An Object-Based Method for Tracking Convective Storms in Convection Allowing Models

The steady-state assumption commonly used in object-based tracking algorithms may be insufficient to determine the right track when a convective storm goes through a complicated evolution. Such an issue is exacerbated by the relatively coarse output frequency of current convection allowing model (CAM) forecasts (e.g., hourly), giving rise to many spatially well resolved but temporally not well resolved storms that steady-state assumption could not account for. To reliably track simulated storms in CAM outputs, this study proposed an object-based method with two new features. First, the method explicitly estimated the probability of each probable track based on either its immediate past and future motion or a reliable “first-guess motion” derived from storm climatology or near-storm environmental variables. Second, object size was incorporated into the method to help identify temporally not well resolved storms and minimize false tracks derived for them. Parameters of the new features were independently derived from a storm evolution analysis using 2-min Multi-Radar Multi-Sensor (MRMS) data and hourly CAM forecasts produced by the University of Oklahoma (OU) Multiscale data Assimilation and Predictability Laboratory (MAP) from May 2019. The performance of the new method was demonstrated with hourly MRMS and CAM forecast examples from May 2018. A systematic evaluation of four severe weather events indicated 99% accuracy achieved for over 600 hourly MRMS tracks derived with the proposed tracking method.

Assessment of Student Learning Through Reflection on Doing in Engineering Design

How can instructors leverage assessment instruments in design, build, and test courses to simultaneously improve student outcomes and assess student learning to improve courses? A Take-away is one type of assessment method. It is unstructured text written by a student in AME4163: Principles of Engineering Design, the University of Oklahoma, Norman, US to record what they understand by reflecting on authentic, immersive experiences throughout the semester. The immersive experiences include lectures, assignments, reviews, building, testing, and a post-analysis for the design of an electro-mechanical system to address a given customer need. In the context of a Take-away, a student then writes a Learning Statement. The Learning Statement is a single sentence written as a triple, i.e., Experience|Learning|Value. Over the past three years at the University of Oklahoma (OU), we collected about 18,000 Take-aways and 18,000 Learning Statements from almost 400 students. In our earlier papers, we primarily concentrate on analyzing students’ Learning Statements by a text mining framework. In this paper, we focus on analyzing students’ Take-aways data using a Latent Dirichlet Allocation (LDA) algorithm, and then relate the Take-away data to the instructor’s expectations using text similarity. By connecting and comparing what students learned (embodied in Take-aways) and what instructors expected the students to learn (embodied in the course booklet), we provide evidence-based guidance to instructors on improving the delivery of AME4163: Principles of Engineering Design. The proposed method can be generalized to be used for the assessment of ABET Student Outcomes 2 and 7.

Economic Comparison of Alternatives for a Stranded Offshore Gas Reservoir

This article, written by JPT Technology Editor Chris Carpenter, contains highlights of paper OTC 30732, “Economic Feasibility Study of Several Usage Alternatives for a Stranded Offshore Gas Reservoir,” by Khoi Viet Trinh, SPE, and Rouzbeh G. Moghanloo, SPE, University of Oklahoma, prepared for the 2020 Offshore Technology Conference, originally scheduled to be held in Houston, 4–7 May. The paper has not been peer reviewed. Copyright 2020 Offshore Technology Conference. Reproduced by permission. This paper compares economics of a floating liquefied natural gas (FLNG) project with those of an onshore LNG plant and gas-to-wire (GTW) processes. Sensitivity analyses and tornado charts are used to evaluate the importance of various uncertain parameters associated with FLNG construction and operation. This study will be helpful for future considerations in using FLNG to convert offshore gas reservoirs previously considered stranded into economically viable resources. The results from this economic model can play a key role in the future of the natural gas industry and energy market in West Africa. Assumptions Before presenting different economic scenarios, the following assumptions must be established: * The pipeline will have the correct diameter, pressure rating, and metallurgy to transport produced gas. Only the pipe length will be considered a variable. * Operating expenses (OPEX) of both onshore LNG and FLNG will be the same. Realistically, however, OPEX of FLNG will be different from that of onshore LNG. * A subsidy from the Nigerian government has been obtained for the onshore LNG plant. * The electricity price is assumed to be $0.25/kWh. * An assumed upstream cost of $2/Mscf to cover onshore LNG gas pretreatment is assumed. * The onshore LNG plant and FLNG will have the same lifespan. However, in reality, availability of FLNG can be lower than that of onshore LNG. Pricing Models FNLG. Because of the relative recency of FNLG, few pricing models have been readily available. For the complete paper, Shell’s Prelude project is the basis for pricing of FLNG. Prelude costs averaged out to approximately $14 billion, which will be used as the cost of the facility for the FLNG scenario in the economic analysis.