The use of unmanned aerial vehicles (UAVs) has seen a significant increase over time in several industries such as defense, healthcare, and agriculture to name a few. Their affordability has made it possible for industries to venture and invest in UAVs for both research and commercial purposes. In spite of their recent popularity; there remain a number of difficulties in the design representation of UAVs, including low image analysis, high cost, and time consumption. In addition, it is challenging to represent systems of systems that require multiple UAVs to work in cooperation, sharing resources, and complementing other assets on the ground or in the air. As a means of compensating for these difficulties; in this study; we use a model-based systems engineering (MBSE) approach, in which standardized diagrams are used to model and design different systems and subsystems of UAVs. SysML is widely used to support the design and analysis of many different kinds of systems and ensures consistency between the design of the system and its documentation through the use of an object-oriented model. In addition, SysML supports the modeling of both hardware and software, which will ease the representation of both the system’s architecture and flow of information. The following paper will follow the Magic Grid methodology to model a UAV system across the SysML four pillars and integration of SysML model with external script-based simulation tools, namely, MATLAB and OpenMDAO. These pillars are expressed within standard diagram views to describe the structural, behavior, requirements, and parametric aspect of the UAV. Finally, the paper will demonstrate how to utilize the simulation capability of the SysML model to verify a functional requirement.

In recent years, Model Based Systems Engineering (MBSE) has continued to develop as a standard for designing, managing, and maintaining increasingly complex systems. Unlike the document centric approach, MBSE puts the model at the heart of system design. Among the various MBSE language development efforts, “Systems Modeling Language (SysML)”, is the most anticipated and broadly utilized in the research and in industrial practice. SysML originated from Unified Modeling Language (UML) and follows the Object-Oriented Systems Engineering Method (OOSEM). SysML diagrams help users create various systems engineering artifacts, including requirements, use cases, operational concepts, system architecture, system behaviors, and parametric analyses of a system model. In the early days of implementation, MBSE languages, including SysML, typically relied on static viewpoints and limited simulation support to depict and analyze a system model. Due the continuous improvement efforts and new implementation approaches by researchers and organizations, SysML has advanced vastly to encompass dynamic viewpoints, in-situ simulation and enable integration with external modeling and simulation (M&S) tools. Virtual Reality (VR) has emerged as a user interactive and immersive visualization technology and can depict reality in a virtual environment at different levels of fidelity. VR can play a crucial role in developing dynamic and interactive viewpoints to improve the MBSE approach. In this research paper, the authors developed and implemented a methodology for integrating SysML and VR, enabling tools to achieve three dimensional viewpoints, an immersive user experience and early design evaluations of the system of interest (SOI). The key components of the methodology being followed in this research paper are the SysML, a VR environment, extracted data and scripting languages. The authors initially developed a SysML for a ground-based telescope system following the four pillars of SysML: Structure, Requirements, Behavior and Parametrics. The SysML diagram components are exported from the model using the velocity template language and then fed into a virtual reality game engine. Then, the SysML diagrams are visualized in the VR environment to enable better comprehension and interaction with users and Digital Twin (DT) technologies. In addition, a VR simulation scenario of space objects is generated based on the input from the SysML, and the simulation result is sent back from the VR tool into the model with the aid of parametric diagram simulation. Hence, by utilizing the developed SysML-VR integration methodology, VR environment scenarios are successfully integrated with the SysML. Finally, the research paper mentions a few limitations of the current implementation and proposes future improvements.

