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This client-side web app tracks the amount of time spent on arbitrary tasks. It allosw the creation of an unlimited number of arbitrarily named tasks ans via simple interactions, tracks the amount of time spent working on the drfined tasks.
This client-side web app tracks the amount of time spent on arbitrary tasks. It allosw the creation of an unlimited number of arbitrarily named tasks ans via simple interactions, tracks the amount of time spent working on the drfined tasks.
This paper summarizes the technical activities of the Task Force on Power System Dynamic State and Parameter Estimation. This Task Force was established by the IEEE Working Group on State Estimation Algorithms to investigate the added benefits of dynamic state and parameter estimation for the enhancement of the reliability, security, and resilience of electric power systems. The motivations and engineering values of dynamic state estimation (DSE) are discussed in detail. Then, a set of potential applications that will rely on DSE is presented and discussed. Furthermore, a unified framework is proposed to clarify the important concepts related to DSE, forecasting-aided state estimation, tracking state estimation and static state estimation. An overview of the current progress in DSE and dynamic parameter estimation is provided. The paper also provides future research needs and directions for the power engineering community.
Background: Mercury is a global contaminant with toxic, persistent effects on human health. Petroleum extraction is an important source of elemental mercury; little is known about human exposure levels near oil fields in the Amazon basin. Objectives: To characterize mercury levels in people living near oil production sites in the Peruvian and Ecuadorian Amazon, controlling for fish consumption, occupation, source of water and socio-demographic characteristics. Methods: Analyze mercury levels in urine samples using cold vapour atomic fluorescence spectrometry from 76 indigenous men and women in eight riverine communities situated near oil wells or pipelines. Subjects answered a questionnaire soliciting socio-demographic, occupational and dietary information. Data were analyzed using multiple linear regression modeling. Results: The mean value of U-Hg was 2.61 μg/g creatinine (95% CI: 2.14–3.08), with 7% of the sample recording values above the global background standard suggested by The World Health Organization (5 μg/g creatinine). Women who used water from a surface source had two and a half times the amount of mercury in their urine (mean=3.70 μg/g creatinine, 95% CI: 2.26–5.15) compared with women who used other water sources (mean =1.39 μg/g creatinine, 95% CI: 0.51–2.25). Men who were involved in an oil clean-up operation had twice as much mercury in their urine (mean =3.07 μg/g creatinine, 95% CI: 1.97–4.16) as did those who worked on other tasks (mean =1.56 μg/g creatinine, 95% CI: 1.48–2.65). Mercury levels were not associated with the number of fish meals per week. Conclusions: Indigenous peoples of the Peruvian and Ecuadorian Amazon living near oil production sites generally had urine mercury levels within the global background standard suggested by the World Health Organization. Increased levels of mercury in urine were detected for men involved in oil spill remediation and for women who relied on surface water for household needs. These findings signal the need for strict safety measures to limit the amount of oil entering the waterways in Andean Amazonia so as to protect the health of indigenous people. - Highlights: • 7% of participants had levels of inorganic mercury at or exceeding levels suggested by WHO (5 μg/g creatinine). • U-Hg levels were 2.5 times higher among women using surface water than those who drew on water from a well, spring or rain. • Men who had worked cleaning up an oil spill had more than twice the amount of mercury in their urine as men who did not.
Increasing the competitiveness of the existing pulverized-coal utility fleet in the United States may be achieved by decreasing heat rate, via increases in steam cycle efficiency through upgraded steam temperatures and use of latest technology available in steam turbine and blading design. The average net plant efficiency of the US coal-fired fleet is approximately 33% (HHV). Plant efficiency increases to approximately 41.4% (HHV) at 1,350°F (732°C) steam temperature. However, achieving these Advanced Ultra-Super Critical (AUSC) steam conditions requires the use of advanced high-temperature materials. While there has been a significant amount of DOE-funded materials R&D, most of the related design work has focused on new (greenfield) units, rather than on opportunities to retrofit this advanced technology to the existing utility fleet. If technology, based upon the advanced materials required for AUSC steam conditions, may be applied to the existing fleet, using an economically viable retrofit, a higher capacity factor can be expected as a result of the increased plant competitiveness. The Electric Power Research Institute (EPRI) was awarded a project by the US Department of Energy to examine the technical and economic feasibility of a series of steam cycle upgrades to the two most prevalent types of U.S. coal power plants: 2,400 psig (16.6 MPa) subcritical and 3,500 psig (24.1 MPa) supercritical pulverized coal units. The nine upgrade options that were originally being considered included increasing the main and reheat steam temperatures from 1,000°F (538°C) to 1,100°, 1,200°, and 1,350°F (593°C, 649°C, and 732°C) while holding the steam pressures constant at their original design values, and cases where just the main steam or reheat steam temperatures were increased. The objective was to minimize the modifications required to the existing power plant while still providing a significant improvement in heat rate. The upgrade options assumed that the boiler enclosure envelope remained unchanged from each base case, and that