and radiated luminosity. Using different gamma-ray emission geometries (Polar Cap, Slot Gap, Outer Gap, One Pole Caustic) and core plus cone geometries for the radio emission, we fit gamma-ray light curves for 76 young or middle-aged pulsars and we jointly fit their gamma-ray plus radio light curves when possible. We find that a joint radio plus gamma-ray fit strategy is important to obtain (alpha, zeta) estimates that can explain simultaneously detectable radio and gamma-ray emission: when the radio emission is available, the inclusion of the radio light curve in the fit leads to important changes in the (alpha, gamma) solutions. The most pronounced changes are observed for Outer Gap and One Pole Caustic models for which the gamma-ray only fit leads to underestimated alpha or zeta when the solution is found to the left or to the right of the main alpha-zeta plane diagonal respectively. The intermediate-to-high altitude magnetosphere models, Slot Gap, Outer Gap, and One pole Caustic, are favored in explaining the observations. We find no apparent evolution of α on a time scale of 106 years. For all emission geometries our derived gamma-ray beaming factors are generally less than one and do not significantly evolve with the spin-down power. A more pronounced beaming factor vs. spin-down power correlation is observed for Slot Gap model and radio-quiet pulsars and for the Outer Gap model and radio-loud pulsars. The beaming factor distributions exhibit a large dispersion that is less pronounced for the Slot Gap case and that decreases from radio-quiet to radio-loud solutions. For all models, the correlation between gamma-ray luminosity and spin-down power is consistent with a square root dependence. The gamma-ray luminosities obtained by using the beaming factors estimated in the framework of each model do not exceed the spin-down power. This suggests that assuming a beaming factor of one for all objects, as done in other studies, likely overestimates the real values. The data show a relation between the pulsar spectral characteristics and the width of the accelerator gap. The relation obtained in the case of the Slot Gap model is consistent with the theoretical prediction.

neutron aEuro" pulsars:↗

Occurrence of Equatorial F Region Irregularities: Evidence for Tropospheric Seeding

We present a new gap-free version of the seasonal and longitudinal 0 (s/l) variations of P(sub EFI), the equatorial F region irregularity (EFI) occurrence probability, based on data from the AE-E spacecraft. The agreement of this and three earlier partial P(sub EFI) patterns verifies all four. We reinterpret another earlier gap-ridden pattern, that of D(bar)(sub RSF), a topside ionogram index of average darkening by range spread F. We compare it with P(sub EFI) and, using ionosonde radio science considerations, we conclude that D(bar)(sub RSF) = P(sub EFI) times a factor depending on the average number of topside plasma bubbles visible to the ionosonde. The s/l variations of D(baar)(sub RSF) thus imply s/l variations in the average spacing of bubbles, whose seeds have an occurrence probability pattern P(sub seed). For discussion we assume P(sub EFI) = P(sub inst)P(sub seed) is the pattern of F region instability. The P(sub EFI) pattern, which is by definition independent of seed and/or bubble spacing, is far too complex to be explained by the dominant paradigm, that of changes in P(sub inst) by simple changes in the F region altitude and/or north-south asymmetry. We examine evidence behind this dominance, and find it unconvincing. Both the asymmetry and sunset-node/altitude hypotheses of 1984 and 1985, respectively, seem to be partly based on misunderstood data, and their features appear displaced in time and space from those of our repeatable P(sub EFI) pattern. In contrast, if P(sub seed) variations influence the P(sub EFI) pattern and depend on thermospheric gravity waves from tropospheric convection near the dip equator, then the seasonal maxima (minima) Of P(sub EFI) could be explained, since they all occur above relatively warm (cold) surface features, where convection is maximal (minimal). Also, the hypothesis of the dominance of the P(sub seed) term could explain an unusual December/January P(sub EFI) maximum in the deep, wide, normal Pacific minimum in the one data set obtained in El Nino years. Based on the experiments we consider, we predict that the s/l variations Of P(sub seed) will be found to be similar to those of P(sub EFI) and largely to explain them. Finally, we find reasons, based on the similarity of the D(sub RSF) variations to s/l patterns of the average scintillation index, for not using, as is commonly done, such scintillation patterns as substitutes for P(sub EFI) or P(sub inst) patterns.

