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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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137 records · Page 8

All sources NASA NTRS DOE OSTI

NASA NTRS2023

Users' Guide to Vinci: Personal Computer Software for Planning Image-based Measurements in Wind Tunnels

Vinci is software that can be used to plan image-based measurements in wind tunnels. It allows the user to plan the placement of cameras and the choice of lenses well in advance of a test, thereby reducing the set-up time and cost when tunnel occupancy begins. It can also be used post-test to display data (pressure-sensitive paint, particle image velocimetry, model deformation) in context with the test article. Vinci is self-contained and runs on personal computers under Windows operating systems. No other software is required. Test articles are represented by CFD-like surface grids that may be read from an external file or created within the program as a combination of simple geometric shapes. The user controls the position and orientation of the test article through a Graphical User Interface (GUI) and may add many additional objects, including tunnel walls and windows, a wide variety of simple geometric shapes, mirrors, lamps, and laser sheets. The application computes simulated images from up to 40 cameras. Images are based on pinhole projection. Each camera is defined by the sensor size and the focal length of the lens. All camera parameters, including position and point angles, are controlled through the GUI. Simulated images are displayed in a window of the GUI and may be saved as bitmaps.

Users’ Guide, Image Planning, Wind Tunnels, Softwa↗

DOE OSTI2026

Coherence-mediated quantum thermometry in a hybrid circuit quantum electrodynamics architecture

Quantum thermometry plays a critical role in the development of low-temperature sensors and quantum information platforms. Here, in this work, we propose and analyze a hybrid circuit quantum electrodynamics architecture in which a superconducting qubit is dispersively coupled to two distinct bosonic modes: one initialized in a weak coherent state as a phase reference and information buffer and the other coupled to a thermal environment. We show that the qubit serves as a sensitive readout of the probe mode, mapping the interplay between thermal and coherent photon-number fluctuations onto measurable dephasing. This coherence-mediated mechanism enables improved sensitivity to thermal energy fluctuations in the sub-millikelvin regime through Ramsey interferometry. We derive analytic expressions for the probe coherence envelope, compute the quantum Fisher information for temperature estimation, and demonstrate numerically that the presence of a coherent reference enhances the qubit's sensitivity to small changes in thermal photon occupancy. Our results establish a coherence-enabled approach to thermometry and provide a scalable platform for future calorimetric sensing in high-energy physics and quantum metrology.

Zhu, Shaojiang [Fermi National Accelerator Laborat↗

DOE OSTI2023

Bottleneck Detection in Modular Construction Factories Using Computer Vision

The construction industry is increasingly adopting off-site and modular construction methods due to the advantages offered in terms of safety, quality, and productivity for construction projects. Despite the advantages promised by this method of construction, modular construction factories still rely on manually-intensive work, which can lead to highly variable cycle times. As a result, these factories experience bottlenecks in production that can reduce productivity and cause delays to modular integrated construction projects. To remedy this effect, computer vision-based methods have been proposed to monitor the progress of work in modular construction factories. However, these methods fail to account for changes in the appearance of the modular units during production, they are difficult to adapt to other stations and factories, and they require a significant amount of annotation effort. Due to these drawbacks, this paper proposes a computer vision-based progress monitoring method that is easy to adapt to different stations and factories and relies only on two image annotations per station. In doing so, the Scale-invariant feature transform (SIFT) method is used to identify the presence of modular units at workstations, and the Mask R-CNN deep learning-based method is used to identify active workstations. This information was synthesized using a near real-time data-driven bottleneck identification method suited for assembly lines in modular construction factories. This framework was successfully validated using 420 h of surveillance videos of a production line in a modular construction factory in the U.S., providing 96% accuracy in identifying the occupancy of the workstations and an F-1 Score of 89% in identifying the state of each station on the production line. The extracted active and inactive durations were successfully used via a data-driven bottleneck detection method to detect bottleneck stations inside a modular construction factory. The implementation of this method in factories can lead to continuous and comprehensive monitoring of the production line and prevent delays by timely identification of bottlenecks.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2022

Detecting Passing Valves at Scale Across Different Buildings and Systems: A Brick Enabled and Mortar Tested Application

