Search Results (8)

This research explores the optimal operation of an offshore wave-powered hydrogen system, specifically designed to supply electricity and water to a bay in Humboldt, California, USA, and also sell it with hydrogen. The system incorporates a desalination unit to provide the island with fresh water and feed the electrolyzer to produce hydrogen. The optimization process utilizes a mixture of experts in conjunction with the Quantitative Structure-Activity Relationship (QSAR) algorithm traditionally used in drug design, to achieve two main objectives: minimizing operational costs and maximizing revenue from the sale of water, hydrogen, and electricity. Many case studies are examined, representing typical electricity demand and wave conditions during typical summer, winter, spring, and fall days. The simulation, optimization, and results are carried out using MATLAB 2018 and SAM 2024 software applications. The findings demonstrate that the combination of the QSAR algorithm and quantum-inspired MoE results in higher revenue and lower costs compared to other current techniques, with hydrogen sales being the primary contributor to increased income. Full article

Here, we describe a dataset of two-dimensional (2D) XBeach model files that were developed for the Coastal Storm Modeling System (CoSMoS) in northern California as an update to an earlier CoSMoS implementation that relied on one-dimensional (1D) modeling methods. We provide details on the data and their application, such that they might be useful to end-users for other coastal studies. Modeling methods and outputs are presented for Humboldt Bay, California, in which we compare output from a nested 1D modeling approach to 2D model results, demonstrating that the 2D method, while more computationally expensive, results in a more cohesive and directly mappable flood hazard result. Full article

Several power take-off (PTO) architectures for wave-powered reverse osmosis (RO) desalination of seawater are introduced and compared based on the annual average freshwater production and the size of the components, which strongly relate to the costs of the system. The set of architectures compared includes a novel series-type PTO architecture not previously considered. These seawater hydraulic PTO architectures are composed of a WEC-driven pump, an RO module, an intake charge pump driven by an electric motor, and a hydraulic motor driving an electric generator for electric power production. This study is performed using an efficient two-way coupled steady-state model for the average performance of the system in a given sea state, including freshwater permeate production, electric power production, and electric power consumption. A multi-objective design problem is formulated for the purposes of this comparative study, with the objectives of maximizing annual freshwater production, minimizing the displacement of the WEC-driven pump, and minimizing the installed RO membrane area. This establishes a framework for comparison in the absence of a mature techno-economic model. The requirement that the system produces enough electric power to meet its consumption is applied as a constraint on the operation of the system. The oscillating wave surge converter Oyster 1 is assumed as the WEC. Weights on performance of the system in a given sea state are based on historical data from Humboldt Bay, CA. This study finds that (1) architectures in a series configuration allow for a reduction in the WEC-driven pump size of 59–92% compared to prior work, (2) varying the displacement of the WEC-driven pump between sea conditions does not provide any significant advantage in performance, and (3) varying the active RO membrane area between sea condition offers improvements between 7% and 41% in each design objective. Full article

Previous work comparing power take-off (PTO) architectures for ocean wave-powered reverse osmosis suggests that variable displacement in the wave energy converter (WEC)-driven pump does not offer a significant performance advantage. A limitation of that study is that the WEC was subject to a constant load within a given sea state (“Coulomb damping”) and did not account for controlled, moment-to-moment variation of the PTO load enabled by a variable displacement pump. This study explores the potential performance advantage of a variable PTO load over Coulomb damping. Model predictive control is used to provide optimal load control with constraints on the PTO load. The constraints include minimum and maximum loads and a limit on the rate of load adjustment. Parameter studies on these constraints enable conclusions about PTO design requirements in addition to providing an estimated performance advantage over Coulomb damping. Numerical simulation of the Oyster 1 WEC is carried out with performance weighted by historical sea state data from Humboldt Bay, CA. The results show a performance advantage of up to 20% higher yearly-average power absorption over Coulomb damping. Additionally, the parameter studies suggest that the PTO load should be adjustable down to at least 25% of the maximum load and should be adjustable between the minimum and maximum loads within a few seconds. Full article

The decapod fauna in the intertidal zone of the rocky shores of Chile is highly diverse, especially along the northern and central mainland coasts, where the influence of the cold Humboldt Current results in high productivity. One of the most abundant species in these ecosystems is the decapod Cyclograpsus cinereus Dana, 1851. The aim of the present study, carried out in the spring and summer seasons between 2018 and 2020, was to determine the spatial distribution patterns of the decapod C. cinereus in different sites along the rocky shores of Antofagasta bay, northern Chile, in order to establish probabilistic models that explain its distribution at each site. Individuals were counted in random quadrants in the intertidal zone. The data thus obtained were processed by application of the variance/mean ratio to determine whether the distribution of individuals was random, aggregated or uniform, associated with Poisson, negative binomial or positive binomial distributions, respectively. The data revealed aggregated (negative binomial) distribution in 15 sampling events, and uniform (positive binomial) distribution in 4 events. The sampling sites were located on rocky shores in four sectors of an urban zone, and two in a protected zone; no significant differences were found between the densities of the sites in the two zones. The results of the interpretative probabilistic models indicated aggregated distribution patterns, agreeing with previously reported interpretative probabilistic models for the distribution of decapods on the rocky shores of central and southern Chile. Full article

