We present a novel, fast differentiable simulator for soft-body learning and control applications. Existing differentiable soft-body simulators can be classified into two categories based on their time integration methods: Simulators using explicit timestepping schemes require tiny timesteps to avoid numerical instabilities in gradient computation, and simulators using implicit time integration typically compute gradients by employing the adjoint method and solving the expensive linearized dynamics. Inspired by
), we present
Differentiable Projective Dynamics
), an efficient differentiable soft-body simulator based on PD with implicit time integration. The key idea in DiffPD is to speed up backpropagation by exploiting the prefactorized Cholesky decomposition in forward PD simulation. In terms of contact handling, DiffPD supports two types of contacts: a penalty-based model describing contact and friction forces and a complementarity-based model enforcing non-penetration conditions and static friction. We evaluate the performance of DiffPD and observe it is 4–19 times faster compared with the standard Newton’s method in various applications including system identification, inverse design problems, trajectory optimization, and closed-loop control. We also apply DiffPD in a
) example with contact and collisions and show its capability of reconstructing a digital twin of real-world scenes.
AbstractA novel explicit three-sub-step time integration method is proposed. From linear analysis, it is designed to have at least second-order accuracy, tunable stability interval, tunable algorithmic dissipation and no overshooting behaviour. A distinctive feature is that the size of its stability interval can be adjusted to control the properties of the method. With the largest stability interval, the new method has better amplitude accuracy and smaller dispersion error for wave propagation problems, compared with some existing second-order explicit methods, and as the stability interval narrows, it shows improved period accuracy and stronger algorithmic dissipation. By selecting an appropriate stability interval, the proposed method can achieve properties better than or close to existing second-order methods, and by increasing or reducing the stability interval, it can be used with higher efficiency or stronger dissipation. The new method is applied to solve some illustrative wave propagation examples, and its numerical performance is compared with those of several widely used explicit methods.
This paper aims to review the critical technology development of avian radar system at airports.
After the origin of avian radar technology is discussed, the target characteristics of flying birds are analyzed, including the target echo amplitude, flight speed, flight height, trajectory and micro-Doppler. Four typical airport avian radar systems of Merlin, Accipiter, Robin and CAST are introduced. The performance of different modules such as antenna, target detection and tracking, target recognition and classification, analysis of bird information together determines the detection ability of avian radar. The performances and key technologies of the ubiquitous avian radar are summarized and compared with other systems, and their applications, deployment modes, as well as their advantages and disadvantages are introduced and analyzed.
The ubiquitous avian radar achieves the long-time integration of target echoes, which greatly improves detection and classification ability of the targets of birds or drones, even under strong background clutter at airport. In addition, based on the big data of bird situation accumulated by avian radar, the rules of bird activity around the airport can be mined to guide the bird avoidance work.
This paper presented a novel avian radar system based on ubiquitous digital radar technology. The authors’ experience has confirmed that this system can be effective for airport bird strike prevention and management. In the future, the avian radar system will see continued improvement in both software and hardware, as the system is designed to be easily extensible.
Living cells process information about their environment through the central dogma processes of transcription and translation, which drive the cellular response to stimuli. Here, we study the transfer of information from environmental input to the transcript and protein expression levels. Evaluation of both experimental and analogous simulation data reveals that transcription and translation are not two simple information channels connected in series. Instead, we show that the central dogma reactions often create a time-integrating information channel, where the translation channel receives and integrates multiple outputs from the transcription channel. This information channel model of the central dogma provides new information-theoretic selection criteria for the central dogma rate constants. Using the data for four well-studied species we show that their central dogma rate constants achieve information gain due to time integration while also keeping the loss due to stochasticity in translation relatively low (< 0.5 bits).
In the present work we investigate for the ﬁrst time the 2D ﬂuid transport of the plasma in WEST during an entire discharge from the start-up to the ramp-down (shot #54487). The evolution of density proﬁle, electron and ion temperatures together with the experimental magnetic equilibrium, total current and gas-puﬀ rate is investigated. Comparisons with the interferometry diagnostic show a remarkable overall qualitative agreement during the discharge that can be quantitative at some locations in the plasma core. If at the onset of the X-points during the ramp-up the electron heat ﬂux is dominant at the target, present results show that the ion heat ﬂux becomes dominant during the stationary phase of the discharge. Using a simple model for erosion, present results assess the tungsten sputtering due to deuterium ions during the start-up and ramp-up phases of the discharge and conﬁrms the need to consider full discharge simulation to accurately treat the W source of contamination. This work also demonstrates the interest of developing magnetic equilibrium free solver including eﬃcient time integration to step toward predictive capabilities in the future for fusion operation.