Assessment of oxygen plasma ashing as a pre-treatment for radiocarbon dating

This study investigates the potential of low-temperature oxygen plasma ashing as a technique for decontaminating charcoal and wood samples prior to radiocarbon dating. Plasma ashing is demonstrated to be rapid, controllable and surface-specific, and clear differences are identified in the rate of ashing in different organic materials. However, the ability of plasma ashing to selectively remove these different components is limited in heterogeneous sample matrices. This is because oxidation is confined to the immediate sample surface. Comparison of radiocarbon dates obtained from identical aliquots of contaminated ancient charcoal pre-treated by acid-base-acid (ABA), acid-base-oxidation-stepped combustion (ABOx-SC) and plasma ashing suggests that the technique performs as well as the ABA pre-treatment but does not remove as much contamination as the ABOx-SC technique. Plasma-ashing may be particularly useful in cases where sample size is limiting

Heterogeneous Unit Clustering for Efficient Operational Flexibility Modeling for Strategic Models

The increasing penetration of wind generation has led to significant improvements in unit commitment models. However, long-term capacity planning methods have not been similarly modified to address the challenges of a system with a large fraction of generation from variable sources. Designing future capacity mixes with adequate flexibility requires an embedded approximation of the unit commitment problem to capture operating constraints. Here we propose a method, based on clustering units, for a simplified unit commitment model with dramatic improvements in solution time that enable its use as a submodel within a capacity expansion framework. Heterogeneous clustering speeds computation by aggregating similar but non-identical units thereby replacing large numbers of binary commitment variables with fewer integers that still capture individual unit decisions and constraints. We demonstrate the trade-off between accuracy and run-time for different levels of aggregation. A numeric example using an ERCOT-based 205-unit system illustrates that careful aggregation introduces errors of 0.05-0.9% across several metrics while providing several orders of magnitude faster solution times (400x) compared to traditional binary formulations and further aggregation increases errors slightly (~2x) with further speedup (2000x). We also compare other simplifications that can provide an additional order of magnitude speed-up for some problems

Optimal Selection of Sample Weeks for Approximating the Net Load in Generation Planning Problems

The increasing presence of variable energy resources (VER) in power systems –most notably wind and solar power– demands tools capable of evaluating the flexibility needs to compensate for the resulting variability in the system. Capacity expansion models are needed that embed unit commitment decisions and constraints to account for the interaction between hourly variability and realistic operating constraints. However, the dimensionality of this problem grows proportionally with the time horizon of the load profile used to characterize the system, requiring massive amounts of computing resources. One possible solution to overcome this computational problem is to select a small number of representative weeks, but there is no consistent criterion to select these weeks, or to assess the validity of the approximation. This paper proposes a methodology to optimally select a given number of representative weeks that jointly characterize demand and VER output for capacity planning models aimed at evaluating flexibility needs. It also presents different measures to assess the error between the approximation and the complete time series. Finally, it demonstrates that the proposed methodology yields a valid approximation for unit commitment constraints embedded in long-term planning models

Airport Congestion Mitigation through Dynamic Control of Runway Configurations and of Arrival and Departure Service Rates under Stochastic Operating Conditions

The high levels of flight delays require the implementation of airport congestion mitigation tools. In this paper, we optimize the utilization of airport capacity at the tactical level in the face of operational uncertainty. We formulate an original Dynamic Programming model that selects jointly and dynamically runway configurations and the balance of arrival and departure service rates at a busy airport to minimize congestion costs, under stochastic queue dynamics and stochastic operating conditions. The control is exercised as a function of flight schedules, of arrival and departure queue lengths and of weather and wind conditions. We implement the model in a realistic setting at JFK Airport. The exact Dynamic Programming algorithm terminates within reasonable time frames. In addition, we implement an approximate one-step look-ahead algorithm that considerably accelerates the execution of the model and results in close-to-optimal policies. In combination, these solution algorithms enable the on-line implementation of the model using real-time information on flight schedules and meteorological conditions. The application of the model shows that the optimal policy is path-dependent, i.e., it depends on prior decisions and on the stochastic evolution of arrival and departure queues during the day. This underscores the theoretical and practical need for integrating operating stochasticity into the decision-making framework. From comparisons with an alternative model based on deterministic queue dynamics, we estimate the benefit of considering queue stochasticity at 5% to 20%. Finally, comparisons with advanced heuristics aimed to imitate actual operating procedures suggest that the model can yield significant cost savings, estimated at 20% to 30%

