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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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This proposed paper will highlight the application of a CSD/CFD methodology currently inuse by the US Army Aerfolightdynamics Directorate (AFDD) to assess the feasibility and fidelity of directly predicting low frequency sounds of helicopter rotors.
Several fixed-winged airplanes have successfully used fly-by-wire (FBW) technology for the last 40 years. This technology is now beginning to be incorporated into rotary wing aircraft. By using FBW technology, manufacturers are expecting to improve upon the weight, maintenance time and costs, handling and reliability of the aircraft. Before mass production of this new system begins in new models such as the UH-60MU, testing must be conducted to insure the safety of this technology as well as to reassure others it will be worth the time and money to make such a dramatic change to a perfectly functional machine. The RASCAL JUH-60A has been modified for these purposes. This Black Hawk helicopter has already been equipped with the FBW technology and can be configured as a near perfect representation of the UH-60MU. Because both machines have very similar qualities, the data collected from the RASCAL can be used to make future decisions about the UH-60MU. The U.S. Army AFDD Flight Project Office oversees all the design modifications for every hardware system used in the RASCAL aircraft. This project deals with specific designs and analyses of unique RASCAL aircraft subsystems and their modifications to conduct flight mechanics research.
Under a recent collaborative effort between the US Army Aeroflightdynamics Directorate (AFDD) and NASA Langley, NASA's general unstructured CFD solver, FUN3D, was modularized as a CREATE-AV Helios near-body unstructured grid solver. The strategies adopted in Helios/FUN3D integration effort are described. A validation study of the new capability is performed for rotorcraft cases spanning hover prediction, airloads prediction, coupling with computational structural dynamics, counter-rotating dual-rotor configurations, and free-flight trim. The integration of FUN3D, along with the previously integrated NASA OVERFLOW solver, lays the ground for future interaction opportunities where capabilities of one component could be leveraged with those of others in a relatively seamless fashion within CREATE-AV Helios.
This study provides a review of the current state of knowledge, gaps, and potential value in research on the prevalence of faults in commercial buildings. Two separate efforts were made in this study: (1) we performed a literature review to determine the extent of currently available fault prevalence data for heating, ventilation, and air-conditioning (HVAC) systems, and (2) we conducted dozens of interviews with subject matter experts and stakeholders to determine the HVAC fault data that would be of greatest value. Through the literature review and interviews, we discovered unmet needs for empirical data on the prevalence of faults at the desired level of granularity, consistency, and scale; this lack of data leads us to recommend future work studying commercial buildings’ HVAC fault prevalence, with robust fault taxonomy and a variety of meaningful fault prevalence metrics.
The primary objective of this project was to leverage digital twin technology to enhance the design and operation of DFW Airport terminals and their associated energy systems. To achieve this, Morpheus, a building digital twin, was developed to guide improvements in airport operations, specifically targeting reductions in peak power demand and overall energy consumption.
Achieving a widespread transition to grid-interactive, efficient buildings (GEBs) depends critically on there being sufficient interoperability among connected building systems. While many critical elements already exist at the technical interoperability level (TCP/IP, BACnet, etc.), a lack of interoperability in the semantic level hinders streamlined integration of interdependent applications. Semantics refers to expressing information about “things” in a way that can be consistently understood by applications. Key components of formalized semantics include identifying what a “thing” is (its “type”), defining general information about that “thing” (its characteristics or properties), and defining the appropriate relationships of that “thing” to other “things” (its function or role in a larger system). Although this might seem initially trivial, the success of smart building applications is highly dependent on maintaining consistent self-descriptive notions of the “things”. Without semantic interoperability, it is technically difficult, labor-intensive, and cost-prohibitive to enable three key objectives of GEBs: optimizing performance, automatically identifying and diagnosing faults, and delivering grid services. Industry, academia, and standards bodies have invested effort in developing information models to facilitate semantic interoperability, however, they have not been widely adopted across the U.S. commercial building portfolio. This paper will present a pathway to drive semantic interoperability through a three-pronged approach to be led by the DOE Building Technologies Office in partnership with NIST and multiple national laboratories comprising: 1) industry engagement and coordination across existing efforts; 2) a semantic interoperability standard that empowers building owners to identify and require interoperable attributes when procuring equipment and applications; 3) tools to assist in implementation and a test framework to verify compliance of products with semantic interoperability specifications. This approach is designed to accelerate the timeline for adoption of semantic interoperability specifications. The intent is to reduce soft costs associated with implementing advanced controls, fault detection and diagnostics, and other smart building technologies and use cases as a necessary step in achieving an energy efficient smart grid future.