McClure, J. P.↗

Problem Reporting Taxonomy and Data Preparation Tool Evaluation

A member of the NASA Engineering and Safety Center (NESC) Systems Engineering Office (SEO) Technical Discipline Team (TDT) requested a SEO-managed activity to perform a gap analysis on the proposed NASA Standard 0006, "Common NASA Taxonomy for Problem Reporting, Analysis, and Resolution", and to create an input filter and set of instructions for using the data-mining/data-cleansing tool TechOasis1 with Space Shuttle Program (SSP) problem reporting data. The work that achieved these objectives and deployment of TechOasis are discussed in this report.

Beil, Robert J.↗

Event-to-Video Conversion for Overhead Object Detection

Collecting overhead imagery using an event camera is desirable due to the energy efficiency of the image sensor compared to standard cameras. However, event cameras complicate downstream image processing, especially for complex tasks such as object detection. In this paper, we investigate the viability of event streams for overhead object detection. We demonstrate that across a number of standard modeling approaches, there is a significant gap in performance between dense event representations and corresponding RGB frames. We establish that this gap is, in part, due to a lack of overlap between the event representations and the pre-training data that the object detectors were initially trained on through a number of experiments. Then, apply an off-the-shelf event-to-video conversion tool that converts event streams into gray-scale video to close this gap. We demonstrate that this approach results in a large performance increase, outperforming even event-specific object detection techniques on our overhead target task. These results suggest that better aligning event representations with existing large pre-trained models may result in greater short-term performance gains compared to end-to-end event-specific architectural improvements.

machine learning (ML), computer vision, Neuromorph↗

Upping the Ante: The TESS Mission Shortens Full Frame Images to 10 Minutes and Introduces a Twenty-Second Data Collection Mode

The Transiting Exoplanet Survey Satellite (TESS) recently completed its initial two-year, near all-sky survey, identifying over 79 exoplanets and over 2000 exoplanet candidates. The mission is well on its way to find at least 50 small, nearby exoplanets for which masses can be ascertained and whose atmospheres can be characterized by ground- and space-based follow-on observations. TESS has unveiled a plethora of exciting non-exoplanet astrophysics results, such as asteroseismology, asteroids, and supernova. In the extended mission, TESS is collecting full frame images (FFIs) at 10-minute intervals rather than at 30-minute intervals, as was the case for the two-year primary mission. TESS is also collecting and providing photometry for up to 1000 20-sec targets in addition to the 20,000 target star postage stamps collected at 2-min intervals. The extended mission will also feature a five-month interval in which the 24°x96° field of view (FOV) will be rotated by 90°from its normal North-South orientation to observe a swath of the ecliptic plane. The FOVs for the remainder of the extended mission will be offset in latitude from those of the prime mission to help fill in the gaps in the full sky coverage. We discuss the performance and behavior of the data products generated by the TESS Science Processing Operations Center (SPOC) at NASA Ames Research Center and highlight the new 20-sec data mode and the 10-min FFIs. The TESS Mission is funded by NASA's Science Mission Directorate as an Astrophysics Explorer Mission.

TESS↗

Private sector involvement in civil space remote sensing. Volume 1: Report

A survey of private sector developers, users, and interpreters of Earth resources data was conducted in an effort to encourage private investment and participation in remote sensing systems. Results indicate positive interest in participation beyond the current hardware contracting level, however, there is a substantial gap between current market levels and system costs. Issues identified include the selection process for an operating entity, the public/private interface, data collection and access policies, price and profit regulation in a subsidized system, international participation, and the responsibility for research and development. It was agreed that the cost, complexity, and security implications of integrated systems need not be an absolute bar to their private operation.

Source record↗

Large Area Scene Selection Interface (LASSI). Methodology of Selecting Landsat Imagery for the Global Land Survey 2005

The Global Land Survey (GLS) 2005 is a cloud-free, orthorectified collection of Landsat imagery acquired during the 2004-2007 epoch intended to support global land-cover and ecological monitoring. Due to the numerous complexities in selecting imagery for the GLS2005, NASA and the U.S. Geological Survey (USGS) sponsored the development of an automated scene selection tool, the Large Area Scene Selection Interface (LASSI), to aid in the selection of imagery for this data set. This innovative approach to scene selection applied a user-defined weighting system to various scene parameters: image cloud cover, image vegetation greenness, choice of sensor, and the ability of the Landsat 7 Scan Line Corrector (SLC)-off pair to completely fill image gaps, among others. The parameters considered in scene selection were weighted according to their relative importance to the data set, along with the algorithm's sensitivity to that weight. This paper describes the methodology and analysis that established the parameter weighting strategy, as well as the post-screening processes used in selecting the optimal data set for GLS2005.