Heating hot water distribution systems are typically used in commercial buildings to condition spaces to provide occupant thermal comfort. However, recent research shows significant distribution losses within these systems that drive down the overall hot water plant efficiency. This research focuses on detecting passing valves in reheat coils found in variable air volume (VAV) terminal units to reduce distribution losses. A passing valve allows hot water flow when the actuator on the valve is commanded to be closed. The fluid causes unintentional heating or cooling to occur, causing comfort and control issues, and wasting energy. We developed the passing valve detection algorithm using a framework based on the Brick schema and Mortar platform to ensure that the application is portable and can scale to many buildings. We applied the same application to analyze 1,335 VAV reheat terminal units in 20 buildings. The diversity found in these large datasets increases confidence that any building with VAV reheat terminal units with the required sensors and Brick data model can run our open-source algorithm with little or no modification. In aggregate, 5% of VAV units analyzed were categorized as having a sensor fault, 14% with potential passing valve fault, and 81% with no faults detected. However, there is a significant variation in the proportion of VAV units with a passing valve detected (1% to 83%) of each building’s analyzed units.

Roa, Carlos Duarte↗

NASA NTRS2005

Geospatial Analysis and Remote Sensing from Airplanes and Satellites for Cultural Resources Management

Cultural resource management consists of research to identify, evaluate, document and assess cultural resources, planning to assist in decision-making, and stewardship to implement the preservation, protection and interpretation of these decisions and plans. One technique that may be useful in cultural resource management archaeology is remote sensing. It is the acquisition of data and derivative information about objects or materials (targets) located on the Earth's surface or in its atmosphere by using sensor mounted on platforms located at a distance from the targets to make measurements on interactions between the targets and electromagnetic radiation. Included in this definition are systems that acquire imagery by photographic methods and digital multispectral sensors. Data collected by digital multispectral sensors on aircraft and satellite platforms play a prominent role in many earth science applications, including land cover mapping, geology, soil science, agriculture, forestry, water resource management, urban and regional planning, and environmental assessments. Inherent in the analysis of remotely sensed data is the use of computer-based image processing techniques. Geographical information systems (GIS), designed for collecting, managing, and analyzing spatial information, are also useful in the analysis of remotely sensed data. A GIS can be used to integrate diverse types of spatially referenced digital data, including remotely sensed and map data. In archaeology, these tools have been used in various ways to aid in cultural resource projects. For example, they have been used to predict the presence of archaeological resources using modern environmental indicators. Remote sensing techniques have also been used to directly detect the presence of unknown sites based on the impact of past occupation on the Earth's surface. Additionally, remote sensing has been used as a mapping tool aimed at delineating the boundaries of a site or mapping previously unknown features. All of these applications are pertinent to the goals of site discovery and assessment in cultural resource management.

Giardino, Marco J.↗

DOE OSTI2026

Sub-Doppler Cooling of a Trapped Ion in a Phase-Stable Polarization Gradient

Trapped ions provide a highly controlled platform for quantum sensors, clocks, simulators, and computers, all of which depend on cooling ions close to their motional ground state. Existing methods like Doppler, resolved sideband, and dark resonance cooling balance trade-offs between the final temperature and cooling rate. A traveling polarization gradient has been shown to cool multiple modes quickly and in parallel, but utilizing a stable polarization gradient can achieve lower ion energies, while also allowing tailorable light-matter interactions in the sub-wavelength regime. In this Letter, we demonstrate cooling of a trapped ion below the Doppler limit using a phase-stable polarization gradient created using trap-integrated photonic devices. At an axial frequency of 2⁢𝜋×1.45 MHz we achieve ⟨𝑛⟩=1.56±0.07 in 150 μ⁢s and cooling rates of ∼0.3 quanta/μ⁢s. Here, we examine ion dynamics under different polarization gradient phases, detunings, and intensities, showing reasonable agreement between experimental results and a multilevel model. Cooling is fast and power efficient, with lower average motional Fock state occupation when compared to simulated operation under the corresponding running wave configuration. Our results demonstrate a well-controlled test bed for studying the dynamics of multilevel atomic systems in a phase-stable polarization gradient.

Atom & ion cooling↗

NASA NTRS2017

Integrated Systems Health Management for Sustainable Habitats (Using Sustainability Base as a Testbed)

