This paper is devoted to the shape optimization of the internal structure of an electric motor, and more precisely of the arrangement of air and ferromagnetic material inside the rotor part with the aim to increase the torque of the machine. The governing physical problem is the time-dependent, nonlinear magneto-quasi-static version of Maxwell’s equations. This multiphase problem can be reformulated on a 2D section of the real cylindrical 3D configuration; however, due to the rotation of the machine, the geometry of the various material phases at play (the ferromagnetic material, the permanent magnets, air, etc.) undergoes a prescribed motion over the considered time period. This original setting raises a number of issues. From the theoretical viewpoint, we prove the well-posedness of this unusual nonlinear evolution problem featuring a moving geometry. We then calculate the shape derivative of a performance criterion depending on the shape of the ferromagnetic phase via the corresponding magneto-quasi-static potential. Our numerical framework to address this problem is based on a shape gradient algorithm. The nonlinear time periodic evolution problems for the magneto-quasi-static potential is solved in the time domain, with a Newton–Raphson method. The discretization features a space-time finite element method, applied on a precise, meshed representation of the space-time region of interest, which encloses a body-fitted representation of the various material phases of the motor at all the considered stages of the time period. After appraising the efficiency of our numerical framework on an academic problem, we present a quite realistic example of optimal design of the ferromagnetic phase of the rotor of an electric machine.

We investigate the hydrodynamic limit problem for a kinetic flocking model. We develop a GCI-based Hilbert expansion method, and establish rigorously the asymptotic regime from the kinetic Cucker–Smale model with a confining potential in a mesoscopic scale to the macroscopic limit system for self-propelled individuals, which is derived formally by Aceves-Sánchez et al. in 2019. In the traditional kinetic equation with collisions, for example, Boltzmann-type equations, the key properties that connect the kinetic and fluid regimes are: the linearized collision operator (linearized collision operator around the equilibrium), denoted by [Formula: see text], is symmetric, and has a nontrivial null space (its elements are called collision invariants) which include all the fluid information, i.e. the dimension of Ker([Formula: see text]) is equal to the number of fluid variables. Furthermore, the moments of the collision invariants with the kinetic equations give the macroscopic equations. The new feature and difficulty of the corresponding problem considered in this paper is: the linearized operator [Formula: see text] is not symmetric, i.e. [Formula: see text], where [Formula: see text] is the dual of [Formula: see text]. Moreover, the collision invariants lies in Ker([Formula: see text]), which is called generalized collision invariants (GCI). This is fundamentally different with classical Boltzmann-type equations. This is a common feature of many collective motions of self-propelled particles with alignment in living systems, or many active particle system. Another difficulty (also common for active system) is involved by the normalization of the direction vector, which is highly nonlinear. In this paper, using Cucker–Smale model as an example, we develop systematically a GCI-based expansion method, and micro–macro decomposition on the dual space, to justify the limits to the macroscopic system, a non-Euler-type hyperbolic system. We believe our method has wide applications in the collective motions and active particle systems.

Adverse selection is a version of the principal-agent problem that includes monopolist nonlinear pricing, where a monopolist with known costs seeks a profit-maximizing price menu facing a population of potential consumers whose preferences are known only in the aggregate. For multidimensional spaces of agents and products, Rochet and Choné (Econometrica, 1998) reformulated this problem as a concave maximization over the set of convex functions, by assuming agent preferences combine bilinearity in the product and agent parameters with a quasilinear sensitivity to prices. We characterize solutions to this problem by identifying a dual minimization problem. This duality allows us to reduce the solution of the square example of Rochet–Choné to a novel free boundary problem, giving the first analytical description of an overlooked market segment.