all applicable OEM design guidelines for normal commercial units were imposed. For the highest temperature supercritical case, an option of using a low-pressure molten salt loop to transfer heat from the furnace to the steam was examined. The first major task of the work scope was designed to examine the technical feasibility of various upgrade options, while the subsequent work determined economic viability of the technically feasible upgrade options. Prior to evaluating the effect of these increased temperatures, a “base case” model of a subcritical and supercritical PC boiler was created, which was used for comparative purposes. Upgrade options were evaluated at full-load, part-load and dynamic transient conditions. Once the technical feasibility of each upgrade option was evaluated, the economic value of the heat rate improvement of each feasible option was determined by detailed modeling of unit dispatch in several regional power markets. The dispatch model was used to estimate the amount of revenue from power sales the upgraded unit would receive in comparison to a non-upgraded version of the same power plant. As a parallel task to the dispatch analysis, the capital cost of implementing the upgrades was estimated. The capital cost estimates were then compared to the increased revenue estimated by the dispatch modeling to determine the economic attractiveness of each upgrade option. Several upgrade options were determined to be technically feasible. The net present value (NPV) of the costs for steam cycle upgrades considered in this study ranged from approximately $\$$111 to $\$$130 million. The economic modeling results show that the unit dispatch changes resulting from steam cycle upgrades are relatively small, due largely to heat rate (and operating cost) changes being relatively small. Additionally, the cost of each upgrade exceeds the net revenue increases associated with the upgrade case. Note that the breakeven values are higher for subcritical retrofits, but the capital costs for the subcritical upgrades are also slightly higher. In typical new pulverized coal plants, fuel accounts for approximately 25% of the cost of electricity (COE), while capital costs represent around 50% of the COE. Therefore, in order to improve the heat rate by 4% one can only afford to increase the capital cost by 2%, at the same cost of electricity. The conclusion of this study is that without a cost for emitting CO 2 , it will be difficult to pay for significant efficiency improvements on plants firing low cost coals.
LiNiO 2 (LNO) represents the end member in the compositional space of the LiNi 1-x-y Mn x Co y O 2 (as x and y approach zero) cathode system. Despite its high theoretical specific capacity (275 mAh/g), LNO suffers from phase transitions with large volume change and unfavorable reactions upon electrochemical cycling, which restricts its practical use in the application of lithium-ion batteries. While the contributing factor to the structural instability is commonly linked to the undesired volume collapse associated with the H2-H3 phase transition, detailed analysis of structural evolution following the entire route of phase transitions (H1-M-H2-H3) in real time under battery operating conditions remains a challenging task. In this work, we employ operando neutron diffraction to study the structural changes (crystal lattice, Li/Ni–O bond length, O–Ni–O bond angles, and LiO 2 /NiO 2 layer thickness) of LNO cathode in a home-built Li x NiO 2 || graphite full cell during Li + de-/intercalation. In particular, the anomalous increase(decrease) of Ni–O(Li–O) bond length at high SOC (>~85 %) in the H3 phase is discussed in the context of O 2- (2p)→Ni 4+ (3d) negative charge transfer.
The unprecedented tetrahedral anion-? receptors have been successfully constructed by a macrocycle-directed approach. The use of large macrocycle precursors bearing four reaction sites enabled kinetic-favored cross-linking pathway and afforded otherwise-inaccessible tetrahedral cages in considerable yields. Crystal structure suggested that the tetrahedral cages have an enclosed three-dimensional cavity surrounded by four electron-deficient triazine faces in a tetrahedral array. The complementary accommodation of a series of tetrahedral and relevant anions including BF4-, ClO4-, H2PO4-, HSO4-, SO42- and PF6- has been observed by ESI-MS. Two complex crystal structures with ClO4- and PF6- demonstrated the anion was nicely encapsulated within the tetrahedral cavity through up to quadruple cooperative anion-? interactions by an excellent shape and size match. The favored complexation energies were established by DFT calculation and further confirmed by negative ion photoelectron spectroscopy study.
Concerns for potential wildlife impacts resulting from land-based and offshore wind energy have created challenges for wind project development. Research is not always adequately supported, results are neither always readily accessible nor are they satisfactorily disseminated, and so decisions are often made based on the best available information, which may be missing key findings. The potential for high impacts to avian and bat species and marine mammals have been used by wind project opponents to stop, downsize, or severely delay project development. The global nature of the wind industry - combined with the understanding that many affected species cross-national boundaries, and in many cases migrate between continents - also points to the need to collaborate on an international level. The International Energy Agency (IEA) Wind Technology Collaborative Programs facilitates coordination on key research issues. IEA Wind Task 34 - WREN: Working Together to Resolve Environmental Effects of Wind Energy-is a collaborative forum to share lessons gained from field research and modeling, including management methods, wildlife monitoring methods, best practices, study results, and successful approaches to mitigating impacts and addressing the cumulative effects of wind energy on wildlife.
