It is commonly assumed that cleaning photovoltaic (PV) modules is unnecessary when the inverter is undersized because clipping will sufficiently mask the soiling losses. Clipping occurs when the inverter's AC size is smaller than the overall modules' DC capacity and leads to the conversion of only part of the PV-generated DC energy into AC. This study evaluates the validity of this assumption, theoretically investigating the current magnitude of clipping and its effect on soiling over the contiguous United States. This is done by modelling energy yield, clipping and soiling across a grid of locations. The results show that in reality, under the current deployment trends, inverter undersizing minimally affects soiling, as it reduces these losses by no more than 1%absolute. Indeed, clipping masks soiling in areas where losses are already low, whereas it has a negligible effect where soiling is most significant. However, the mitigation effects might increase under conditions of lower performance losses or more pronounced inverter undersizing. In any case, one should take into account that degradation makes clipping less frequent as systems age, also decreasing its masking effect on soiling. Therefore, even if soiling was initially mitigated by the inverter undersizing, its effect would become more visible with time.
Current biogeochemical models produce carbon–climate feedback projections with large uncertainties, often attributed to their structural differences when simulating soil organic carbon (SOC) dynamics worldwide. However, choices of model parameter values that quantify the strength and represent properties of different soil carbon cycle processes could also contribute to model simulation uncertainties. Here, we demonstrate the critical role of using common observational data in reducing model uncertainty in estimates of global SOC storage. Two structurally different models featuring distinctive carbon pools, decomposition kinetics, and carbon transfer pathways simulate opposite global SOC distributions with their customary parameter values yet converge to similar results after being informed by the same global SOC database using a data assimilation approach. The converged spatial SOC simulations result from similar simulations in key model components such as carbon transfer efficiency, baseline decomposition rate, and environmental effects on carbon fluxes by these two models after data assimilation. Moreover, data assimilation results suggest equally effective simulations of SOC using models following either first-order or Michaelis–Menten kinetics at the global scale. Nevertheless, a wider range of data with high-quality control and assurance are needed to further constrain SOC dynamics simulations and reduce unconstrained parameters. New sets of data, such as microbial genomics-function relationships, may also suggest novel structures to account for in future model development. Overall, our results highlight the importance of observational data in informing model development and constraining model predictions.
Asymmetric scattering is a phenomenon in which the field scattered from a discontinuity is dependent on the direction of incidence. In waveguide systems such as elastic plates, the existence of multiple propagating modes provides a platform to explore asymmetric scattering through direction-dependent mode coupling. This paper describes this concept in the context of reciprocal systems and how to utilize it in a general manner.
The phononic dispersion relations calculated by solving an eigenvalue problem while applying Bloch-Floquet boundary conditions are applied to three varieties of phononic pseudocrystals interposers useful for suppressing the transmission of structure-born vibration.
This paper presents a new approach for autonomous motion planning for aircraft suffering from a loss-of-thrust emergency. Specifically, we show how modifications to the Closed-Loop Rapidly exploring Random Trees (CL-RRT) framework combined with controlled energy dissipation can enable rapid and effective kinodynamic motion planning. This CL-RRT Glide algorithm uses closed-loop prediction not only for node connections but also to estimate the remaining energy and prune infeasible paths. This greatly speeds up the search process, which is essential for emergency situations. In addition, we improve the ability of the gliding aircraft to reach a goal position and energy state. We do so by creating a Dissipative Total Energy Control Scheme (TECS). Dissipative TECS enables the glider to lose excess altitude in order to reach a desired energy level. Simulation results illustrate how the proposed methods enable faster motion planning. We also integrate the system into a small unmanned aerial vehicle system and experimentally demonstrate autonomous glide planning and execution during a motor-failure event. This type of algorithm can primarily benefit unmanned aircraft but can also serve to assist pilots in stressful emergency situations.
Stanek, Lucas J.; Hansen, Stephanie B.; Kononov, Alina K.; Cochrane, Kyle; Clay III, Raymond C.; Townsend, Joshua P.; Dumi, Amanda; Lentz, Meghan; Melton, Cody A.; Baczewski, Andrew D.; Knapp, Patrick F.; Haines, Brian M.; Hu, S.X.; Murillo, Michael S.; Stanton, Liam G.; Whitley, Heather D.; Baalrud, Scott D.; Babati, Lucas J.; Bethkenhagen, Mandy; Blanchet, Augustin; Collins, Lee A.; Faussurier, Gerald; French, Martin; Johnson, Zachary A.; Karasiev, Valentin V.; Kumar, Shashikant; Nichols, Katarina A.; Petrov, George M.; Recoules, Vanina; Redmer, Ronald; Ropke, Gerd; Schorner, Maximilian; Shaffer, Nathaniel R.; Sharma, Vidushi; Silvestri, Luciano G.; Soubiran, Francois; Suryanarayana, Phanish; Tacu, Mikael; White, Alexander J.
We report the results of the second charged-particle transport coefficient code comparison workshop, which was held in Livermore, California on 24-27 July 2023. This workshop gathered theoretical, computational, and experimental scientists to assess the state of computational and experimental techniques for understanding charged-particle transport coefficients relevant to high-energy-density plasma science. Data for electronic and ionic transport coefficients, namely, the direct current electrical conductivity, electron thermal conductivity, ion shear viscosity, and ion thermal conductivity were computed and compared for multiple plasma conditions. Additional comparisons were carried out for electron-ion properties such as the electron-ion equilibration time and alpha particle stopping power. Overall, 39 participants submitted calculated results from 18 independent approaches, spanning methods from parameterized semi-empirical models to time-dependent density functional theory. In the cases studied here, we find significant differences—several orders of magnitude—between approaches, particularly at lower temperatures, and smaller differences—roughly a factor of five—among first-principles models. We investigate the origins of these differences through comparisons of underlying predictions of ionic and electronic structure. The results of this workshop help to identify plasma conditions where computationally inexpensive approaches are accurate, where computationally expensive models are required, and where experimental measurements will have high impact.