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At least 55 records · Page 3

Robust Medium-Voltage Distribution System State Estimation using Multi-Source Data

Due to the lack of sufficient online measurements for distribution system observability, pseudo-measurements from short-term load or distributed renewable energy resources (DERs) forecasting are used. However, the accuracy of them is low and thus significantly limits the performance of distribution system state estimation (DSSE). In this paper, a robust DSSE that integrates multi-source measurement data is proposed. Specifically, the historical low-voltage (LV) side smart meters are used to forecast load and DERs injections via the support vector machine (SVM) with optimally tuned parameters. By contrast, the online smart meters at LV side are utilized to derive equivalent power injections at the MV/LV transformers, yielding more accurate pseudo-measurements compared to the forecasted injections. Furthermore, to deal with bad data caused by communication loss, instrumental errors and cyber attacks, robust DSSE that relies on generalized maximum-likelihood (GM)-estimation criterion is developed. The projection statistics are developed to adjust the weights of each measurement, leading to better balance between pseudo- and real-time measurements. Numerical results conducted on modified IEEE 33-bus system with DG integration demonstrate the effectiveness and robustness of the proposed method.

distribution system state estimation↗

SU-E-T-527: Is CTV-Based Robust Optimized IMPT in Non-Small-Cell Lung Cancer Robust Against Respiratory Motion?

Purpose: To determine which proton planning technique on average-CT is more vulnerable to respiratory motion induced density changes and interplay effect among (a) IMPT of CTV-based minimax robust optimization with 5mm set-up error considered, (b, c) IMPT/SFUD of 5mm-expanded PTV optimization. Methods: Three planning techniques were optimized in Raystation with a prescription of 60/25 (Gy/fractions) and almost the same OAR constraints/objectives for each of 10 NSCLC patients. 4D dose without/with interplay effect was recalculated on eight 4D-CT phases and accumulated after deforming the dose of each phase to a reference (exhalation phase). The change of D98% of each CTV caused by density changes and interplay was determined. In addition, evaluation of the DVH information vector (D99%, D98%, D95%, Dave, D50%, D2%, D1%) which compares the whole DVH by η score = (cosine similarity × Pearson correlation coefficient − 0.9) × 1000 quantified the degree of DVH change: score below 100 indicates changed DVH. Results: Three 3D plans of each technique satisfied our clinical goals. D98% shift mean±SD (Gy) due to density changes was largest in (c): −0.78±1.1 while (a): −0.11±0.65 and (b): − 0.59±0.93. Also the shift due to interplay effect most was (c): −.54±0.70 whereas (a): −0.25±0.93 and (b): −0.12±0.13. Moreover lowest η score caused by density change was also (c): 69, while (a) and (b) kept around 90. η score also indicated less effect of interplay than density changes. Note that generally the changed DVH were still acceptable clinically. Paired T-tests showed a significantly smaller density change effect in (a) (p<0.05) than in (b) or (c) and no significant difference in interplay effect. Conclusion: CTV-based robust optimized IMPT was more robust against respiratory motion induced density changes than PTV-based IMPT and SFUD. The interplay effect was smaller than the effect of density changes and similar among the three techniques. The JSPS Core-to-Core Program (No. 23003), Japan Society for the Promotion of Science Grant-in-Aid for Scientific Research (No. 23390300), Grant-in-Aid for Young Scientists (B) (No. 21791194) and Grant-in-Aid for Cancer Research (H22-3rd Term Cancer Control-General-043)

60 APPLIED LIFE SCIENCES↗

Residuals-based distributionally robust optimization with covariate information

We consider data-driven approaches that integrate a machine learning prediction model within distributionally robust optimization (DRO) given limited joint observations of uncertain parameters and covariates. Our framework is flexible in the sense that it can accommodate a variety of regression setups and DRO ambiguity sets. We investigate asymptotic and finite sample properties of solutions obtained using Wasserstein, sample robust optimization, and phi-divergence-based ambiguity sets within our DRO formulations, and explore cross-validation approaches for sizing these ambiguity sets. Through numerical experiments, we validate our theoretical results, study the effectiveness of our approaches for sizing ambiguity sets, and illustrate the benefits of our DRO formulations in the limited data regime even when the prediction model is misspecified.