Habitation systems provide a safe place for astronauts to live and work in space and on planetary surfaces. They enable crews to live and work safely in deep space, and include integrated life support systems, radiation protection, fire safety, and systems to reduce logistics and the need for resupply missions. Innovative health management technologies are needed in order to increase the safety and mission-effectiveness for future space habitats on other planets, asteroids, or lunar surfaces. For example, off-nominal or failure conditions occurring in safety-critical life support systems may need to be addressed quickly by the habitat crew without extensive technical support from Earth due to communication delays. If the crew in the habitat must manage, plan and operate much of the mission themselves, operations support must be migrated from Earth to the habitat. Enabling monitoring, tracking, and management capabilities on-board the habitat and related EVA platforms for a small crew to use will require significant automation and decision support software.Traditional caution and warning systems are typically triggered by out-of-bounds sensor values, but can be enhanced by including machine learning and data mining techniques. These methods aim to reveal latent, unknown conditions while still retaining and improving the ability to provide highly accurate alerts for known issues. A few of these techniques will briefly described, along with performance targets for known faults and failures. Specific system health management capabilities required for habitat system elements (environmental control and life support systems, etc.) may include relevant subsystems such as water recycling systems, photovoltaic systems, electrical power systems, and environmental monitoring systems. Sustainability Base, the agency's flagship LEED-platinum certified green building acts as a living laboratory for testing advanced information and sustainable technologies that provides an opportunity to test novel machine learning and controls capabilities. In this talk, key features of Sustainability Base that make it relevant to deep space habitat technology and its use of these kinds of subsystems previously listed will be presented. The fact that all such systems require less power to support human occupancy can be used as a focal point to serve as a testbed for deep space habitats that will need to operate within finite energy budgets.

Systems Health Management↗

DOE OSTI2026

Robotics for HVAC applications: A critical review and future perspectives

Recent advances in artificial intelligence (AI), enhanced computational capabilities, and innovations in sensors and hardware have driven the increasing development and application of robots in heating, ventilation, and air conditioning (HVAC) systems. We selected and reviewed 101 studies published between 2005 and 2025, sourced from IEEE Xplore, Scopus, Web of Science, and the ACM Digital Library. To analyze these works, we developed a five-dimensional analytical framework (morphology, sensing, navigation, task execution, and system integration), inspired by the Springer Handbook of Robotics and tailored specifically for robotic applications in HVAC. Based on the reviewed studies, six distinct tasks spanning the entire HVAC lifecycle have been identified. Among the six tasks, inspection and maintenance dominate (59 %), followed by indoor monitoring and auditing (21 %), whereas leakage detection, comfort support, and installation/retrofit remain less explored. To address the identified gaps, this review proposes future research directions including investigating robot-aware HVAC design principles, developing multimodal HVAC sensing and data fusion techniques, enhancing robot training and hardware capabilities, and expanding robotic applications beyond Maintenance and Operations (M&O). The findings from this review inform future robotics research for HVAC applications and ultimately enhance system affordability, energy efficiency, resilience or reliability, and occupant environmental comfort. Moreover, it seeks to inspire researchers to explore the intersections of robotics, computer science, building science, and HVAC engineering fostering advancements in this multidisciplinary field.

AI↗

DOE OSTI2023

Spatio-Temporal Anomaly Detection with Graph Networks for Data Quality Monitoring of the Hadron Calorimeter

The Compact Muon Solenoid (CMS) experiment is a general-purpose detector for high-energy collision at the Large Hadron Collider (LHC) at CERN. It employs an online data quality monitoring (DQM) system to promptly spot and diagnose particle data acquisition problems to avoid data quality loss. In this study, we present a semi-supervised spatio-temporal anomaly detection (AD) monitoring system for the physics particle reading channels of the Hadron Calorimeter (HCAL) of the CMS using three-dimensional digi-occupancy map data of the DQM. We propose the GraphSTAD system, which employs convolutional and graph neural networks to learn local spatial characteristics induced by particles traversing the detector and the global behavior owing to shared backend circuit connections and housing boxes of the channels, respectively. Recurrent neural networks capture the temporal evolution of the extracted spatial features. We validate the accuracy of the proposed AD system in capturing diverse channel fault types using the LHC collision data sets. The GraphSTAD system achieves production-level accuracy and is being integrated into the CMS core production system for real-time monitoring of the HCAL. We provide a quantitative performance comparison with alternative benchmark models to demonstrate the promising leverage of the presented system.

