Sensitivity analysis of sensor placement in energy-efficient, grid-interactive ready small office buildings with dynamic shading and lighting control
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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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The overarching goal of this project is to establish a center of excellence program at the University of Maine that is focused on Harsh Environmental Materials and Fabrication Techniques for Wireless Sensor Applications. UMaine is well-positioned to build on previous successes in the areas of materials science research and sensor engineering. Since 1980, the Laboratory for Surface Science & Technology (LASST) has been a very successful interdisciplinary UMaine research center with a well-established infrastructure to investigate surfaces, interfaces, thin films, and micro/nano-fabrication. This infrastructure established through NSF, DOE, DOD, NASA, the State of Maine, and industry includes (i) a 3,500 ft2 clean room with nano/microfabrication and photolithography instrumentation, (ii) thin film synthesis, processing and characterization, (iii) surface and thin film analytical chemistry tools, and (iv) device packaging, electronic testing, wireless devices, system fabrication, and sensor test facilities. This strong foundation is the basis for a planned significant growth in R&D capacity currently underway. To that end, since the start of this project in the Fall of 2019, LASST has undergone a transition to become a new interdisciplinary center at UMaine, named the Frontier Institute for Research in Sensor Technologies (FIRST). This new focus represents a commitment and investment by UMaine that aligns with the proposed DOE-EPSCoR theme, capitalizing on the state-of-the-art instrumentation to form an energized group of faculty and students pursuing advances in sensor materials, devices, and applications.
This paper addresses the task of explaining anomalous predictions of a black-box regression model. When using a black-box model, such as one to predict building energy consumption from many sensor measurements, we often have a situation where some observed samples may significantly deviate from their prediction. It may be due to a sub-optimal black-box model, or simply because those samples are outliers. In either case, one would ideally want to compute a responsibility score indicative of the extent to which an input variable is responsible for the anomalous output. In this work, we formalize this task as a statistical inverse problem: Given model deviation from the expected value, infer the responsibility score of each of the input variables. We propose a new method called likelihood compensation (LC), which is founded on the likelihood principle and computes a correction to each input variable. To the best of our knowledge, this is the first principled framework that computes a responsibility score for real valued anomalous model deviations. We apply our approach to a real-world building energy prediction task and confirm its utility based on expert feedback.
A fiber-optic voltage sensor developed a decade ago for NASA's aircraft and space power systems has been the building block for a string of new sensor products offering safe, accurate detection and measurement for electrically noisy and hazardous environments.
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The Clementine Mission, a joint project of the Strategic Defense Initiative Organization (SDIO) and NASA, has been planned primarily to test and demonstrate a suite of lightweight sensors and other lightweight spacecraft components under extended exposure to the space environment. Although the primary objective of the mission is to space-qualify sensors for Department of Defense applications, it was recognized in 1990 that such a mission might also be designed to acquire scientific observations of the Moon and of Apollo asteroid (1620) Geographos. This possibility was explored jointly by SDIO and NASA, including representatives from NASA's Discovery Program Science Working Group, in early 1991. Besides the direct return of scientific information, one of the benefits envisioned from a joint venture was the development of lightweight components for possible future use in NASA's Discovery-class spacecraft. In Jan. 1992, SDIO informed NASA of its intent to fly a 'Deep Space Program Science Experiment,' now popularly called Clementine; NASA then formed an advisory science working group to assist in the early development of the mission. The Clementine spacecraft is being assembled at the Naval Research Laboratory, which is also in charge of the overall mission design and mission operations. Support for mission design is being provided by GSFC and by JPL. NASA's Deep Space Network will be utilized in tracking and communicating with the spacecraft. Following a recommendation of the COMPLEX committee of the Space Science Board, NASA will issue an NRA and appoint a formal science team in early 1993. Clementine is a 3-axis stabilized, 200 kg (dry weight) spacecraft that will be launched on a refurbished Titan-2G. One of the goals has been to build two spacecraft, including the sensors, for $100M. Total time elapsed from the decision to proceed to the launch will be two years.
The multi-scale and complex process of printing additively manufactured (AM) parts can have unexpected, but predictable, build conditions that result in material microstructure variability. In this work, we describe a fully parallel reduced order modeling approach that has been developed to evaluate the evolution of AM processes, termed the AM moment measure method. This method couples the known sequence of the AM process with a physically informed nearest neighbors’ calculation to map the conditions of a part-scale build. The result is a map of the build that is derived directly from build files or in-situ process monitoring sensors. The methodology and terminology of the approach will be described, and computed build maps will be calculated and compared for various laser powder bed fusion (LPBF) builds of Ti-6Al-4V. Such comparative results develop understanding of how the sequential process actions can affect the LPBF-AM build quality and microstructure variability.
