The Magdalena Ridge Observatory Interferometer is an ambitious project to build a 10 telescope long-baseline optical/near-infrared in the mountains about a one-hour drive outside of Socorro, NM. The project is being led by New Mexico Institute of Mining and Technology and being built in cooperation with our primary collaborators at the University of Cambridge. We are currently funded via a cooperative agreement with the Air Force Research Lab in Albuquerque, NM to demonstrate imaging capabilities on geosynchronous objects. We have recently installed the second full beamline for the interferometer system and are working our way towards first fringes on an ~8m baseline later this year. In this manuscript, we report on the status of each of the subsystems, the installation progress and challenges to date, and on the ramp-up to measurements of first fringes. We also report on plans for early science and offer public shared-risk access with the facility in the near future.
The Magdalena Ridge Observatory Interferometer (MROI) Beam Relay System (BRS) comprises a network of airevacuated pipes and relay stations, consisting of a pier and vacuum can containing a relay mirror, shear alignment sensors, and control electronics. Located at precise points along the arms of the interferometer array, the BRS piers contain remotely controllable mirrors which can be precisely adjusted to direct light from the adjacent unit telescope down the beamline and into the Beam Combining Facility (BCF), where interference fringes are made. Changing the array configuration is a planned function of interferometer operation, but is time consuming and complicated, as it will involve moving mirror assemblies between the vacuum cans (VC). The Vacuum Can Hub (VCH) is a network Modbus message processor and instrumentation hub that connects the Vacuum Can (VC) instrumentation to the MROI power and communication infrastructure via a single Power over Ethernet (PoE) access point. This greatly simplifies and speeds up array reconfiguration. In this paper we shall discuss the MROI Automated Alignment System (AAS), which is tasked with ensuring precise alignment of beamlines connecting the UTs with the BCF, and its role as supervisor of the VCH. We also discuss the BRS components interfaced by the VCH: first, the VC 1-wire temperature sensor network, whose data is used by the AAS for driving fine adjustments of the BRS relay mirrors via the AAS’s feed-forward open-loop thermal mechanical model. Second, twin shear sensors used for coarse beam alignment, each consisting of custom designed 10 × 10 pixel photodiode arrays, whose electronics and software allow direct access by the AAS by using the VCH’s message routing capabilities. The VCH’s ability to translate and relay Modbus messages between the network and serial domain allow high flexibility in defining the quantity and types of BRS hardware that can be installed in VCs.
KEYWORDS: Mirrors, Education and training, Beam path, Relays, Beam diameter, Telescopes, Optical components, Design, Beam combiners, Signal to noise ratio
The Magdalena Ridge Observatory Interferometer has been designed to deliver an unprecedented capability for model-independent imaging of faint astronomical targets. As a consequence, its design methodology has focused on optimizing the interferometric sensitivity of all of its opto-mechanical subsystems. We report here on initial testing of one of the MROI beam-trains, outlining the performance metrics utilized to characterize the elements of the optical train from the Unit Telescopes through to the MROI beam combiner tables, the tests performed on each subsystem, and how our results compare to the design error budget for the MROI. The impact of the tests on the initial sensitivity limit of the MROI are discussed.
The Beam Relay System at the Magdalena Ridge Observatory Interferometer, exposed to outdoor environmental conditions, includes 6-inch mirrors mounted on aluminum frames and steel platforms, equipped with piezoelectric motors and a laser/camera alignment system. This subsystem faces challenges with misalignments that disrupt observations, addressed by a proposed correction strategy. The system uses temperature sensor data around mirrors to predict and correct misalignments as a feedforward control system through calibrated motors, and incorporates a periodic closed-loop control system using light source and camera. Advanced predictive models refined over time using temperature, shear, and tilt data, aim to maintain beam stability within interferometric tolerances, ensuring optimal performance.
