Lagrangian large eddy simulations via physics-informed machine learning.

High-Reynolds number homogeneous isotropic turbulence (HIT) is fully described within the Navier-Stokes (NS) equations, which are notoriously difficult to solve numerically. Engineers, interested primarily in describing turbulence at a reduced range of resolved scales, have designed heuristics, known as large eddy simulation (LES). LES is described in terms of the temporally evolving Eulerian velocity field defined over a spatial grid with the mean-spacing correspondent to the resolved scale.

Statistical mechanics of thermostatically controlled multizone buildings.

We study the collective phenomena and constraints associated with the aggregation of individual cooling units from a statistical mechanics perspective. These units are modeled as thermostatically controlled loads (TCLs) and represent zones in a large commercial or residential building. Their energy input is centralized and controlled by a collective unit-the air handling unit (AHU)-delivering cool air to all TCLs, thereby coupling them together.

Prediction and prevention of pandemics via graphical model inference and convex programming.

Hard-to-predict bursts of COVID-19 pandemic revealed significance of statistical modeling which would resolve spatio-temporal correlations over geographical areas, for example spread of the infection over a city with census tract granularity. In this manuscript, we provide algorithmic answers to the following two inter-related public health challenges of immense social impact which have not been adequately addressed (1) Inference Challenge assuming that there are N census blocks (nodes) in the city, and given an initial infection at any set of nodes, e.g.

Which Neural Network to Choose for Post-Fault Localization, Dynamic State Estimation, and Optimal Measurement Placement in Power Systems?

We consider a power transmission system monitored using phasor measurement units (PMUs) placed at significant, but not all, nodes of the system. Assuming that a sufficient number of distinct single-line faults, specifically the pre-fault state and the (not cleared) post-fault state, are recorded by the PMUs and are available for training, we first design a comprehensive sequence of neural networks (NNs) locating the faulty line. Performance of different NNs in the sequence, including linear regression, feed-forward NNs, AlexNet, graph convolutional NNs, neural linear ordinary differential equations (ODEs) and neural graph-based ODEs, ordered according to the type and amount of the power flow physics involved, are compared for different levels of observability.

Mean-field control for efficient mixing of energy loads.

We pose an engineering challenge of controlling an ensemble of energy devices via coordinated, implementation-light, and randomized on/off switching as a problem in nonequilibrium statistical mechanics. We show that mean-field control with nonlinear feedback on the cumulative consumption, assumed available to the aggregator via direct physical measurements of the energy flow, allows the ensemble to recover from its use in the demand response regime, i.e.

Power of Ensemble Diversity and Randomization for Energy Aggregation.

We study an ensemble of diverse (inhomogeneous) thermostatically controlled loads aggregated to provide the demand response (DR) services in a district-level energy system. Each load in the ensemble is assumed to be equipped with a random number generator switching heating/cooling on or off with a Poisson rate, r, when the load leaves the comfort zone. Ensemble diversity is modeled through inhomogeneity/disorder in the deterministic dynamics of loads.

Optimal structure and parameter learning of Ising models.

Reconstruction of the structure and parameters of an Ising model from binary samples is a problem of practical importance in a variety of disciplines, ranging from statistical physics and computational biology to image processing and machine learning. The focus of the research community shifted toward developing universal reconstruction algorithms that are both computationally efficient and require the minimal amount of expensive data. We introduce a new method, interaction screening, which accurately estimates model parameters using local optimization problems.

Ensemble of Thermostatically Controlled Loads: Statistical Physics Approach.

Thermostatically controlled loads, e.g., air conditioners and heaters, are by far the most widespread consumers of electricity.

Fault-induced delayed voltage recovery in a long inhomogeneous power-distribution feeder.

We analyze the dynamics of a distribution circuit loaded with many induction motors and subjected to sudden changes in voltage at the beginning of the circuit. As opposed to earlier work by Duclut et al. [Phys.

Hysteresis, phase transitions, and dangerous transients in electrical power distribution systems.

The majority of dynamical studies in power systems focus on the high-voltage transmission grids where models consider large generators interacting with crude aggregations of individual small loads. However, new phenomena have been observed indicating that the spatial distribution of collective, nonlinear contribution of these small loads in the low-voltage distribution grid is crucial to the outcome of these dynamical transients. To elucidate the phenomenon, we study the dynamics of voltage and power flows in a spatially extended distribution feeder (circuit) connecting many asynchronous induction motors and discover that this relatively simple 1+1 (space+time) dimensional system exhibits a plethora of nontrivial spatiotemporal effects, some of which may be dangerous for power system stability.

Synchronization in complex oscillator networks and smart grids.

The emergence of synchronization in a network of coupled oscillators is a fascinating topic in various scientific disciplines. A widely adopted model of a coupled oscillator network is characterized by a population of heterogeneous phase oscillators, a graph describing the interaction among them, and diffusive and sinusoidal coupling. It is known that a strongly coupled and sufficiently homogeneous network synchronizes, but the exact threshold from incoherence to synchrony is unknown.

Message passing for optimization and control of a power grid: model of a distribution system with redundancy.

We use a power grid model with M generators and N consumption units to optimize the grid and its control. Each consumer demand is drawn from a predefined finite-size-support distribution, thus simulating the instantaneous load fluctuations. Each generator has a maximum power capability.

Loop calculus in statistical physics and information science.

Considering a discrete and finite statistical model of a general position we introduce an exact expression for the partition function in terms of a finite series. The leading term in the series is the Bethe-Peierls (belief propagation) (BP) contribution; the rest are expressed as loop contributions on the factor graph and calculated directly using the BP solution. The series unveils a small parameter that often makes the BP approximation so successful.

Extreme outages caused by polarization mode dispersion.

We study the dependence on fiber birefringence of the bit-error rate (BER) caused by amplifier noise in a linear optical fiber telecommunication system. We show that the probability-distribution function of the BER obtained by averaging over many realizations of birefringent disorder has an extended tail that corresponds to anomalously large values of BER. We specifically discuss the dependence of the tail on such details of pulse detection at the fiber output as setting the clock and filtering procedures.

Phenomenology of Rayleigh-Taylor turbulence.

I analyze the advanced mixing regime of the Rayleigh-Taylor incompressible turbulence in the small Atwood number Boussinesq approximation. The prime focus of my phenomenological approach is to resolve the temporal behavior and the small-scale spatial correlations of velocity and temperature fields inside the mixing zone, which grows as proportional, variant t(2). I show that the "5/3"-Kolmogorov scenario for velocity and temperature spectra is realized in three spatial dimensions with the viscous and dissipative scales decreasing in time, proportional, variant t(-1/4).

Compensation for extreme outages caused by polarization mode dispersion and amplifier noise.

Fluctuations of Bit-Error-Rate (BER) stimulated by birefringent disorder in an optical fiber system are found to be strong. The effect may not be analyzed in terms of the average BER but rather requires analyzing the Probability Distribution Function (PDF) of BER. We report the emergence of the extremely extended algebraic-like tail of the PDF, corresponding to anomalously large values of BER.