This study was designed to investigate the effects of hemodynamic environment and design factors on the hydraulic performance and hemocompatibility of interventional blood pumps using computational fluid dynamics methods combined with specialized mathematical models. These analyses assessed how different hemodynamic environments (such as support mode and artery size) and blood pump configurations (including entrance/exit blade angles, rotor diameter, blade number, and diffuser presence) affect hydraulic performance indicators (rotational speed, flow rate, pressure head, and efficiency) and hemocompatibility indicators (bleeding, hemolysis, and thrombosis). Our findings indicate that higher perfused flow rates necessitate greater rotational speeds, which, in turn, reduce both efficiency and hemocompatibility. As the artery size increases, the hydraulic performance of the pump improves but at the cost of worsening hemocompatibility. Among the design parameters, optimal configurations exist that balance both hydraulic performance and hemocompatibility. Notably, a configuration without a diffuser demonstrated better hydraulic performance and hemocompatibility compared to one with a diffuser. Further analysis revealed that flow losses primarily contribute to the degradation of hydraulic performance and deterioration of hemocompatibility. Shear stress was identified as the major cause of blood damage in interventional blood pumps, with residence time having a limited impact. This study comprehensively explored the effects of operating environment and design parameters on catheter pump performance using a multi-faceted blood damage model, providing insights into related complications from a biomechanical perspective. These findings offer valuable guidance for engineering design and clinical treatment.
Within the deregulation process of distribution systems, the distribution locational marginal price (DLMP) provides effective market signals for future unit investment. In that context, this paper proposes a two-stage stochastic bilevel programming (TS-SBP) model for investors to best allocate battery energy storage systems (BESSs). The first stage obtains the optimal siting and sizing of BESSs on a limited budget. The second stage, a bilevel BESS arbitrage model, maximizes the arbitrage revenue in the upper level and clears the distribution market in the lower level. Karush-Kuhn-Tucker (KKT) optimality conditions, strong duality theory, and the big-M method are utilized to transform the TS-SBP model into a tractable two-stage stochastic mixed-integer linear programming (TS-SMILP) model. A novel statistics-based scenario extraction algorithm is proposed to generate a series of typical operating scenarios. Then, scale reduction strategies for BESS candidate buses and inactive voltage constraints are proposed to reduce the scale of the TS-SMILP model. Finally, case studies on the IEEE 33-bus and 123-bus systems validate the effectiveness of the DLMP in incentivizing BESS planning and the efficiency of the two proposed scale reduction strategies.
A polarization-insensitive multimode antisymmetric waveguide Bragg grating (MASWBG) filter based on an SiN-Si dual-layer stack is demonstrated. Carefully optimized grating corrugations patterned on the sidewall of a silicon waveguide and SiN overlay are used to perturbate TE and TM modes, respectively. Furthermore, the lateral-shift apodization technique is utilized to improve the sidelobe suppression ratio (SLSR). A good overlap between the passbands measured in TE and TM polarization states is obtained. Insertion losses, SLSRs, and 3-dB bandwidths of measured passbands in TE/TM polarizations are 1/1.72 dB, 18.5/19.1 dB, and 5.1/3.5 nm, respectively.
The consensus on the potential of market-targeting cyberattacks to cause catastrophic damage has driven recent research on electricity market cybersecurity analysis. This paper identifies two missing components in current literature. First, ISO revenue adequacy has not been analyzed under the context of cyberattacks. The false data injection attacks (FDIAs) could disturb the market settlement impacting revenue adequacy for ISOs. The lack of such analysis prevents ISOs from comprehensively assessing the financial consequences of market cyberattacks. Second, market attackers need to anticipate the market-clearing results to maximize their attack objectives. Thus, current literature focuses on formulating the attacker model and the market-clearing model as a bilevel problem. However, the coupling between the attack decision, the dispatch at ex-ante, and the price calculation at ex-post have not been explored. To fill those two research gaps, this paper first analytically explores the impact of FDIAs on real-time market operations on ISO revenue adequacy. Then, cyber-impact analysis is proposed to numerically analyze the revenue adequacy. The attacker model, ex-ante dispatch model, and ex-post incremental model are formulated as a trilevel problem to provide a reliable cyber-impact analysis on revenue adequacy. The proposed analysis and platform are demonstrated with the New-England 39-bus system.