97 MATHEMATICS AND COMPUTING↗

IPL-Annealed Mixed-Cation Perovskites with Robust Coating Window toward Scalable Manufacturing of Commercial Perovskite Solar Cells

Perovskite solar cells (PSCs) are a promising alternative solar technology, but the technical challenges of (1) stability/durability, (2) efficiency at scale, and (3) manufacturability must be overcome to achieve widespread PSC commercialization. The challenge of balancing solution ink formulation and scalable manufacturing is often overlooked in the literature, where focus is on adopting inks from processes that will not scale. In this study, we apply a classical roll-to-roll manufacturing perspective, utilizing both compositional engineering and intense pulsed light (IPL) annealing, to develop a mixed-cation perovskite ink with a robust coating window that simultaneously solve issues of stability and manufacturability for PSCs. Our method resulted in blade-coated, flexible, mixed-cation PSCs on ITO-PET substrates with a champion power conversion efficiency (PCE) efficiency of 16.7% using IPL annealing of the absorber layer and, to our knowledge, is one of the fastest processing methods for the perovskite layer. This overall reduction in processing time with a stable ink represents an advance toward the scaled production of perovskite solar cells on flexible substrates.

flexible perovskite solar cells↗

Covalent Functionalization of Silicon with Plasma-Grown “Fuzzy” Graphene: Robust Aqueous Photoelectrodes for CO 2 Reduction by Molecular Catalysts

Carbon electrodes are ideal for electrochemistry with molecular catalysts, exhibiting facile charge transfer and good stability. Yet for solar-driven catalysis with semiconductor light absorbers, stable semiconductor/carbon interfaces can be difficult to achieve, and carbon’s high optical extinction means it can only be used in ultrathin layers. Here, we demonstrate a plasma-enhanced chemical vapor deposition process that achieves well-controlled deposition of out-of-plane “fuzzy” graphene (FG) on thermally oxidized Si substrates. The resulting Si|FG interfaces possess a silicon oxycarbide (SiOC) interfacial layer, implying covalent bonding between Si and the FG film that is consistent with the mechanical robustness observed from the films. The FG layer is uniform and tunable in thickness and optical transparency by deposition time. Using p-type Si|FG substrates, noncovalent immobilization of cobalt phthalocyanine (CoPc) molecular catalysts was employed for the photoelectrochemical reduction of CO 2 in aqueous solution. The Si|FG|CoPc photocathodes exhibited good catalytic activity, yielding a current density of ∼1 mA/cm 2 , Faradaic efficiency for CO of ∼70% (balance H 2 ), and stable photocurrent for at least 30 h at −1.5 V vs Ag/AgCl under 1-sun illumination. Furthermore, the results suggest that plasma-deposited FG is a robust carbon electrode for molecular catalysts and suitable for further development of aqueous-stable Si photocathodes for CO 2 reduction.

CO2 reduction↗

Structure-Assisted Functional Anchor Implantation in Robust Metal-Organic Frameworks with Ultra large Pores

A facile functionalization assisted by the structural attributes of PCN-333 has been studied while maintaining the integrity of the parent MOF including ultralarge pores, chemical robustness, and crystallinity. Herein we thoroughly analyzed ligand exchange phenomena in PCN-333 and demonstrate that the extent of exchange can be tailored by varying the exchange conditions as potential applications may require. Through this method a variety of functional groups are incorporated into PCN-333. To further show the capabilities of this system introduction of a BODIPY fluorophore as a secondary functionality was performed to the functionalized framework via a click reaction. We anticipate the PCN-333 with functional anchor can serve as a stable platform for further chemistry to be explored in future applications

Park, J↗

Robust and compact entanglement generation from diode-laser-pumped four-wave mixing

Four-wave-mixing processes are now routinely used to demonstrate multi-spatial-mode Einstein-Podolsky-Rosen entanglement and intensity difference squeezing. Diode-laser-pumped four-wave mixing processes have recently been shown to provide an affordable, compact, and stable source for intensity difference squeezing, but it was unknown if excess phase noise present in power amplifier pump configurations would be an impediment to achieving quadrature entanglement. Here, we demonstrate the operating regimes under which these systems are capable of producing entanglement and under which excess phase noise produced by the amplifier contaminates the output state. We show that Einstein-Podolsky-Rosen entanglement in two mode squeezed states can be generated by a four-wave-mixing source deriving both the pump field and the local oscillators from a tapered-amplifier diode-laser. This robust continuous variable entanglement source is highly scalable and amenable to miniaturization, making it a critical step toward the development of integrated quantum sensors and scalable quantum information processors, such as spatial comb cluster states.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Robust non-Abelian spin liquid and a possible intermediate phase in the antiferromagnetic Kitaev model with magnetic field

In this work, we investigate the non-Abelian topological chiral spin-liquid phase in the two-dimensional Kitaev honeycomb model subject to a magnetic field. By combining density matrix renormalization group and exact diagonalization we study the energy spectra, entanglement, topological degeneracy, and expectation values of Wilson loop operators, allowing for a robust characterization. While the ferromagnetic Kitaev spin liquid is already destroyed by a weak magnetic field with Zeeman energy $H^{FM}_\ast ≈ 0.02$, the antiferromagnetic (AFM) spin liquid remains robust up to a magnetic field that is an order of magnitude larger, $H^{AFM}_\ast ≈ 0.2$. Interestingly, for larger fields $H^{AFM}_\ast < H < H^{AFM}_{\ast\ast}$, an intermediate gapless phase is observed, before a second transition to the high-field partially polarized paramagnet. We attribute this rich phase diagram, and the remarkable stability of the chiral topological phase in the AFM Kitaev model, to the interplay of strong spin-orbit coupling and frustration enhanced by the magnetic field. Our findings suggest relevance to recent experiments on RuCl 3 under magnetic fields.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Dark Energy Survey Year 3 results: Cosmology from cosmic shear and robustness to data calibration