Achieving simultaneously high carrier density and lifetime is crucial to II-VI semiconductor-based applications such as photovoltaics and infrared detectors; yet, it is a challenging task. In this work, high purity CdTe single crystals doped with indium (In) were grown by vertical Bridgman melt growth under carefully controlled stoichiometry. Two-photon excitation time-resolved photoluminescence was employed to measure bulk recombination lifetime by eliminating surface recombination effects. By adjusting stoichiometry with post growth annealing, high-net free carrier density approaching 10 18 cm -3 was attained simultaneously with lifetime approaching the radiative limit by suppressing non-radiative recombination centers.
Zirconium-based alloys are used in the manufacturing of nuclear fuel tubes. These tubes need to be clad with zirconium-tin (Zr-0.3 wt.% Sn) alloy to enhance the lives of tubes. Manufacturing of such clad tubes is a challenging task, due to work hardening and dynamic softening phenomenon. In this study, hot deformation behavior of Zr-0.3Sn alloy is investigated at different temperatures and strain rates. It is found that fully recrystallized microstructure can be obtained by working at around 900 °C and high strain rate of 10 s{sup −1}. Further, constitutive equations are developed for the entire domain of deformation range and fitted into standard FEM-based simulation model for extrusion. The simulation results are validated with experimental data. The difference in flow stresses values obtained from numerical and experimental methods was around 14%.
Solar modules in utility-scale systems are expected to maintain decades of lifetime to rival conventional energy sources. However, cyclic thermomechanical loading often degrades their long-term performance, highlighting the importance of effective design to mitigate thermal expansion mismatches between module materials. Given the complex composition of solar modules, isolating the impact of individual components on overall durability remains a challenging task. In this work, we analyze a comprehensive data set that comprises bill-of-materials (BOM) and thermal cycling power loss from 251 distinct module designs to identify the predominant design factors and their impacts on the thermomechanical durability of modules. The methodology of our analysis combines machine learning modeling (random forest) and Shapley additive explanation (SHAP) to correlate design factors with power loss and interpret the model’s decision-making. The interpretation reveals that silicon type (monocrystalline or polycrystalline), encapsulant thickness, busbar numbers, and wafer thickness predominantly influence the degradation. With lower power loss of around 0.6% on average in the SHAP analysis, monocrystalline cells present better durability than polycrystalline cells. This finding is further substantiated by statistical testing on our raw data set. The SHAP analysis also demonstrates that while thicker encapsulants lead to reduced power loss, further increasing their thickness over around 0.6 to 0.7 mm does not yield additional benefits, particularly for the front side one. In addition, other important BOM features such as the number of busbars are analyzed. This study provides a blueprint for utilizing explainable machine learning techniques in a complex material system and can potentially guide future research on optimizing the design of solar modules.
The proximity of the order of magnitude molecular mean free path and pore sizes in nanopores leads to remarkable interactions between molecules and walls. In such systems, the thermodynamic property and the transport behavior of fluids deviate from those at bulk conditions. Molecular dynamics (MD) simulation may be used to investigate the effects of confinement on fluid physics in nanosize pores. However, translating these subscale observations into a larger scale of interest remains a challenging task. In this work, we propose a modified extension of Peng-Robinson equation of state (PR-EOS) motivated and guided by MD simulation results. The shift of critical properties, i.e., pressure and temperature, are evaluated independently. A temperature dependent parameter is introduced to account for the existence of capillary pressure in the two-phase region. Here, this formulation is capable of capturing the shift in critical properties as well as density phase diagrams under various confinement scenarios. We incorporate the proposed EOS in the lattice Boltzmann method (LBM) to study coupled confined phase behavior and transport of methane in nano-size slit pores. Adsorptive strength is determined such that the resulting density ratio matches that from MD simulation. Results indicate that the use of the proposed EOS leads to smaller fluid velocities compared to PR-EOS. This effect is due to stronger interactions between fluid particles under confinement. Also, results show that transport characteristics are impacted by the pressure of the system: in systems with a relatively low pressure, transport seems to be dominated by Knudsen diffusion; however, at a higher pressure, the contribution from viscous flow increases as the pore widens while the influence of Knudsen and surface diffusion diminishes.