43 PARTICLE ACCELERATORS↗

DOE OSTI2022

A System Approach to Deep Heating Savings Through Measurement, Management, and Motivation

Across multi-tenant commercial office and multifamily buildings, centrally metered fuel use represents a substantial fraction of whole-building energy use. Energy audit practitioners understand that improving heating distribution efficiency is typically more of an opportunity than combustion efficiency and that differing thermal comfort preferences between tenants are the bane of operators across these building typologies. There is an unmet market need for retrofit technologies that allow for the delivery of the right amount of heat to the right spaces, at the right time. The Energy Management and Information System (EMIS) package fills this gap through enhanced controls and metering, incorporating low-cost sensors and wireless communication infrastructure to provide a platform for ongoing commissioning and tenant feedback, including heat cost allocation. With support from the US DOE Building Technologies Office, Steven Winter Associates, Inc. (SWA) partnered with Sentient Buildings, E Source, building owners, and utility and policy stakeholders, to demonstrate a market viable EMIS that achieves a reduction in space heating energy use by reducing heating load, improving control, and positively impacting behavior while providing an acceptable financial return. In this study, EMIS packages were implemented in two New York City multifamily rental buildings. Both buildings conducted basic mechanical work (e.g., repairing steam traps) to ensure the heating system was operating well before any tenant feedback was layered in. Heating Energy Use Reports (HEUR) were created to provide tenants with social comparisons and energy savings tips to influence their behavior; these were provided monthly to all tenants in both buildings. Additionally, one building allocated heating costs to a portion of the tenants. Heat cost allocation (HCA) has a long history in the European Union (EU), although it is not common in the US or in steam-heated buildings. SWA leveraged existing EU best practices and stakeholder feedback to develop a Heat Cost Allocation algorithm that was considered equitable and intuitive. Energy use and tenant behavior impacts were tracked throughout the study. The basic mechanical repair work saved between 11-20% of heating energy. Those savings rose to 17-24% with the addition of tenant feedback. While it may not be possible to precisely determine the impact of COVID-19 on research studies like this, there may have been additional savings realized had the study taken place in a period of normal occupancy patterns. These types of central heating systems have been a blind spot for utilities, who have traditionally had little visibility into detailed behind-the-meter gas usage. Heating energy savings stayed consistent during the coldest months, indicating the potential for utilities to utilize EMIS packages for peak gas demand reductions or demand response programs. Tenant comfort was also improved. Post installation, room temperatures more closely matched thermostat set points. Perhaps due to this greater level of control, the vast majority of tenants being billed for heating were accepting of the allocation costs. And tenants receiving heat cost allocations were more likely to reduce their thermostat setpoints than tenants receiving behavioral feedback without financial impacts were. Variation in building specifics makes it difficult to provide precise energy and financial savings estimates. But within the range of expected conditions, the study identified a few key variables that can have the greatest impact on financial returns: the cost of fuel, the ability and willingness to allocate heating costs to tenants, and a well-functioning heating system as a starting point. This study focused on two multifamily buildings, but additional use cases, such as commercial buildings and affordable housing, should be explored to better understand the full market potential. While this type of upgrade has the potential for deep energy reductions and cost savings, future projects should take into account the balance of costs and benefits between owners and tenants, especially in the affordable, regulated, or other low-to-moderate income (LMI) segments of the market. Rent credits, utility allowances, or a shared savings program are possible options to accelerate adoption of this strategy in these market segments.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2024

Building ControlScore: General Service Administration Office Building Deployment

Improvements to building control systems can lead to energy savings and increased occupant comfort. In an optimized system, process variables such as air temperature will closely follow their desired setpoints and avoid excess energy use. Typically, experts must manually inspect individual control loops to identify poor performance and opportunities for improvement. However, this approach is difficult in modern buildings that have a prohibitively large number of controllers. To address this issue, Pacific Northwest National Laboratory (PNNL) created the ControlScore concept, which takes operating data from the many controllers within a building and generates standardized scores for each loop on a scale of 0 to 10 (a score of 0 indicates poor control, a score of 10 indicates good control). PNNL applied the Building ControlScore application to all available data from a General Services Administration office building within the period of January 1, 2023, to March 9, 2023. The building scored a 4.7 overall, with all 74 of the building’s loops fitting a roughly normal distribution centered around 5. These results indicate that the analyzed systems have below-average performance with room for improvement, especially in the poorly scored systems. Airflow loops tended to have much lower scores than zone temperature loops. The lowest and highest performing systems in the building section were identified, as were all loops with a score less than 1. While the ControlScore identifies loops and systems that aren’t meeting their designated setpoints, it does not indicate the cause of those issues. For example, consider a supply air terminal unit’s airflow loop that received a low score due to it delivering less air than specified by the setpoint. The lower-than-desired airflow could be due to equipment limitations (e.g., the terminal unit or duct serving is too small to accommodate that airflow), malfunctioning equipment (e.g., a stuck damper or bad sensor), or something else entirely. The ControlScore does not diagnose problems it simply identifies the symptoms that can be explored and addressed by building operators.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