Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “BUSINESS”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 325 records · Page 18
All sourcesNASA NTRSDOE OSTI
DOE OSTI2015

Small Businesses Save Big: A Guide to Help SBA Lenders Understand and Communicate the Value of Energy Efficiency Investments (Fact Sheet)

Dollars saved through energy efficiency can directly impact your bottom line. Whether you are planning for a major renovation or upgrading individual pieces of building equipment, these improvements can help reduce operating costs, save on utility bills, and boost profits. This fact sheet provides guidelines for SBA lenders to understand the value of financing energy efficiency investments.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2017

Future Scenario Development from Disruptive Exploration Technologies and Business Models in the U.S. Geothermal Industry

With recent trends toward intermittent renewable energy sources in the U.S., the geothermal industry in its current form faces a crossroad: adapt, disrupt, or be left behind. Strategic planning with scenario analysis offers a framework to characterize plausible views of the future given current trends - as well as disruptions to the status quo. To inform strategic planning in the Department of Energy's (DOE) Geothermal Technology Office (GTO), the Geothermal Vision Study is tasked with offering data-driven pathways for future geothermal development. Scenario analysis is a commonly used tool in private industry corporate strategic planning as a way to prioritize and manage large investments in light of uncertainty and risk. Since much of the uncertainty and risk in a geothermal project is believed to occur within early stage exploration and drilling, this paper focuses on the levers (technical and financial) within the exploration process that can be pulled to affect change. Given these potential changes, this work first qualitatively explores potential shifts to the geothermal industry. Future work within the Geothermal Vision Study will incorporate these qualitative scenarios quantitatively, in competition with other renewable and conventional energy industries.

15 GEOTHERMAL ENERGY↗
DOE OSTI2022

Initial Scoping Efforts for a Plant-Wide Digital Infrastructure Modernization Business Case Study

This research report describes the preparatory efforts to perform a BCA on an expanded set of digital upgrades envisioned for implementation at the Luminant?s Comanche Peak nuclear plant. It captures efforts to scope the digital upgrade effort to enable performance of the BCA. The final BCA will be the subject of a subsequent report. LWRS pilot research in this area is intended to enable this effort and to provide a roadmap to others to follow. INL appreciates the Luminant?s participation in this research.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2023

Pilot Business Case Analysis for Digital Infrastructure

The Inflation Reduction Act Has Provided an Opening to Dramatically Change and Improve the Economics of Nuclear Power Until recently, the commercial nuclear sector has faced unprecedented financial challenges driven by low natural gas prices and subsidized renewables, in a marketplace that did not reward carbon-free baseload capacity. The industry is also plagued by labor shortages, increasingly obsolete labor-centric operating models and antiquated analog technology that threaten the viability of the long-term operations of domestic nuclear facilities. In this context, the economic survival of nuclear power plants requires an efficient and technology-centric operating model that harvests the native efficiencies of advanced technology. Such transformations have been made in many other industries – notably, oil and gas. The passage by Congress of the Inflation Reduction Act (IRA) in 2022 provides nuclear operators with unprecedented economic incentives to pursue these upgrades. To realize the benefits of these incentives and achieve the necessary transformations in the nuclear operating model, the nuclear industry must overcome both the continuing unease about licensing pathways and uncertainty related to implementation costs.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2018

Efficiency Improvement in a Busy Radiology Practice: Determination of Musculoskeletal Magnetic Resonance Imaging Protocol Using Deep-Learning Convolutional Neural Networks

The purposes of this study are to evaluate the feasibility of protocol determination with a convolutional neural networks (CNN) classifier based on short-text classification and to evaluate the agreements by comparing protocols determined by CNN with those determined by musculoskeletal radiologists. Following institutional review board approval, the database of a hospital information system (HIS) was queried for lists of MRI examinations, referring department, patient age, and patient gender. These were exported to a local workstation for analyses: 5258 and 1018 consecutive musculoskeletal MRI examinations were used for the training and test datasets, respectively. The subjects for pre-processing were routine or tumor protocols and the contents were word combinations of the referring department, region, contrast media (or not), gender, and age. The CNN Embedded vector classifier was used with Word2Vec Google news vectors. The test set was tested with each classification model and results were output as routine or tumor protocols. The CNN determinations were evaluated using the receiver operating characteristic (ROC) curves. The accuracies were evaluated by a radiologist-confirmed protocol as the reference protocols. The optimal cut-off values for protocol determination between routine protocols and tumor protocols was 0.5067 with a sensitivity of 92.10%, a specificity of 95.76%, and an area under curve (AUC) of 0.977. The overall accuracy was 94.2% for the ConvNet model. All MRI protocols were correct in the pelvic bone, upper arm, wrist, and lower leg MRIs. Deep-learning-based convolutional neural networks were clinically utilized to determine musculoskeletal MRI protocols. CNN-based text learning and applications could be extended to other radiologic tasks besides image interpretations, improving the work performance of the radiologist.

62 RADIOLOGY AND NUCLEAR MEDICINE↗