In this paper, we consider an adaptive hybridizable discontinuous Galerkin (HDG) method based on the discrete fracture model for approximation of a single-phase flow in fractured porous media. We are interested in the case that the flow rate in fracture is large enough to justify the use of Forchheimer’s law for modeling flow within the fracture, while Darcy’s law is applied to the surrounding matrix. The HDG method could be designed to simulate the flow in porous media with reduced fractures which consist of many straight lines or planes. More specifically, we use piecewise polynomials of degree [Formula: see text] to approximate the velocity and pressure in fracture and surrounding porous media. The existence and uniqueness of discrete solutions are proved by the Brouwer fixed point theorem, and an efficient and reliable a posteriori error estimator is obtained with respect to an energy norm. Moreover, the HDG scheme, the existence and uniqueness of discrete solutions, and the a posteriori error estimates are also extended to the problem with non-planar, embedded, and intersecting fractures. Finally, several numerical examples are provided to validate the performance of the obtained a posteriori error estimator.

This paper presents a mathematical theory of behavioral swarms, where the state of interacting entities, which are called active particles, includes in addition to position and velocity, an internal variable, called activity, which has the ability to interact with mechanical variables thus affecting the interaction rules. In turn, the mechanical variables can modify the dynamics of activity variable. This approach is useful for describing the dynamics of living systems with a finite number of interacting entities. This paper provides a general conceptual framework that extends the pioneering work [N. Bellomo, S.-Y. Ha and N. Outada, Towards a mathematical theory of behavioral swarms, ESAIM[Formula: see text] Control Theory Var. Calculus 26 (2020) 125, https:/[Formula: see text]/doi.org/10.1051/cocv/2020071]. The theory is firstly developed for the constant number of active particles. Then, it is considered for the case of particles tending to infinity. This theory is useful for describing the dynamics of living systems. Therefore, it provides the conceptual basis for developing a mathematical theory of behavioral swarms, which naturally lead to the study of a theory of swarm intelligence. A study of the dynamics of swarms shows how the theory can be applied to real world collective dynamics.

This paper proposes and rigorously analyzes novel high-order bound-preserving oscillation-eliminating discontinuous Galerkin (BP-OEDG) schemes with the Harten–Lax–van Leer (HLL) numerical flux for the Kapila five-equation two-phase flow model. The evolution equation for the volume fraction is formulated as a conservative advection equation with an additional non-conservative source term. Utilizing a technical splitting approach, we design a uniformly high-order discretization for this source term, incorporating an “upwind” discretization of the non-conservative product at cell interfaces based on the HLL wave speeds. This method inherently ensures the symmetry of the volume fractions, which is crucial for establishing the bound-preserving property. The positivity of partial densities and internal energy is rigorously proven using the geometric quasilinearization (GQL) approach, which transforms the nonlinear pressure positivity constraint into equivalent linear constraints. To suppress potential spurious oscillations, we incorporate a scale-invariant and linearity-invariant oscillation elimination (OE) procedure that damps the DG modal coefficients after each Runge–Kutta stage, as proposed in [M. Peng, Z. Sun and K. Wu, OEDG: Oscillation-eliminating discontinuous Galerkin method for hyperbolic conservation laws, Math. Comput. (2024), https://doi.org/10.1090/mcom/3998]. This OE procedure, acting as a post-processing filter based on the jumps of the DG solution at cell interfaces, is easy to implement, maintains the Abgrall equilibrium condition around an isolated material interface, and preserves the high-order accuracy of the DG schemes. The effectiveness and robustness of the proposed high-order BP-OEDG schemes are demonstrated through several benchmark numerical experiments.

We consider the no-flux initial-boundary value problem for the growth-expansion model with chemotaxis in nutrient-replete environments in smoothly bounded domains [Formula: see text]. It is shown that if [Formula: see text] or if [Formula: see text] under some structural assumptions on parameter functions therein, for any suitably regular initial data the problem admits a unique global bounded classical solution. For any dimensions [Formula: see text], we also prove that the problem has a unique global classical solution which is bounded under a small assumption on the initial data. Moreover, we obtain that these solutions stabilize to a uniquely determined spatially uniform equilibrium. We also provide exponential rates of convergence of solutions in a special case.