A stochastic search algorithm for voltage and reactive power control with switching costs and ZIP load model
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Feinberg, Eugene↗
SEARCH · Engineering Papers
Results for “Cost Model”
Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.
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Laboratory simulations of the mixed solvent extraction recovery of dominate polymers in electronic waste
Highlights: • Mixed plastics in e-waste are separated with a solvent extraction method. • Recovery procedure obtained an acceptable recovery rate with high purity. • The recovered plastics are greatly energy-saving compared with virgin polymers. • Cost-saving can be potentially achieved for specific composition of plastics. - Abstract: The recovery of four dominant plastics from electronic waste (e-waste) using mixed solvent extraction was studied. The target plastics included polycarbonate (PC), polystyrene (PS), acrylonitrile butadiene styrene (ABS), and styrene acrylonitrile (SAN). The extraction procedure for multi-polymers at room temperature yielded PC, PS, ABS, and SAN in acceptable recovery rates (64%, 86%, 127%, and 143%, respectively, where recovery rate is defined as the mass ratio of the recovered plastic to the added standard polymer). Fourier transform infrared spectroscopy (FTIR) was used to verify the recovered plastics’ purity using a similarity analysis. The similarities ranged from 0.98 to 0.99. Another similar process, which was denoted as an alternative method for plastic recovery, was examined as well. Nonetheless, the FTIR results showed degradation may occur over time. Additionally, the recovery cost estimation model of our method was established. The recovery cost estimation indicated that a certain range of proportion of plastics in e-waste, especially with a higher proportion of PC and PS, can achieve a lower cost than virgin polymer product. It also reduced 99.6%, 30.7% and 75.8% of energy consumptions and CO{sub 2} emissions during the recovery of PC, PS and ABS, and reduced the amount of plastic waste disposal via landfill or incineration and associated environmental impacts.
12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
EverBatt: A Closed-loop Battery Recycling Cost and Environmental Impacts Model
The cumulative global electric vehicle (EV) sales surpassed 3.1 million units in 2017, with 1.9 million units of battery electric vehicles (BEVs), and 1.2 million units of plug-in hybrid electric vehicles (PHEVs). Of the cumulative global EV sales, The U.S. accounted for 0.40 million BEV sales, and 0.36 million PHEV sales (IEA 2018). Assuming a lifespan of 10 years for EVs, an average battery pack weight of 300 kg for BEVs, and an average battery pack weight of 200 kg for PHEVs, by 2027, 0.2 million metric tons of EV batteries would reach their end-oflife (EOL) in the U.S. Globally, the volume of spent automotive batteries would amount to 0.8 million metric tons by 2027. As the annual global EV sales are expected to grow from 1.4 million in 2017 to 21.5 million in 2030 (IEA 2018), the volume of spent automotive batteries would increase markedly beyond 2027.
25 ENERGY STORAGE↗
Low cost tracking Navaids error model verification
Features and characteristics of the tracking navaids (Microwave Scanning Beam Landing System, Radar Altimeter, Tacan, rendezvous radar and one way Doppler extracter) were investigated. From the investigation, a set of specifications were developed for building equipment to verify the error model of the tracking navaids. Breadboard verification equipment (BVE) was built for the Microwave Scanning Beam Landing System and the radar altimeter. The breadboard verification equipment generates signals to the tracking navaids which simulate the space shuttles trajectory in the terminal area. The BVE simulates sources of navaids error by generating pseudorandom perturbations on the navaids signals. Differences between the trajectory value and the navaid derived values are taped and form the basis for the navaids error model.
Charych, A.↗
cost and benefits optimization model for fault-tolerant aircraft electronic systems
The factors involved in economic assessment of fault tolerant systems (FTS) and fault tolerant flight control systems (FTFCS) are discussed. Algorithms for optimization and economic analysis of FTFCS are documented.
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Space station WP-04 power system preliminary analysis and design document, volume 3
Rocketdyne plans to generate a system level specification for the Space Station Electric Power System (EPS) in order to facilitate the usage, accountability, and tracking of overall system level requirements. The origins and status of the verification planning effort are traced and an overview of the Space Station program interactions are provided. The work package level interfaces between the EPS and the other Space Station work packages are outlined. A trade study was performed to determine the peaking split between PV and SD, and specifically to compare the inherent total peaking capability with proportionally shared peaking. In order to determine EPS cost drivers for the previous submittal of DRO2, the life cycle cost (LCC) model was run to identify the more significant costs and the factors contributing to them.
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Cost estimating methods for advanced space systems
NASA is responsible for developing much of the nation's future space technology. Cost estimates for new programs are required early in the planning process so that decisions can be made accurately. Because of the long lead times required to develop space hardware, the cost estimates are frequently required 10 to 15 years before the program delivers hardware. The system design in conceptual phases of a program is usually only vaguely defined and the technology used is so often state-of-the-art or beyond. These factors combine to make cost estimating for conceptual programs very challenging. This paper describes an effort to develop parametric cost estimating methods for space systems in the conceptual design phase. The approach is to identify variables that drive cost such as weight, quantity, development culture, design inheritance and time. The nature of the relationships between the driver variables and cost will be discussed. In particular, the relationship between weight and cost will be examined in detail. A theoretical model of cost will be developed and tested statistically against a historical database of major research and development projects.
Cyr, Kelley↗
High-Performance Computational Electromagnetic Modeling Using Low-Cost Parallel Computers
(view graphs) Beowulf System (Hyglac), Hyglac cost, Hyglac Performance vs. T3D, FDTD Interior Communication, Boundary Communication, Timing.