We present lightcurves, rotation periods, and colors for the first asteroid discoveries made with the NSF-DOE Vera C. Rubin Observatory. These are the first science results derived from the 2103 asteroid discoveries released as part of the Rubin First Look (RFL) media event on 2025 June 23, in which the first LSST Camera commissioning images were released. The ∼340,000 observations in which the discoveries were made span nine nights between 2025 April 21 and May 5. With a limiting single-epoch 5 σ depth of ∼23–25 mag and dense temporal sampling under an irregular, commissioning-driven cadence, the RFL observations provide an ideal test bed for determination of rotation periods, including sensitivity to rapid rotation. We model lightcurves and derive rotation periods and colors for the ∼2000 objects. We find 75 main-belt asteroids (MBAs) and one near-Earth object (NEO) with reliable rotation periods spanning 0.031–21.3 hr and a photometric precision in the range of 0.05–0.15 mag. We find 19 superfast rotators with periods shorter than the 2.2 hr spin barrier. Rubin-discovered MBA 2025 MN ₄₅ is the fastest-rotating d > 0.5 km known asteroid with a rotation period of 1.9 minutes; along with NEO 2025 MJ ₇₁ (1.9 minutes) and Rubin-discovered MBAs 2025 MK ₄₁ (3.8 minutes), 2025 MV ₇₁ (13 minutes), and 2025 MG ₅₆ (16 minutes), these five super- to ultrafast rotators join a couple of NEOs as the fastest-spinning subkilometer asteroids known. As this study demonstrates, even in early commissioning, Rubin is successfully probing a previously sparsely sampled region of the subkilometer size−spin rate regime for MBAs.

Model-Based Systems Engineering (MBSE) prioritizes system design through models rather than documents, and it is implemented with the Systems Modeling Language (SysML), which is the state-of-the-art language in academia and industry. Virtual Reality (VR), an immersive visualization technology, can simulate reality in virtual environments with varying degrees of fidelity. In recent years, the technology industry has invested substantially in the development of head-mounted displays (HMDs) and related virtual reality (VR) technologies. Various research has suggested that VR-based immersive design reviews enhance system issue/fault identification, collaboration, focus, and presence compared to non-immersive approaches. Additionally, several research efforts have demonstrated that the VR environment provides higher understanding and knowledge retention levels than traditional approaches. In recent years, multiple attempts have been made to visualize conventional 2D SysML diagrams in a virtual reality environment. To the best of the author’s knowledge, no empirical evaluation has been performed to analyze the benefits and drawbacks of visualizing SysML diagrams in a VR environment. Hence, the authors aimed to evaluate four key benefit types and drawbacks through experiments with human subjects. The authors chose four benefit types—Systems Understanding, Information Sharing, Modeling and Training Experience, and Digital Twin based on the MBSE value and benefits review performed by researchers and benefits claimed by the evaluations for similar visual formalism languages. Experiments were conducted to compare the understanding, interaction, and knowledge retention for 3D VR and conventional 2D SysML diagrams. The authors chose a ground-based telescope system as the system of interest (SOI) for system modeling. The authors utilized a standalone wireless HMD unit for a virtual reality experience, which enabled experiments to be conducted irrespective of location. Students and experts from multiple disciplines, including systems engineering, participated in the experiment and provided their opinions on the VR SysML implementation. The knowledge test, perceived evaluation results, and post-completion surveys were analyzed to determine whether the 3D VR SysML implementation improved these benefits and identified potential drawbacks. The authors utilized a few VR scenario efficacy measures, namely the Simulation Sickness Questionnaire (SSQ) and System Usability Scale (SUS), to avoid evaluation design-related anomalies.

The Vera C. Rubin Observatory will soon survey the southern sky, delivering a depth and sky coverage that is unprecedented in time-domain astronomy. As part of commissioning, Data Preview 1 (DP1) has been released. It comprises a Legacy Survey of Space and Time (LSST) Commissioning Camera observing campaign between 2024 November and December with multiband imaging of seven fields, covering roughly 0.4 deg ² each, providing a first glimpse into the data products that will become available once the LSST begins. In this work, we search three fields for extragalactic transients. We identify eight new likely supernovae (SNe), and three known ones from a sample of 369,644 difference image analysis objects. Photometric classification using Superphot+ assigns subclasses with >95% confidence to only one SN Ia and one SN II in this sample. Our findings are in agreement with SN detection rate predictions of 15 ± 4 SNe from simulations using simsurvey . The SN detection rate in the data is possibly affected by the lack of suitable templates. Nevertheless, this work demonstrates the quality of the data products delivered in DP1 and indicates that the Rubin Observatory’s LSST is well placed to fulfill its discovery potential in time-domain astronomy.