Unmanned aerial vehicles (UAVs) are being widely used to monitor microtopographic and vegetation changes in coastal habitats using remote sensing techniques. Sand dune habitats are vital ecosystems along the North coast of Humboldt County in California. This study was conducted at the Manila Dunes, west of the Humboldt Coastal Nature Center, in Manila, California. Various factors influence dune movements, including vegetative stabilization and the creation of social trails. The purpose of this paper is to understand the dune movements in relation to social vs. established trails, vegetation density, topography, and also, mapping invasive vs. native species in the Mal-le’l Dunes area of the Humboldt Bay National Wildlife Refuge. A DJI Mavic Pro multicopter small unmanned aerial vehicle (UAV) was used to fly a 22.5-acre plot of the Manila Dunes. The images from this flight were used to create an orthomosaic image using a photogrammetry process (Structure-from-Motion (SfM)). From our analysis, the installation of trails lessened the impact of dune movements. Social trails digitized within the study site were found to have more local movements than the established trails when compared to movements across the entire site. We compared two methods of classification, viz., the object-based feature extraction method and a pixel-based supervised maximum likelihood classification method, in order to identify the best way to classify dune vegetation. In conclusion, this study is useful for providing baseline dune movement information that can aid in informing how trail and infrastructure constructions can be impacted in land management or in areas with dynamic communities of flora and fauna. Full article

Coastal megaclast deposits are dominated by detrital particles larger than 1 m in size. These attract significant attention of modern researchers because of the needs of sedimentary rock nomenclature development and interpretation of storm and tsunami signatures on seashores. If so, finding localities that exhibit coastal megaclast deposits is an important task. Field studies do not offer a quick solution, and, thus, remote sensing tools have to be addressed. The application of the Google Earth Engine has permitted to find four new localities, namely Hondarribia in northern Spain (Biscay Bay), the Ponza Island in Italy (Tyrrhenian Sea), the Wetar Island in eastern Indonesia (Banda Sea), and the Humboldt o Coredo Bay at the Colombia/Panama border (eastern Pacific). In these localities, coastal megaclast deposits consisting of blocks (1–10 m in size) and some megablocks (>10 m in size) are delineated and preliminary described in regard to the dominant size of particles, package density, mode of occurrence, etc. The limitations of such virtual surveys of coastal megaclast deposits are linked to an insufficiently high resolution of satellite images, as well as ‘masking’ effects of vegetation cover and cliff shadows. However, these limitations do not diminish the importance of the Google Earth Engine for finding these deposits. Consideration of some tourism-related information, including photos captured by tourists and bouldering catalogues, facilitates search for promising areas for subsequent virtual surveying of megaclast distribution. It is also established that the Google Earth Engine permits quantitative analysis of composition of coastal megaclast deposits in some areas, as well as to register decade-long dynamics or stability of these deposits, which is important to interpret their origin. The current opportunities for automatic detection of coastal megaclast deposits seem to be restricted. Full article

The Ma-le’l Dunes are located at the upper end of the North Spit of Humboldt Bay, California and are home to a range of plant and animal species. The goal of this study was to determine which classification method was the most accurate in identifying dune features when performed on a large, diverse area. The data sources used for this study were an orthomosaic image (2017) with 14 cm spatial resolution and NAIP images (2012, 2014, and 2016) with 1 m spatial resolution. A DJI Mavic Pro Unmanned Aerial Vehicle (UAV) was used to fly a 31 acre plot of the Ma-le’l Dunes at a height of about 80 m. The images from this flight were used to create an orthomosaic image in AgisoftPhotoScan. The dune feature classes were compared with two images using supervised, unsupervised, and feature extraction classification methods and accuracy assessments were performed using 100 ground control points. The classified feature classes were beach grass, shore pine, sand, other vegetation, and water. Overall, the NAIP classified maps showed a higher accuracy for all classification methods than UAV classified maps, with 86% overall accuracy for the supervised classification. A feature extraction method showed a low accuracy for both NAIP (46%) and UAV ortho classified images (30%). Of the classified methods for the orthomosaic image, the unsupervised classification showed a high accuracy (44%). The Ma-le’l dune habitats are more heterogeneous and some classes were overlapping (i.e., beach grass and sand) due to high microtopographic variation of the dune, resulting in lower accuracy for the feature extraction method. Monitoring dune habitats and geomorphic changes over time with UAV images is important for implementing suitable management practices for species conservation and mitigating coastal vulnerabilities. Full article