Franks, Shannon↗

The Anatomy of Software Changes and Bugs in Autonomous Operating System

Cyberphysical systems with autonomous functions are complex pieces of software, consisting of many components, some of which implement autonomous functionality and some may use AI or machine learning algorithms. Software bugs in an autonomous system are of particular concern, as they can have catastrophic consequences. However, detailed studies based on empirical data are rare and therefore these bugs are not well understood. This paper aims to contribute towards filling that gap by investigating the software changes and bugs in Autonomy Operating System (AOS) for Unmanned Aircraft Systems (UAS), which consist of 26 components containing about 103,000 lines of code and having a total of 772 bugfixes. Based on the data extracted from the code repository and semi-structured interviews with the developers of AOS, we explore the differences among autonomous software components, components developed using Model-based Software Engineering, and reuse with respect to change proneness, fault proneness, distribution of bugfixes among AOS components and files of these components, and characteristics of bugs of different AOS components. Our results show that the autonomous components were significantly more change prone (measured in number of commits and code churn) and fault prone (measured in bugfixes per KLoC) than non-autonomous components. The distribution of the locations of bugfixes was skewed, both at component and file level (i.e., a small number of components / files contained the majority of bugs). These evidence-based findings provide important insights to researchers and practitioners alike and can be used to efficiently improve the quality and reliability of autonomous systems.

Katerina Goseva-Popstojanova↗

Three-Dimensional Analysis of Deep Space Network Antenna Coverage

There is a need to understand NASA s Deep Space Network (DSN) coverage gaps and any limitations to provide redundant communication coverage for future deep space missions, especially for manned missions to Moon and Mars. The DSN antennas are required to provide continuous communication coverage for deep space flights, interplanetary missions, and deep space scientific observations. The DSN consists of ground antennas located at three sites: Goldstone in USA, Canberra in Australia, and Madrid in Spain. These locations are not separated by the exactly 120 degrees and some DSN antennas are located in the bowl-shaped mountainous terrain to shield against radiofrequency interference resulting in a coverage gap in the southern hemisphere for the current DSN architecture. To analyze the extent of this gap and other coverage limitations, simulations of the DSN architecture were performed. In addition to the physical properties of the DSN assets, the simulation incorporated communication forward link calculations and azimuth/elevation masks that constrain the effects of terrain for each DSN antenna. Analysis of the simulation data was performed to create coverage profiles with the receiver settings at a deep space altitudes ranging from 2 million to 10 million km and a spherical grid resolution of 0.25 degrees with respect to longitude and latitude. With the results of these simulations, two- and three-dimensional representations of the area without communication coverage and area with coverage were developed, showing the size and shape of the communication coverage gap projected in space. Also, the significance of this communication coverage gap is analyzed from the simulation data.

Kegege, Obadiah↗

Cost‐benefit assessment framework for robotics‐driven inspection of floating offshore wind farms

Abstract Operations and maintenance (O&M) of floating offshore wind farms (FOWFs) poses various challenges in terms of greater distances from the shore, harsher weather conditions, and restricted mobility options. Robotic systems have the potential to automate some parts of the O&M leading to continuous feature‐rich data acquisition, operational efficiency, along with health and safety improvements. There remains a gap in assessing the techno‐economic feasibility of robotics in the FOWF sector. This paper investigates the costs and benefits of incorporating robotics into the O&M of a FOWF. A bottom‐up cost model is used to estimate the costs for a proposed multi‐robot platform (MRP). The MRP houses unmanned aerial vehicle (UAV) and remotely operated vehicle (ROV) to conduct the inspection of specific FOWF components. Emphasis is laid on the most conducive O&M activities for robotization and the associated technical and cost aspects. The simulation is conducted in Windfarm Operations and Maintenance cost‐Benefit Analysis Tool (WOMBAT), where the metrics of incurred operational expenditure (OPEX) and the inspection time are calculated and compared with those of a baseline case consisting of crew transfer vessels, rope‐access technicians, and divers. Results show that the MRP can reduce the inspection time incurred, but this reduction has dependency on the efficacy of the robotic system and the associated parameterization e.g., cost elements and the inspection rates. Conversely, the increased MRP day rate results in a higher annualized OPEX. Residual risk is calculated to assess the net benefit of incorporating the MRP. Furthermore, sensitivity analysis is conducted to find the key parameters influencing the OPEX and the inspection time variation. A key output of this work is a robust and realistic framework which can be used for the cost‐benefit assessment of future MRP systems for specific FOWF activities.

17 WIND ENERGY↗