Due to the Lagrangian nature of Smoothed Particle Hydrodynamics (SPH), the adaptive resolution remains a challenging task. In this work, we first analyse the influence of the simulation parameters and the smoothing length on solution accuracy, in particular in high strain regions. Based on this analysis we develop a novel approach to dynamically adjust the kernel range for each SPH particle separately, accounting for the local flow kinematics. We use the Okubo–Weiss parameter that distinguishes the strain and vorticity dominated regions in the flow domain. The proposed development is relatively simple and implies only a moderate computational overhead. We validate the modified SPH algorithm for a selection of two-dimensional test cases: the Taylor–Green flow, the vortex spin-down, the lid-driven cavity and the dam-break flow against a sharp-edged obstacle. The simulation results show good agreement with the reference data and improvement of the long-term accuracy for unsteady flows. For the lid-driven cavity case, the proposed dynamical adjustment remedies the problem of tensile instability (particle clustering).
The use of small field sizes is increasingly becoming important in radiotherapy particularly since the introduction of stereotactic radiosurgery and intensity-modulated radiation therapy techniques. The reliable measurement of delivered dose from such fields with conventional dosimeters, such as ionization chambers, is a challenging task. In this work, methacrylic and ascorbic acid in gelatin initiated by copper polymer gel dosimeters are employed to measure dose in 3 dimensions. Field sizes of 5 × 5 mm{sup 2}, 10 × 10 mm{sup 2}, 20 × 20 mm{sup 2}, and 30 × 30 mm{sup 2} are investigated for a 6-MV x-rays. The results show an agreement with Gafchromic film, with some variation in measured doses near the edge of the fields, where the film data decrease more rapidly than the other methods. Dose penumbra widths obtained with gel dosimeters and Gafchormic film were generally in agreement with each other. The results of this work indicate that polymer gel dosimetry could be invaluable for the quantification of the 3-dimensional dose distribution in small field size.
Linking the macroscopic flow properties and nanoscopic structure is a fundamental challenge to understanding, predicting, and designing disordered soft materials. Under small stresses, these materials are soft solids, while larger loads can lead to yielding and the acquisition of plastic strain, which adds complexity to the task. In this work, we connect the transient structure and rheological memory of a colloidal gel under cyclic shearing across a range of amplitudes via a generalized memory function using rheo-X-ray photon correlation spectroscopy (rheo-XPCS). Our rheo-XPCS data show that the nanometer scale aggregate-level structure recorrelates whenever the change in recoverable strain over some interval is zero. The macroscopic recoverable strain is therefore a measure of the nano-scale structural memory. We further show that yielding in disordered colloidal materials is strongly heterogeneous and that memories of prior deformation can exist even after the material has been subjected to flow.
Efficient semiconductor optical emitters in the deep-ultraviolet spectral window are encountering some of the most deep rooted problems of semiconductor physics. In III-Nitride heterostructures, obtaining short-wavelength photon emission requires the use of wide bandgap high Al composition AlGaN active regions. High conductivity electron (n-) and hole (p-) injection layers of even higher bandgaps are necessary for electrical carrier injection. This approach requires the activation of very deep dopants in very wide bandgap semiconductors, which is a difficult task. In this work, an approach is proposed and experimentally demonstrated to counter the challenges. The active region of the heterostructure light emitting diode uses ultrasmall epitaxially grown GaN quantum dots. Remarkably, the optical emission energy from GaN is pushed from 365 nm (3.4 eV, the bulk bandgap) to below 240 nm (>5.2 eV) because of extreme quantum confinement in the dots. This is possible because of the peculiar bandstructure and band alignments in the GaN/AlN system. This active region design crucially enables two further innovations for efficient carrier injection: Tunnel injection of carriers and polarization-induced p-type doping. The combination of these three advances results in major boosts in electroluminescence in deep-ultraviolet light emitting diodes and lays the groundwork for electrically pumped short-wavelength lasers.
Throughout the history of non-equilibrium thermodynamics a number of theories have been proposed in which complex, far from equilibrium flow systems are hypothesised to reach a steady state that maximises some quantity. Perhaps the most celebrated is Paltridge's principle of maximum entropy production for the horizontal heat flux in Earth's atmosphere, for which there is some empirical support. There have been a number of attempts to derive such a principle from maximum entropy considerations. However, we currently lack a more mechanistic explanation of how any particular system might self-organise into a state that maximises some quantity. This is in contrast to equilibrium thermodynamics, in which models such as the Ising model have been a great help in understanding the relationship between the predictions of MaxEnt and the dynamics of physical systems. In this paper we show that, unlike in the equilibrium case, Paltridge-type maximisation in non-equilibrium systems cannot be achieved by a simple dynamical feedback mechanism. Nevertheless, we propose several possible mechanisms by which maximisation could occur. Showing that these occur in any real system is a task for future work. The possibilities presented here may not be the only ones. We hope that by presenting them we can provoke further discussion about the possible dynamical mechanisms behind extremum principles for non-equilibrium systems, and their relationship to predictions obtained through MaxEnt.