In order to explore and develop new crystal materials in the 2.7–3.0 μm band, Pr, Yb, Ho:GdScO<sub>3</sub> crystal are successfully grown by the Czochralski method for the first time. X-ray diffraction measurement is performed to obtain powder diffraction data. Raman spectra aree measured and the vibration peaks are identified. The transmission spectrum, emission spectrum and fluorescence lifetime of Pr, Yb, Ho:GdScO<sub>3</sub> crystal are also characterized. The center of the strongest absorption band is at 966 nm with a half-peak width of 90 nm, which comes from the transition of Yb<sup>3+</sup>:<sup>2</sup>F<sub>7/2</sub> → <sup>2</sup>F<sub>5/2</sub>. The absorption cross section of Yb<sup>3+</sup> is calculated and the values at 966, 973, 985 nm are 0.62×10<sup>–20</sup>, 0.60×10<sup>–20</sup> and 0.58×10<sup>–20</sup> cm<sup>2</sup> respectively. The maximum emission peak is at 2850 nm and the half-peak width is 70 nm, the lifetimes of Ho<sup>3+</sup>:<sup>5</sup>I<sub>6</sub> and <sup>5</sup>I<sub>7</sub> are measured to be 1094 and 56 μs respectively, and the emission cross section at 2850 and 2935 nm are calculated to be 3.6×10<sup>–20</sup> cm<sup>2</sup> and 1.21×10<sup>–20</sup> cm<sup>2</sup>, respectively. Comparing with Yb, Ho: GdScO<sub>3</sub> crystal, the absorption peak of Yb<sup>3+</sup> and the emission peak are both broadened, which are related to the increase of crystal disorder. The lifetime of the lower energy level decreases significantly. Furthermore, the energy transfer mechanism between <inline-formula><tex-math id="Z-20240305181828">\begin{document}$\rm Ho^{3+} $\end{document}</tex-math><alternatives><graphic xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="5-20231362_Z-20240305181828.jpg"/><graphic xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="5-20231362_Z-20240305181828.png"/></alternatives></inline-formula> and Pr<sup>3+</sup> is analyzed, and the energy transfer efficiency between Ho<sup>3+</sup>:<sup>5</sup>I<sub>7</sub> and Pr<sup>3+</sup>:<sup>3</sup>F<sub>2</sub>+<sup>3</sup>H<sub>6</sub> is calculated to be 99%, which is higher than those in other materials. All the results show that Pr, Yb, Ho:GdScO<sub>3</sub> crystal is an excellent 2.7–3 μm laser material, and is easier to achieve laser output than Yb, Ho:GdScO<sub>3</sub> crystal.
The increasing penetration of distributed PV systems challenges the distribution system voltage profile. When the system loading level is relatively low on a sunny day, the reverse power flow is expected to be large and the bus voltage is likely to exceed the upper bound. This paper conducts a sensitivity study on the Volt- VArcontrol of distributed PV systems for mitigating the overvoltage problem. The distribution system components, including the ZIP load, shunt capacitor and onload tap changer, are fully considered. The simulation study indicates that the Volt-VArcontrol can effectively reduce the daily maximum bus voltage and slightly reduce the network power loss. In addition, this control scheme does not require additional VAR compensation and communication devices. Therefore, it has great potential in future distribution systems if the PV penetration keeps increasing.
We demonstrate a high efficiency, high linearity and high-speed silicon Mach-Zehnder modulator based on the DC Kerr effect enhanced by slow light. The two modulation arms based on 500-µm-long grating waveguides are embedded with PN and PIN junctions, respectively. A comprehensive comparison between the two modulation arms reveals that insertion loss, bandwidth and modulation linearity are improved significantly after employing the DC Kerr effect. The complementary advantages of the slow light and the DC Kerr effect enable a modulation efficiency of 0.85 V·cm, a linearity of 115 dB·Hz2/3, and a bandwidth of 30 GHz when the group index of slow light is set to 10. Furthermore, 112 Gbit/s PAM4 transmission over 2 km standard single mode fiber (SSMF) with bit error ratio (BER) below the soft decision forward error correction (SD-FEC) threshold is also demonstrated.
With the increasing application of artificial intelligence (AI) and machine learning (ML), the topic of technical debt management for machine learning systems is gaining more attention. Additionally, industrial systems including manufacturing or logistics processes are also supposed to benefit from AI and ML, which is reported in many publications related to ML application models. However, fewer studies on "how is technical debt managed in context of ML systems" are being published. This contribution fills this gap by reporting findings from 15 semi-structured and in-depth interviews conducted with industrial practitioners. Based on the interview results, suggestions for an initial technical debt management process and two document artifacts that facilitate the process are addressed.
In this paper, a fuel-based distributed generator (DG) allocation strategy is proposed to enhance the distribution system resilience against extreme weather. The long-term planning problem is formulated as a two-stage stochastic mixed-integer programming (SMIP). The first stage is to make decisions of DG siting and sizing under the given budget constraint. In the second stage, a post-extreme-event-restoration (PEER) is employed to minimize the operating cost in an uncertain fault scenario. In particular, this study proposes a method to select the most representative scenarios for the SMIP. First, a Monte Carlo Simulation (MCS) is introduced to generate sufficient scenarios considering random fault locations and load profiles. Then, the number of scenarios is reduced by the K-means clustering algorithm. The advantage of scenario reduction is to make a trade-off between accuracy and computational efficiency. Finally, the SMIP is solved by the progressive hedging algorithm. The case studies of the IEEE 33-bus and 123-bus test systems demonstrate the effectiveness of the proposed algorithm in reducing the expected energy not served (EENS), which is a critical criterion of resilience.
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