Zhang
Yanwu
Zhang
Yanwu
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ArticleAutonomous tracking and sampling of the deep chlorophyll maximum layer in an open-ocean eddy by a long-range autonomous underwater vehicle(Institute of Electrical and Electronics Engineers, 2020-10-13) Zhang, Yanwu ; Kieft, Brian ; Hobson, Brett W. ; Ryan, John P. ; Barone, Benedetto ; Preston, Christina M. ; Roman, Brent ; Raanan, Ben-Yair ; Marin, Roman ; O’Reilly, Thomas C. ; Rueda, Carlos A. ; Pargett, Douglas ; Yamahara, Kevan M. ; Poulos, Steve ; Romano, Anna ; Foreman, Gabe ; Ramm, Hans ; Wilson, Samuel T. ; DeLong, Edward F. ; Karl, David M. ; Birch, James M. ; Bellingham, James G. ; Scholin, Christopher A.Phytoplankton communities residing in the open ocean, the largest habitat on Earth, play a key role in global primary production. Through their influence on nutrient supply to the euphotic zone, open-ocean eddies impact the magnitude of primary production and its spatial and temporal distributions. It is important to gain a deeper understanding of the microbial ecology of marine ecosystems under the influence of eddy physics with the aid of advanced technologies. In March and April 2018, we deployed autonomous underwater and surface vehicles in a cyclonic eddy in the North Pacific Subtropical Gyre to investigate the variability of the microbial community in the deep chlorophyll maximum (DCM) layer. One long-range autonomous underwater vehicle (LRAUV) carrying a third-generation Environmental Sample Processor (3G-ESP) autonomously tracked and sampled the DCM layer for four days without surfacing. The sampling LRAUV's vertical position in the DCM layer was maintained by locking onto the isotherm corresponding to the chlorophyll peak. The vehicle ran on tight circles while drifting with the eddy current. This mode of operation enabled a quasi-Lagrangian time series focused on sampling the temporal variation of the DCM population. A companion LRAUV surveyed a cylindrical volume around the sampling LRAUV to monitor spatial and temporal variation in contextual water column properties. The simultaneous sampling and mapping enabled observation of DCM microbial community in its natural frame of reference.
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ArticleDetection of unanticipated faults for autonomous underwater vehicles using online topic models(John Wiley & Sons, 2017-12-26) Raanan, Ben-Yair ; Bellingham, James G. ; Zhang, Yanwu ; Kemp, Mathieu ; Kieft, Brian ; Singh, Hanumant ; Girdhar, YogeshFor robots to succeed in complex missions, they must be reliable in the face of subsystem failures and environmental challenges. In this paper, we focus on autonomous underwater vehicle (AUV) autonomy as it pertains to self‐perception and health monitoring, and we argue that automatic classification of state‐sensor data represents an important enabling capability. We apply an online Bayesian nonparametric topic modeling technique to AUV sensor data in order to automatically characterize its performance patterns, then demonstrate how in combination with operator‐supplied semantic labels these patterns can be used for fault detection and diagnosis by means of a nearest‐neighbor classifier. The method is evaluated using data collected by the Monterey Bay Aquarium Research Institute's Tethys long‐range AUV in three separate field deployments. Our results show that the proposed method is able to accurately identify and characterize patterns that correspond to various states of the AUV, and classify faults at a high rate of correct detection with a very low false detection rate.
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ArticleAutonomous four-dimensional mapping and tracking of a coastal upwelling front by an autonomous underwater vehicle(John Wiley & Sons, 2015-07-14) Zhang, Yanwu ; Bellingham, James G. ; Ryan, John P. ; Kieft, Brian ; Stanway, Michael J.Coastal upwelling is a wind-driven ocean process that brings cooler, saltier, and nutrient-rich deep water upward to the surface. The boundary between the upwelling water and the normally stratified water is called the “upwelling front.” Upwelling fronts support enriched phytoplankton and zooplankton populations, thus they have great influences on ocean ecosystems. Traditional ship-based methods for detecting and sampling ocean fronts are often laborious and very difficult, and long-term tracking of such dynamic features is practically impossible. In our prior work, we developed a method of using an autonomous underwater vehicle (AUV) to autonomously detect an upwelling front and track the front's movement on a fixed latitude, and we applied the method in scientific experiments. In this paper, we present an extension of the method. Each time the AUV crosses and detects the front, the vehicle makes a turn at an oblique angle to recross the front, thus zigzagging through the front to map the frontal zone. The AUV's zigzag tracks alternate in northward and southward sweeps, so as to track the front as it moves over time. This way, the AUV maps and tracks the front in four dimensions—vertical, cross-front, along-front, and time. From May 29 to June 4, 2013, the Tethys long-range AUV ran the algorithm to map and track an upwelling front in Monterey Bay, CA, over five and one-half days. The tracking revealed spatial and temporal variabilities of the upwelling front.