Two of the large EOS observatories, Aqua (formerly EOS-PM) and Aura (formerly EOS-CHEM) will fly is nearly the same inclination with 1:30 PM -15 min ascending node equatorial crossing times. Between Aura and Aqua a series of smaller satellites will be stationed: Cloudsat, CALYPSO (formerly PICASSO-CENA), and PARASOL. This constellation of low earth orbit satellites will provide an unprecedented opportunity to make near simultaneous atmospheric cloud and aerosol observations. This paper will provide details of the science opportunity and describe the sensor types for the afternoon constellation. This constellation by accretion provides a prototype for the Earth Science Vision sensor web and represent the building books for a future web structure.
Additive manufacturing (AM) is a rapidly growing technology. An area of major importance is the integrity and repeatability of AM parts. The goal is to reduce obstacles to certify AM built parts to allow for use in critical aerospace applications. In-situ nondestructive evaluation sensors can be used for build assessment and can potentially play a key role in certifying AM parts. For example, melt pool features are understood to have a strong correlation to microstructural defects and the use of a near infrared (NIR) camera can be used to record the melt pool, cooling areas, and temperature gradients during the build. This work explores the use of a low cost NIR camera to obtain single line track imagery of the Ti-6Al-4V melt pools for various processing parameters. The NIR camera is radiometrically calibrated and configured in-line with the laser source to obtain high resolution imagery of the melt pool shape and dynamics. The challenge to measure melt pool shapes is to identify the transition points between the metal solid to liquid phase. Factors for melt pool measurements such as thermal camera pixel resolution, surface emissivity, and blurring due to the laser beam movement are discussed. Lastly, the melt pool imagery are compared to optical microscopy measurements for validation.
Dasymetric mapping involves the disaggregation of count data, usually relating to population/demographics, from census enumeration areas to smaller target zones with the aid of an ancillary layer related to population density. The ancillary layer is often a binary classification such as developed versus undeveloped, building versus non-building, and residential versus non-residential, in which one class is treated as populated and the other as unpopulated. While dasymetric mapping relies heavily on ancillary data, little research has been done to address the error in ancillary data and its effects on dasymetric mapping accuracy. This chapter reports our research effort to investigate the effect of image classification accuracy on dasymetric population estimates by developing a binomial classification of buildings from high-resolution remote sensor imagery. The classifier was systematically and iteratively manipulated to generate a series of outputs with variegated accuracy characteristics. Lastly, we generated a corresponding series of population estimates based on the mapped building area from each iteration to investigate the relationship between the accuracy of classification and population estimation.
This report describes the design, development, and testing of passive fiber optic sensors and a multiplexing electro-optic architecture (EOA) for installation and flight test on a NASA-owned F-18 aircraft. This hardware was developed under the Fiber Optic Control Systems for Advanced Aircraft program, part of a multiyear NASA initiative to design, develop, and demonstrate through flight test 'fly-by-light' systems for application to advanced aircraft flight and propulsion control. This development included the design and production of 10 passive optical sensors and associated multiplexed EOA hardware based on wavelength division multiplexed (WDM) technology. A variety of sensor types (rotary position, linear position, temperature, and pressure) incorporating a broad range of sensor technologies (WDM analog, WDM digital, analog microbend, and fluorescent time rate of decay) were obtained from different manufacturers and functionally integrated with an independently designed EOA. The sensors were built for installation in a variety of aircraft locations, placing the sensors in a variety of harsh environments. The sensors and EOA were designed and built to have the resulting devices be as close as practical to a production system. The integrated system was delivered to NASA for flight testing on a NASA-owned F-18 aircraft. Development and integration testing of the system provided valuable information as to which sensor types were simplest to design and build for a military aircraft environment and which types were simplest to operate with a multiplexed EOA. Not all sensor types met the full range of performance and environmental requirements. EOA development problems provided information on directions to pursue in future fly-by-light flight control development programs. Lessons learned in the development of the EOA and sensor hardware are summarized.
The focus of the research is to build a compact, high performance lightstripe rangefinder using a Very Large Scale Integration (VLSI) smart photosensor array. Rangefinding, the measurement of the three-dimensional profile of an object or scene, is a critical component for many robotic applications, and therefore many techniques were developed. Of these, lightstripe rangefinding is one of the most widely used and reliable techniques available. Though practical, the speed of sampling range data by the conventional light stripe technique is severely limited. A conventional light stripe rangefinder operates in a step-and-repeat manner. A stripe source is projected on an object, a video image is acquired, range data is extracted from the image, the stripe is stepped, and the process repeats. Range acquisition is limited by the time needed to grab the video images, increasing linearly with the desired horizontal resolution. During the acquisition of a range image, the objects in the scene being scanned must be stationary. Thus, the long scene sampling time of step-and-repeat rangefinders limits their application. The fast range sensor proposed is based on the modification of this basic lightstripe ranging technique in a manner described by Sato and Kida. This technique does not require a sampling of images at various stripe positions to build a range map. Rather, an entire range image is acquired in parallel while the stripe source is swept continuously across the scene. Total time to acquire the range image data is independent of the range map resolution. The target rangefinding system will acquire 1,000 100 x 100 point range images per second with 0.5 percent range accuracy. It will be compact and rugged enough to be mounted on the end effector of a robot arm to aid in object manipulation and assembly tasks.