FDTD PHOEBUS↗
Utilizing Expert Knowledge in Estimating Future STS Costs
A method of estimating the costs of future space transportation systems (STSs) involves classical activity-based cost (ABC) modeling combined with systematic utilization of the knowledge and opinions of experts to extend the process-flow knowledge of existing systems to systems that involve new materials and/or new architectures. The expert knowledge is particularly helpful in filling gaps that arise in computational models of processes because of inconsistencies in historical cost data. Heretofore, the costs of planned STSs have been estimated following a "top-down" approach that tends to force the architectures of new systems to incorporate process flows like those of the space shuttles. In this ABC-based method, one makes assumptions about the processes, but otherwise follows a "bottoms up" approach that does not force the new system architecture to incorporate a space-shuttle-like process flow. Prototype software has been developed to implement this method. Through further development of software, it should be possible to extend the method beyond the space program to almost any setting in which there is a need to estimate the costs of a new system and to extend the applicable knowledge base in order to make the estimate.
Fortner, David B.↗
A Robust Schema for Storing and Managing Machine Learning Data and Models
- Machine Learning (ML) has enabled models that can improve efficiency and decrease computational cost - ML models are crucial in enabling Integrated Computational Materials Engineering (ICME) - Large data sets require robust means of storing ML data and models
Brandon L. Hearley↗
Section 5: Analysis of Steady-State Reliability and Detailed Costs Using the FESTIV Model
Abstract not provided
17 WIND ENERGY↗
Systematic Approach to Better Understanding Integration Costs: Preprint
When someone mentions integration costs, thoughts of the costs of integrating renewable generation into an existing system come to mind. We think about how variability and uncertainty can increase power system cycling costs as increasing amounts of wind or solar generation are incorporated into the generation mix. However, seldom do we think about what happens to system costs when new baseload generation is added to an existing system or when generation self-schedules. What happens when a highly flexible combined-cycle plant is added? Do system costs go up, or do they go down? Are other, non-cycling, maintenance costs impacted? In this paper we investigate six technologies and operating practices--including VG, baseload generation, generation mix, gas prices, self-scheduling, and fast-start generation--and how changes in these areas can impact a system's operating costs. This paper provides a working definition of integration costs and four components of variable costs. It describes the study approach and how a production cost modeling-based method was used to determine the cost effects, and, as a part of the study approach section, it describes the test system and data used for the comparisons. Finally, it presents the research findings, and, in closing, suggests three areas for future work.
17 WIND ENERGY↗
Front-end engineering design (FEED) studies: a quantitative analysis
NETL has devised a methodology for normalizing FEED study metrics of interest and allowing cautious quantitative comparison across FEED studies. This presentation introduces the novel quantitative comparison methodology and presents results from utilizing this methodology to examine data presented in recent FEED study reports. The quantitative methodology developed for the examination of FEED study performance and cost also allows comparison of real-world performance and costs against NETL TEA model predicted performance and cost. Learnings from examining NETL model predicted performance and cost versus real world reported values are highlighted. These learnings provide insight into NETL TEA model uncertainty and highlight opportunities for further model development.
FEED Studies↗
Utility-Scale Lithium-Ion Storage Cost Projections for Use in Capacity Expansion Models
This work presents U.S. utility-scale battery storage cost projections for use in capacity expansion models. We create battery cost projections based on a survey of literature cost projections of battery packs and balance of system costs, with a focus on lithium-ion batteries. Low, mid, and high cost trajectories are created for the overnight capital costs and the operating and maintenance costs. We then demonstrate the impact of these cost projections in the Regional Energy Deployment System (ReEDS) capacity expansion model. We find that under reference scenario conditions, lower battery costs can lead to increased penetration of variable renewable energy, with solar photovoltaics (PV) seeing the largest increase. We also find that additional storage can reduce renewable energy curtailment, although that comes at the expense of additional storage losses.
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Estimating Software-Development Costs With Greater Accuracy
COCOMOST is a computer program for use in estimating software development costs. The goal in the development of COCOMOST was to increase estimation accuracy in three ways: (1) develop a set of sensitivity software tools that return not only estimates of costs but also the estimation error; (2) using the sensitivity software tools, precisely define the quantities of data needed to adequately tune cost estimation models; and (3) build a repository of software-cost-estimation information that NASA managers can retrieve to improve the estimates of costs of developing software for their project. COCOMOST implements a methodology, called '2cee', in which a unique combination of well-known pre-existing data-mining and software-development- effort-estimation techniques are used to increase the accuracy of estimates. COCOMOST utilizes multiple models to analyze historical data pertaining to software-development projects and performs an exhaustive data-mining search over the space of model parameters to improve the performances of effort-estimation models. Thus, it is possible to both calibrate and generate estimates at the same time. COCOMOST is written in the C language for execution in the UNIX operating system.
Baker, Dan↗
Satellite broadcasting system study
The study to develop a system model and computer program representative of broadcasting satellite systems employing community-type receiving terminals is reported. The program provides a user-oriented tool for evaluating performance/cost tradeoffs, synthesizing minimum cost systems for a given set of system requirements, and performing sensitivity analyses to identify critical parameters and technology. The performance/ costing philosophy and what is meant by a minimum cost system is shown graphically. Topics discussed include: main line control program, ground segment model, space segment model, cost models and launch vehicle selection. Several examples of minimum cost systems resulting from the computer program are presented. A listing of the computer program is also included.
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