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PreprintDiversity and toxicity of Pseudo-nitzschia species in Monterey Bay : perspectives from targeted and adaptive sampling( 2018-08) Bowers, Holly A. ; Ryan, John P. ; Hayashi, Kendra ; Woods, April ; Marin, Roman ; Smith, G. Jason ; Hubbard, Katherine A. ; Doucette, Gregory J. ; Mikulski, Christina M. ; Gellene, Alyssa G. ; Zhang, Yanwu ; Kudela, Raphael M. ; Caron, David A. ; Birch, James M. ; Scholin, Christopher A.Monterey Bay, California experiences near-annual blooms of Pseudo-nitzschia that can affect marine animal health and the economy, including impacts to tourism and commercial/recreational fisheries. One species in particular, P. australis, has been implicated in the most toxic of events, however other species within the genus can contribute to widespread variability in community structure and associated toxicity across years. Current monitoring methods are limited in their spatial coverage as well as their ability to capture the full suite of species present, thereby hindering understanding of HAB events and limiting predictive accuracy. An integrated deployment of multiple in situ platforms, some with autonomous adaptive sampling capabilities, occurred during two divergent bloom years in the bay, and uncovered detailed aspects of population and toxicity dynamics. A bloom in 2013 was characterized by spatial differences in Pseudo39 nitzschia populations, with the low-toxin producer P. fraudulenta dominating the inshore community and toxic P. australis dominating the offshore community. An exceptionally toxic bloom in 2015 developed as a diverse Pseudo-nitzschia community abruptly transitioned into a bloom of highly toxic P. australis within the time frame of a week. Increases in cell density and proliferation coincided with strong upwelling of nutrients. High toxicity was driven by silicate limitation of the dense bloom. This temporal shift in species composition mirrored the shift observed further north in the California Current System off Oregon and Washington. The broad scope of sampling and unique platform capabilities employed during these studies revealed important patterns in bloom formation and persistence for Pseudo-nitzschia. Results underscore the benefit of expanded biological observing capabilities and targeted sampling methods to capture more comprehensive spatial and temporal scales for studying and predicting future events.
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ArticleTargeted sampling by autonomous underwater vehicles(Frontiers Media, 2019-08-14) Zhang, Yanwu ; Ryan, John P. ; Kieft, Brian ; Hobson, Brett W. ; McEwen, Robert S. ; Godin, Michael A. ; Harvey, Julio B. ; Barone, Benedetto ; Bellingham, James G. ; Birch, James M. ; Scholin, Christopher A. ; Chavez, Francisco P.In the vast ocean, many ecologically important phenomena are temporally episodic, localized in space, and move according to local currents. To effectively study these complex and evolving phenomena, methods that enable autonomous platforms to detect and respond to targeted phenomena are required. Such capabilities allow for directed sensing and water sample acquisition in the most relevant and informative locations, as compared against static grid surveys. To meet this need, we have designed algorithms for autonomous underwater vehicles that detect oceanic features in real time and direct vehicle and sampling behaviors as dictated by research objectives. These methods have successfully been applied in a series of field programs to study a range of phenomena such as harmful algal blooms, coastal upwelling fronts, and microbial processes in open-ocean eddies. In this review we highlight these applications and discuss future directions.