Fiber optic technology is expected to be used in future advanced weapons platforms as well as commercial aerospace applications. Fiber optic waveguides will be used to transmit noise free, high speed data between a multitude of computers as well as audio and video information to the flight crew. Passive optical sensors connected to control computers with optical fiber interconnects will serve both control and monitoring functions. Implementation of fiber optic technology has already begun. Both the military and NASA have several programs in place. A cooperative program, called FOCSI (Fiber Optic Control System Integration), between NASA Lewis and the NAVY to build, environmentally test and flight demonstrate sensor systems for propulsion and flight control systems is currently underway. Integrated Optical Circuits (IOC's) are also being given serious consideration for use in advanced aircraft systems. IOC's will result in miniaturization and localization of components to generate, detect optical signals and process them for use by the control computers. In some complex systems IOC's may be required to perform calculations optically if the technology is ready, replacing some of the electronic systems used today. IOC's are attractive because they will result in rugged components capable of withstanding severe environments in advanced aerospace vehicles. Manufacturing technology developed for microelectronic integrated circuits applied to IOC's will result in cost effective manufacturing. This paper reviews the current FOCSI program and describes the potential role of IOC's in FOCSI applications.
The Goddard Earth Sciences Distributed Active Archive Center (GES DAAC) has been archiving and distributing Radiance data, and serving science and application users of these data, for over 10 years now. The user-focused stewardship of the Radiance data from the AIRS, AVHRR, MODIS, SeaWiFS, SORCE, TOMS, TOVS, TRMM, and UARS instruments exemplifies the GES DAAC tradition and experience. Radiance data include raw radiance counts, onboard calibration data, geolocation products, radiometric calibrated and geolocated-calibrated radiance/reflectance. The number of science products archived at the GES DAAC is steadily increasing, as a result of more sophisticated sensors and new science algorithms. Thus, the main challenge for the GES DAAC is to guide users through the variety of Radiance data sets, provide tools to visualize and reduce the volume of the data, and provide uninterrupted access to the data. This presentation will describe the effort at the GES DAAC to build a bridge between multi-sensor data and the effective scientific use of the data, with an emphasis on the heritage of the science products. The intent is to inform users of the existence of this large collection of Radiance data; suggest starting points for cross-platform science projects and data mining activities; provide data services and tools information; and to give expert help in the science data formats and applications.
Climate science and applications require access to vast amounts of archived high quality data, software tools and services for data manipulation and information extraction. These on the other hand require gaining detailed understanding of the data's internal structure and physical implementation to data reduction, combination and data product production. This time-consuming task must be undertaken before the core investigation can begin and is an especially difficult challenge when science objectives require users to deal with large multi-sensor data sets of different formats, structures, and resolutions. In order to address these issues the Goddard Space Flight Center (GSFC) Earth Sciences (GES), Data and Information Service Center (DISC) Distributed Active Archive Center (DAAC) has made great progress in facilitating science and applications research by developing innovative tools and data services applied to the Earth sciences atmospheric and climate data. The GES/DISC/DAAC has successfully implemented and maintained a long-term climate satellite data archive and developed tools and services to a variety of atmospheric science missions including AIRS, AVHRR, MODIS, SeaWiFS, SORCE, TOMS, TOVS, TRMM, and UARS and Aura instruments providing researchers with excellent opportunities to acquire accurate and continuous atmospheric measurements. Since the number of climate science products from these various missions is steadily increasing as a result of more sophisticated sensors and new science algorithms, the main challenge for data centers like the GES/DISC/DAAC is to guide users through the variety of data sets and products, provide tools to visualize and reduce the volume of the data and secure uninterrupted and reliable access to data and related products. This presentation will describe the effort at the GES/DISC/DAAC to build a bridge between multi-sensor data and the effective scientific use of the data, with an emphasis on the heritage satellite observations and science products for climate applications. The intent is to inform users of the existence of this large collection of data and products; suggest starting points for cross-platform science projects and data mining activities and provide data services and tools information. More information about the GES/DISC/DAAC satellite data and products, tools, and services can be found at http://daac.gsfc.nasa.gov.