An experimental investigation of two large annular diffusers with swirling and distorted inflow

Two annular diffusers downstream of a nacelle-mounted fan were tested for aerodynamic performance, measured in terms of two static pressure recovery parameters (one near the diffuser exit plane and one about three diameters downstream in the settling duct) in the presence of several inflow conditions. The two diffusers each had an inlet diameter of 1.84 m, an area ratio of 2.3, and an equivalent cone angle of 11.5, but were distinguished by centerbodies of different lengths. The dependence of diffuser performance on various combinations of swirling, radially distorted, and/or azimuthally distorted inflow was examined. Swirling flow and distortions in the axial velocity profile in the annulus upstream of the diffuser inlet were caused by the intrinsic flow patterns downstream of a fan in a duct and by artificial intensification of the distortions. Azimuthal distortions or defects were generated by the addition of four artificial devices (screens and fences). Pressure recovery data indicated beneficial effects of both radial distortion (for a limited range of distortion levels) and inflow swirl. Small amounts of azimuthal distortion created by the artificial devices produced only small effects on diffuser performance. A large artificial distortion device was required to produce enough azimuthal flow distortion to significantly degrade the diffuser static pressure recovery

Large-scale wind tunnel investigation of a ducted fan - Deflected-slipstream model with an auxiliary wing

Wind tunnel investigation of longitudinal aerodynamic characteristics of semispan wing deflected-slipstream configuration with double slotted flap and auxiliary win

Scenario analysis of carbon capture and sequestration generation dispatch in the western U.S. electricity system

AbstractWe present an analysis of the feasibility of dispatch of coal-fired generation with carbon capture and sequestration (CCS) as a function of location. Dispatch es for locations are studied with regard to varying carbon dioxide (CO2) prices, demand load levels, and natural gas prices. Using scenarios with a carbon price range of $0 to$ 100 per ton - CO2, we show that a hypothetical CCS generator would be dispatched on a marginal cost basis given a high enough carbon price but that the minimum carbon price required for dispatch varies widely by location and system demand

Geometry dependence of the clogging transition in tilted hoppers

We report the effect of system geometry on the clogging of granular material flowing out of flat-bottomed hoppers with variable aperture size D. For such systems, there exists a critical aperture size Dc at which there is a divergence in the time for a flow to clog. To better understand the origins of Dc, we perturb the system by tilting the hopper an angle Q and mapping out a clogging phase diagram as a function of Q and D. The clogging transition demarcates the boundary between the freely-flowing (large D, small Q) and clogging (small D, large Q) regimes. We investigate how the system geometry affects Dc by mapping out this phase diagram for hoppers with either a circular hole or a rectangular narrow slit. Additionally, we vary the grain shape, investigating smooth spheres (glass beads), compact angular grains (beach sand), disk-like grains (lentils), and rod-like grains (rice). We find that the value of Dc grows with increasing Q, diverging at pi-Qr where Qr is the angle of repose. For circular apertures, the shape of the clogging transition is the same for all grain types. However, this is not the case for the narrow slit apertures, where the rate of growth of the critical hole size with tilt angle depends on the material

Rail Infrastructure Manager Problem: Analyzing Capacity Pricing and Allocation in Shared Railway System

This paper proposes a train timetabling model for shared railway systems. The model is formulated as a mixed integer linear programming problem and solved both using commercial software and a novel algorithm based on approximate dynamic programming. The results of the train timetabling model can be used to simulate and evaluate the behavior of the infrastructure manager in shared railway systems under different capacity pricing and allocation mechanisms. This would allow regulators and decision makers to identify the implications of these mechanisms for different stakeholders considering the specific characteristics of the system