Journal of Energy Engineering

A project in Honolulu to use marine algae mass for energy has demonstrated that the use of angled plates in shallow (100–150 mm) raceways, where cultures of marine algae are grown, significantly increased algae production. The reasons for higher productivity are not fully understood, but the increased production rates were clearly demonstrated. Accepting the premise that angled plates in shallow raceways significantly increased algal production, the research objectives of a complementary project described here were to study the mixing relationships in shallow (100 mm) water flows with low velocity (∼0.3 m/s) that are created by variously shaped and positioned submerged plates and to identify the optimum energy efficiency. Based on six test runs with combinations of three to five 100 mm square and triangular plates set at 10° and 20° angles to the water flow, the velocities directly behind the test plates were consistently higher than those in between for up to 4.5 m downstream (thus creating desired mixing conditions); the 20° angled plates created a notably higher degree of mixing than those at 10°; the use of three 100 mm plates (particularly the square-shaped ones) provided adequate mixing in comparison to five plates; the energy loss between the plate section and a section 4.5 m downstream was essentially negligible; and the drag force on the plates was relatively insignificant regardless of the plate shape or angle of attact.

This work documents a major part of a large effort to characterize the uncertainty present in key elements of the U.S. Department of Energy's new National Energy Modeling System (NEMS). It is expected that NEMS will be used to estimate the impact that Federal policy initiatives, such as taxes, subsidies, and regulations, will have on energy markets well into the 21st century. But, the effective use of NEMS requires that the uncertainties in its predictions be well understood. So, the Energy Information Administration, the Washington Consulting Group, and the School of Information Technology and Engineering of George Mason University collaborated on the development and testing of methods for quantifying uncertainty in the three most important NEMS submodel types, namely, linear-optimization, econometric, and heuristic or balance equations. We constructed assessment procedures for each of these classes, and used them on the Energy Information Administration transportation sector demand model, petroleum market model, and electricity fuel dispatch model. The methods used include special sampling procedures applied to computer-based experiments, response surface techniques, and Taylor series methods, and they are described in this first of a two-part paper on the complete study. The important numerical results of our experiments and their subsequent analyses are presented in the companion paper.

This is the second of two papers on characterizing the uncertainty present in key elements of the U.S. Department of Energy's new National Energy Modeling System. The theory behind the assessment procedures developed was described in the first paper, and the current work presents the important numerical results and analyses of our experiments, all done as a collaborative effort between the Energy Information Administration, the Washington Consulting Group, and the School of Information Technology and Engineering of George Mason University. The method testing involved the three most important National Energy Modeling System submodel types, namely, linear optimization, econometric, and heuristic or balance equations. The results of using the uncertainty procedures on the Energy Information Administration's transportation sector demand and petroleum market models are provided here.