The Simons Observatory is building both large (6 m) and small (0.5 m) aperture telescopes in the Atacama Desert in Chile to observe the cosmic microwave background CMB radiation with unprecedented sensitivity. Simons Observatory telescopes in total will use over 60,000 transition edge sensor (TES) detectors spanning center frequencies between 27 and 285 GHz and operating near 100 mK. TES devices have been fabricated for the Simons Observatory by NIST, Berkeley, and HYPRES/SeeQC corporation. Iterations of these devices have been tested cryogenically in order to inform the fabrication of further devices, which will culminate in the final TES designs to be deployed in the field. The detailed design specifications have been independently iterated at each fabrication facility for particular detector frequencies. We present test results for prototype devices, with emphasis on NIST high frequency detectors. A dilution refrigerator was used to achieve the required temperatures. Measurements were taken both with 4-lead resistance measurements and with a time-domain Superconducting Quantum Interference Device (SQUID) multiplexer system. The SQUID readout measurements include analysis of current versus voltage (IV) curves at various temperatures, square wave bias step measurements, and detector noise measurements. Lastly, normal resistance, superconducting critical temperature, saturation power, thermal and natural time constants, and thermal properties of the devices are extracted from these measurements.
For over 16 years, the Louisiana Space Grant Consortium (LaSPACE), the NASA Balloon Program Office (BPO), and the NASA Columbia Scientific Balloon Facility (CSBF) have collaborated in a series of high altitude balloon-based programs involving hands-on authentic learning experiences that expose university students and other participants to technical skills, teamwork dynamics, and effective communication methods. Such programs go beyond what is possible to achieve in a normal classroom and help prepare future engineers and scientists for a successful aerospace workforce career. In our collaborative effort, LaSPACE has focused on the program content and student mentoring while NASA BPO and CSBF provide balloon flight support and operations. The entry-level Louisiana Aerospace Catalyst Experiences for Students (LaACES) builds students’ skills in basic electronics, sensor interfacing, real-time programming, mechanical development, and project management. These skills are then applied to the design, development, fabrication, and flight of a small (∼500 gram) balloon payload. Finally, the payloads are flight-tested to an altitude of ∼30 km using a 2 kg latex sounding balloon. The LaACES program includes a set of lectures, activities, and Arduino Mega based electronic kits that are used for skill building and as a core control system for the student payload. The more advanced High Altitude Student Platform (HASP) is designed to carry ∼twelve 3 to 20 kg student payloads to an altitude of about 36 kilometers with flight durations of 10 to 20 hours using a ∼311,500 cubic meter, zero pressure balloon. HASP provides all student payloads with power, downlink telemetry, uplink commanding, and real-time HD video for instrument control and assessment during the flight. While originally developed for university students, these programs have been adapted to projects focused on high school teachers as well as affecting minorities underrepresented in aerospace related science and engineering fields. We are now in the process of adapting the LaACES materials to a pre-engineering curriculum for high school students as well as for widespread access over the internet. During this presentation, we will provide details of both the LaACES and HASP programs, how these programs have engaged participants from all demographic groups, and our current plans for continuing and expanding upon our success.
The occupant-centric control (OCC) is receiving an increasing attention due to its ability to reduce building heating ventilation and air-conditioning (HVAC) system energy consumptions while not affecting the occupant thermal comfort. This paper aims to investigate and quantify the nationwide energy-saving potential of implementing the occupant-centric HVAC controls in typical office buildings using a whole building simulation software EnergyPlus. First, the medium office and large office from the Department of Energy (DOE) Commercial Prototype Building Models (CBPM) were enhanced to have detailed layouts and dynamic occupancy schedules. Then, a comprehensive simulation plan was created by incorporating the multiple zone-level and system-level occupant-centric building HVAC controls recommended by the updated ASHRAE Standard 90.1 – 2019 and ASHRAE Guideline 36 – 2018. Three control scenarios with different occupancy sensing methods were identified in this simulation plan. A nation-wide parametric analysis which includes two building types, three occupancy sensing scenarios, two building code versions, and 16 U.S. climate zones was carried out. The simulation results of the key control variables and HVAC energy consumption suggest that generally, both the occupancy presence sensor and occupant counting sensor could achieve energy savings for the office buildings in majority of the scenarios. However, compared with the occupancy presence sensor, which could support both the temperature setpoint reset and operational breathing zone airflow rate reset for the unoccupied zones, the occupant counting sensor only brings a marginal benefit. Besides, a higher HVAC energy-saving ratio could be achieved in the heating-dominated zone, since the energy reduction brought with the minimum outdoor airflow rate reset is stronger in the heating mode.