This work, together with its companion paper, Secco, Samuroff et al., presents the Dark Energy Survey Year 3 cosmic shear measurements and cosmological constraints based on an analysis of over 100 million source galaxies. With the data spanning 4143 deg 2 on the sky, divided into four redshift bins, we produce the highest significance measurement of cosmic shear to date, with a signal-to-noise of 40. We conduct a blind analysis in the context of the ΛCDM model and find a 3% constraint of the clustering amplitude, S 8 ≡ σ 8 (Ω m /0.3) 0.5 = 0.759$^{+0.025}_{-0.023}$. A ΛCDM-Optimized analysis, which safely includes smaller scale information, yields a 2% precision measurement of S 8 = 0.772$^{+0.018}_{-0.017}$ that is consistent with the fiducial case. The two low-redshift measurements are statistically consistent with the Planck Cosmic Microwave Background result, however, both recovered S 8 values are lower than the high-redshift prediction by 2.3σ and 2.1σ (ρ-values of 0.02 and 0.05), respectively. The measurements are shown to be internally consistent across redshift bins, angular scales and correlation functions. The analysis is demonstrated to be robust to calibration systematics, with the S 8 posterior consistent when varying the choice of redshift calibration sample, the modeling of redshift uncertainty and methodology. Similarly, we find that the corrections included to account for the blending of galaxies shifts our best-fit S 8 by 0.5σ without incurring a substantial increase in uncertainty. We examine the limiting factors for the precision of the cosmological constraints and find observational systematics to be subdominant to the modeling of astrophysics. Specifically, we identify the uncertainties in modeling baryonic effects and intrinsic alignments as the limiting systematics.

79 ASTRONOMY AND ASTROPHYSICS↗

Robust structural analysis of native biological macromolecules from multi-crystal anomalous diffraction data

Anomalous diffraction signals from typical native macromolecules are very weak, frustrating their use in structure determination. Here, native SAD procedures are described for enhancing the signal to noise in anomalous diffraction by using multiple crystals are described. Five applications demonstrate that truly routine structure determination is possible without the need for heavy atoms. Structure determinations for biological macromolecules that have no known structural antecedents typically involve the incorporation of heavier atoms than those found natively in biological molecules. Currently, selenomethionyl proteins analyzed using single- or multi-wavelength anomalous diffraction (SAD or MAD) data predominate for such de novo analyses. Naturally occurring metal ions such as zinc or iron often suffice in MAD or SAD experiments, and sulfur SAD has been an option since it was first demonstrated using crambin 30 years ago; however, SAD analyses of structures containing only light atoms (Z{sub max} ≤ 20) have not been common. Here, robust procedures for enhancing the signal to noise in measurements of anomalous diffraction by combining data collected from several crystals at a lower than usual X-ray energy are described. This multi-crystal native SAD method was applied in five structure determinations, using between five and 13 crystals to determine substructures of between four and 52 anomalous scatterers (Z ≤ 20) and then the full structures ranging from 127 to 1200 ordered residues per asymmetric unit at resolutions from 2.3 to 2.8 Å. Tests were devised to assure that all of the crystals used were statistically equivalent. Elemental identities for Ca, Cl, S, P and Mg were proven by f′′ scattering-factor refinements. The procedures are robust, indicating that truly routine structure determination of typical native macromolecules is realised. Synchrotron beamlines that are optimized for low-energy X-ray diffraction measurements will facilitate such direct structural analysis.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Response of precipitation extremes to idealized global warming in an aqua-planet climate model: towards a robust projection across different horizontal resolutions

Current climate models produce quite heterogeneous projections for the responses of precipitation extremes to future climate change. To help understand the range of projections from multimodel ensembles, a series of idealized 'aquaplanet' Atmospheric General Circulation Model (AGCM) runs have been performed with the Community Atmosphere Model CAM3. These runs have been analysed to identify the effects of horizontal resolution on precipitation extreme projections under two simple global warming scenarios. We adopt the aquaplanet framework for our simulations to remove any sensitivity to the spatial resolution of external inputs and to focus on the roles of model physics and dynamics. Results show that a uniform increase of sea surface temperature (SST) and an increase of low-to-high latitude SST gradient both lead to increase of precipitation and precipitation extremes for most latitudes. The perturbed SSTs generally have stronger impacts on precipitation extremes than on mean precipitation. Horizontal model resolution strongly affects the global warming signals in the extreme precipitation in tropical and subtropical regions but not in high latitude regions. This study illustrates that the effects of horizontal resolution have to be taken into account to develop more robust projections of precipitation extremes.

54 ENVIRONMENTAL SCIENCES↗