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    Effect of Fans’ Placement on the Indoor Thermal Environment of Typical Tunnel-Ventilated Multi-Floor Pig Buildings Using Numerical Simulation
    (Basel : MDPI AG, 2022) Wang, Xiaoshuai; Cao, Mengbing; Hu, Feiyue; Yi, Qianying; Amon, Thomas; Janke, David; Xie, Tian; Zhang, Guoqiang; Wang, Kaiying
    An increasing number of large pig farms are being built in multi-floor pig buildings (MFPBs) in China. Currently, the ventilation system of MFPB varies greatly and lacks common standards. This work aims to compare the ventilation performance of three popular MFPB types with different placement of fans using the Computational Fluid Dynamics (CFD) technique. After being validated with field-measured data, the CFD models were extended to simulate the air velocity, air temperature, humidity, and effective temperature of the three MFPBs. The simulation results showed that the ventilation rate of the building with outflowing openings in the endwall and fans installed on the top of the shaft was approximately 25% less than the two buildings with fans installed on each floor. The ventilation rate of each floor increased from the first to the top floor for both buildings with a shaft, while no significant difference was observed in the building without a shaft. Increasing the shaft’s width could mitigate the variation in the ventilation rate of each floor. The effective temperature distribution at the animal level was consistent with the air velocity distribution. Therefore, in terms of the indoor environmental condition, the fans were recommended to be installed separately on each floor.
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    Application of the Phase-Space Path Integral to Strong-Laser-Field-Assisted Electron-Ion Radiative Recombination: A Gauge-Covariant Formulation
    (Basel : MDPI AG, 2020) Esquembre Kučukalić, Ali; Becker, Wilhelm; Milošević, Dejan B.
    We consider the problem of the choice of gauge in nonrelativistic strong-laser-field physics. For this purpose, we use the phase-space path-integral formalism to obtain the momentum-space matrix element of the exact time-evolution operator. With the assumption that the physical transition amplitude corresponds to transitions between eigenstates of the physical energy operator rather than the unperturbed Hamiltonian H0=(−i∂/∂r)2/2+V(r), we prove that the aforementioned momentum-space matrix elements obtained in velocity gauge and length gauge are equal. These results are applied to laser-assisted electron-ion radiative recombination (LAR). The transition amplitude comes out identical in length gauge and velocity gauge, and the expression agrees with the one conventionally obtained in length gauge. In addition to the strong-field approximation (SFA), which is the zeroth-order term of our expansion, we present explicit results for the first-order and the second-order terms, which correspond to LAR preceded by single and double scattering, respectively. Our general conclusion is that in applications to atomic processes in strong-field physics the length-gauge version of the SFA (and its higher-order corrections) should be used. Using the energy operator as the basis-defining Hamiltonian, we have shown that the resulting transition amplitude is gauge invariant and agrees with the form commonly derived in length gauge.
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    Microfluidic Network Simulations Enable On-Demand Prediction of Control Parameters for Operating Lab-on-a-Chip-Devices
    (Basel : MDPI AG, 2021) Böke, Julia Sophie; Kraus, Daniel; Henkel, Thomas
    Reliable operation of lab-on-a-chip systems depends on user-friendly, precise, and predictable fluid management tailored to particular sub-tasks of the microfluidic process protocol and their required sample fluids. Pressure-driven flow control, where the sample fluids are delivered to the chip from pressurized feed vessels, simplifies the fluid management even for multiple fluids. The achieved flow rates depend on the pressure settings, fluid properties, and pressure-throughput characteristics of the complete microfluidic system composed of the chip and the interconnecting tubing. The prediction of the required pressure settings for achieving given flow rates simplifies the control tasks and enables opportunities for automation. In our work, we utilize a fast-running, Kirchhoff-based microfluidic network simulation that solves the complete microfluidic system for in-line prediction of the required pressure settings within less than 200 ms. The appropriateness of and benefits from this approach are demonstrated as exemplary for creating multi-component laminar co-flow and the creation of droplets with variable composition. Image-based methods were combined with chemometric approaches for the readout and correlation of the created multi-component flow patterns with the predictions obtained from the solver.