Beam misalignment causes visibility loss in fringe measurements made by long-baseline optical interferometers. An Automated Alignment System (AAS) has been designed for the Magdalena Ridge Observatory Interferometer (MROI) to keep the visibility loss associated with misalignment under ∼1%. Production versions of collimated reference light sources and precision beam alignment sensors for the AAS have recently been integrated into the first beamline of the MROI. This paper describes the lessons learned during their installation and provides results from their site acceptance tests.
The Magdalena Ridge Observatory Interferometer has been conceived to be the most ambitious optical/near-infrared long-baseline imaging interferometer in the world today. We anticipate receiving the second telescope mount and enclosure and associated beamline infrastructure to enable us to attempt first fringes measurements early in 2023. Having reached this important milestone, we anticipate receiving the third copy of all beamline components about one year later and attempting closure phase measurements thereafter. We will present a status update and plans under the new Cooperative Agreement with AFRL for the next phases of the project.
This paper discusses the established and potential applications of high-dimensional data analysis in the fields of structural health monitoring and non-destructive evaluation. Despite the significant potential of high dimensional data analytic methods, a few applications have been implemented in structural health monitoring and non-destructive evaluation. Further, as measuring technologies improve, the requirement of applying these approaches grows. This paper uses thermal videos as an example of high-dimensional data in the non-destructive evaluation field. These thermal videos are used to detect and localize delamination in composite plates, typically found in aircraft wings. Using traditional statistical approaches to analyze videos presents theoretical and practical challenges due to their high dimensionality. Tensor analysis methods help to overcome these issues. To locate the damage, two tensor factorization algorithms are used. For a rectangular damage zone, two vectors are enough to localize the extent of the damage. For more sophisticated cases like a damage in the shape of a circle, higher order of core tensors with larger projection tensors are needed. The results demonstrate these methods are accurate and efficient in terms of computing cost.
3D-printed one-way valves were designed and fabricated to relieve the corrosion-induced internal pressure on concrete structures. These valves were post-installed onto concrete to increase corrosion resistance in the concrete structure and extended the service life. This study investigated an Internet-of-Things device to continuously monitor corrosion in steel-reinforced concrete in order to determine the effectiveness of the valves in preventing corrosion. The IoT device monitors acoustic emission to determine the corrosion stage of reinforced concrete. The ongoing results show that the current valve design is an effective one-way check valve that will allow the internal pressure of the concrete to be released. This type of valve will prevent reinforced concrete surface cracking and extend the life of concrete structures by only releasing internal pressure without allowing for external materials to further corrode the steel reinforcement in concrete.
Surface crack patterns are one of the earliest damage signs in concrete structures. Existing procedures to visually evaluate the damage rely on experts' judgment to interpret the existing cracks. The initial necessary step to quantify and automate this procedure is crack detection. Precise crack detection provides a reliable basis to update the structural parameters and to predict future behavior. Several methods have been investigated to detect cracks based on image processing methods; but, there are several limitations and inaccuracies in these methods. In a number of cases, recordings during damage occurrence are available. The videos comprise not only spatial information but also temporal information. The videos provide a set of images for a unique damage situation. In this study, using video processing methods, a methodology is developed to track crack formation. In this regard, robust principal component analysis is employed to detect new crack propagation. The experimental test data of RC shear walls are used to assess the implemented methodology. The quasi-static cyclic load is applied to these walls, and several cameras captured the video of walls' behavior. Taking advantage of the phase-based motion processing method, a video stabilization is implemented to enhance the accuracy of the crack detection step. Propagation of cracks is monitored by calculating Gini coefficients for each frame. The results show that monitoring this coefficient can indicate new crack formations.
Access to the requested content is limited to institutions that have purchased or subscribe to SPIE eBooks.
You are receiving this notice because your organization may not have SPIE eBooks access.*
*Shibboleth/Open Athens users─please
sign in
to access your institution's subscriptions.
To obtain this item, you may purchase the complete book in print or electronic format on
SPIE.org.
INSTITUTIONAL Select your institution to access the SPIE Digital Library.
PERSONAL Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.