Chao Li

In viscoelastic fluids, the inherent memory effects lead to the temporal correlation between damping and thermal noise. This poses a fundamental challenge to the design of control protocols that achieve the efficient and high-precision operation, thereby limiting the regulation of microscale heat engines and molecular motors. To address this problem, we formulate a theoretical framework using the generalized Langevin equation and derive the corresponding stochastic thermodynamics via the auxiliary variable approach. We further develop a reverse-engineering approach to characterize the nonequilibrium effects under external control. Within this framework, the optimization of dissipation under fast driving is transformed into a geodesic solution in the parameter space. We also introduce entropic bounds to quantify the trade-off between dissipation and precision. Our analysis demonstrates theoretically that, under non-Markovian memory effects, the optimal precision–dissipation trade-off is achieved when the Cauchy–Schwarz inequality is saturated. The theoretical findings of this work can be extended to the finite-time optimal design of microscopic transport and energy conversion systems, thereby offering a theoretical framework to analyze the efficiency limits within the class of microscopic energy conversion systems operating in non-Newtonian environments.

To improve the combustion and emission performance of a micro diesel pilot-ignition (DPI) natural gas (NG) engine, four groups of piston shapes were designed and the effects of piston shapes and swirl ratios on the combustion process were discussed by computational fluid dynamics (CFD) coupled with the simplified chemical kinetic mechanism. Based on a calibrated CFD model, the effects of piston shape and swirl ratio on the combustion and emission characteristics of a DPI NG engine were investigated in detail, and some new findings were obtained. Both P_max and the peak heat release rate (HRR) increase first and then fall with the swirl ratio increasing from 0.5 to 3.0 in the four piston shapes. Additionally, the HRR has only one peak as the swirl ratio ≤1.0 but two peaks if the swirl ratio ≥1.5. When the piston shape changes from P0 to P3, P_max decreases gradually and the position of P_max advances from 14.7°CA to 11.3°CA. The ignition delay becomes shorter as the swirl ratio increases from 0.5 to 3.0. Additionally, it is observed that the ignition delay is the longest in P3, which has a larger opening size and shallower grooves, even at the same swirl ratio. Moreover, P3 leads to a decrease in NO_x emissions, with a maximum reduction of 1446 ppm. Except for P3, when the swirl ratio increases, both CH₄ and CO emissions show an increasing trend with a maximum increase of 298 ppm and 277 ppm, respectively. All these are helpful for the design and optimization of the combustion system of a DPI NG engine to meet stringent emission standards.

The exploration of the control parameters for experimental facility in terms of their coupling effects can provide direct guidance for experimental research of fuel cells. In this study, a model based on an improved generalized regression neural network (GRNN) is proposed to study the coupling effect of control parameters that can be set and adjusted directly during the experiment. In addition, the expectation-maximization algorithm and the ensemble filter algorithm are introduced to preprocess data; the adaptive learning factor and the differential evolution strategy are introduced to improve the GRNN. Moreover, a moment-independent global sensitivity analysis is introduced to apply for sensitivity analysis by the dimensional reduction technique and principle of maximum entropy. The results indicated that the improved model can accurately predict performance in a dynamic environment; the relative error was <1.7%, the prediction errors were, respectively, reduced by 35.61%, 19.78%, 60.99%, and 37.55% as compared with the GRNN model, demonstrating the effectiveness of the improvement strategy; the back pressure and inlet temperatures, dew point, and cell temperatures were classified as sensitive factors; when the anodic back pressure was approximately 1 atm, the cathodic back pressure had little influence, the performance conforms to the maximum level.