Large Load Reductions Research Articles

The potential for nitrate removal during infiltration: Mapping with machine learning informed by field and laboratory experiments

AbstractManaged aquifer recharge (MAR) can increase groundwater supply and, under some conditions, improve groundwater quality simultaneously. However, the conditions under which water quality improvements can be achieved during infiltration for MAR have not been systematically examined in a spatially explicit manner. This work aims to address that gap by synthesizing observations from laboratory tests, field experiments and operational facilities at four MAR sites within the Pajaro Valley, California, USA to develop a predictive model of nitrate removal during infiltration. We compare two machine learning approaches; random forest and boosted regression trees, to multiple linear regression. The preferred model uses boosted regression trees, with four predictor variables (initial nitrate concentration of infiltrating water, residence time in the soil, soil organic carbon content, and soil percent clay). We apply this model to simulate the spatial distribution of potential nitrate removal (NRp) across a heterogeneous and mixed‐use landscape, finding that >87% of the region has the potential to remove nitrate during infiltration. To link potential nitrate removal capacity to available water for MAR, we combine a map of NRp with independently simulated hillslope runoff, and find that potential load reduction is highest in urban areas (median = 18.8 kg‐N/yr) where large runoff volumes are collocated with soils having high nutrient cycling capacity compared to forested and agricultural areas (median = 1.6 and 3.5 kg‐N/yr, respectively). We analyse potential load reduction across dry, normal, and wet precipitation scenarios, which shows that urban areas have the potential to yield large load reductions (median = 11.3 kg‐N/yr) even under relatively dry conditions. However, much of the generation of elevated nitrate in runoff is associated with agricultural activity. These results suggest that the urban–agricultural interface represents a crucial link between hydrologic and biogeochemical cycles where water supply and quality goals may be met simultaneously. The technical approach used in this study is highly flexible and can help guide decisions in resource management and identify promising MAR sites. More broadly, this approach also elucidates heterogeneity in biogeochemical cycling across complex landscapes.

Analysis and enhancement of Barcelona’s power grid resilience

Climate change is causing an increase in extreme weather events that can stress the electric grid as it was not originally designed to withstand them, and at the same time, new unexpected threats emerge such as cyberattacks making the grid more vulnerable. On top of that, situations such as the new pandemic of Covid-19 pose the grid under new scenarios of large load reduction where renewable energies gain importance and traditional sources are strongly curtailed. On this basis, the resilience of the electrical grid turns into a key feature to be analysed and strongly enhanced. Thus, the power grid is being analysed by researchers in recent years to assess such hazards along with what measures or resources are effective against them, such as distributed energy resources based on renewable energies. Based on these studies, this paper aims to explore which power grid resilience KPIs fit more to describe the scenarios of the disruptive events for the consequent discussion of the installation of renewable sources to prioritize investments in order to minimize impacts. Furthermore, a geographic information system based model is developed to analyse a static study case of flooding in the city of Barcelona. Results show that the city’s power grid is vulnerable to the scenario, but it has the potential of renewable energies to mitigate its consequences.

Modeling of Internal Pressure Dynamics in Mass-Impregnated Nondraining HVDC Cables

Changing the current loading of mass-impregnated nondraining (MIND) power cables causes the pressure in the insulation to vary over a wide range. It is generally recognized that under certain conditions—typically after a large load reduction—the pressure becomes so low that shrinkage cavities (voids) form in the insulation and that partial discharges (PDs) may damage the insulation ignite. A finite-element model for temperature, electric field, and pressure dynamics throughout the insulation layer has been developed. Comparisons with previously obtained measurements on full-scale high voltage direct current (HVDC) subsea cable samples subjected to a variety of loading patterns, external pressures (sea depths), and ambient temperatures show that the model replicates the pressure behavior of the insulation reasonably well. Most importantly, the complicated viscoelastic properties of the lead sheath, which have a profound effect on the internal pressure dynamics and thereby on the prospects of forming potentially harmful cavities, appear to be sufficiently accurately modeled.

The feedwater control system and steam dump control system responses during large-load reduction transient for Maanshan PWR Plant

In this study, the development of TRACE (TRAC/RELAP Advanced Computational Engine) models for Maanshan nuclear power plant (NPP) important control systems, such as feedwater control system and steam dump control system, are performed in using SNAP (Symbolic Nuclear Analysis Program) / TRACE. The large-load reduction transient analysis of the Maanshan NPP control system TRACE models are also performed and the responses of the control systems of TRACE models compare with Maanshan NPP startup tests data to verify their accuracy. Analysis results of TRACE indicate that the responses of the Maanshan NPP control system TRACE models are consistent with the plant data for large-load reduction transient.

The Feedwater Control System and Steam Dump Control System Responses During Large-Load Reduction Transient for Maanshan PWR Plant

In this study, the development of TRACE (TRAC/RELAP Advanced Computational Engine) models for Maanshan nuclear power plant (NPP) important control systems, such as feedwater control system and steam dump control system, are performed in using SNAP (Symbolic Nuclear Analysis Program) / TRACE. The large-load reduction transient analysis of the Maanshan NPP control system TRACE models are also performed and the responses of the control systems of TRACE models compare with Maanshan NPP startup tests data to verify their accuracy. Analysis results of TRACE indicate that the responses of the Maanshan NPP control system TRACE models are consistent with the plant data for large-load reduction transient.

Benchmark calculations of pressurizer model for Maanshan nuclear power plant using TRACE code

The pressurizer plays an important role in controlling the pressure of the primary coolant system in pressurized water reactor (PWR) nuclear power plants. An accurate modeling of the pressurizer is needed to determine the pressure response of the primary coolant system, and thus to successfully simulate overall PWR nuclear power plant behavior during transients. The purpose of this study is to develop a pressurizer model, and to assess its pressure transients using the TRACE code version 5.0. The benchmark of the pressurizer model was performed by comparing the simulation results with those from the tests at the Maanshan nuclear power plant. Four start-up tests of the Maanshan nuclear power plant are collected and simulated: (1) turbine trip test from 100% power (Test PAT-50); (2) large-load reduction at 100% power (Test PAT-49); (3) net-load trip at 100% power (Test PAT-51); and (4) net-load trip at 50% power (Test PAT-21). The simulation results show that the predictions of the pressure response are in reasonable agreement with the power plant's start-up tests, and thus the pressurizer model built in this study is successfully verified and validated.

Application of hash to data base machine and its architecture

In this paper we discuss the application of the dynamic clustering feature of hash to a relational data base machine. By partitioning the relation using hash, large load reductions in join and set operations are realized. Several machine architectures based on hash are presented. We propose a data base machineGRACE which adopts a novel relational algebraic processing algorithm based on hash and sort. Whereas conventional logic-per-track machines perform poorly in a join dominant environment,GRACE can execute join efficiently inO(N+M/K) time, whereN andM are the cardinalities of two relations andK the number of memory banks.