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Brian Johnson

Publications and source records attributed to Brian Johnson.

8 recordsLinked to original sources

An overview of stray light findings and interpretation during on-sky commissioning of LSSTCam

Wide-field telescopes are intrinsically difficult to shield from unwanted stray and scattered light, while the search to identify sources of contaminating light is frequently a challenging task. The Vera C.~Rubin Observatory, which achieved its first photon with the LSST Camera (LSSTCam) on April 15, 2025, will initiate a revolutionary era for the study of dark matter, dark energy, the transient sky, the Solar System, and the Milky Way. LSSTCam will provide near seeing-limited images of the sky in six bands ($u,g,r,i,z,y$) over a $3.^\circ 5$-diameter field of view, and over the course of a decade, it will execute the Legacy Survey of Space and Time (LSST). This work provides an overview of the dedicated stray and scattered light test campaign that has been undertaken since the start of Rubin commissioning. In particular, we highlight the processes used to characterize, model, and mitigate stray light present in LSSTCam images. The Rubin commissioning team created a series of testing and analysis tools to track stray light artifacts from their initial discovery through reproduction with timely observations, simulation using ray tracing to identify opto-mechanical origins, and finally devising corrective actions. The complex stray light features encountered by Rubin provide a wealth of experience for the future wide-field and extremely wide-field observatories. This work covers the many stages of a long journey that started with conceiving an innovative and challenging optical design, followed by the engineering and system engineering efforts to build it, to finally delivering an optimized and revolutionary cutting-edge facility.

astro-ph.IM

Small-signal Stability of a Unified Single-unit Infinite-bus Swing-equation Model for Generators and Inverters

We present a swing-equation model with generalized and equilibria-dependent inertia, damping, and synchronization constants for energy conversion interfaces with second-order active-power versus voltage-phasor-angle dynamics connected to an infinite bus. The model is unified in that prudent parameterization of the second-order angle-to-power transfer function aligns with reduced-order models for synchronous generators, grid-following inverters with fast frequency-response capability, and droop- and virtual synchronous generator-based grid-forming inverters. Parametric necessary and sufficient conditions to examine small-signal stability of angle equilibria are derived from the unified swing-equation model.

eess.SY

A Unified Approach for Learning the Dynamics of Power System Generators and Inverter-based Resources

The growing prevalence of inverter-based resources (IBRs) for renewable energy integration and electrification greatly challenges power system dynamic analysis. To account for both synchronous generators (SGs) and IBRs, this work presents an approach for learning the model of an individual dynamic component. The recurrent neural network (RNN) model is used to match the recursive structure in predicting the key dynamical states of a component from its terminal bus voltage and set-point input. To deal with the fast transients especially due to IBRs, we develop a Stable Integral (SI-)RNN to mimic high-order integral methods that can enhance the stability and accuracy for the dynamic learning task. We demonstrate that the proposed SI-RNN model not only can successfully predict the component's dynamic behaviors, but also offers the possibility of efficiently computing the dynamic sensitivity relative to a set-point change. These capabilities have been numerically validated based on full-order Electromagnetic Transient (EMT) simulations on a small test system with both SGs and IBRs, particularly for predicting the dynamics of grid-forming inverters.

eess.SY

Model Reduction for Inverters with Current Limiting and Dispatchable Virtual Oscillator Control

This paper outlines reduced-order models for grid-forming virtual-oscillator-controlled inverters with nested current- and voltage-control loops, and current-limiting action for over-current protection. While a variety of model-reduction methods have been proposed to tame complexity in inverter models, previous efforts have not included the impact of current-reference limiting. In addition to acknowledging the current-limiting action, the reduced-order models we outline are tailored to networks with resistive and inductive interconnecting lines. Our analytical approach is centered on a smooth function approximation for the current-reference limiter, participation factor analysis to identify slow- and fast-varying states, and singular perturbation to systematically eliminate the fast states. Computational benefits and accuracy of the reduced-order models are benchmarked via numerical simulations that compare them to higher-order averaged and switched models.

eess.SY

Singular Perturbation and Small-signal Stability for Inverter Networks

This paper examines small-signal stability of electrical networks composed dominantly of three-phase grid-following inverters. We show that the mere existence of a high-voltage power flow solution does not necessarily imply small-signal stability; this motivates us to develop a framework for stability analysis that systematically acknowledges inverter dynamics. We identify a suitable time-scale decomposition for the inverter dynamics, and using singular perturbation theory, obtain an analytic sufficient condition to verify small-signal stability. Compared to the alternative of performing an eigenvalue analysis of the full-order network dynamics, our analytic sufficient condition reduces computational complexity and yields insights on the role of network topology and constitution as well as inverter-filter and control parameters on small-signal stability. Numerical simulations for a radial network validate the approach and illustrate the efficiency of our analytic conditions for designing and monitoring grid-tied inverter networks.

math.OC

Dispatchable Virtual Oscillator Control for Decentralized Inverter-dominated Power Systems: Analysis and Experiments

This paper presents an analysis and experimental validation of dispatchable virtual oscillator control (dVOC) for inverter-dominated power systems. dVOC is a promising decentralized control strategy that requires only local measurements to induce grid-forming behavior with programmable droop characteristics. It is dispatchable i.e., the inverters can vary their power generation via user-defined power set-points and guarantees strong stability. To verify its feasibility, a testbed comprising multiple dVOC-programmed inverters with transmission line impedances is designed. With an embedded synchronization strategy, the dVOC inverters are capable of dynamic synchronization, black start operation, and transient grid voltage regulation with dynamic load sharing, and real-time-programmable droop characteristics for backward compatibility. All these features are experimentally verified.

math.OC

Patch-based Texture Synthesis for Image Inpainting

Image inpaiting is an important task in image processing and vision. In this paper, we develop a general method for patch-based image inpainting by synthesizing new textures from existing one. A novel framework is introduced to find several optimal candidate patches and generate a new texture patch in the process. We form it as an optimization problem that identifies the potential patches for synthesis from an coarse-to-fine manner. We use the texture descriptor as a clue in searching for matching patches from the known region. To ensure the structure faithful to the original image, a geometric constraint metric is formally defined that is applied directly to the patch synthesis procedure. We extensively conducted our experiments on a wide range of testing images on various scenarios and contents by arbitrarily specifying the target the regions for inference followed by using existing evaluation metrics to verify its texture coherency and structural consistency. Our results demonstrate the high accuracy and desirable output that can be potentially used for numerous applications: object removal, background subtraction, and image retrieval.

cs.CV

Synchronization of Nonlinear Circuits in Dynamic Electrical Networks with General Topologies

Sufficient conditions are derived for global asymptotic synchronization in a system of identical nonlinear electrical circuits coupled through linear time-invariant (LTI) electrical networks. In particular, the conditions we derive apply to settings where: i) the nonlinear circuits are composed of a parallel combination of passive LTI circuit elements and a nonlinear voltage-dependent current source with finite gain; and ii) a collection of these circuits are coupled through either uniform or homogeneous LTI electrical networks. Uniform electrical networks have identical per-unit-length impedances. Homogeneous electrical networks are characterized by having the same effective impedance between any two terminals with the others open circuited. Synchronization in these networks is guaranteed by ensuring the stability of an equivalent coordinate-transformed differential system that emphasizes signal differences. The applicability of the synchronization conditions to this broad class of networks follows from leveraging recent results on structural and spectral properties of Kron reduction---a model-reduction procedure that isolates the interactions of the nonlinear circuits in the network. The validity of the analytical results is demonstrated with simulations in networks of coupled Chua's circuits.

math.OC