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ArticleAutonomous tracking of salinity-intrusion fronts by a long-range autonomous underwater vehicle(Institute of Electrical and Electronics Engineers, 2022-04-18) Zhang, Yanwu ; Yoder, Noa ; Kieft, Brian ; Kukulya, Amy L. ; Hobson, Brett W. ; Ryan, Svenja ; Gawarkiewicz, Glen G.Shoreward intrusions of anomalously salty water along the continental shelf of the Middle Atlantic Bight are often observed in spring and summer. Exchange of heat, nutrients, and carbon across the salinity-intrusion front has a significant impact on the marine ecosystem and fisheries. In this article, we developed a method of using an autonomous underwater vehicle (AUV) to detect a salinity-intrusion front and track the front's movement. Autonomous front detection is based on the different vertical structures of salinity in the two distinct water types: the vertical difference of salinity is large in the intruding saltier water because of the salinity “tongue” at mid-depth, but is small in the nearshore fresher water due to absence of the salinity anomaly. Every time the AUV crosses and detects the front, the vehicle makes a turn at an oblique angle to cross the front, thus zigzagging through the front to map the frontal zone. The AUV's zigzags sweep back and forth to track the front as it moves over time. From June 25 to 30, 2021, a Tethys-class long-range AUV mapped and tracked a salinity-intrusion front on the southern New England shelf. The frontal tracking revealed the salinity intrusion's 3-D structure and temporal evolution with unprecedented detail.
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ArticleEvolution of a physical and biological front from upwelling to relaxation(Elsevier, 2015-08-08) Zhang, Yanwu ; Bellingham, James G. ; Ryan, John P. ; Godin, Michael A.Fronts influence the structure and function of coastal marine ecosystems. Due to the complexity and dynamic nature of coastal environments and the small scales of frontal gradient zones, frontal research is difficult. To advance this challenging research we developed a method enabling an autonomous underwater vehicle (AUV) to detect and track fronts, thereby providing high-resolution observations in the moving reference frame of the front itself. This novel method was applied to studying the evolution of a frontal zone in the coastal upwelling environment of Monterey Bay, California, through a period of variability in upwelling intensity. Through 23 frontal crossings in four days, the AUV detected the front using real-time analysis of vertical thermal stratification to identify water types and the front between them, and the vehicle tracked the front as it moved more than 10 km offshore. The physical front coincided with a biological front between strongly stratified phytoplankton-enriched water inshore of the front, and weakly stratified phytoplankton-poor water offshore of the front. While stratification remained a consistent identifier, conditions on both sides of the front changed rapidly as regional circulation responded to relaxation of upwelling winds. The offshore water type transitioned from relatively cold and saline upwelled water to relatively warm and fresh coastal transition zone water. The inshore water type exhibited an order of magnitude increase in chlorophyll concentrations and an associated increase in oxygen and decrease in nitrate. It also warmed and freshened near the front, consistent with the cross-frontal exchange that was detected in the high-resolution AUV data. AUV-observed cross-frontal exchanges beneath the surface manifestation of the front emphasize the importance of AUV synoptic water column surveys in the frontal zone.
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ThesisSpectral feature classification of oceanographic processes using an autonomous underwater vehicle(Massachusetts Institute of Technology and Woods Hole Oceanographic Institution, 2000-06) Zhang, YanwuThe thesis develops and demonstrates methods of classifying ocean processes using an underwater moving platform such as an Autonomous Underwater Vehicle (AUV). The "mingled spectrum principle" is established which concisely relates observations from a moving platform to the frequency-wavenumber spectrum of the ocean process. It clearly reveals the role of the AUV speed in mingling temporal and spatial information. For classifying different processes, an AUV is not only able to jointly utilize the time-space information, but also at a tunable proportion by adjusting its cruise speed. In this respect, AUVs are advantageous compared with traditional oceanographic platforms. Based on the mingled spectrum principle, a parametric tool for designing an AUVbased spectral classifier is developed. An AUV's controllable speed tunes the separability between the mingled spectra of different processes. This property is the key to optimizing the classifier's performance. As a case study, AUV-based classification is applied to distinguish ocean convection from internal waves. The mingled spectrum templates are derived from the MIT Ocean Convection Model and the Garrett-Munk internal wave spectrum model. To allow for mismatch between modeled templates and real measurements, the AUVbased classifier is designed to be robust to parameter uncertainties. By simulation tests on the classifier, it is demonstrated that at a higher AUV speed, convection's distinct spatial feature is highlighted to the advantage of classification. Experimental data are used to test the AUV-based classifier. An AUV-borne flow measurement system is designed and built, using an Acoustic Doppler Velocimeter (ADV). The system is calibrated in a high-precision tow tank. In February 1998, the AUV acquired field data of flow velocity in the Labrador Sea Convection Experiment. The Earth-referenced vertical flow velocity is extracted from the raw measurements. The classification test result detects convection's occurrence, a finding supported by more traditional oceanographic analyses and observations. The thesis work provides an important foundation for future work in autonomous detection and sampling of oceanographic processes.