Data Assimilation

Accurate wind and severe-weather forecasts are crucial for wind-energy production and grid-load management. Most of the prevailing wind power forecast methods rely heavily on statistical approaches that typically do not deal directly with weather processes. Currently employed numerical weather prediction (NWP) models are deemed insufficiently accurate by many industry stakeholders for wind power prediction, even though they have been used for such applications. The reason is partly because the NWP products used for power forecasting are typically produced by the coarse-resolution models at the major operational weather centers. Although a few of high-resolution models are run by some wind energy industries, most of these model do not contain advanced data assimilation capabilities that are required to initialize the model prediction with the important high-resolution weather information.

Solar power generation is highly fluctuating due to its dependence on atmospheric conditions. The integration of this variable resource into the energy supply system requires reliable predictions of the expected power production as a basis for management and operation strategies. This is one of the goals of the Solar Cloud project, funded by the Italian Ministry of Economic Development (MISE)—to provide detailed forecasts of solar irradiance variables to operators and organizations operating in the solar energy industry. The Institute of Methodologies for Environmental Analysis of the National Research Council (IMAA-CNR), participating to the project, implemented an operational chain that provides forecasts of all the solar irradiance variables at high temporal and horizontal resolution using the numerical weather prediction Advanced Research Weather Research and Forecasting (WRF-ARW) Solar version 3.8.1 released by the National Center for Atmospheric Research (NCAR) in August 2016....

The goal of adaptive sampling in the ocean is to predict the types and locations of additional ocean measurements that would be most useful to collect. Quantitatively, what is most useful is defined by an objective function and the goal is then to optimize this objective under the constraints of the available observing network. Examples of objectives are better oceanic understanding, to improve forecast quality, or to sample regions of high interest. This work provides a new path-planning scheme for the adaptive sampling problem. We ...

In this study, the fifth-generation Pennsylvania State University–National Center for Atmospheric Research Mesoscale Model (MM5) with three-dimensional variational data assimilation (3DVAR) is utilized to investigate influences of GPS occultation refractivity on simulations of typhoons past Taiwan. Two recent cases were simulated, including Typhoon Nari in September 2001 and Typhoon Nakri in July 2002. The GPS observation data are taken from the Challenging Minisatellite Payload for Geophysical Research and Application (CHAMP) and Satélite de Aplicaciones Científicas-C (SAC-C) satellites that provide several retrieved refractivity profiles in the simulated domain near the initialization time. Through 3DVAR, the observed refractivity can be quickly ingested into the model initial conditions to recover the information over the ocean. The initial moisture increments from ingested GPS refractivity soundings exhibit a maximum magnitude of about 1.5 g kg−1 associated with temperature incr...

Cross-cultural church planting is more than a by-product of foreign missions. A successful cross-cultural church plant will not only impact a new culture, one new to the planter, but will also impact neighboring communities within a new culture to disciple and send out other church planters. This process should become cyclical. The goal of cross-cultural church planting then is not about four walls, institution, or creating a safe-haven for worship, but the ability to establish a living organism in another culture, for the purpose of spreading the Gospel and building a relational network of supportive churches. These supportive churches should each grow exponentially within their own cell. This research paper will be presented in a six stage process regarding cross-cultural church planting: (1) targeting and demographics (2) acculturation and assimilation (3) indigenization and contextualization (4) holistic mission and structure (5) discipleship (6) and transforming into germinal churches. Each of these stages will be reflective of the Savior, demonstrating the need for the cross-cultural church planter to assist new converts to become imitators of Christ (Eph. 5:1), with a common goal of building relationships through love, trust, and incarnational living.

A strategy for adaptive control and energetic optimization of aerobic fermentors was implemented, with both air flow and agitation speed as manipulated variables. This strategy is separable in its components: control, optimization, estimation. We optimized parameter’s estimation (from the usual KLa correlation) using sinusoidal excitation of air flow and agitation speed. We have implemented parameter’s estimation trough recursive least squares algorithm with forgetting factor. We carried separate essays on control, optimization and estimation algorithms. We carried our essays using an original computational simulation environment, with noise and delay generating facilities for data sampling and filtering.

Our results show the convergence and robustness of the estimation algorithm used, improved with use of both forgetting factor and KLa dead-band facilities. Control algorithm used in our work compares favorably with PID using the integrated area criteria for deviation between oxygen molarity and critical molarity (set point). Optimization algorithm clearly reduces energetic consumption, respecting critical molarity. Integration of control, optimization and adaptive algorithms was implemented, but future work is needed for stability. Methods were defined and implemented for stability improvement. We have implemented data acquisition and computer manipulation of air flow and agitation speed for actual fermentors.